|April 6/13, 2005|
Feigenbaum is a Professor of Computer Science at Yale University whose research
interests include Internet algorithms, computational complexity, security
and privacy, and digital copyright.
She is a principal investigator for the National Science Foundation-funded Privacy, Obligations, and Rights in Technologies of Information Assessment (PORTIA) Project and the Office of Naval research-funded The Standford-Penn-Yale-Cornell Experiment (SPYCE).
Feigenbaum was Editor-in-Chief of the Journal of Cryptology from 1997 to 2002; is on the boards of the Institute for Mathematics and its Applications, and the National Academy of Sciences Computer Science and Telecommunications; and is a Fellow of the Association of Computing Machinery. She was Program Chair for the 2002 Association of Computing Machinery Workshop on Digital Rights Management, and Program Co-Chair for the 2004 Association of Computing Machinery Conference on Electronic Commerce.
Feigenbaum holds a bachelor of arts in Mathematics from Harvard and a doctorate in Computer Science from Stanford. She worked for AT&T from 1986 to 2000, where she founded and managed a research group in Algorithms and Distributed Data. Her Web site is cs-www.cs.yale.edu/homes/jf/.
Technology Research News Editor Eric Smalley carried out an email conversation with Feigenbaum during the week of March 28th, 2005:
TRN: What got you interested in science and technology?
Feigenbaum: When I was growing up, I was a good student overall; I did well in science and math courses, but I did well in other courses, too. As a freshman at Harvard, I decided to major in math, because math was hard. Why spend all of that money, time, and effort on getting a college degree, unless I was going to learn something that's really worth knowing and that I was unlikely to learn on my own?
In between my junior and senior years in college, I had a summer internship at Bell Labs and got a glimpse of what it's like to do research in Computer Science. The next year, I was accepted to a PhD program in CS at Stanford, and my interest in CS had been broadening, deepening, and evolving ever since.
TRN: What are the important or significant trends you see in science and technology research?
Feigenbaum: Two of the longest lived, most robust trends in information technology are the ever-decreasing cost of data storage and the ever-increasing ubiquity of computers and networks in business, government, recreation, and many other aspects of daily life.
Thus, more and more sensitive data about people and organizations are created, captured, and stored; here, by "sensitive data," I mean those that can harm the data subjects, data owners, data users, or others if they are misused. Not surprisingly, concern about the accuracy, privacy, security, ownership, and appropriate use of sensitive data is widespread. Currently, this is motivating a lot of research in Computer Science and related disciplines, including the PORTIA project (crypto.stanford.edu/portia/), on which I am the Yale [principal investigator].
One trend that we should see but that I've not yet seen is a huge, glorious, well funded, multidisplinary effort to design and implement the post-petroleum society.
It's totally obvious that the world has already suffered terribly from the fact that life in the US and other developed countries is over-reliant on driving in particular and oil-powered activity in general; it's equally obvious that
(1) the problems caused by over-reliance on petroleum are growing worse as people in emerging economies drive more, and
(2) the world is running out of oil anyway.
So let's find a better way to do things! In the past, the US government funded the Manhattan Project (which helped the Allies win World War II), the Apollo Project (which put astronauts on the moon), and the Arpanet Project (which created the Internet).
Right now, the US should be mobilizing all of the best minds in academia, industry, business, and government for an ESIPPS project: Economic Success in the Post-Petroleum Society. We need new transportation technologies, new food-production technologies, new geographic configurations, … new everything. It's going to happen, assuming that the human race survives longer than the oil supply. Is the US going to lead the way, or are we going to cede that leadership role to someone else?
TRN: Tell me about the trends in information privacy and security. What are the pluses and minuses of these technologies as they exist today? What do you see as the most urgent needs in these areas?
Feigenbaum: We can expect the aforementioned trends to continue. We can also expect sensor-nets and surveillance systems of all sorts to become commonplace.
We should strive to accompany sensitive data by easy-to-understand and easy-to-enforce policy metadata. Note that there has already been some good work on "privacy policies," [for example,] the P3P work of the World Wide Web consortium (w3c.org/P3P), but there has been little or no work on pushing these policies through all of the information technology that sensitive data encounter throughout their lifetimes and making sure that these policies are enforced.
TRN: Your PORTIA project seems to be aimed at having it both ways, supporting data mining and privacy. What are the technological trade-offs required to accomplish this, and how do they relate to the social and economic conflicts involved?
Feigenbaum: Terminology is important, and the term "privacy" may be misleading at this point. It is important to note that much of the sensitive information that is proliferating at great rates is not "private" in a traditional or intuitive sense of that word.
