White House Office of Science & Technology Policy, 25th Anniversary Symposium (pt.3) MIT 5/1/2001


[MUSIC PLAYING] MORGAN: Well, two of our
speakers this afternoon have obligations
elsewhere and need to get out of here on time. This has been just a fascinating
morning of history taught by those who actually lived it. We’re going to
move on now to talk about a set of issues related
to the present and the future. But before we do, since many of
you didn’t live this history, I thought I should yield
to the professor in me and offer a very short
list of suggested readings, since this is a
topic on which there has been, in fact, a great
deal of academic endeavor. We heard already this
morning about several books that Bill Golden has edited,
the most recent of which is called Science and
Technology Advice: To the President,
Congress, and Judiciary. It’s a series of essays
by more or less everyone who spoke this morning, plus
a large number of others. Another nice discussion
of many of the issues we heard about this
morning is a book by Greg Herken called Cardinal
Choices: Presidential Science Advising From the
Atomic Bomb to SDI. And it picks up
the theme that was present in many of this
morning’s discussions about the very large role
that defense and Cold War considerations have played
through much of the science advice of that period. Third on my list
of four is a book by Bruce Smith, The
Advisers: Scientists in the Policy Process,
which is broader than just presidential science advising. It also talks about things like
Defense Science Board and EPA Science Advisory Board,
but has a chapter on White House science advice. And finally, a lovely
new book, which makes a very good companion
to Hunter Dupree’s classic that took science
technology policy up to about the time of
the Second World War is a book by David
Hart, Forged Consensus: Science, Technology, and
Economic Policy in the United States, 1921 to 1953. Now it’s also a great pleasure– some of you have figured
out what’s going on here. Morgan is stalling a few
minutes to get more audience into the room for our speakers. But it’s also a great
pleasure to be here at MIT, at this function convened
by the Technology Policy Program, the first
of what I believe is planned to be a
series of functions of this sort in
the years to come. Technology Policy Program
here has become part now of a larger
organizational group, this Engineering
Systems Division, which incorporates
a number of policy and also management-related
activities under one cross-cutting
umbrella that cuts across several departments
of the engineering college. And those of us who have worked
in this area for a long time and observe activities at MIT
are really rooting for this to be a big success, because
to the extent things succeed at MIT, they will succeed
in many other places. TPP was built through 24
years of enormous effort and dedication by
Richard de Neufville and a number of colleagues. And it’s now, as you
heard this morning, in the very capable
hands of Dan Hastings. This morning, Chuck
Vest described TPP as, quote, “The largest
program of its kind.” It is the largest master’s
program in this field, though as a guest here, I guess
I have to be well-behaved. I can’t resist noting that
the Department of Engineering and Public Policy
at Carnegie Mellon has the largest undergraduate
program, the largest doctoral program,
and the largest interdisciplinary tenured
faculty in this area. [LAUGHTER] All right. Well, I’ve stalled long enough. We’ve got about half the
audience back, so let me do three quick introductions. This session is called
Cross-Cutting Issues, and the first speaker
is Rita Colwell. She’s going to talk to the
topic the human capital crisis in science and engineering. Dr. Colwell obtained a
multidisciplinary education in bacteriology, genetics,
and oceanography. Now she’s had a very
distinguished academic career at Georgetown University and
at the University of Maryland. She’s a member of
the National Academy, and has held many
important positions and served in many
advisory capacities, including service as a member
of the National Science Board, President of the AAAS,
and a number of others. She currently directs the
National Science Foundation. The second speaker this
afternoon will be William Wulf, and his topic is New Engineering
Ethics: Great Achievements and Grand Challenges. Dr. Wulf’s formal education
was in engineering physics, electrical engineering,
and computer science. His distinguished
career has included a tour on the faculty at
Carnegie Mellon University, time spent as CEO of
Tartan Laboratories, and time on the faculty of
the University of Virginia from which he’s currently
on leave, serving as President of the National
Academy of Engineering. And the third talk this
afternoon in this session is by Dan Hastings, who’s
going to talk about technology and policy education needs. Chuck Vest has already given
you a rather full introduction for Professor Hastings, who
holds a PhD in aeronautics and astronautics. And after a distinguished tour
as Chief Scientist of the Air Force, has recently
returned, as I said, to a faculty position at MIT
that involves appointments both in aero astro and as
head of the Technology Policy Program in the newly created
Engineering Systems Division. [APPLAUSE] COLWELL: Good afternoon. It’s a genuine honor to
join all of you today. And my thanks go to Chuck
Vest and Daniel Hastings for inviting me and to
MIT for hosting all of us. Before I start my talk,
I’d like to point out, just hot off the press, is
the NSF strategy in brief. If any of you are
interested, I’ve left a few copies on the table. It simply describes how NSF
operates, our strategic goals, and our core strategies. Well, there’s no question
that OSTP has been vital to our nation’s scientific
and technological advancement. Just as was mentioned this
morning, just as Merlin used his great visionary
powers to counsel King Arthur on the affairs of Camelot,
each science advisor has done a magical job advising
our presidents on science and technology policy. And the variations
of the theme have been fascinating to listen to. The OSTP directors have brought
a very rich and diverse set of perspectives to the position,
ultimately steering our nation in a direction that’s
enhanced the growth and development of our
society, our economy, and most of all, humanity. It’s fitting that we address
the topic of the human capital crisis in science
and engineering. Attracting women and
minorities into these fields has been a concern of
mine for some time, and so I’ve titled my remarks
Confronting the Human Capital Crisis: Tapping the Talent. I will talk about the future
of the science, engineering, and technology
workforce, though I do think that the charts we
saw this morning comparing electrical engineering and
parks and recreation and related subjects was pretty
dramatic, if not devastating. Then I’d like to talk
a little bit about what NSF is doing through its
efforts of recruiting women and minorities in
its K-12 programs to develop the workforce. And this is an issue that
is critical to all of us. It’s been a theme running
through many of the talks this morning. At NSF, it’s the very core of
our vision and our mission. The National Science
Foundation is as much about preparing
a world class workforce as it is about discovery. Although we continually
break new ground through the research
and the education we support, we need people
to turn that new knowledge into innovation. Now, worrisome signals about
the science, engineering, and technology workforce
are much too familiar. We’ve heard of the
shortages of skilled workers that have plagued the IT,
the information technology sector, and the numbers of
computer scientists coming out, 800 or so. That’s appalling. Well, here are some other data. While degrees in engineering,
physical sciences, and math and computer sciences are
either static or declining, as we have seen, other
nations are boosting degrees in all these fields. Carrying a little bit
further from the data that was provided in the charts,
let me put it another way. A 24-year-old in
Japan, for example, is three times more likely
to hold a bachelor’s degree in engineering than a
24-year-old in the United States. And the recent studies report
that graduate enrollments in science and engineering
have increased in the US for the first time in a decade. Unfortunately,
that’s the good news. The bad news is the
growth is almost entirely the result of an increase in
the number of foreign students. Graduate enrollment in these
fields among US students has continued to decline. From 1986 to 1997, bachelor’s
degrees in mathematics declined by approximately
30%, from 16,000 or so to about 12,000 or so. Since 1998, the number
of doctoral degrees awarded in science and
engineering dropped 5%. There was a slight
uptick in 1999, but that was due, as I
said earlier, entirely to foreign student enrollment. Well, the lesson that we
should take from these examples is not that we should
discourage foreign students. It’s about tapping the
full range of the nation’s native-born science
and engineering talent. We’re simply not producing
enough workers trained in science, math,
and engineering to meet the needs of today’s
technology-based society. And that’s where the crisis is. I quote from a report released
in January by the US Commission on National Security
for the 21st century. I’m sure that most of
you are familiar with it. And it states very
bluntly, “The inadequacies of our systems of
research and education pose a greater threat
to US national security over the next quarter century
than any potential conventional war we might imagine.” Very strong words. If ever there were any question
about the nation’s need to develop its science
and engineering talent, this should banish all doubts. Well, what should we be
doing about this situation? The title of another recent
report suggests an answer. It’s Land of Plenty: Diversity
as America’s Competitive Edge in Science,
Engineering, and Technology. That report, it
provides the findings of a congressional commission
on the advancement of women and minorities in science,
engineering, and technology. We refer to it as
the COMSAT report. It was chaired by Representative
Morella from Maryland, and it was co-chaired by
Representative Eddie Bernice Johnson from Texas. It issues a very
clear call, a warning. We are making some strides
toward including everyone in the general workforce,
although we do have a distance to go, but there’s
some progress. Unfortunately, we’re not
making significant progress in changing the composition
of the science and engineering workforce. It still looks mighty exclusive. Well, in the parlance
of my children, pale, male, and they would say
stale, but I didn’t say that. Although white males make up
about 42% of the US workforce, they constitute nearly 70%
of the science, engineering, and technology workforce. Women of all races and
ethnicities make up only 15% of the S&T, the
science, engineering, technology workforce. African Americans and
Hispanics of both genders, male and female, account
for about 3% each. The general workforce
already reflects much more gender equality and
racial and cultural diversity. Projections show that growth in
the US labor force through 2008 will come mostly from
women and minorities. The growth will come from
expanding the pool of science and engineering talent, and we
need the talent of every worker in order to compete and prosper. That expansion must come from
the mostly untapped potential of underrepresented
minorities and women. And I’d like to say that
that, in fact, represents America’s competitive
edge for the 21st century. The National Science
Foundation is committed to building a
science and engineering workforce that’s
inclusive and draws on all the talent in the nation. And in fact, people
don’t really view the NSF as a people agency. We fund 200,000
people every year. 70,000 or 80,000
teachers, 35,000 to 40,000 graduate students, undergraduate
students, high school students, faculty, and various programs. That is not even
to mention those that are touched
by the IMAX films, Public Radio broadcasts, and
so forth, which reaches out to about 50 million people. I’d like to tell you a little
bit about some of the things we’re doing at NSF to
address this issue. I’ll begin with recruitment
of women and minorities in science and
engineering, and then I’ll talk about the K-12
education programs. One of the newest programs
at the National Science Foundation– it went on
the web just a month ago– addresses the very
small numbers of women in science and engineering. It’s called ADVANCE. The program intends to
catalyze system-wide changes in universities. That is, to induce change in the
universities and colleges that will foster a more
positive climate for women to pursue academic careers. And ADVANCE also aims
to bring more women into science and engineering. It addresses what
we inelegantly refer to as the two-body problem
or the trailing spouse, and that is to provide an
opportunity for funding for women who are
returning to the workforce or who are moving
because their husband has taken a position in
another institution. It’s an opportunity for them
to have funding in order to move with the spouse. And it’s also open
to men, spouses of women who have received a
position in an institution. It allows them, the husband
to apply, since he’s part of a two-body problem. The message is that
NSF values and rewards the hard work needed to change
the conditions for women in science and engineering. And this will give
participants an opportunity to make a real difference
over the long term. Now I’d also like to mention
the Louis Stokes Alliances for Minority Participation. These alliances target
the underrepresentation of minorities in
science and engineering. It’s about 10 years old. The program links two
and four-year educational institutions with business,
industry, and government. And there are now
about 28 alliances across the United States. The key features of the success
include a summer bridge program to help high school graduates
prepare for college, as well as provide
them with research experiences and mentoring. A study done by the National
Science Board back in 1988 shows that one of the most
powerful correlates of success in science and engineering
measured by a senior position or success in a prize, a
Nobel Prize or last reward or full professorship or
whatever is the opportunity to do research in a laboratory
with a mentorship being provided. Now the programs have
made a real impact on the number of degrees awarded
to minorities in the alliance institutions. In 1990, before
the program began, degrees in the first
group of institutions, the two-year institutions,
totaled under 4,000. By the year 2000, this had
increased to more than 7,000. For all of the
alliance institutions, the total by the
year 2000, last year, was over 21,000 degrees, a
number that continues to grow. And I would say that’s
success by any measure. I should also underscore
that NSF’s largest investment in women and minority
scientists and engineers is through our ongoing
research and education efforts. NSF support for women
researchers, for example, has tripled over the last
decade to about $500 million, about half a billion dollars. We still have a long way to go,
I certainly would admit that. But we are reaching
out and cashing in on the talents and skills
of many more of our citizens. Now another area where we need
to do a better job tapping the nation’s talent is with
a K-12 science and math education. Here’s where attracting more
women and minorities to bolster the S&E workforce really begins. Today, however, far too many
girls, women, minorities fail even to cross the threshold
into science and engineering. We know that there
are lots of obstacles and stereotyped
cultural conditioning that begins to appear
very early in life. And we refer to the grades
between four and eight as the valley of death. And interestingly, not only
for girls, but also for boys, where the interest that’s so
keen in the first few grades in science,
engineering, discovery wanes and is socially
sort of dissuasive. Now I’ve often told the story of
how when I was in high school, girls were simply not
allowed to take physics. Yes, that’s true. More to the point, my high
school chemistry teacher told me I’d never
make it in chemistry. Girls couldn’t do chemistry. Later on in life as an
undergraduate student– and I won’t say where– applying for a
graduate fellowship, my department chair said that
he didn’t waste fellowships on women. Well, today, no one would ever
say outright they would not waste a fellowship on a woman. Yet when we consider how to
attract women and minorities to science and
technology, we really have to begin by re-examining
our assumptions about education across the board,
from kindergarten to lifelong learning. And this is an absolute
imperative for today’s children if they’re going to
participate successfully in the workforce of tomorrow. And yet, too many of them
leave science and technology and just abandon it before
they leave high school. This is all part of a
much larger challenge. Most of us are familiar
with the results of the Third International
Mathematics and Science Study, better known as TIMSS. It’s become almost a
mantra, unfortunately. The study compared the average
performance of US students to students in other countries. Although US fourth graders
performed above average in the study, performance
declined by eighth grade. And by the 12th
grade, US students were right at the bottom. The most recent TIMSS
study, repeated only for the eighth
graders, was released just a month ago in Washington. We had a press conference. It gives us some
reason to be hopeful, but it still shows
a long way to go, because some of the
individual school districts made it to the top of the
international rankings. And so that suggests
that, yes, we can raise the performance
of US children through improvements in the
quality of K-12 education. Now we at NSF are really pleased
that the president has asked us to lead the math and
science partnerships called the No Child Left Behind
education initiative. At the center of NSF’s FY 2002
budget request is $200 million of a five-year, $1
billion investment. And this will be used
to strengthen and reform K-12 science and math education. NSF will provide funds for the
states and the local school districts to join
