IEEE IS Special Issue - advanced notice
My IEEE Intelligent Systems editorial for the May/June issue will be replaced by a introduction to a special issue on the Future of AI. I welcome your comments
-Jim H
(preprint - needs editing, but hey, this is a blog!)
Introduction to the “Future of AI”
As you know doubt know by now, 2006 is the 50th Anniversary of the Dartmouth summer workshop that, if not the birth of modern AI, was certainly the party celebrating that birth. Although machine intelligence workshops had been held in both the US and UK, and indeed Alan Turing’s famous “imitation game,” now referred to as the Turing test, was proposed in a paper he published in 1950 , the 1956 summer school brought the leading researchers in the field together, along with a small number of bright students interested in learning more about this newly emerging “Artificial Intelligence” thing.
It was tempting, as Editor in Chief, to create a volume, as several other AI magazines and journals have, that would look back at 50 years of AI and speculate as to where we’ve been. However, the more I thought about this issue, and about the stories I’d heard of the early days of the field, the more I started thinking about how exciting it must have been when no one talked of “AI winter” or, as one AAAI Spring Symposium was so foolishly titled, “What Went Wrong and Why?” Rather, the field was focused on an exciting journey into a bright and unknown future. Working with primitive computers surpassed by the microprocessor in today’s microwave oven, these daring scientists dreamed of solving one of the most enduring of all the problems in science – what is intelligence and what might it mean that we have it? How exciting that must have been.
Our Bright and Unknown Future
But wait! How exciting it should be now! After 50 years of exploring the field of AI with ever more powerful computers we have learned so much more than we knew then. We have learned of problems whose complexity boggles the mind, where “intractable” is better than the oh so dreaded, and way too often occurring, undecidability result. Cognition turns out to be harder than we ever dreamed, and surpassing human capabilities at even simple games like chess was not as simple as it first seemed, and hard games, whether exponential nightmares like Go or unsolvable puzzles such as interactive strategy games, are still to be mastered. Despite the incredible power of the computer and the awesome information space that is the Web, search engine technology remains primitive and the real understanding of human language seems as far away as ever. In short, we remain poised on the edge of an exciting journey into a bright and unknown future!
Given the unsolved problems that still remain, and given our tendency to sometimes forget how exciting is the quest to build the intelligent machine, IEEE Intelligent Systems has chosen to devote this special issue, at the time of the 50th anniversary of the Dartmouth meeting to the Future of AI – may we look forward to the next decades having as many successes, and surprises, as the
To explore the future of our field, I invited a number of well-known scientists representing a wide range of approaches to contribute articles speculating about where AI may be going in the future, and how we might get there. A small number of people were asked to contribute full articles about where they saw AI going, and a much larger number were invited to contribute shorter perspectives. You may also have noticed invitations in my past editorials to any readers who wanted to contribute and I’m pleased that a couple of people took us up on this We also solicited articles from some researchers living in various parts of the world to talk about AI from their regional perspective. In short, we cast a very wide net to get as many opinions as we could. The response was wonderful! (Not everything fit in this one issue, so expect to see articles, perspectives and readers’ opinions appearing in future issues). I think you will agree.
Papers in this issue
To start with, I solicited a set of longer articles that would represent a wide variety of work in the AI field. The papers that appear in this issue include:
An article from Dartmouth workshop attendee Oliver Selfridge, one of the earliest researchers in the area machine learning, who has worked in both academia and industry, as well as serving as a advisor to many US government agencies. When I first asked Oliver if he would do a paper for a special issue on the Dartmouth 50th, he was hesitant – until he learned that I was asking him to write about the future, not the past. Oliver has always been a visionary, and he shares with us his continuing vision for the future of machine learning – summarizing some of the traps into which researchers often fall, and describing some of the challenges yet to be addressed.
Edwina Rissland, a professor at the University of Massachusetts and one of the founders of case-based reasoning and AI and the law also rises to the challenge of exploring an area of AI with a long history, but a long way to go. In her article, Edwina argues that work in similarity-driven reasoning, for example reasoning by analogy, has accomplished much in the past 50 years, but still has a long way to go. She explores the approaches that have been taken, and outlines many unsolved problems in the domain that remain to be tackled.
A paper from Raj Reddy, former Dean of the School of Computer Science at Carnegie-Mellong University, and a recipient of the 1994 Turing Award for his seminal work in large-scale applied AI. In this issue, he explores how work in intelligent systems could have a major, beneficial, impact on society as computer power continues to increase, and as AI and robotics make strides forward in the future. Raj explores the many ways in which robotic research is being deployed today, and opines that “Such capabilities can be used to further increase the gap between the haves and have-nots, or to help the poor, the sick and the illiterate.” He challenges us to take the right path as AI moves into the future.