No one could object to the use of "private" to describe information that should, by its very nature, be known only to one or a few people - one's private thoughts, private family life, private sex life, private communication with friends, etc. Sensitive medical or financial information is of a different nature: There are many (sometimes thousands of) people and machines that have legitimate reasons to access it. For good reasons, the term "private" is often equated with the terms "confidential" or "secret."
Thus, use of this term naturally leads security researchers to try to "solve the privacy problem" with encryption or other techniques designed to hide information altogether from those without authorization to access it. However, hiding information will not help to solve the problem that most sensitive data objects (and their owners, subjects, and users) encounter, namely the fact that data created and/or collected for legitimate purposes can later be used for illegitimate purposes.
Protection of sensitive data is not a "problem" that can be definitively "solved." As technologists and researchers, we expect to make progress and, in the best cases, to "solve" today's technical problems and then move on to tomorrow's. This is an unrealistic expectation when it comes to rights and responsibilities in cyberspace and, in particular, to the protection of sensitive data.
Technological, social, and political change will pose new threats to privacy even as (or before!) the old threats are dealt with, and people will not stop complaining when they are intruded upon or defrauded by malevolent actors in cyberspace. Marc Rotenberg of the Electronic Privacy Information Organization (www.epic.org) made a useful analogy at the 2005 Annual Meeting of the American Association for the Advancement of Science:
Invasion of privacy is like environmental pollution. It will not be completely eliminated, but nor can it be ignored. Just as environmental-impact analyses must be part of any real-world development project, privacy-impact analyses must be part of any cyber-world development project. Research at the interface of computer science and the social sciences can develop the tools needed for these analyses.
TRN: The data entanglement scenario you describe in one of your papers -- a method of linking people's data so that an unscrupulous data storage provider can't discard or damage someone's data without risking damaging all of the stored data -- brings to mind the notion of data as property.
There's been a lot of discussion about the intellectual property rights of content providers, but what about personal data as personal property? How do property rights and property law apply to data? For example, can you consider medical records in the context of property rights?
Feigenbaum: I think that the rights of data subjects and data users definitely need to be clarified, with respect to medical data and many other types of data as well. This is one part of the PORTIA agenda. But I don't think that "property rights" as they are conventionally understood are the right starting point for this work; the OECD Fair Information Practices may be a better starting point. For example, I think that US citizens should have a very broad, very enforceable right to have erroneous data about them corrected (promptly!) by whoever controls the database in question.
"Data entanglement," as my collaborators and I conceived it in the paper you're referring to, is an abstract technical notion and doesn't really answer any implicit questions about ownership and rights in cyberspace.
TRN: What is your view of Digital Rights Management, and how do you feel about the way the media portrays the issue?
Feigenbaum: Well designed, well implemented DRM can be one part of a content-distribution service but only one, relatively small part.
I really haven't seen much discussion of DRM as such in the media; ever since Napster, people have been talking non-stop about "piracy" and "file-sharing," but I'm sure that there's a lot of innovation to come in content distribution. I-tunes is just the beginning.
TRN: The media tends to portray this issue as technology vs. intellectual property. Does this oversimplify or distort the issue?
Feigenbaum: Yes, this is definitely an oversimplification. The US Constitution empowers Congress to create intellectual-property law in order to "promote progress in science and the useful arts."
There are many forms an intellectual-property legal regime could take that would be simpler, more enforceable, and more conducive to progress in science and the useful arts than the legal regime that we have today. We've had great technological progress in recent decades: Computers and networks have enabled unprecedented levels of content creation and content distribution. The next step will probably be business innovation; iTunes is an early example.
Let's hope that, once it's clear how both commercial and non-commercial content distributors can use the new technologies effectively, Congress will modernize copyright law and stop letting the interests of analog-era content distributors determine everything.
TRN: The SPYCE project seems like it encompasses much of the work toward automating the policies and transactions of grid computing. How is diffuse computing different from grid computing?
Feigenbaum: Grid computing is part of the diffuse-computing agenda but not all of it. The phrase "grid computing" conjures up a community of users who, although geographically dispersed, are intellectually coherent and possessed of a common purpose; often that purpose is a scientific goal.
In the diffuse-computing world that we live in today, agents need not be members of long-lived, focused communities; they join into and depart from distributed computations of all sorts frequently.
TRN: What will become more complicated 10 and 50 years down the road, and what will become simpler?
Feigenbaum: Unfortunately, I think that many of the "complications" we will face between 10 and 50 years from now will be the result of short-sighted and self-destructive things that the US and other developed countries are doing now.
Climate change and other forms of environmental degradation will leave the scientific and technological community with some very hard-to-solve or even unsolvable problems.