with institutions of higher learning. For example, the local school
districts in Boston with MIT. The goal is to help ensure
that all K-12 students have the opportunity to perform
to high standards in science and math. And we’re asking scientists,
mathematicians, engineers at universities and colleges
to work with educators in the elementary,
middle, and high schools to achieve some very
ambitious goals. The partnerships program aims
to strengthen math and science standards, to improve
curricula in textbooks, and to raise the
quality of teacher professional development. Bringing research experiences
into the classroom really should help improve
student achievement. But the program
doesn’t end just there. We hope to eliminate
the performance gap between minority
and majority students and reach underserved
schools and students in creative new ways. Well, let me point out just
one other program that’s very important that’s been
proven very successful, and that’s our GK-12 program,
graduate student K-12 involvement. The program works with having
an individual scientist and an institution or an
engineer, a higher education institution partnering
with a teacher in the elementary,
middle, or high school, and developing a program
to enhance science and math education. Funding goes to
graduate students. They receive a
stipend of $18,000. And we hope with the new
money provided in our budget to raise the stipend
to $20,500, though for the graduate
students in the audience, we would like to
raise it to $25,000. In any case, this
provides an opportunity for the student, who receives
the stipend has grant fees and tuition covered, to
then spend 20 hours a week with a school teacher in the
elementary, middle, or high school, providing the
content, the mentorship, and the excitement
of the research. And perhaps schoolchildren
will learn that engineers do things besides drive trains. Well, let me stop here. I look forward to a
bit of discussion. My simple message is one
of always pushing ahead, constant improvement, meeting
ever tougher challenges. We’ve made some tremendous steps
forward across our society. In some areas,
science and technology has inspired the progress
that we have made. In other areas, we’ve trailed. Now we can change that,
and I know that all of us are committed to
making a difference. Thank you. [APPLAUSE] MORGAN: Do we have
a question or two? Yes? AUDIENCE: I think
it’s marvelous, the programs you’ve outlined. And how are we
getting [INAUDIBLE]?? But the thing that
concerns me is– I looked at all the
figures and data. The thing that concerns me
is, what about the other end? Is it realistic to think
even at the K-12 level that unless people can see
a secure future in the sense that if you get a good education
and do well that there’ll be a good job for you? Is it realistic to
think that people will flow into these fields? For instance, I
think we may have a crisis in biological
sciences, because we already have an enormous
oversupply of people in postdoctoral positions. That may not be
oversupplied compared to some measure of demand,
but it is compared to jobs. And so is someone looking hard
at what we do at the job end? COLWELL: Well, there’s
a very serious anomaly. On the one hand, we were
increasing H1-B visas to bring in nearly 200,000
people technically trained from other countries. 55,000 from India alone from the
Indian Institute of Technology, and other very productive
institutions there at a time that now we are seeing a
cascade in job opportunities. In other words, we cannot
address our needs for science and technology talent
by importation. It doesn’t work. What we need to do is reflect
on how we are educating. And in fact, to produce students
who graduate, who are flexible, and who will be
prepared as they must to have seven or eight career
changes before retirement. You and I could expect to stay
in one job or one kind of– for example, I’m
a microbiologist, and I’m still
doing microbiology. That isn’t going to happen for
those who graduate this spring. And so we need to
not only focus on how we’re teaching our
students, but also on what we’re teaching them,
and then for the expectations that we are providing them. We do have a tremendous
need for mathematicians across all of society. I don’t think we
will have a glut even if we are successful in the
push that we’re making to put more money into mathematics. I could go on and on
for an hour about that. I won’t. MORGAN: Yeah
[INAUDIBLE] question. Unfortunately, we
have a hard 3 o’clock deadline for [INAUDIBLE]. So I’m going to stop
now, and perhaps there’ll be an opportunity for
another few questions a little later in the program. The program will run full time. Thank you very much, Rita. [APPLAUSE] WULF: Sorry. Thanks, Granger. I want to add my
thanks to Chuck and Dan for hosting this anniversary
celebration symposium. I think this is really nifty. And to get sorted many of
the former science advisors here at the same time is
really pretty special. When Dan asked me
to speak today, he asked me to in
essence repeat the talk that I gave at the annual
meeting of the National Academy of Engineering last fall. And so in some
sense, this is going to be an abbreviated
version of that. The full talk
tried to first talk about the kinds of
contributions that engineering has made to our quality of
life, and the second half was to look forward and ask,
what are the challenges facing engineering for
the 21st century? I’m going to lop off the
first self-congratulatory part of the talk altogether,
and I’m going to focus in on just one
challenge for the 21st century, a challenge that I think
may be the greatest one that we have to face. And it is, in fact,
engineering ethics. Now what Dan didn’t
tell me was that I was going to be talking right
after Harold Shapiro talked about ethics. He was vaguely apologetic
about not being a scientist. I’ll be vaguely apologetic about
not being an ethicist as well. I want to start out by making
it clear that I believe that engineers and engineering
by and large are very ethical. There are courses in engineering
ethics at many universities. There’s a stack about
two, two and a half feet high of books that have been
written just in the last five years on the question
of engineering ethics. ABET 2000, the criteria by
which engineering schools are accredited, require an
exposure to ethics, at least in the context of
a capstone project. And every single
engineering society has a professional
code of ethics. The one that most of
them are modeled on is from the National Society
of Professional Engineers, and it starts out
saying that engineers will hold paramount the health
and safety of the public. And then goes on
in great detail, some 170 or so separate points
of specific responsibilities that engineers have to their
customers, to the public, and so on. So with all of
that in place, why did I try and tell
the academy that I thought one of the greatest
challenges for the 21st century was engineering ethics? It’s because I think the
practice of engineering is changing, and
changing in a way that raises new kinds of ethical
issues, ones that engineers at least haven’t
had to face before. The existing codes
of the vast majority of the books, the context in
which the ABET requirement is written all deal with what
is known as micro ethics. And I don’t mean micro to
mean small or unimportant, but rather, ethics
that have to do with the behavior
of an individual as opposed to macro
ethics, which deal with the behavior of the
profession as a whole. Perhaps illustrating the point
with another field will help. In medicine, the ethical
codes that a doctor subscribes to for his or
her individual behavior bear an amazing resemblance to
the engineering ethical codes. The behavior of
the individual is specified in very similar ways. But medicine has had
to deal with some of these macro ethical problems,
which engineering has not. The most easily accessible
example is allocation. If there are less
organs to transplant than there are
patients who need them, how do we decide which
patient gets them? That’s not a decision for
the individual doctor. Similarly, if
there’s less medicine than the number of people
ill, or if there’s simply less time for the
physician to allocate to all of the people who are
ill, how do you do triage? How do you decide who gets the
attention and who does not? Again, those are macro
ethical questions, because they’re questions
that either the profession has to decide upon,
or perhaps better, society informed by the
profession needs to decide. Well, I said the
practice of engineering is changing in ways that raise
these macro ethical problems. I’m going to focus on just
one such change, again, in the interest of time, and
that’s the issue of complexity. Particularly, complexity arising
from information technology, from biotechnology, and
perhaps in the near future from nanotechnology. Simple fact is it
is possible today to build systems for which it
is impossible to predict all of their behaviors a priori. It’s not just hard. It’s not just if you thought
about it more, you could do it. It is literally impossible. Perhaps the best
way I can illustrate that is from my own
field in computing. We’ve got some physicists
in the audience, and so maybe somebody can
give me the exact number, but I believe that there
are kind of order of 10 to the 100th elementary
particles in the universe. I’m looking at Allan Bromley to
tell me whether that’s right. Okay, he’s saying it is. It’s 10 raised to one followed
by a couple of digits. Maybe it’s 120. I want you to compare that
to the number of states in my laptop. By state, I simply mean
the number of patterns of ones and zeros in my laptop. That number is 10 raised
to 10 to the 20th power. So whereas the number
of atoms in the universe is 10 to the one
followed by two zeros, the number of
states in my laptop is 10 raised to one
followed by 20 zeros. If every atom in the
universe were a computer and every one of
them could do 10 to the 100th
operations per second, there isn’t enough
time since the big bang to examine all of the
states in my laptop. Okay? That’s the sense in which I
mean we can build systems that are so complicated that it
is impossible to predict their behavior. It’s not that there
isn’t an algorithm, which given enough
time could determine all of the outcomes,
all of the behaviors. It’s that there
isn’t enough time. A very concrete
example of this was a report issued by the
Naval Research Laboratory. One of my areas of research
has been computer security over the years. And there was an NRL
report about 1993, if I remember correctly,
that looked at the reasons for about 50 security failures,
lapses in security that happened. Because the way these 50
examples were selected– the numbers I’m about to
give are not necessarily representative of anything. But of those 50
examples, 22 were errors in the specifications,
errors in the sense that a property
which was thought to be essential for the correct
behavior of the system, it in fact turned out to be the
vehicle by which somebody could crack the system. In every case, it was
because the particular way that the cracking
was done was not anticipated for exactly
the reasons I’m describing. The system’s too complicated. It’s impossible to
predict its behavior. So the question then
is, how does one behave ethically in such cases? What does it mean to
ethically engineer when you know that the
system that you build will have behaviors that you
did not predict, some of which might be negative, some of which
might be absolutely disastrous? And in fact, we have to begin
to rethink the process by which we engineer. I mean, the kind
of standard process you’re taught in
engineering school is that somebody gives you a
specification for a problem, for a solution to a problem. You go find a design that
affects that solution. You build it. You test it. Go home. Well, I’m sorry. The error’s going to be
back in the specification, or the problem’s going to be
back in the specification. So how do we modify the
process by which we behave? I think there’s no better
example right at the moment than people are talking about
remediation of the Everglades. We’re about to do some
multi-billion dollar re-engineering of
the Everglades. Let me tell you, that’s one
of these complicated systems for which we will not
be able to predict the consequences of what we do. And yet, doing nothing is not
an acceptable solution either. Doing nothing is also
a conscious decision, and it will have consequences. So how do we ethically engineer
in such a circumstance? I’ve got another example, but
we’re going to run out of time, and so let me defer
that to any questions, or defer that to
questions at the end. I wish Harold were still here. It might get into a more
interesting conversation. Thank you. [APPLAUSE] MORGAN: Well, I will make
the first question to Bill, and then Bill, if time
runs out and the two have to run for a
cab, I will alternate. So a question. Yeah? AUDIENCE: Well,
although we can’t– although we can’t know the– although we can’t know the
states of a particular future, we can– and Dr. Morgan has
just written about [INAUDIBLE] in some way that we
have some idea about– like say in the case
of the Everglades, we have some idea
what will happen over a small period of time. Of course, we don’t have
large periods of time. And how would you
think about that? WULF: Yeah, I’d like to have
some conversations with people who are more expert than I,
but a plausible suggestion is that instead of design– sorry– specify,
design, build, test, you say, well, let’s specify
a little and design a little and build a little
and test a little, and then go back and
ask what’s happened. But that’s a much more
organic interaction with whatever it is that
you’re producing than engineers are accustomed to. MORGAN: Yes? AUDIENCE: On the
question of large numbers and the impossibility
of specification, isn’t it a question partly
of how and what you specify? Ordinary statistical
mechanics is a way of dealing with
very, very large numbers. Maybe only 10 to the 30th
rather than 10 to the 100th. But most of the
states become outliers on a distribution for which
certain macroscopic variables can be defined fine. [INAUDIBLE] in most of the
situations one encounters take care of. I mean, can one deal
similarly statistically with these large numbers? WULF: Let’s see. In the case of continuous
systems, maybe. The trouble with digital systems
is that they’re not continuous. A one-bit change can
lead you to a state which has no relationship to
the state you changed from. You don’t have continuity. And it’s a problem. MORGAN: [INAUDIBLE] Dr. Colwell. There was one over here
that I [INAUDIBLE].. Yes? AUDIENCE: Rita, we’ve heard
a lot about workforce, and we’ve talked
about micro and macro, and I and everybody applauds
what you and others are doing. In a big macro picture sense
from a national point of view, if there is a crisis, as your
title says, and there is, including the workforce
minorities, women, and human beings, what
in a big picture sense can we try to do to
bring some elevation of political awareness
so that there’s policy action on this
critical, critical issue? COLWELL: I don’t
think we’ve ever had a time more salubrious
with respect to the White House actually saying that
education is the number one priority for the country. And I think what we need to
do is ensure that we take advantage of this wonderful
opportunity when there is a focus on K-12 education. And I think the big problem
has been the disconnect– I call it the scorched earth– between the elementary, middle,
and high school and the higher education. Somehow we have risen above
it, which is sort of bizarre. And we need to reconnect,
and it is our problem. And I think if we can
take advantage of this, this really excellent
opportunity and time that we have, we can
make a big difference. I really do. And I really worry about
simplistic solutions. They’re not simple solutions. One of the things we
would like to do– and I’m going to give you
a little commercial here– is establish centers
focused on the science of learning and teaching, and
to develop these centers just as we so successfully did for
engineering research centers and science and
technology centers– they are a big success– where we require the industry,
the local school system, higher education, the community,
and private foundations to be partners and
totally responsible. Provide opportunities
regionally for teachers to regain their
professionalism, to regain their pride of
profession, and then to have a place to go for the
best practices, curricula, et cetera. Anyway, I think this
could be very effective. MORGAN: Very good. Here’s a mic. AUDIENCE: Yeah, Rita, I’m sorry. I came in just on the
tail end of your talk, but I know what’s
in it, so it’s– [LAUGHTER] COLWELL: You’ve heard it before. AUDIENCE: I’ve heard it before. But the question I
have for you is this. If you remember back
in the mid 1980s, the National Science Board and
the National Science Foundation made a big pitch for
increased numbers of scientific and
technical personnel. If we had followed
through with that, we would have not had quite
as bad a decline as we’ve had. I mean, the timing was
absolutely correct. However, the political
system beat us to death. And the reason
that I know so well is I was on the National Science
Board at the time and chair it one time in that
period of time, and we literally
got slaughtered. That’s the only word
I can say for it. And the reason we did was that
we had a small recession which lasted for a year or
two and a few chemistry PhDs were driving taxicabs. And we just got killed. Now the problem you
have is we are now looking at an
economy which is not as robust as it was this time
last year, and the issue– my concern is that
we’re going to end up with the same kind of response. And if we do, then
the next time around– I mean, it will simply
be now twice as bad as it was the time before. How do we get
people to understand that this is not a response
to whatever is doing today? And interestingly enough,
I have to say this. In the 1985, ’86 problem, the
universities did not help us. COLWELL: Well, Mary,
there is a difference. Today from that unhappy
period of time– which I remember so
well because I too was on the science board
with you, as you’ll remember. The difference is that
we have had an attitude in the past which
