By David C. Brock
Director and Curator
Software History Center, CHM
Senior Audio/Video and Digital Archivist &
Oral History Program Coordinator, CHM
Today, we are bombarded by messages about the ways in which artificial intelligence (AI) is changing our world and its future promises and perils. But today’s AI, called machine learning, is very different from much of AI in the past. From the 1970s until the 1990s, a very different approach, called “expert systems,” appeared poised to radically change society in many of the same ways that today’s machine learning seems. Expert systems seek to encode into software systems the experience and understanding of the finest human specialists in everything from diagnosing an infectious disease to identifying the sonar fingerprint of enemy submarines, and then have these systems suggest reasoned decisions and conclusions in new, real-world cases. Today, many of these expert systems are commonplace in everything from systems for maintenance and repair, to automated customer support systems of various sorts. While such uses appear prosaic today, expert systems were viewed as a major advance, able to meet or exceed the capabilities of human experts in a set of specific domains.
In May 2018, CHM hosted a unique two-day meeting titled “AI: Expert Systems Pioneer Meeting.” The meeting was a collaboration between the Software History Center and the Software Industry Special Industry Group. The goal was to bring together important pioneers in expert systems and let them tell their stories. As Burt Grad, one of the moderators and organizers, highlighted during his opening remarks, attendees were invited describe the history of the field from their personal perspective. As he put it, “tell what you know personally, either from people you worked with or things you experienced.”1 The result was an engaging conversation covering the 1950s to the 1990s with attention to the expert systems companies founded in those years.
The first day opened with an interesting discussion about the origins of AI as a field. The attendees shared memories about the people and the institutions that created the field in its first two decades. In particular the session focused on the contributions of Marvin Minsky, John McCarthy, Allen Newell, and Herb Simon. The attendees also discussed different definitions of what terms such as “expert systems,” “knowledge-based systems,” and “artificial intelligence” meant in those years. The conversation also touched on the relationship between academic research and business application of AI.
The day ended with an overview of some of the early companies that embraced expert systems from the 1960s to 1980s. The founders of companies such as Machine Intelligence, Symantec, Advanced Decision Systems, AI Corporation, and others explained how and when each company was founded, their primary products and services, and discussed their main sources of funding and revenue. This discussion also offered attendees the opportunity to address how the signature AI programming language, LISP, affected the growth of expert systems companies. To use the words of one of the attendees, “LISP machines were the best development environment ever invented.”1
The second day of the meeting focused on companies created in the 1980s and 1990s such as CyCorp, Syntelligence, and Neuron Data. Attendees also discussed how larger companies like IBM, Schlumberger, and Franz Inc. implemented this technology. The discussion provided not only an overview of how these companies grew and, in the end, failed, but also the technical problems they were trying to address.
The meeting ended with an interesting analysis of how today's dominant approach to AI—machine learning—differs from expert systems. As Edward Feigenbaum summarizes, the main difference “[i]t's a granularity issue. When we were going after knowledge from a doctor, we wanted a gold bar; we didn't want gold dust. We wanted it all packaged up with your expertise and all your rules of good judgment, all packaged together. What you get now is gold dust, and you need 100,000 of them.”2 During the final discussion attendees underscored how this change of the approach to AI was intertwined with technological advances such as advances in computing power.
The following day, CHM recorded four oral histories with some of the meeting attendees Herb Schorr, Alain Rappaport, Brad Allen, and Peter Friedland. By sharing their personal stories, these four AI pioneers had the opportunity to provide extra context to the topics discussed during the meeting.
Now for the first time, CHM is releasing these recordings from its archives and adding historical context to today’s conversations surrounding AI and machine learning.
“We are proud to release these important recordings, including companion oral histories, from our “AI: Expert Systems Pioneer Meeting,” says CHM CEO Dan’l Lewin. “These recordings highlight the voices of AI legends and contributors like Edward Feignbaum, Herb Schorr, Peter Norvig, Peter Hart, Brad Allen, Peter Friedland and many others in an engaging story about the people behind expert systems companies from the 1970s to the 1990s. As CHM continues its commitment to decoding the history and impact of AI, we are honored to preserve and make accessible these unique discussions with some of the field’s leading pioneers.”
By recording the voices and stories of these AI pioneers CHM is providing an invaluable contribution to the understanding of one of most fascinating technologies of our era.