This theme is also reflected in an article by Austin Tate who holds a chair in Knowledge-Based Systems at the University of Edinburgh and is a Fellow of the Royal Society of Edinburgh, Scotland’s National Academy. (Austin is also a member of the Advisory Board of IEEE Intelligent Systems, having served as an associate editor in chief for a number of years.) He argues in this paper that other AI technologies than robotics, especially intelligent cooperating agents, can be used to create a “helpful environment” giving examples from a number of projects including disaster relief, emergency response and rescue.
Representing a different view of creating agents in the future is a paper by Luc Steels the co-founder and former chairman of the Computer Science Department at Vrije Universiteit Brussel, and one of Europe’s leading proponents of what is sometimes called “nouveau AI.” In this article, Luc explores how “semiotic dynamics,” the process by which groups of agents, human or machine, can collectively invent and negotiate shared symbol systems that they then can use for detailed communication. He argues that human language is best understood as a complex dynamic system shaped by evolution of communication. He explores this idea with a number of examples from work in robotics, agents, and learning, and proposes this as a challenge to the way AI and linguistics have traditionally viewed language as the competence of an idealized speaker. He proposes that this new approach to exploring language may make for a complete change in how we view and build human to computer (and human to human) communication systems.
Jordan Pollack, Professor of Computer Science at Brandeis University, takes this sort of approach even further. Jordan was one of the authors on a 2000 Nature paper describing robots with physical locomotion system developed by evolution from simple electro-mechanical systems, rather than human design – a paper that generated a huge amount of interest and spawned a great deal of new work in the Artificial Life community. In this paper, Jordan explores the underlying principles that make evolutionary results like this possible, arguing that the whole of traditional AI may be based on a misapprehension about what it is to be intelligent. In an analogy sure to be painful to many in the AI community, he questions whether traditional symbolic AI is arguing that intelligence is too complex to have evolved without some sort of “intelligent designer” involved in the loop.
On another front, we have an article in which the former Editor in Chief of this magazine, Nigel Shadbolt of Southampton University, teams with MIT’s Tim Berners-Lee, the inventor of the World Wide Web, and Wendy Hall, Southampton’s Head of School in Electronics and Computer Science and one of the best-known computer scientists in Britain, revisit the Semantic Web vision and explore what it will take to make it flourish in the future. They remind us of the notion of the Semantic Web as the “web of data” and explore what that could mean, and how we can get there, providing a guiding vision for this important new area of AI research.
In addition to these seven, we have a number of shorter articles by a wide range of AI leaders from around the world. Perspectives on the field were invited from the members of our advisory and editorial boards, and from a number of leading researchers in a number of AI’s subdisciplines and approaches. I can’t actually enumerate all of these, because at the time I am writing this we have received too much to fit in a single issue, and are still working out which papers will appear in the special issue (those that won’t fit will be carried over into future issues. We will also offer perspectives on the future in several of our regular columns this issue.
Your Submissions
In previous issues of this magazine, I have invited you to submit your own papers for this issue. A few readers have taken us up on this, and one of these papers appears in this special issue, a contribution entitled “AI and Science’s Lost Realm,” by Colin Hale, a graduate student at the University of Melbourne, who has returned to get his PhD after almost twenty years in industry. Self-described on his Web Site as “a mature age student following the trail towards fun,” Colin challenges some of the traditional views of AI and science, even exploring whether “metaphysics” might be a better way of approaching some of the problems of the field.
Somewhere in this issue is sure to be an article you disagree with. We can’t wait to receive your letters to the Editor, or your own short papers expressing your opinions on the future of the field. We will be reserving some space in forthcoming issues for these pieces, and I hope you will join in the fun by writing provocative pieces of your own.
AI’s Ten to Watch
It would be hard to find a triter phrase than “our children are our future,” but in academia, as in our “real” lives, it remains true. The true innovations in the next 50 years of our field will need to come from those who are starting their academic careers today, and who will guide the field through the many changes sure to come as computers continue to evolve, as human intelligence continues to be explored, and as the challenge of solving the most primal of all scientific questions – “What is intelligence” – continues to be a goal. To honor the future leaders of the Intelligent Systems field, we are excited to include the “AI’s Ten to Watch” section, which identifies some of the most promising young researchers in the field today. A competitive process, with nominations received from leading AI researchers around the world, led to the selection of these impressive young scientists for inclusion in this issue. While we only give them one page each today, some of them may well end up writing the long articles by leading AI researchers when we reach the 100th anniversary. I wish we could have included all the wonderful young scientists who were nominated for this award, but I hope you will agree, the people will chose represent some of the best that AI has to offer.
Dedication of this special issue
Unfortunately, I am forced to end on a sad note. Push Singh, one of the recipients of the AI Ten to Watch award passed away in February, not too long after he was notified that he had won the award, but before he had a chance to claim his prize. The page describing his vision is thus, unfortunately, replaced with an in memorium piece talking about his work and what a special person he was. I hereby dedicate this special issue to his memory, a piece of the Future of AI that will be forever missing.
Jim Hendler
April, 2006