served us well, that we would educate the
best and the brightest, and they would lead us– and they did– into the future
as the best in our fields. The difference now is that
the technological work skill demands are across the board. And so in order to
be an auto mechanic, you’ve got to know mathematics. You have to know
something about computers. In fact, you have to
know about computers, because there are probably 20
or 30 of them under the hood. So I think we have a
different kind of challenge than we did at that time. And also, when you try
to predict directions, if you try to predict for
kids where they will go, that is a mistake. Again, changing
education so that we educate kids who will be
lifelong learners, who will be self-educated. And of course,
distance education, as MIT is doing so well
in making available in its curricula, another
way of educating that’s very, very important
in a new century. So there are differences. MORGAN: I think we have time
for just two more questions. There’s one there. AUDIENCE: There’s a
great deal of complaining about the lack of people moving
into science and technology, but I would suggest there’s
no real economic evidence that that is a problem. You are not finding
the kinds of salaries for engineers that are
being paid for MBAs going into consulting companies. And so when a company
president complains to me about the shortage of
engineers, and I said, well, would you pay as much
as you do for the top MBAs, he said, well, of course
we couldn’t do that. And there you are. COLWELL: Well, that’s
anecdotal, and it’s valid. But let me counter with
an anecdote as well. A friend of mine who’s an
African American mathematician, he finished his
PhD early last year before the H1-B visas were
full, were completely exhausted. They were all taken. And he could not get a job. But as soon as the last of
the H1-B visas were gone, then he had several job offers. So I think there is
something very– there’s an important message
there that we are not looking to our Native Americans,
and we’re not providing the job opportunities. And we’re using an
artificial source for filling the jobs
that are very important. And the IT jobs do pay 60%
more than the average wage, so they’re not exactly
crummy jobs, so to speak. WULF: No, in fact, that’s
something that ought to be very disturbing to us. A new engineer with a BS
degree gets from 50% to 100% more than a person graduating
with a BA Degree, on average. And yet, in the
face of that, we’re still losing market share. We’re still getting a
smaller and smaller fraction of those people who do
enter college, who even have the appropriate math and
science prerequisites, opting not to take engineering. MORGAN: I think that
both in the interests of getting two of our panel
members out to a waiting cab and giving Dan his whole
time, we should stop here. My apologies to the couple of
you who still have questions. Thanks again to
both Rita and Bill. [APPLAUSE] HASTINGS: To finish
up this session, which was to look at some of the
cross-cutting issues that are affecting the human
capital in this country, I want to talk a
bit about the need for an integrative technology
and policy education. I subtitled this
Bridging the Gap. And the question I
want to address today was actually framed
by Donald Kennedy, I thought very well, in his
insightful book Academic Duty. And in the final chapter
he asks the question, can the universities really
make a difference with respect to the big problems facing us? And in the actual
chapter, the big problems is capitalized, which I
can’t quite say it that way. He suggests that the list
of challenges facing us ranged from arms
proliferation and disarmament to ethical issues in genetic
testing and counseling, as we heard today at lunch,
to utilization in centers and health care systems. And these issues are indeed
intellectually exciting and analytically demanding. However, the problem
is that they do not come in disciplinary packages. And furthermore, he
asserts in his book, those who wish to work on them
face suspicion in the academy, which he asserts stems partly
from the traditional academic reluctance to do,
quote, “applied work,” and partly from the
considerable difficulty of being an interdisciplinary scholar. And he points out the critiques
often heard in these messes that it’s so valuable to go to. The critique of those who
engage in interdisciplinary work is often their work is watered
down or somehow has gone soft. And therefore, it’s
hard to encourage people, academics to
actually think hard about some of these issues. He points out, however,
that these issues are indeed real and complex, and they’re
problems of large scale, and they need the attention
of thoughtful intellectuals. So then the question
as he frames in the last chapter
of his book is whether the academy can
overcome the resistance of departmental structure
to re-engineer itself in the face of these challenges. And in this talk,
what I want to argue that part of the answer
to this big question lies in educating
leaders flowing out of a new vision of engineering,
which to some extent you heard from Bill Wulf and his
emphasis on engineering ethics. This new vision
of engineering is going to operate at the
interface of technology and policy. Now in terms of
building that argument, I first want to
argue that we live in a world of two
cultures, and I think we’ve heard quite a
bit about that already today. And secondly, in a world of
accelerating technological change with profound
social consequences. And President Shapiro
made a very good case for some of the consequences
in terms of the stories that guide us in our lives here. And thirdly, I’m going to
argue that the paradigm for engineering is changing. And from this new
paradigm can emerge the kind of leaders
that can transform the academy, if we allow
it to actually happen. The first thing to
consider, of course, is here in the first part of
the 21st century of modern day America, we see a staggering
technological change and innovation. So the reality is even though
as Representative Porter pointed out, many in the
Congress may not entirely appreciate the worlds of
science and technology. Our lives have been
fundamentally transformed by science and technology. It’s hard for those people
who are much older– and you talk to
people much older, you compare people
[INAUDIBLE] today, it’s hard to understand the
dimension of the changes. So I even talk to my own
sons who live in a world where there’s always been CDs
and VCRs and transatlantic phone calls, and they just
don’t think of anything else. That level of communication
has just changed their lives in ways that they don’t
even completely appreciate. Now an awful lot
of that, of course, has flowed from the success of
what’s occurred in the academy. A lot of the inventions and
discoveries– not all of them– have flowed from the academy. And in that sense, a
disciplinary formulation has proven to be,
you’ve got to say on the basis of the evidence,
remarkably successful. However, we still live in
a world of two cultures. Many people, as Representative
Porter suggested, who end up in leadership come
up through a liberal arts education. The liberal arts education
very correctly emphasizes the human condition, but
gives relatively little shrift to the increasing scientific
and technological forces which are changing our
understanding of the world. Many of the people who end
up with this liberal arts education end up in law and
public policy positions, which teaches them very well
to articulate their cases, but does not teach them very
well fundamentally if they’re talking about science
and technology exactly what they’re
actually arguing about. Sometimes this leads to amusing
results, and sometimes worse. What was very
interesting to observe in reading about the
voting issues in Florida was the debates over
voting machines. Whereas those of
us trained in more of the technocratic
tradition would have said, well, there’s a fundamental
issue about uncertainty here, which is
fundamentally unresolvable. But it was just hard to get
that point across to people. By contrast, many
like myself who’ve been educated through
a scientific indication end it with a technocratic
view of the world, which often does not take account
of the role of human beings. I thought that one of
the ways to understand what President Shapiro
said at lunchtime today was to hear the fact that he
was articulating a view where human stories are at
the center of the way that human beings
actually think. And often in a technocratic
view of the world, it’s just not clear that
people understand that. This leads to the
constant amazement that scientists
and engineers have that the exposition of the data
is insufficient to convince policymakers. They just don’t understand,
most scientists and engineers, the nature of stakeholders,
the problem of the commons, and they typically have very
little interest or patience with the necessary
political process. Of course, this is not true of
the esteemed gentlemen sitting here, who I’m sure do understand
the nature of the commons and stakeholder interests. So thus, we find
ourselves in a society where we have this divide– not the only divide, but
certainly one of the divides– where large segments
of the public either do not
trust or understand the advances in
science and technology. And many technologists
do not understand the public or the
real constraints that decision makers
actually face. So I would suggest here
the ongoing controversies over genetically modified
foods, the concerns over the spread of
ubiquitous network computing, loss of privacy as well
as global climate change. They have many
dimensions about them, but certainly, some
of the dimensions are due to the
fact that you have two different– more
than two– but certainly two different
groups of people who come from very different
positions on these things, and very different ways of
understanding the world. Two issues are very
important for leaders to understand and articulate. One is public
mistrust of certain but not all types of scientific
or engineering advances. For example, GMOs. But for example, not for
example, personal computers. Most people accept the
notion of personal computers. They may not accept the
notion of networked personal computers, but certainly
personal computers, they accept. Another issue that leaders have
to understand and articulate is the role of objective
scientific analysis in addressing policy
decisions or problems. For example, global
warming, HIV, mercury contamination
in fish, and so on. Now some of the
issues that arise arise from perceptions of
scientists and engineers. It’s very interesting. You can tell a lot
about a culture by going and looking at the
things they have on television and have in movies. And I find it insightful
to look at some of the images of
scientists and engineers as seen in television
and movies. Much of the time, scientists and
engineers are seen as wizards. So I thought it was interesting,
[INAUDIBLE] description that he was known as
the president’s Merlin, as somebody who does this
wizardry that you don’t quite understand, but
nevertheless, it turns out to be important to life. So much of the time scientists
and engineers are seen as wizards, able to work
wonders that people cannot see and understand. I mean, just look at some
of the movies and TV shows that people actually
watch, and you see this happen again and again. Generally speaking, the
wonders are good for society, but sometimes they
require others to help scientists and engineers
make the right decisions. This accelerating rate of
change in science and technology we see in our lives
around us combined with this lack of
understanding on both sides then leads to situations where
the public is distrustful of science and technology and
where policy is often dragged into reactive positions. Sometimes these
positions are correct. Sometimes they reflect
ignorance and fear. Sometimes it’s politics
and competing values which cause policymakers to hide
or ignore scientific evidence. For example, perhaps with
coal-fired power plants. These continued divides
in society combined with the urgency of the issues
facing us I’m going to argue suggests a need for both
research and education that bridges the divide. In part, what is
needed is the kind of integrative education in
the academy and research that will produce individuals
who can lead and understand the interface of science
and technology and society, and articulate the case to
both sides of the divide. So that is, they must have a
foot in both sets of worlds. This brings me to the
role that accelerating technological change actually
plays in these issues. These integrative leaders,
I’m going to argue, are needed to actually help
society deal with accelerating change. Accelerating
technological change is fundamentally transforming
the way in which we actually live. Over the last few decades,
we’ve seen the introduction of lots of new
technologies ranging from consumer plastics on
TV to desktop computing and the internet. These have exerted profound
influences on our lifestyles and the ethical and material
development of our science and polity. I mean, I think we, again,
heard that today at lunch. And if the past is any
prologue, the issues surrounding emergence
of new technologies will be even more profound
than in recent decades. So again, I cite
innovations in the field of genetic engineering,
nanotechnology [INAUDIBLE] computing, and so on. As globalization of
these technologies continues to deepen
and accelerate, it’s going to
become increasingly difficult to
anticipate and address the political and
ethical issues, as well as the cultural and societal
issues before we are swept up in them in a
reactive kind of way. And that’s because of the
accelerating rate of change. So the task then of
improving, understanding, and of responding
to rapid innovation is inherently
difficult. It’s marked by uncertainty over
technical advances, uncertainty with
respect to the side effects on our natural
and economic systems, and uncertainty in the political
and cultural responses to them. Too often, the assessments
of technological advances begin with speculation
before the fact that’s based on an inadequate
understanding of science to be followed by speculations
after the fact on what could have actually been done better. As a result, discussions
tend to oscillate. And you can see this very
clearly if you read the op ed pages of the papers. Discussions tend to oscillate
on the implications of advancing technologies, tend to oscillate
between techno optimism– so some of you may
recall electricity which would be too cheap to meter– and techno phobia where
a great deal of fear is expressed about the
appropriate technology, until finally after a
period of oscillation, more realistic appraisals emerge
and then some kind of policy is actually set into place. Any new technology,
I’m going to argue, has the potential
for consequences beyond those that are considered
when it is actually developed. Because our knowledge of the
future can never be perfect, it means that we
actually have to start thinking about the
implications of the science and technology we do as we’re
in the process of actually doing it. And I’m going to
argue, again, that we need the kind of
integrative leaders who can do that kind of thinking
as the science and technology is actually being developed. The circumstances
then– so okay. So let me argue that
what that then needs is a revolution in the academy,
that an academy is exactly the sort of place where those
kind of thoughts should occur. But an academy divided along
narrow disciplinary lines, an academy with a disdain
for multidisciplinary work is not the place
where it will occur. That what the academy needs
is an intellectual revolution in the way we think
about means and ends and about the very purpose
of innovation itself. And if we’re going to answer
the questions of Donald Kennedy, then the academy itself has
to be changed along some of these actual dimensions. The circumstances then
in order to do this not only will make evaluation
of policy and ethical context actually easier if
it’s actually done, but also provide a lot
of potential benefits. Now we could think of many
of the ways in which this can actually be done. I’m going to argue that
one of the things that has to happen in
academies like this is that they have to
strategically reposition themselves. And one of the
repositioning is going to occur through a redefinition
of what we actually mean by engineering. The field of engineering,
I’m going to argue, is changing very rapidly now. You heard some of what Bill
Wulf had to actually say, the notion of the complexity
of the systems we have, meaning we have to develop new
kinds of engineering ethics. Given that system and product
complexity are actually increasing at an
accelerating rate, as are the complexities of operating
in a global context where technical, natural, and social
systems are increasingly interacting, then
what we need to do is develop new kinds of leaders. I’m going to argue those leaders
will be engineering system professionals who consider
the technological components of what they do as part of
a larger engineering system paradigm, and who utilize
different approaches on that based upon a narrow disciplinary
engineering science paradigm. And these engineering
system professionals should consider the context
in which the system operates as a design variable as
opposed to a constraint. Thus, they’ll be concerned with
the design of the organization that has to manufacturer a
system or product, as well as regulations and public
policies governing its use and disposition, marketing the
relationship with suppliers, distributors, and other
participants in the value chain. Now as an example of the
broadened perspective of this, I think it’s
extremely instructive to look at the changes that have
occurred in automotive design and manufacture of automobiles. The automobile was
once considered to be a technologically
mature product. I well remember there was a
time even a few years ago where some of the car
companies actually had trouble getting MIT
graduates to go to some of them, because there was
nothing new that was actually happening there. Once considered a
technologically mature product, it’s now influenced
by new technology, including at the
level of technologies are lightweight materials,