Right now, we should be imagining, innovating, developing, and planning for a post-petroleum society; that would be an intellectually fascinating thing to do, in addition to being a vital service to society. Instead, we are fighting wars and ripping up wildlife refuges so that people can drive SUVs!
As far as "what will be simpler" goes, I'd say it's very likely (but not 100% certain) that information technology will be simpler to use and to integrate with everything else. Certainly, that is a goal within the IT community.
TRN: What do you imagine you or your successor will be working on in 10 years? In 20 years?
Feigenbaum: I think that ACM President Dave Patterson's SPUR agenda (Security, Privacy, Usability, and Reliability, www.acm.org/pubs/cacm/toc/2005/march_toc.html) should (and probably will) occupy much of the Computer-Science research community for the next 10 to 20 years.
TRN: The New York Times has a story today [April 2] about DARPA curtailing funding for basic and open-ended computer science research. What are your thoughts about this?
Feigenbaum: I think it's tragic that DARPA, which has funded so many basic research projects from which our society now benefits, is cutting back on basic research. What justification could the Defense Department or the Administration (or anybody for that matter) possibly give for killing the goose that lays the golden egg?
I really wish that [Anthony] Tether and other decision makers at DARPA would explain why they're doing this, instead of "declin[ing] repeated requests for interviews." They give reasons for funding some of the stuff that they are funding, but they don't give reasons for abandonning their basic-research strategy that has been
so successful in the past; it's infuriating.
TRN: What's the most important piece of advice you can give to a child who shows interest in science and technology?
Feigenbaum: Take all of the math and science courses that your school has to offer, and enroll in more advanced courses in a nearby college if you can.
Learn how to program a computer, and learn basic statistics; these are essential parts of the "knowledge base" for science and engineering, and they're sometimes given short shrift. Get to know a practicing scientist, mathematician, or engineer; if there is none in your social circle, seek out an online mentoring program (e.g., MentorNet www.MentorNet.net).
Most importantly, stick with it! Real appreciation of science and math takes a long time and a lot of work.
TRN: What's the most important piece of advice you can give to a college student who shows interest in science and technology?
Feigenbaum: First and foremost, I'd say "Go for it!" Science, technology, engineering, and math (STEM) courses are some of the most interesting, rigorous, and ultimately satisfying courses taught in colleges today, and it's disgraceful that so few of the best US college students take them. STEM careers that these courses can lead to are also great opportunities - engineers and scientists do tremendously important, challenging work, and we often have fun while we're doing it.
But, even if you don't ultimately become a scientist, studying science in college is worthwhile; you'll learn something of unimpeachable value that you're very unlikely to learn on your own, and you'll be taught by accomplished, serious people.
Finally, if you get a chance to be a summer intern at a high-tech company, take it.
TRN: What are your thoughts on the state of conventional wisdom on science and technology?
Feigenbaum: I don't see much "wisdom" out there. The general public's appreciation of science, math, and engineering seems almost non-existent. Even many non-science majors at elite US colleges admit that they don't know anything about science, math, or engineering and don't see why they should.
TRN: What could be done to improve the pursuit of science and technology research in terms of business trends, politics, and/or social trends?
Feigenbaum: I and many friends and colleagues have been saying for a long time that entertainment media could do a lot to raise the profile and improve the image of scientists and engineers. Think of a prime-time TV drama entitled "L.A. Lab."
TRN: What are your interests outside of work, and how do they inform how you understand and think about of science and technology?
I live in New York City and love being a New Yorker - going to the theatre, to museums, to great restaurants, etc. I read fiction, including a lot of detective fiction, and love the experience of "losing myself" in a good book. I also follow politics.
Most of this has nothing to do with science and technology, but I would love to see the scientific and technological community mobilize to defeat the radical right-wing politicians who have been in power for quite some time and have done so much damage.
TRN: What are your favorite detective fiction writers?
P.D. James, Elizabeth George, Ruth Rendell (only when she writes about Inspector Wexford), Martha Grimes (only when she writes about Richard Jury and his friends), Henning Mankell, and the later works of Val McDermid.
TRN: Do you see any connection between mysteries and the problem solving of science and engineering?
No. These detective novels are stories about people, not about problem solving. From my vantage point as a professional mathematician/computer scientist, there is not even a superficial resemblance between what I do and what well drawn fictional detectives do.
TRN: Is there anything else you would like to say?
Feigenbaum: Some of my answers are taken from an untitled and unpublished position paper I wrote for a workshop on Cyberinfrastructure for the Social Sciences: cs-www.cs.yale.edu/homes/jf/Malevolence-Airlie.pdf.
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