smart electronic components, alternate propulsion systems. But in addition to that,
there are other things that affect the automobile. The globalization of
the automobile industry has shifted locations of
both design and manufacturing facilities from a national
to international context. Concerns such as quality,
human resource management, time to market have motivated
fundamental changes in automotive product
development, manufacturing and supply chain design. New approaches such as just
in time inventory control, integrated product
development teams, lean production
techniques have reshaped companies’ automotive
production processes, while social concerns such
as air pollution, materials recycling, global
warming, and safety have had a major impact on
auto design and production. Furthermore, design
and manufacturing are only part of the system now. Government policies determine
the role of automobiles in providing personal mobility,
ensuring automotive safety, and impacting the environment
and urban development. The development of effective
policies to deal with this system we call the automobile
cannot be based solely on technical expertise,
but require instead an understanding in addition
to technical expertise, understanding of
institutions, economics, human behavioral responses, and
non-technical considerations. So the leaders that are
necessary to do that, I’m going to argue
that these leaders have to develop this
interdisciplinary approach of which the automobile
is an example of these. So these leaders will
then consider the context for which systems are initiated,
designed, manufactured, constructed, implemented,
and maintained. The context is undergoing
significant change as a result of globalization,
the information revolution, and emerging social concerns. For example, sustainability. Now I have to quote here
from President Vest, because I think he
said it very well. He says this
perspective is reflected in President Vest’s comments
in the president’s report. “Humankind’s advances
will depend increasingly on new integrative approaches
to complex systems, problems, and structures. Design synthesis and synergy
across traditional disciplinary boundaries will be essential
elements of both education and research.” So in closing,
I’m going to argue that the big issues in society,
this cultural divide that is created and perpetuated by
our current educational system, and the accelerating role
pace of technological change in society demands a
change in the academy. And it demands a new kind of
societal leader who I will argue cannot flow from a
new vision for engineering. So at this point, I need to
quote my colleague, Dr. Larry Linden. And he says, “What
the academy must do is seek to produce societal
leaders who are, one, skilled intellectually
in dealing with the many crucial
technological dimensions of our society; two, have the
practical results orientation characteristic of engineering
professionals; three, have the courage based
on early experience to take on the most difficult
systems problems; and four, have the leadership skills to
bring others forward as they themselves move forward. These will be leaders bridging
the gap between technology and policy. I think part of the
challenge facing OSTP, well as the
academy, is how to help the academy
re-engineer itself to produce these kind of leaders
to deal with these kind of complex systems. In so doing, I think
it will help ameliorate the societal responses to the
technologically driven changes. If anything, they’re
only going to increase. And not doing that, the
status quo will prevail, and we will continue this
oscillation between techno optimism, techno pessimism,
and reactive policies which sometimes occur as
a result of them. So let me finish
my comments here. [APPLAUSE] MORGAN: We have a few minutes
for a couple of questions. Yes? AUDIENCE: Yeah, I
think after having listened to all the speeches,
something that is missing– nobody has ever talked about
how are the students admitted into the universities? And how are the
engineers trained? Because the universities only
train engineers to get jobs, not necessarily to know what
they’re going to do out there. To train people who are
going to get the best job. And they market them
so well that they have become scientists with
that knowledge [INAUDIBLE].. Thank you. HASTINGS: Well, let me– I didn’t completely understand
the thrust of your question, but I think it is the case– I’m arguing that one
of the things that needs to happen in
engineering education is that engineers need
to be trained to– at least some set
of engineers need to be trained to become
these kind of leaders. Now having said
that, I think also there could be a continued
need to train engineers as disciplinary
people who go out and engineer the next product
well, as long as there are also people who will help understand
how those products are actually integrated into
society, which can also be the role of engineers as
long as it’s done properly in the educational system. MORGAN: We have one more
question or comment. Yes? AUDIENCE: You focused mainly
on the role of engineer– how technology and policy
can reach out to engineering, and I was just wondering if
you could comment some more too on how perhaps scientific– well, science majors
in particular, how that can be
integrated as well instead of just engineering. HASTINGS: [INAUDIBLE]. That’s an interesting question. I think that it’s important
for some subset of scientists to think clearly about the
implications of the science that they do. I’m not sure I believe it’s
important for all scientists to be trained this way,
because I think it’s important that scientists continue
to be trained to do fundamental science, right? But there needs to be enough
of a leavening in the science community– so this doesn’t mean everybody. It just means it needs enough
of a leavening in the science community so that the questions
that President Shapiro raised can be raised by
scientists themselves. That is, is it the case that
we should always go down this path, given that
we have the potential to go down this path? I think it’s not a good
thing for the society if it’s the case that you have
this divide where scientists and engineers just pursue
one set of paths, which is a technocratic path, and you
have other people, humanists who have another set of
ways of looking at things and bringing that into it. And you end up getting this
kind of oscillation and divide. I think that some
subset of scientists should be thinking about
these kind of broader– let’s call it system
and societal issues. So I wouldn’t do it
for all scientists. Now I’m much more inclined
to say since engineers are in the business of building– creating things which
presumably help society, I would argue much
more strongly that you need to do this with
a lot more engineers than you need to do
this with scientists. I mean, that’s my– MORGAN: We’re going to
take a 20-minute break now, after which Dan Roots
will share a session and we’ll look at defense
technology, biotechnology, information technology,
environmental [INAUDIBLE].. [APPLAUSE] MODERATOR: Looks at issues
in science and technology policy, current topics. Before we get into
the presentations, I just wanted to
say a few words. Several people have come
up to me and asked me, what is the Engineering
Systems Division, which is one of the
sponsors of this program? And Granger alluded to
it, and Dan Hastings talked about the philosophy
behind the creation of ESD, and one of the
principle programs of the division, the
Technology and Policy Program. And let me just
take a few minutes and try and answer
that question, because this is a
new unit at MIT, which was set up two years ago. And many of us talk about
government bureaucracy, and I suppose the
only organizations more bureaucratic than
government are universities. And so the Engineering
Systems Division, I think, is the first new
institutional unit in the School of Engineering
at MIT in about 25 years. So it is significant
from that point of view. It is an interdisciplinary
unit with faculty from management, engineering,
and the social sciences. All the faculty in ESD,
of which we have 30, have dual appointments. So they have a half of their
appointment in the division and a half of their
appointment in one of the departments
in engineering or in the Sloan
School of Management. We have eight faculty from
the Sloan School of Management or one of the social
science departments. So what it does is it creates an
institutional home which we’ve never had for faculty who
are interested in a range of broader issues beyond
engineering science. And the charter
of the division is to broaden engineering
education and broaden engineering practice. It’s to look at how one develops
large-scale, complex systems, be they transportation systems
or communication systems or energy systems,
recognizing that technology is a significant
portion of the creation. We should have technical
people in leadership roles, but if they’re going to
be in leadership roles, they have to understand more
than simply the technology. So in a sense, it’s
going the next step beyond what were very
successful programs created over the last 20 years at MIT,
of which TPP is certainly one. Others that you may
be familiar with are our Leaders for
Manufacturing program, System Design and Management. These are programs that focus
on professional practice and the broader
aspects of engineering. And we’re very,
very pleased to be one of the principal
sponsors of this as kind of the new kids in town. And if any of you are interested
in finding out more about ESD, just come up and
speak to me, and we’ll be delighted to send
you some information. Well, let me turn to the
session this afternoon. We have four presentations. And during the
morning session, we got the sense of the
minute-to-minute activities in Washington and the reactive
nature of the policymaking process. And we are seeing it in
living action in that one of our speakers–
fortunately only one– had a crisis today, and was
unfortunately unable to attend. But we’re very pleased that we
have Dr. Charles Holland, who’s a Director of Information
Systems in the DoD office overseeing science
and technology who has, at the last minute,
agreed to come up and speak to us today. He has a PhD in
applied mathematics from Brown University,
early career in academia, and he’s had 20 years of
government research management experience in DoD. And I’ll go through
the presentations. He will speak on
defense technology. Our second speaker
is Dr. Phillip Sharp. Professor Sharp joined
the MIT faculty in 1974 as an associate professor
in the Department of Biology and the Center for
Cancer Research. He was promoted to a
full professor in 1979. He served as Director of the
Center for Cancer Research from ’85 until ’91 when he
became head of the biology department, making that
absolutely world class department. In 1992, he was named the
Salvador Luria Professor of Biology. And in 1993, Professor
Sharp shared the Nobel Prize in physiology or medicine
for work that fundamentally changed scientists’
understanding of the structure of genes. He and Dr. Richard Roberts
of New England Biolabs was awarded the prize for
their independent discovery that some of the genes
of higher organisms are split or present in
distinct segments along the DNA molecule. In 1999, in recognition of
his world-renowned research and his service to the
MIT community and nation, Professor Sharp was named
Institute Professor, the highest honor
awarded by the faculty and administration at MIT. And of a faculty
of close to 1,000, I think there was something
like 13 Institute Professors. So it really is a very,
very distinguished title at this institution. Phil is a graduate
of Union College. He received this
PhD in chemistry from the University
of Illinois at Urbana. And in addition to
the Nobel Prize, he has received numerous
awards and honors, including the Albert Lasker
Basic Medical Research Award in 1988, honorary
doctorates of science from five universities, and the James
R. Killian Faculty Achievement Award from MIT. Again, that’s one of
our highest honors. Dr. David Clark is
our third speaker, and he is going to speak on
the internet communications and information technology. David Clark is a senior research
scientist at the MIT Laboratory for Computer Science. Since the mid
’70s, Dr. Clark has been leading the
development of the internet. From 1981 to 1989, he acted
as chief protocol architect in this development, and he
chaired the Internet Activities Board. Recent activities
include extensions to the internet to
support real-time traffic, explicit allocation
of service pricing, and related economic issues
and policy issues surrounding local loop employment. New activities focus on the
architecture of the internet in the post-PC era. Dr. Clark is Chairman
of the Computer Science and Telecommunications Board of
the National Research Council. And our final speaker is
Professor Ronald Prinn. Professor Prinn is
a TEPCO Professor of Atmospheric
Science, and he’s head of our Department of Earth,
Atmospheric and Planetary Science. Professor Prinn’s
research interests incorporate the
chemistry, dynamics, and physics of the atmosphere
of the Earth and other planets and the chemical
evolution of atmospheres. At MIT, he directs the Center
for Global Science Change and co-directs the joint program
on the Science and Policy of Global Change. Let me just mention
for a moment, since I don’t think Ron will
get into it in his talk, a little bit about
that program, because I think it’s very relevant in
terms of our discussion today. One of the roles that an
institution like MIT can play– and we’ve heard this
a number of times today– is to bring objectivity
to a set of complex issues where we can look at
data, we can do analysis, we can look at a
variety of alternatives and what their impacts are. But in many ways, the forms
of communication have changed. And if all we did was to
publish scholarly papers, it’s not clear how many
people would really read those, particularly
industry executives and government officials. And those are the
people who we really want to be aware of
the objective analysis. So what we have tended to
do in this program, which brings together a group of
scientists and economists and policymakers, is to serve as
an honest broker or facilitator where on the basis of
once or twice a year, a group of people from
around the world in industry and government and
other stakeholders get together with
the researchers, with Ron and his group, and they
present their research results, and there’s a discussion. And so it’s much
more of a dialogue in which the university really
is taking on an important role to hopefully influence
policymaking. But we’re not
proposing the policies. We’re simply
providing the analysis to this group for discussion. Well, Ron leads the Advanced
Global Atmospheric Gases Experiment in which
the rates of increase of the concentrations of
the trace gases involved in greenhouse effect
and ozone depletion have been measured continuously
over the global environment since 1978. He’s pioneering the use
of inverse methods, which use such measurements to
determine trace gas emissions and understand atmospheric
chemical processes. Dr. Prinn is a fellow of the
American Geophysical Union, a 1981 recipient of the AGU’s– make sure I’ll get this right– Macelwane Medal, in the ’84
Vernadsky Memorial Lecture of the USSR Academy of Sciences. He served as chair for
Atmospheric and Hydrospheric Sciences in the
American Association for the Advancement of
Science, Inaugural Chair of the International Global
Atmospheric Chemistry Project, and Chair of the National
Research Council Committee on Earth Sciences. And we have, I am
told, a special treat at the end of Ron’s
presentation, which we’ll find out more about. So let me turn this now
over to our first speaker. [APPLAUSE] HOLLAND: Good afternoon. It’s a pleasure to be here. When I first found out about
this conference several months ago, I was very interested
in attending this conference, because over the
last 20 years or so, I’ve been involved in a
series of policy issues. I did leave out one
part of my biography, that I actually worked at the
Office of Technology Assessment under Jack Gibbons and produced
a report on world petroleum availability that
almost succeeded in getting the organization
eliminated in 1980 since it got published during the Reagan
election win, campaign win. And while we thought we had
just a technical assessment, there were some
people who thought there were political
overtones in the report. I didn’t get the
organization eliminated, but I guess it survived
for another 25 years or so, or 20 years or so before
unfortunately, it’s in a state of
inactivity, I guess, is a good way of putting it. But since then, I’ve
also been involved in a series of issues related
to sort of high performance computing, information
assurance that involve the important
interactions with OSTP, and trying to convey what the
Defense Department can really do in certain
activities that are sort of both domestic
and international. But my boss this
morning, she found out that she had to be
somewhere this afternoon, and she gave me a
phone call and said, could I please give
this talk for her? So I agreed to do so. So the government can
move fast, you know? [LAUGHTER] At least I can. So there’s a little
bit of a caution here. This is sort of her
talk, but you know, whenever I stray a
little bit from what appears to be standard remarks,
it’s probably my remarks, and I’m the guilty
culprit if you want to refer back to anyone. What’s happening, of course,
in the Defense Department right now is like
every other agency, we’re going through a transition
from the political appointees at the top of the
previous administration to the replacements in
this administration. We have a new
secretary of defense. We have a new
undersecretary of defense. And then if we move down
the chain of command to science and technology,
we have Pete Aldridge, who went up for congressional
hearings last week, who’s in charge of acquisition,
technology, and logistics. It’s my guess he’ll probably
be confirmed this week. And then we’ll get down to the
director of defense research and engineering
position, which is the first major
position that oversees science and technology. I happen to be a
career political– I mean, I happen to
be a career employee in the federal government. Okay. A little bit about
the importance of science and technology to
the Department of Defense, our job is to make sure that we
develop superior and affordable technology that
give our soldiers warfighting and
war-winning capabilities. And we’ve been pretty successful
at that over the last 20 years. And I’ll tell you a
little bit about how we go about that business. If you look at some
of the advances that we rely upon today to
execute the missions that we’ve been successful
in such a stealth, night vision, global
positioning systems, phased array radars on Aegis,
lasers, adaptive optics– in the upper right-hand
corner of that slide, you see a picture of the
projected ABL system, for example, that comes
out of high-energy lasers. These are very
important capabilities for the Department of Defense. They’ve taken 20 or
so years to mature, and they require sort of a–
you know, a sustained investment in science and technology. If you think about
the ABL program, for example, their first work
on the chemical oxygen iodine laser was in the early ’70s. So we’ve actually
got a good portfolio of programs and techniques
for the current environment. But in fact, the current
environment is changing, and that’s part of the
challenges that we face. The challenges that the
Defense Department faces is in, I would say, at
least three dimensions. In one dimension, it’s
the fact that we’re doing something other than
just fighting one major threat, the former Soviet threat. We’re involved in
a series of sort of activities that range
from sort of peacekeeping to humanitarian. The second challenge
that we face is that we now have
adversaries who can attack us in asymmetric ways. We’re very concerned about sort
of chem biowarfare, information assurance. And the challenge
for us, of course, in the Defense
Department is not only to help us win the activities
that we’re involved in, but we sort of
have to understand what role we’re expected to
play in homeland defense also. The third challenge for
us or the third dimension is the globalization
of technology. With the web and
everything, people are getting access to
technology as quickly as we’re getting access
to it in most areas. And how do we quickly get
it into systems much faster than our adversary? So technology is both
a benefit and sort of a potential problem for us. But our belief is we’ve just
got to keep running faster. So how do we run faster? Well, we run faster
with dollars, and we spend it in
important areas. If you look at the roughly
$300 billion defense budget, there’s an RDT&E line which
everybody talks about, which is $41 billion. But it’s really the science
and technology dollars down there, the
roughly $9 billion that we use to
generate the ideas that are going to produce the
future forces that we have for the military departments. And there’s a classification
that goes from 6.1 to 6.3. That number is $9
billion this year. We’re reasonably optimistic. So now you can quote me
on this, and this is not my boss’s statement, that I
think that number will be up next year. So a couple of slides
quickly to try and set the stage for the
Defense Department. There are agencies
that have money, and then they give
the money to people. Within the Defense
Department, there’s the Army, the Navy,
the Air Force. There’s the Defense Advanced
Research Projects Agency. There’s the Office of
the Secretary of Defense, which I report to. And other agencies such
as [INAUDIBLE] and DTRA. And what you see here
is a color-coded chart that goes from 6.1 to 6.3. And this is how the
distribution of funds start. Each of these activities run
sort of competitive programs to attack their Title
X responsibilities. And we also do
joint planning, make sure we have an
integrated program. And this money then
from 6.1 to 6.3 goes out to academia,
the government labs, and to industry. And as you might expect,
in 6.1, universities are the major recipients
of that funding. As you move to 6.2,
the universities still get a reasonable
amount of money, but it’s sort of split
between the government labs and industry as being
the dominant funder. And then as you get closer
to more applied programs, it goes up. The contribution to
industry increases. A little bit about the
perspective of that money. If you really look at that
for the Defense Department as a whole, that money
in science and technology you saw for the Army, the
Navy, and the Air Force, that’s roughly 2% of
the service budgets. And we like to think
of it in this respect. What do you get for that 2%? Well, we do three things. We fight today or
we operate today. We’re trying to procure new
systems for the next force. So F-22, JSF. But I only list the politically
correct procurements underway, I guess, right now. And those are the ones here. But the S&T is really
about the force after next. It’s a small amount
of money, only being 2% of the service budget. Therefore, it’s important that
we spend every dollar wisely. And we always need to keep
reminding those people who have problems over here, this
is a small amount of money. We can’t really pay
the bills in case there are increased operations. We can’t pay the
bills in case there are cost overruns
on procurements. Well, how have we been
doing over history? Well, not a slide
I wanted to show, but I think we’re doing okay. In ’01, we’ve leveled off. But I think the ’02
number’s going to go up. What you see in the difference
between the appropriated and the president’s
budget request is that Congress always
gives us a little bit extra. A lot of times, that’s in
programs that we really want. Sometimes it’s– well, I think
we’d rather have a little bit more flexibility in the dollars. Okay. One last slide about budgets. We always put this slide up. To me, this is a slightly
depressing budget for one service, which
shows you that 12 years ago and in the late
’80s, the Air Force was the leading
service in investing in science and technology. And as you can see
now, it’s third. So what are the
challenges that face us, and what are we
trying to do about it? We’re a big believer
in basic research. We’re always worried
about the generation of new ideas, especially within
this era for which we seem to have some supremacy
and we really need to make sure that
we’re generating new talent. I mean, we have the same
concerns that Dr. Colwell has, and we have strong educational
programs and support for postdocs. But we need to keep
that pipeline full. We’re responding to some
really hard problems today. So as you think about
attacking things from the more applied side, I
would say the three challenges for us today that
are significant are chem biological defense,
information assurance. How do you protect
your networks? How do you ensure that
the commercial software that you buy from
somebody really is going to work as intended? And as we’ve sort of won
the ability in certain areas to be able to attack our
adversaries, what they’ve done is they’ve gone really
underground on us. A lot of facilities we’d like to
get at from chem bio to other, they’re either deep underground
or they’re in tunnels. And so we have a real challenge
about trying to figure out how to find those targets,
characterize those targets, and come up with mechanisms
for attacking those targets. And there’s a lot of science
and technology involved in that arena. We’re pursuing some
revolutionary capabilities. I’ll just list three here. We’re very interested in high
energy lasers for the ABL and other activities. Perhaps instead
of electric drive, it should say
electric technologies in general for both
unmanned vehicles, as well as sort of other
high-power applications. And we really think the time
is right to sort of pursue robotics, both in the air,
the ground, and the sea. In that regard, I would like to
say that the Army, for example, didn’t make it to Kosovo. And so they were
advised that, you know, you really are supposed to
show up in the first 30, 60, 90 days. And so the Army is undergoing
a major transformation. They have a series of sort of
contracts, grants and contracts [INAUDIBLE]. How do we become lighter? How do we actually
get somewhere in time? And so I think you’re going
to see a big change in the way the army is planning
to fight in the future. And then we have– not everything is revolutionary. You’ve really got to
sustain certain areas. High-performance computing,
computing architectures. Some areas that,
in fact, I think we’ve let fall below
the critical mass level. And I should say that in
additional technical issues, there’s a range of
non-technical issues. Sometimes you get
excited about the fact that budget’s going up one
year, but you can’t ever let your guard down,
because it might go back down the next year. We’re producing a
lot of technology. Our challenge is,
as I said earlier, is getting it into
fielded systems. And we have a big problem
with the S&T workforce. And for us, that’s academia as
well as the government labs. You know, how do
we generate people? How do we hire people? So we have a lot of
challenges, but I would like to conclude by
saying science and technology is very critical for the
Department of Defense. We take these
challenges seriously, because it’s very
important for us. Thank you. [APPLAUSE] MODERATOR: Do we
have some questions? HOLLAND: Yes? AUDIENCE: In your sales
campaign with the Congress, how much do you lose
because some of your things are so highly classified? HOLLAND: You know,
there are a lot of programs that I
don’t know about, and those programs that are so
highly classified, I wouldn’t know if we lost them or not. [LAUGHTER] So I don’t know. You know, the only thing– I used to have these discussions
with people in the Air Force. And of course it was, well,
maybe the Air Force doesn’t need so much in S&T,
because we’re really doing it all in the black. So that’s another
aspect of that question. I don’t really think they
are, but I don’t know, right? And the thing is that, you know,
with classification, there’s some good things
about classification. There’s some bad things
about classification. Yeah. Yes? AUDIENCE: [INAUDIBLE],,
I was impressed with the effort of Andy
Marshall and others and doing a new [INAUDIBLE]
bottoms up review on defense strategy. I was really impressed,
because I frankly felt that in the Clinton years, the
attempt on the quadrennial review [INAUDIBLE] fighting
two wars at the same time, opposite ends of the Earth
with no allies was a figment of somebody’s
imagination rather than– MODERATOR: [INAUDIBLE] AUDIENCE: Oh. Figment of imagination
rather than someone’s realistic estimate
of a credible threat. What was the threat scenario
used in this review? Or can you talk about that yet? HOLLAND: Well, you know, I’m
not part of the Army Marshall review. Like you, I’m still waiting
to hear exactly the outcome of that review. AUDIENCE: It’s not known within
the even OSD what’s going on? HOLLAND: I would say– I would only answer that I
personally do not know that. AUDIENCE: Okay. You have any idea of
when that’s going to be– HOLLAND: I mean,
Andy Marshall works in the office of
Secretary of Defense, so it’s [INAUDIBLE] OSD
at the highest levels. But I’m just not party to that. MODERATOR: We’ll take
one final question. Gene? AUDIENCE: I’m just
curious when– MODERATOR: Mic, Gene. AUDIENCE: I’m just curious
whether in the budget, national missile defense will
come out of your future S&T, or whether it has
to be an add-on. HOLLAND: You mean,
do I think it’s going to come out of that $9 billion? If you’re asking me for
an unofficial statement, I don’t think the S&T– the current S&T budget
is going to pay for NMD. MODERATOR: Okay. Thank you very much. [APPLAUSE] Phil? SHARP: [INAUDIBLE]. Thank you. It’s been an enjoyable day,
and I congratulate the OSTP on its 25th anniversary. My relationship
with OSTP is that I had the pleasure of
serving on PCAST under Jack Gibbons for a number of
years, and it taught me that public policy
is a slow process. [LAUGHTER] It takes years sometimes. And being there
at the right time to say the right word
at the right place is key to the whole process. We heard today a
number of issues that I had listed on
my comment to raise as issues that a science
advisor and OSTP might address in the future, things
like stem cells and cloning and human genetics
and genetic engineering. All these are very
significant issues that has been mentioned
throughout today. They all directly
address the issue of what it means in
some ways to be human. We are beginning to
understand more and more about the human creature, and
to understand how it evolved and how it functions. And this information
is very new, challenges a lot of
people’s thoughts, and will always be a very
complicated political issue. But as we work
through that, I want to hark back to the beginning of
biotechnology for a few moments and remind you of where
this science came from and how it was introduced. Obviously, the origins
of biotechnology really began in ’53
with Watson and Crick discovering the structure of DNA
and the birth of the discipline of molecular biology. And then over the intervening
years from ’53 to the mid ’70s, universities such as MIT
and Harvard and many others made large investments
in molecular biology, primarily because it
was an intellectually challenging and exciting
new frontier in science. There was very little
or almost no discussion of the potential applications
of this technology to either societal
problems in pharmaceuticals or in any other aspect. And then in mid ’70s,
there was this discovery of recombinant DNA, the ability
to genetically engineer DNA, join DNA together. And the scientific
community stepped back at that moment in the
mid ’70s and said, let’s debate this issue. And there was a large and
very widespread public debate. And in fact, a year
ago, I had the pleasure of going out to celebrate the
25th anniversary of Asilomar, where a group of
scientists met and debated after a moratorium, a moratorium
respected around the world, I should note, doing
recombinant DNA. Debated the introduction
of this technology and how this introduction
should be regulated as it’s introduced into society. And I want to remind you of
what those regulations were. They were guidelines. They were guidelines
left at the level of NIH. And those guidelines
were meant to evolve as the technology evolved. And through this
very public process, we gained the confidence,
both of the country and of the city of
Cambridge ultimately, to begin this research. And this was painful. Believe me, this was painful
for a young scientist such as myself
who’d just arrived at MIT who wanted nothing
more than to be left alone in the laboratory to exploit
this wonderful technology for which I could explore
the essence of what a human cell was like. But it was out of
that public debate and out of that public response
that we gained the confidence of the country to move forward. And we have embraced genetic
engineering and recombinant DNA in this country as
no other country has. And I believe it was this
public process that achieved it. Now we’re setting out a second
revolution, a revolution that I would hearken
back to being as great as the
recombinant DNA revolution. And that revolution is being
brought by the human genome sequence and the advent of
large, massive sequencing. And this information is wedding
in the most simplistic way biology and computation
and informational sciences. And we are collecting massive
amounts of information that we can then use as
we come to each experiment and try to understand
how biological systems both function in multi-gene
analysis, systems biology, as well as how they
arose in evolution. And this is a wonderful advance
brought forth by public funding and in the very public sector. And I want to say one
thing about this science. It needs to continue. After we sequence a human
with this technology, we’re just beginning. We need to sequence the
mouse, and that’s ongoing. We need to sequence the rat. But we need to sequence
about all organisms. We need to sequence this plant. We need to sequence that flower. We need to sequence
every agricultural crop. We need to sequence
mosquitoes in Brazil. We need to sequence. And because we have
learned that obtaining the sequence of a wide variety
of organisms and comparing them is the most direct and
powerful and cost-efficient way of understanding how
biological systems function and how they arose in evolution. Now the sequence itself
of the human genome is not even close
to being the end of the science of studying man. If you look at the
initial publications which proposed 35,000
genes, I can tell you from detailed analysis
of what a gene is like, we don’t know how many
genes are in a human genome. 35,000 is a good guess,
but it could be something– depending on how you define
a gene as much larger, or it even could be
more simple if you’re looking at specific functions. And if we look at
those 35,000 genes, we only know the function. We don’t know the function
at all of 42% of them. Of the other 58%, we know
the general function, but not the specific function
for most of them. So we know the specific
function of only about 10%. 15%, I would say,
of the human genome. So there’s a great deal
of science to be done, and it will be the basis of
increasing rate of discovery, which will drive biomedical
science and biotechnology to create new and
more sophisticated drugs and therapies
and treatments over the next decades. And then society is going
to look at that technology and have to come to grips
with the issue of how we deal with the cost of medical care. Cost of medical care, the
total fraction of cost is approximately 15% to 20%
of the gross national product. This new technology
is going to drive it. There’s going to be change to
pharmaceuticals [INAUDIBLE].. Maybe in hospitalization and
changes in the whole process. And that in essence is going to
be part of a political process that the country is
going to have to decide how it’s going to do it. However, new
technology is coming, and the new technology
will drive this change. And that is mostly
biomedical science. Now behind this human genome
sequence is human genetics, and it will be the most
direct and immediate impact of having the sequence. We will have rapid
advances in human genetics to both diagnose
and then predict the treatment of diseases. But as you well know, and has
been mentioned several times, the application and distribution
of human genetic information across society is a major issue
dealing with genetic privacy, informed consent in
terms of obtaining the genetic material of
individuals, disclosure of genetic information, job
discrimination, and insurance coverage. All these issues
are very important. Have to be dealt with in a
political and societal means. And we heard today
from Harold and others about this as policy issues. I only want to raise one
little sector of this. It’s how you draft those
regulations is going to impact on how this science advances. So you have to
remember as you draft these regulations that the
science is going to change. The power of science
changes much more rapidly than you anticipate. What is one issue today
is another issue tomorrow. And if you have
to go to Congress to change laws or rules,
it’s a very slow process. So when possible, that should
be incremental in any way that you can make it. Now as we’ve heard
today, and I just want to reiterate the
statement, being a biologist, it has been a fantastic
vote of confidence in my science in the
doubling of the NIH budget. But I have to echo
the words that others have said as to how important
it is for biological science that research moneys in
math, physics, chemistry, and engineering
is also increased. One of the major limitations
now in biotechnology is actually production of
these very large, complicated biological molecules. Fermentation tanks, facilities
that cost hundreds of million dollars to put together. It is actually limiting
for some therapeutics now to produce them
with technology. And it is engineers
and process scientists who know how to do this and
are needed in that technology. In the area of imaging
and the human brain, if I could image activity
in the human brain at the level of a
single cell in the time resolution of a millisecond,
I could give you fundamental advances in how
the human brain processes information that I am certain
will lead to treatment and control of diseases
that we can’t treat now and are tragic in terms of the
humanity of specific people. And that advance is directly
dependent upon engineering, physics, and chemistry,
because that’s where the science has to come
from that’ll make ultimately that type of advance. I want to say one thing
about stem cells, which have been mentioned
here many times before, and that is that
stem cell research is one of the more exciting
frontiers developing in human physiology. I have seen
publications of people who have been able to use stem
cells to regenerate liver. I’ve seen publications of stem
cells regenerating muscle. I’ve seen publications of
stem cells taken from humans, put into mouse, and
regenerating in mouse what looks like neurons. Now you may ask, why
would a scientist put a stem cell of a human into
a mouse and generate neurons? Are they asking for trouble? No. But what we could
do by that method, if it turns out that
these are really truly functional
neurons, is to understand the nature of genetic
diseases in men by studying the
physiology of them in a complex model
system where we can look at directly the
function of a cell in a wiring complicated
physiological system. So I can’t tell you
where stem cells are going to lead in the
potential understanding and treatment of
human disease, but I do know it’s an important
area of science. It’s an area in
which we need to deal with the issues of
public policy and how stem cells are obtained. There are multiple
sources of stem cells. Not all of them are
equivalent, and we need the access to stem cells
from early embryonic tissue or eggs to actually fully
explore this area of science. Last, I want to mention the
international nature of science and health. We have seen in
the press daily now the debate of the control
of AIDS in South Africa and in the third world. And clearly, health and health
policy in the third world influences us. The world is a small place
with very rapid travel between different
places, and how HIV is controlled
in the third world impacts on us not only in the
context of the virus moving from one location to the
other, but in the context of drug-resistant
variance arising that will quickly bypass the
therapeutics that we have. So developing an understanding
and international control of disease is an important
issue for this country and for the health of the
citizens in this country. And I only have to remember last
summer when my home in Newton was sprayed because
someone found a crow that was dead with
West Nile virus in it. And in fact, all of Cambridge
was sprayed several times by helicopter because
of a West Nile virus being found in crows that
were dead in this part of the country. Now I don’t know if
we’re going to have West Nile reappear this summer. It is possible. But in essence, this
is a small world, and we need to
deal with diseases in an international way. And I want to end with
one statement about this. Ultimate control
of HIV in the world is going to depend on vaccines. Vaccines are underdeveloped. It should shortly be
hopefully possible to develop a vaccine against HIV. And as soon as we have a
vaccine against HIV, which will have to be developed
and in some way tested in third world as
well as the US, we’re going to have to
have a policy of how to distribute that vaccine
in the third world. And I expect that
to be a major issue if we are so lucky as to be able
to develop one in the next four years. Thank you. [APPLAUSE] MODERATOR: Thanks, Phil. Questions? Yes? AUDIENCE: One big difference
between Asilomar and now is the emergence of
the biotech industry. And you’re proposing
a model of regulation which is built on
voluntary compliance, or at the most,
restrictions on what people who get federal funds do as
in stem cells and cloning. And I wonder whether the
community of scientists is strong enough to bring
the biotech industry into some community
standards in the present era. Is this mode of regulation
really relevant for today, given the differences
between now and the beginning of the period? SHARP: I want to
make two statements. Maybe I was not clear. One of the take-home
messages from my comments about recombinant DNA and
the introduction of it is that it is healthy
for wide public debate. So in GMO organisms, what we
missed in the last 15 years is a wide public debate of
how those organisms were used. So I think the public
debate is the only way to reach consensus. Second I’ll save
for the biotech and the pharmaceutical industry. There is nothing that
shakes one of the executives and those industries as much
as the prospect of litigation. So if there is a public
policy that says, we do not do x, I can
almost guarantee you that in the private
sector related to that, x will not be done
because of this issue. So in the pharmaceutical
industries that depend upon obviously societal support
through the stock market and other means, I cannot say
what the response would be in other private organizations
that might be much smaller and more entrepreneurial. But I don’t believe in
large pharmaceuticals, if there was a public policy
that was uniformly recommended, that they would bridge that. AUDIENCE: Yes. Do you see the future
of proteomics– MODERATOR: Excuse
me, use the mic. AUDIENCE: Oh, I’m sorry. AUDIENCE: Do you see the future
of proteomics being perhaps more promising than genomics? [LAUGH] SHARP: I’m so flush with
excitement about genomics right now and trying to bring
that to fruition, I wouldn’t want to answer the question. Proteomics is a very
important technology. It is an area of
science that doesn’t have a simple one
answer like genomics. There’s only one genome. You’ve got the
sequence the genome, you know what the
sequence of the genome is. Proteomics is a much more
open-ended subject, much more biological. And in many ways,
much more interesting and profound because of that. But how it will impact on
society through the development and treatment of disease,
understanding diagnosis and treatment of
disease, is before us. AUDIENCE: Hi. So if biotechnology
is essentially sort of the mix between
engineering and medicine, what was being discussed
before in terms of engineering ethics and its relation
to medicine when it comes to something like an HIV vaccine
in context of, let’s say, a trillion dollar tax cut? What do you think
that debate will look like in terms of
current pharmaceutical policy and general societal feeling
towards helping people in the third world with diseases
we know how to cure already? SHARP: I don’t think– there’s a lot of issues in
there, but I’ll take one. [LAUGH] Biotechnology and a large number
of pharmaceutical companies are making large investments in
how to develop an HIV vaccine, and that’s wonderful. I would love to have, and the
society needs an HIV vaccine. At the time in making
the decision as to how this vaccine, if we are so
successful as to achieve one, is going to be made
available in the third world, you can’t leave that
on the shoulders of the pharmaceutical industry. That’s going to have to be
a participation by a broader society who is also going
to invest in some ways in doing that, because
it’s just something that a subset of the
whole sector of society would not be able to do. It’s a broader
question, and we’re going to have to develop a
national consensus that that’s important for national health. [APPLAUSE] CLARK: Good afternoon. So it’s getting late
in the day, and I have 15 minutes to say
something new and interesting about the internet, which
is a bit of a challenge, since I think all known
pundits have tried to do exactly the same thing. Sort of a worn out
topic, but I’ll try. I note that the OSTP
and the internet are about the same age. If you want to make the
internet look older, you can tack the ARPANET
years onto the beginning. But basically, what I call real
internet data started flowing sometime around the mid 1970s. And so that’s only
about 25 years. That’s a rather
astonishing amount of stuff that’s happened. It doesn’t seem that
long ago, although from a personal perspective,
I got my PhD in 1973, so I guess it’s been
my whole career. Sort of, time flies when you’re
having fun kind of a situation. We spent the ’70s basically
just getting the basic structure right. I like to remind people how
little we knew in the 1970s. We didn’t even
have the experience back then or the confidence
to believe we could write down a specification such that if two
people then went off and wrote some code based on
that specification that the resulting systems
would talk to each other. Unless you can do that, you
can’t build an open system, and there was a lot of
doubt that we could actually build it. Today, it seems sort of obvious. But in fact, it wasn’t
until it was proved. And that was sort of the
1970s of the internet era. So what happened
in the 1980s was we dealt with the problem
of getting big. And Bill talked about, well,
there’s the classic engineer. First you specify, and then
you design and you build and you test. Well, the internet ain’t that. The internet’s classic
example of a system that was hardly ever
designed and we’ll never get done building it. We’ve been doing remedial
engineering of a sort that sometimes we’re
proud of and sometimes we hide for about 24 years. What happened in the 1980s
is people figured out some of the original design
decisions wouldn’t scale. For example, in the
beginning, we named computers in a very simple way. They had names like MIT 1,
MIT 2, MIT 3, and that was it. Okay. Well, that doesn’t scale to,
say, 100 million computers. So computer scientists
applied the only technology they have to solve this
problem, which is hierarchy, and that’s what gave us
the domain name system. So now you get names like, you
know, mumblemumble.lcs.mit.edu. We had to do the same
thing with the addresses. It used to be we had a very
simple address structure. We could name a huge number of
networks, like 256, I think. We’ve actually realized
that that was wrong twice. And we also had to
change the routing, the way we send little
messages around the internet. Initially, every single
machine in the internet knew about every other machine. We said, well, you know, if you
have a few million machines, that’s not going to work. So we impose hierarchy, right? The other thing we
did in the 1980s is we realized that the
management structure itself was getting big, and
we had to organize that. When we started, there
were 12 people in the room, and we could do anything we
wanted, because nobody cared. And sometime in the ’80s,
there was a watershed meeting. We held a meeting,
and 100 people came. And we basically said, oh gosh. Unless we do something,
we’re going to die. And so we did the only good
thing you know how to do. We created hierarchy. We created a person in charge
in areas and subcommittees and working groups. And in fact, that has, along
with some more formal design processes, done pretty well. Today, the internet
meetings are still open. Anybody can go to an
engineering task force meeting. Typical attendance
would be about 2,000. Most people find it a little
overwhelming, but you can come. The other thing that happened
in the ’80s, in the late ’80s, something happened that was
important to me personally. I was asked to be on a study
committee of the Computer Science and
Telecommunications Board, which is part of the National
Academies down in Washington. It was actually one of the first
studies that the CSTB released. It was called Toward a
National Research Network. And it was the encouragement to
the National Science Foundation to build up the network
that became the NSFNET. There was originally
one built out of– I hate to remind people– 56 kilobit links. Our national links
in the beginning were the speed you can get
the data, the dial-up modem. And that went to T1, which
is a megabit and a half, and then it went to DS3. And it was only in
1988 that the advice to the NSF that this
was a good thing and they should keep doing
it came out of the CSTB. It was also a milestone for
me, because it represented an opportunity to get exposed
to people, not all of whom were pure techies. I met the board
director, a woman named Marjory Blumenthal,
who basically beat me up and persuaded me it
was appropriate to talk to economists and lawyers
and social advocates and policymakers. And this was quite
a revelation to me. I actually ended up working on
a series of internet studies for the board. Those are interesting
check points. How did we think about
this at various times in the distant past that
we can no longer remember, like six years ago? So if the ’80s were the
decade of getting big, the ’90s were the decade
of commercialization. Commercial internet
service providers appeared as a new
industry player, and they proposed to start
carrying internet traffic as a profit-making venture,
which in the beginning was remarkable and astonishing. [INAUDIBLE] people
actually think they’re going to make money doing this? That really sped things up. I like to remember that
NSFNET was decommissioned in 1994, plus or minus
a year, depending on how you think about it. That’s only, like, six
or seven years ago. All of the commercial
activity, the investment, the internet bubble, the
shattered stock prices, all of this has
happened in something like seven years, which
is really quite amazing. So now the question is, what
does the next decade bring? We’ve gone through the ’70s
and the ’80s and the ’90s. I don’t know– what do
you call the next decade? The ’00s? I don’t know. What comes after
commercialization? Well, the overused
word is convergence. I would say collision. What happened in
the ’80s and ’90s, this tremendous expansion
that we saw, really occurred unimpeded because it was
happening in a vacuum. If you think about the
worldwide web, when it happened, there wasn’t a pre-existing
industry player that supplied sort of
proprietary web service. It was an empty space, and
the web just blew into it. Same for email. Actually, if you want to think
about a cycle of innovation, the web is a
fascinating example. The web at the time when
it was first proposed was not a new idea. If you chase back the general
vision of linked information, you go back at least
to Vannevar Bush. And there were prior attempts
to do something like the web, but they fizzled. They didn’t launch. The timing wasn’t right or
they were too proprietary, or something happened. Well, when the web launched,
it launched about as fast as anything we’ve seen. I mean, maybe Napster
launched faster, but then it didn’t
achieve orbit. The first working paper
for the web was about 1990. Tim Berners Lee wrote it, and
he still has it on his wall. So that’s almost–
you know, it’s not quite 11 years
from very first concept to what we see today. I find that astonishing too. But at the same time, it’s
an anomaly, because as I say, these things happened
in the vacuum. As soon as you say the words
internet telephony or internet music distribution
or internet radio, you’re launching into a space
occupied by an entrenched, multi-hundred-billion-dollar
industrial player. And he doesn’t just roll over
and die when you touch him. At a minimum, he
thrashes around a lot. And even if he
eventually dies, he does a lot of damage
in the meantime. So it’s interesting to ask,
can you actually imagine a telephone company dying? I was interested that the
recent rumor that got loose that Lucent was about
to file for bankruptcy caused its price to drop from
its current miserable level of $9 to an even more
miserable level of $6. So there were people out
there who believed it. And there was a senior vice
president of AT&T in 1995 who said to me, you
know, the only problem that AT&T has over
the next 10 years is to move from our
current revenue model to a new revenue model
without accidentally going out of business in
the next 10 years. [LAUGHTER] So they have three or
four more years to try it. They’ve since then torn
themselves apart three times, or twice. Now of course, the
telephone industry’s special, because
not only did they have to deal with the
internet, but they had to deal with being– the imposition of
competition on what had been a monopoly
and the whole sort of aftershocks of divestiture. So they had two problems at
once, which is probably more than most people can bear. But what happens when you run
into a pre-existing industry? Well, some things are obvious. One is, of course,
the growth slows. Okay? Another thing that happens
is that across the boundary of the collision, you get
slow diffusion of insight. So internet people got a
little more like bell heads, and bell heads got a little
bit more like internet people. But the diffusion
process was slow. We had cultural problems. But the thing that really
was bucket of cold water to the internet designers,
who of course had grown up in what you might call the
Silicon Valley mentality, is that some of these
industries came equipped with something we
hadn’t seen before, which was a
regulatory framework. And people were
saying, well, you know, if you’re going to carry
internet telephone calls, then you should be regulated
like a telephone company. That was an unthinkable thought. That was a heresy. That was like we’d
entered a different world. I guess it was just– it
happened to be the one that was centered in Washington, DC. And the real
horrifying insight was that this was only the
first of many collisions. We said, internet telephony
first, and so the telephone companies went– [CLEARS THROAT] But internet radio has
its regulatory context. Internet and music
distribution and what you might call some concerns about
intellectual property rights. We might discover we
carried every single one of those burdens
at the same time. If the internet
can carry anything for some value of
anything, then don’t we have all of these obligations? Aren’t we simultaneously
a content distributor and a common carrier? This is an alarming thought. And sometime in the ’90s,
it came into focus for me in a very clear way, which is
the revelation that the techies were no longer in charge. They we’re simply going
along for the ride. And I have to say, that’s when
the CSTB, where I had a chance to talk to economists and
businessmen and lawyers, got more interesting. I joke I spent 10 years learning
how to talk to economists, and now I have to
talk to lawyers. Trying to talk to the
FCC the first time was a total disaster. So what’s going to
happen in the ’00s? Well, another thing
is we’re going to have to figure out how
to pay for the internet. I don’t actually
believe in banner ads. But if banner ads tank,
then what happens? Well, if the revenue for
the web pages dries up, then there aren’t
as many web pages. If there aren’t many web
pages, then maybe the consumer experience gets boring. And if the consumer
experience gets boring, they stop buying
the whole thing. Goes back and crawls in a
hole, and it was all a mistake. You know, that’s a
little pessimistic. But part of what I
did learn is that we don’t know how to route money
around the internet very well. We can’t implement all the value
equations that people have. And somebody very
cynically said, you’re a bunch of damn techies. You were good at
routing packets. You’re lousy at routing money. And I have to say, back
in 1975 or even ’85, it was hard to realize that
the internet was really about routing money. But you know, okay. Wake up. So here’s the third
point about the ’00s. What we’re really going to have
to deal with in the next decade is the extent to which
society has a say in how the internet comes out. In 1990– I don’t know, 2, there
was an interesting phenomenon which is Gore stood
up and said, I have a vision of the national
information infrastructure. And it was an interesting
moment for me. He said that, and there was
this [INAUDIBLE] feeding frenzy when everybody came to
Washington to get the money. And then he said, the private
sector will build the NII, and they all went away again. Now there was actually sort
of spontaneous creation of various sort of
standards, bodies, and advocacy groups, which
having come into existence in that moment, immediately
set about preserving their own existence. But you know, they faded
into the landscape. We hardly think
about them anymore. But what I learned
is that a vision is a dangerous thing, especially
to the private sector. The private sector sort
of explores the world by experimenting
in all directions. And if you survive,
you get to play again. And a vision tilts
the playing field. And what happens if I tilt
the playing field against you? Well, that’s completely
unacceptable. So a vision is a
very dangerous thing. So what really happened right
then to a significant extent is that we, where we, a
sum value, the government representing society or the
internet leaders who suddenly realized we no longer
had a mandate to lead, we took our hands
off the controls, and the internet
sort of drifted. I’m sorry. Drifted is too passive a word. Went in all directions
as fast as it could. Okay. Well, how’s it going to come
out over the next 10 years? It’s going to take
a lot of talking. And what interests me– you know, my
libertarian friends say, well, I’m worried about
the government getting involved in the internet. That doesn’t
particularly worry me. We sort of know what
the government does. What worries me is the new
industrial players we created. Think about the internet
service provider for a minute. You can predict what the
government’s going to do. They’re concerned with law
enforcement and consumer protection. But what’s the ISP want to do? It wants to make money. Having created [INAUDIBLE] a
profit-making organization. How’s it going to make money? Well, any way he
can figure out that doesn’t fall prey
to, say, antitrust. And it’s an interesting
structural problem. The ISP sits in the
center of the net. Well, what’s in the
center of the net? Just packet forwarding. It’s very primitive. So it’s pretty much
a commodity business. If you’re in the middle and
you’d like to make money, what would you like to do? You’d like to get control
of what people are doing. Well, the internet was
supposed to be transparent. Carry any kind of packet. What happens when
you get in the middle and you start controlling
what people can do? For example, some
ISPs, they have rules. They say, you can’t have
a server in your house. You can’t have a game
server or a web server or this kind of server or that. If you want to have a server,
you’ve got to pay me more. You can have a
client in your house. Well, to a person who’s
familiar with sort of the economics
of value pricing, that’s just trying to discover
the internet equivalent of the Saturday night stay. But classic internet thinkers,
it’s simply a moral wrong. It needs to be rectified. We’re going to have
to sort this out, and it’s going to
take a lot of talking. So what can we say
about the future? Well, the first thing is the
results of commercialization are not clear. It’s going to work itself out
in the next decade, I think. It’s going to result
no doubt in calls to the government to protect the
internet, protect its virtue, protect the purity of
the end-to-end argument. Maybe it’s an argument
that the internet should be defined by the government. And we’re going to have a rather
fascinating societal debate about who’s in
charge, or at least who gets to sit at the table
when the future of the internet is debated. We’re going to sort out
the role of the government, and it’s going to be a new role,
because they’re not in charge nor are they completely
stepping away from the table. I said I don’t necessarily
believe that we’re doing a good job of convergence. But when you get these
collisions between sectors, one of the things that
inevitably happens is that boundaries blur, and
you have to deal with that. We sort of have confidence that
we know what a phone call is. But what’s an internet
telephone call? Well, is it a phone call if by
definition you cannot dial 911? Is it a phone call
if it doesn’t ring? Now that’s a scary space. We’re talking about the
edge of definitions. Engineers like to stand in
the middle of definitions. You say, oh, build a bridge
that holds up 10,000 pounds. Well, fine. We say, I’ll build a bridge
that can hold up 30,000 so I don’t have to think
about the edges of the def– no engineer asked to build
a bridge that holds up 10,000 pounds would build
a bridge that falls down at 10,100. Who likes to stand at the
edge of a definition and say, am I over the line yet? Am I over [INAUDIBLE]? He’s called a lawyer. [LAUGHTER] Lawyers like the edges
of definitions, right? And judges. Why do we call them [INAUDIBLE]? They picked the job of standing
on a slippery slope, right? So all of a sudden, we’re going
to have lawyers telling us what is and is not internet
radio, what is and is not an internet telephone call. Okay. It’s really scary, okay? It’s also reality. Now the last
observation I would make is that we still have a
lot of remedial engineering to do in the internet. And in the 1980s, the
remedial engineering had to do with getting big. In the ’90s, the
remedial engineering had to do with the fact
that commercialization raised some special problems. In the ’00s, the remedial
engineering will have to do with addressing some
serious social issues. And this brings me
back to the space that Dan Hastings
was talking about, because I go to some of
my colleagues and I say, here’s a good, hard,
technical problem. And they say, but that’s
just a social issue. I don’t want to work on that. We have something broken
in our collective culture. Even a hard technical
problem that derives from a social
motivation as opposed to, it doesn’t go fast enough. We should stop being a
speed-centered discipline. Somehow seems less
exciting, credible, hard. We have to get over that. And of course, the other thing
we have to do in the ’00s is figure out how to pay for it. [APPLAUSE] MODERATOR: We have time for
one quick question for Dave. Okay. CLARK: I detect there
are no quick questions. You’ve left us speechless. [LAUGHTER] Rod. PRINN: Well, I’m going to
talk about global warming. I realize this is one of the
many environmental issues that face us. But I think it provides a good
paradigm of the difficulty in translating scientific
research into a form that can be understood by the public. MODERATOR: [INAUDIBLE] PRINN: So I’ll– so the focus– is it on now? MODERATOR: Yes. PRINN: I’ll focus my talk around
communication of the science, but at the same time,
take the opportunity to tell you about where the
science of global warming stands at the present time. Now there are a variety of
ways in which people have tried to communicate global warming,
and here’s a recent example which is useful. I think that it
probably made people buy this particular issue
of Time magazine, at least to find out what was going on. However, you look at this,
and you decide, you know, it’s a frying pan
with an egg in it. And some people may
get deeply worried about that, that we’re frying
the Earth, which is clearly a very wrong depiction of
what global warming is about. At the same time, if
you like fried eggs, you might conclude that
global warming is good. [LAUGHTER] So that’s an attempt, and
maybe it has some success. Another way to do it,
which I’ve used many times, is to use simple cartoons. And this is an example
of one of them. Schematic of the
greenhouse issue. And this can be useful. I use this to make the
point that the greenhouse effect is real. Despite what you
may hear sometimes, the greenhouse effect
is a real effect. On the left-hand side here, it’s
a reasonable place to start, because we’re talking
about human activity. Anthropogenic is a fancy
word for human activity. Anthropogenic and
natural sources of greenhouse gases
and also aerosols, which I’ll say
something briefly about, we are adding these
into the atmosphere. And then there are
various natural sinks for these chemical
compounds, these gases, and these particles
in the atmosphere. Now these gases have
the important property that they absorb infrared
radiation that radiates off from the surface of the planet. The planet can radiate
energy to space to make up for the input
of energy from the sun. And if it does that
in equal amounts, then it can remain in
an equitable and fairly equilibrium climate. Added to the complexity is the
fact that the ocean can take up some heat, and on a time
scale of 100 to 1,000 years, can play a profound role in
slowing down or speeding up the amount of climate change
that may be occurring. Aerosols add a complexity. Man-made aerosols, in fact,
reflect sunlight to space, and that’s the point of the
little piece of the cartoon on your left-hand side. This is useful, I think,
as a communication device. It’s particularly
useful, I think, to people who have a little
bit of scientific training and know what
infrared radiation is. Most people know what
solar radiation is. So it is helpful, and it’s one
approach that I’ve found useful in many audiences. Another one is to actually
show people some evidence of past climate change. People on the street have
heard about ice ages. So another way is to
sneak in some science by showing them a long-term
record of the ice ages. I hope this projects
reasonably well in the back. But on the left-hand side
of this diagram is today, and on the right-hand
side is 400,000 years ago. This information comes from
drilling into the Vostok area of Antarctica. The uppermost curve is the
trace of carbon dioxide levels in the ice core going
back to 400,000 years ago. The middle curve, the red
curve, is the temperature derived from the ice core. And the lower curve is
methane concentrations derived from the ice core. And this is a good way
of telling people firstly that carbon dioxide and
methane are greenhouse gases. And for them to
notice something, that there is a very
strong correlation going back 400,000 years between
levels of methane and carbon dioxide and temperature,
such that the higher the levels of these
greenhouse gases, the higher the temperature. I should interject that you
can’t explain these climate changes by these relatively
small changes in the greenhouse gases, but at least this
tells the scientists there’s a positive
feedback here, that if you do warm
the world a bit, you get more methane
and carbon dioxide. That’s worrisome. Climate scientists do not like
to discover positive feedback, but they exist in the system. So this tells you that the
greenhouse gases are certainly active and that
climate does change. And of course, the cool times,
the dips in these curves, are the various ice ages. Then you go back
through time, and you see that we’ve had a
variety of ice ages. This is the most recent. Then we had the very warm
period of the [INAUDIBLE].. Another ice age, another
warm interglacial. An ice age, a warm
interglacial, and so on. Of course, the human influence
on this diagram is very small. We’re just existing
here at the point here of the very
beginning of this plot on the left-hand side. So this doesn’t tell us
about the human influence, but at least it
might help convince the person on the street
that climate does change, that it is not a constant. So then to talk about things
closer to the present day, it’s useful then to look at the
reconstructions of temperature change. And I want to go to the one
on the bottom first that says the past 1,000 years. So now we’re getting a
closer and closer focus onto today’s times. This goes from the year
1000 to the year 2000. And the blue curve
that you see there with the sort of light
blue shading around it is an attempt to
reconstruct temperatures from a variety of
proxy approaches, from tree rings,
corals, ice cores. Of these, probably the ice
cores are the most reliable, and those are the ones that
provided the record that I just showed you on the
previous graph. If you believe the
central estimates here, you’d say, well, the world was
calling a very small amount. But clearly, what’s happened
in the last 150 years is that we are rising
way out beyond this range of variability that we saw
in the past 1,000 years, and we’re way up here. Now even if you are
a skeptic and you want to believe that the
blue here, that I could start here and have
the best estimate going from here over to here rather
than in this direction, you would still reach
the strong conclusion that we seem to be rising out
of the noise of the system in the last 1,000 years. You can quibble the way
these are reconstructed. But if you believe
this information that I’ve got in front of you,
you do come to that conclusion. In other words, that the
world really is warming up. Now if you focus in the last 140
years and look in more detail, this is now dependent on
the thermometer record. So these are direct
measures of temperature. There are all sorts of
difficulties in the thermometer record to do with spatial
and temporal sampling biases. And you can imagine the
southern hemisphere being poorly covered in the last century,
vast parts of the ocean similarly. Nevertheless, this is an
attempt, a best attempt around to reconstruct what’s
gone on in the last 140 years. And again, you see
through to the year 1900, it seems to have
been rather constant. Between 1900 and
1945, a significant rise in temperature. 1945 to about 1970 or so, it
actually cooled a little bit. And then 1970 onwards,
significant warming. Now there’s a lot
of research gone on in the past two or three
years in particular on trying to work out what
fraction of this warming is due to human
activity and what might be due to natural activity. And you can imagine
for that, you’ve got to have some idea of how
the natural system works, and that proves to be a
problem in this research. But there’s little
doubt in my own mind that there is a human
influence on climate, and it’s evident in
that warming sequence. I can’t tell you what
the percentage is. It might be only 10%. It might be 50%. But it’s there. And you get that
conclusion from looking at the pattern of the warming
and seeing that there are patterns in the warming that– what you might expect due
to rising greenhouse gases. It still remains a
matter of controversy about what the fraction
of the warming we see. The warming is definitely
there, but the fraction due to human
influence is debated. So what do we do if we want
to forecast into the future if we’re convinced that
at least humans have some small influence
on the system? In 1990, I was interested
in this problem, but then I just quickly
discovered something that had me worried, and
that is to project climate into the future,
I needed to know about human activity
in the future, and then I had to go
talk to economists. And well, it happened. We got together. We got a group here together. And this is just
a cartoon to show you the various elements
of a global system model that we put together. There’s an economic
model up here. There’s a climate model here. There’s an ecosystem
model here, and there’s a model of natural emissions
of various greenhouse gases over here. And you can see all the
arrows going between them. This is a highly
[INAUDIBLE] system, a great deal of complexity
in each of these models. And each of the models
has great uncertainty. Now to do this type of exercise
and to attempt to do what we really wanted to do– that
is, to get our arms around the range of possible outcomes
looking at the next 100 years– it’s a big task. And of course, it requires
an unusual combination of intelligence, computer
technology, and arrogance to do this sort of thing. And those are qualities that are
often found here at MIT, so– [LAUGHTER] So we were in good shape
to do that sort of thing. First thing we did is we
forecast seven forecasts, because three years ago, we
didn’t have the computed power that we have today,
and so we decided we would do seven forecasts. We recognized from the beginning
that economic models have huge uncertainties, all right? I thought climate
models were uncertain. Then I learned further
about uncertainties when I talked to economists
constructing their models. Nevertheless, we’ve made
a very detailed attempt to get our hands around
those uncertainties. And for the climate model,
the model that we have here, it’s a highly flexible model. And it has the
advantage that we can make sure that the various
versions of the model that we put in an uncertainty analysis,
that they at least can simulate or lay within the
envelope of the temperature changes in the last
140 years where we have some idea of
the greenhouse gas emissions in their time. So we can test or make sure
that the climate model versions that we use at least give
a reasonable simulation of past climate. And so that’s a
constraint on the process. And this also enables me
to point something out that may not be
known to many of you, and that is that if you
look at climate predictions from our climate
model and many others, if this is the north pole and
this is the south pole here, and this is just degrees
of temperature rise, and these are the
seven forecasts. And the uppermost one–
let’s have a look at it– is labeled HHH. And the average temperature,
global average temperature rise over the year time frame from
1990 to 2,100 in this forecast was about five
degrees centigrade. But you’ll notice that it’s
uneven across the world. An important thing is
that it’s about 10 degrees centigrade in the
northern polar region and about four degrees
centigrade in the tropics. And that focuses your
attention on something. And say a 10-degree
centigrade rise in the polar region,
believe me, that’s something you should be
deeply worried about. We have some big
ice masses up there. We have tundra with great
amounts of carbon stored in it. So you finally begin by looking
at a little bit more detail here why predicting climate
as a function of latitude that maybe this is
a serious issue. However, this diagram, when you
look at these seven forecasts, you could also focus on the
lowest curve and say, wow, look. This is a feasible
forecast, right? You can justify the
various settings in the economic model
and the climate model that produced this. My answer when I
and my colleagues did this, when we talk
about it is that, yeah. We can justify the assumptions
made here or made here. So this one’s useful. But at the end, we
couldn’t answer a question we were often
asked, and that is, what are the odds of these
rather extreme forecasts? Like this one was the
one you’d worry about. If it’s anything down here, this
is not such a great concern. But that’s the nature
of the climate problem is that if we admit
the uncertainties that exist in these forecasts,
then we get this range. But we can’t talk
about the odds. Well, I’d say at the
beginning of this year, we finally completed what
we really wanted to do. This is now very [INAUDIBLE]. What we wanted to do is compute
the probability distribution function of the climate
outputs, often known as PDFs. Now I should say, I’ve
been doing these PDFs now and concerned with them
for so much time now, I get excited when
someone sends me an email and said there’s a PDF, right? And so many times, I’ve been so
disappointed what the PDF was. I thought it was one of these. What is the conclusion? This is from 100 forecasts now. For those of you
who do statistics, we use a Latin hypercube
sampling technique that’s a way to
get around having to do huge numbers in a
Monte Carlo simulation. But this was with 100. And then this is a curve
fit to the discrete PDF that you obtain. And what’s the conclusion here? It says that the median
temperature rise predicted for the next 100 years is
about two and a half degrees centigrade, corresponding
to about four or five degrees centigrade
at the pole, all right? That’s something to
be concerned about. There’s about a– here’s
the upper 95% bound, 4.8 degrees centigrade. So there’s about a chance
in 40, one chance in 40 of being greater than
4.8 degrees centigrade. That helps you
calibrate the people who say it’s going to
be the end of the world. It’s a chance in 40 that
it’s going to be big. And it helps to calibrate
at the other end. The lower 95% bound was
0.9 degrees centigrade, so that says there’s
a chance in 40 of being less than 0.9
degrees centigrade. So that helps you calibrate
the people that are often called naysayers,
the ones that say this is a very small problem. Well, the nature of
the issue is such that you can’t rule them
out, but at least now with this approach, we
can give it some odds. Keep in mind that
there’s 50/50 chance then that the temperature rise
could be greater than two and a half degrees centigrade. Now, then you’d want
to use this approach and say, well, what if I
enact a policy designed to lower the emissions
of greenhouse gases? How will it change
the shape of that? And most importantly,
what are the odds now of very significant warming? Can I decrease the odds of
very significant warming? That’s what you want
to do with a policy. You don’t really care about
the low end of the PDF. So this has recently
been completed as well. And the actual numbers
don’t matter here so much as the principle that we
are trying to get across with this approach. I should say, by the
way, that this has been done by a team of people. And Mort Webster, who’s I
think here in the audience, did a great deal of the work. Chris Forest and
the usual collection of more senior researchers
have been involved in it. Here is just a sample policy. It turns out to be a policy,
a very stringent policy. Involves all the
countries of the world. And I’d say the chances of
enacting such a policy– you know, the Red Sox
have a greater chance of winning the World
Series than us being able to enact this
particular policy, and all other countries in the
world get on board, and so on. Nevertheless, it
illustrates what one would like to see in a policy. Here is the old PDF
that I just showed you, which said no policy. Here is the range of
temperature outcomes. And then the dashed
line is with the policy. And so in this particular case,
the policy, a very stringent one. Interestingly, it’s
called Beyond Kyoto Case, so I won’t go through the
details of what it is. But the Beyond Kyoto
Case, the upper 95% bound is now two and a half
degrees centigrade. That was a median value
for the no policy case, and so that was 50/50
chance of being greater than two and a half degrees. Now with this policy,
we’re down to one chance in 40 of being greater than two
and a half degrees centigrade. So if we could do this
and afford to do it and politically it was
possible, then this would say, let’s go and do it. Of course, I think all of
you know the hard facts of the politics of this issue. But at the end of the day, if
I showed this in any audience other than here at MIT
and talked about PDFs, eyes would glaze over. And again, people would
confuse it with some attachment that they’d been sent by email. It probably wouldn’t work. So we finally, after much
desperation and discussion, decided that some sort of a
wheel of fortune was necessary. And we’ve got one
over here, and so I’m going to pull it out now. [LAUGHTER] And I’m going to appeal to
our illustrious president of our institution here to– [LAUGHTER] But before I do, I want to
explain what he’s going to do. So do you realize the
implications of this? VEST: We were
expecting Vanna White. [LAUGHTER] PRINN: There were a couple
of no-shows, as you saw, and Vanna was one of them. And whatever happened,
I don’t know. Now let’s look at the wheel. The wheel has been set up now
according to the probabilities. Not of 100 forecasts,
but now of 250 forecasts. So this is even more detail
behind it and greater accuracy in defining probabilities. But let just look
at the wheel first, and I want to go
at the top here. Now I want you to focus on
these two ones at the top. This sort of very
dark red color here says greater than eight
degrees Fahrenheit. That’s bad news. So if Chuck rolls this and it
ends up here, that’s bad news. And less than two
degrees Fahrenheit means the naysayers are there. But the vast rest of this circle
here goes from two to three, three to four degrees
Fahrenheit, four to five, five to six, six and seven. You’ll notice something
I’ve done here. I switched units, because
another thing that’s useless talking to the public
about in the United States is degrees centigrade. Their eyes glaze over as well. So it’s in Fahrenheit. Another important
point to make here is a policy would shrink the
greater than eight degrees Fahrenheit and the
seven to eight. So these red colors
here, a policy would shrink the size
of these and increase the size of the blue,
the green, and so on, because these are the
lesser temperature rises, and that’s what you’d
want with a policy. And you see the
effect of the policy would be to make it
much less probable that Chuck is going
to spin and land on the greater than eight
degrees Fahrenheit, which is clearly one we want to avoid. So I think with
that in mind, I’ll just add that the world
has one spin, all right? Because we’ve already worked
out the probabilities here. The probabilities
have been worked out. So the world has one spin. If we don’t do
anything, this is it. This is the spin. So with that in mind, I want
you to move over to this side. [LAUGHTER] And you’ve got to
give it a good spin, because if it doesn’t go
around more than twice, I’m going to figure that
it’s going to be biased and you’re trying to
work out how to land it. So [INAUDIBLE]. [BUZZING] [APPLAUSE AND CHEERING] AUDIENCE: Save the world. Saved the world. MODERATOR: I have to remind
you the press is present. I can see the headline tomorrow. MIT– [LAUGHTER] PRINN: It looks like it’s
around three degrees Fahrenheit. Thank you, Chuck. I think that’s– [APPLAUSE] VEST: And the first is to
thank everybody whose name is on these two sheets of paper. We really appreciate
all that you did to make this day possible. And I actually mean
that very much. And certainly do want to thank
all of our guests who spoke and who provided such leadership
to the nation over the years. I was asked to say a
few words to summarize today’s discussions. And I took copious
pages of notes, but I think I will
spare you all of that. And I just wanted to
walk through a few themes that I believe I heard pretty
clearly during this day from our various speakers. And these are
divided a little bit into those which have
very directly to do with the functioning of the
presidential science advisor and the Office of Science
and Technology Policy, and those that perhaps
represent broader issues and challenges even
than what goes on in that part of the executive
branch of our government. And if you’ll bear
with me through that, I’m going to present a
brief treatise on science and technology policy
in which I promise to answer the most important
question in science policy and tell you what the most
important challenge is. So let’s begin with some
themes that I believe have been present today. First, obviously
in this audience, in this symposium,
a common belief that the importance of
science and technology to our future in almost
every dimension is growing. Indeed, accelerating. And that meeting it
is going to require, among other things, a
strong and differently balanced federal budget
for science and technology. But even more
fundamental, I think, is the juxtaposition
of this importance that we all ascribe to
advancing science and technology with the reality that
science is simply an outlier in a highly political
environment in Washington. Second, we heard
several times through this wonderful
historical dialogue on OSTP and science advisors
going all the way back to Bill Golden and
President Harry Truman. That at the end of the day,
it’s the personal relationship coupled with political
realities that determine how successful
someone can be in that office. And the personal
relationships, particularly with the president, but also
as we heard several times, with the director of the Office
of Management and Budget, and the ability of these
folks to pose things within the realm of relevance
to the administration’s agenda. Third, we heard several
times the age-old story that I think someday we’re
going to have to figure out how to take to heart,
which is that we have a very fundamental
problem in this country in the fragmentation
of our S&T budgets into little pieces across
different appropriation committees within our Congress. And also, I would put right
alongside with that this very important term that was
used of the perceived utility of science
and technology, that people in
Congress and indeed in much of the
executive branch’s enthusiasm for
investment in science is going to be based on their
perception of its utility. Not an easy thing for many of
us to automatically accept, but undoubtedly a reality. It also seemed to me that there
were some interesting drifts and oscillations that
went through some of the historical talks,
particularly the oscillation in different historical periods
for the role of the science advisor between being in a
position where there ended up being a single dominant
issue and those who were able to deal with a
much broader spectrum of S&T agenda items. And also, we heard a
bit about the drift in and out of science
and technology policy over the years of the
role of the private sector as opposed to just the role
of the government, and perhaps the government and
coupled with academia. This wonderful term of the
citizen scientist was used. And whether or not
that term was used throughout the discussions,
we heard over and over again that we must bring
science to the government, that we must in fact
be citizen scientists and explain the importance
of what we do, how we do it, and what the consequences for
good and ill of what we do are. We heard a plea a couple
of times for something that I think many of us
believe is just incredibly overlooked in this
country, and that is a call for serious
education R&D, or whatever terminology
you want to use. That we have an industry,
namely education, that’s most arguably the most
important societal function that we take on for
our young people, and we invest something
less than a tenth of a percent of its value
into really understanding how we learn and how we can
improve teaching and learning. Dan Hastings was quite
elegant and quite eloquent. He was elegant also, but he was
quite eloquent in reminding us that we need to develop a
far more integrated approach to education and
research, particularly for many of our
engineers so that they can bridge important
gaps and can really become the new
leaders of an age that is highly dependent on
scientific and technological knowledge for very
important decisions. And finally, I want
to end with what I would conclude,
if we were to take a consensus among our
speakers, are the two most important issues going forward. And the first is
the whole plethora of issues about our
science and engineering workforce in this country. And I think I hardly
need to expand on that, because it
was said so many times in so many different ways. But meeting the challenges of
the scientific and engineering workforce, and as Jay
Forrester reminded us, the effective and efficient
use of that workforce is one of perhaps the two
most dominant questions. And the final one which we
heard from many people– Phil Sharp this afternoon,
many of the other speakers, and certainly in a quite
wonderful and remarkable manner from Harold Shapiro over lunch– we must be much more
cognizant than we have been of the set of
moral and ethical issues that are raised in a period
of incredible acceleration of scientific knowledge and
technological capability. And that we must understand
at a much deeper level the consequences of these
advances for our society, and we must really internalize
the way in which they affect people’s anxieties. And we must respond to
those through policy and through the way we
carry on public dialogue. Now since you all
were good enough to sit through all
of this, I wanted to end with pointing
out this question and– or answer to a question,
and to pose a challenge. And we’ve had many
people you’ve heard from today who have written
entire erudite books on science and technology policy. But being an engineer, I’m
a quite pragmatic fellow. And I’ve decided that the most
important practical question in science and technology
policy is, how do you decide what research, what areas
to fund with finite resources? And I think the
answer is very simple. You come to great universities
like this one and many others across the country,
and you look around and you ask the really
bright young people what they want to do,
and that’s where you ought to place your money. So that leaves us with the
central challenge of science and technology
policy, and I believe the grand challenge that more
or less subsumes most of what we’ve talked about
today is, how do we connect what Congressman
Porter referred to as the perceived
utility of science to what these great
young people want to do? With that, let me thank,
again, all the participants, and thank particularly the
Sloan Foundation for its support that made this possible,
and all the wonderful staff members from MIT and elsewhere
who rolled up their sleeves and made this wonderful
day possible for us. And Dan, again, thank you
very much for your leadership, and also to Duncan Moore, who
had to leave just a little bit ago, for conceiving
the whole thing. Happy birthday, OSTP. [APPLAUSE]




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