For the longest time, people thought that humans could not run a mile in less than four minutes. Then, in 1954, Sir Roger Bannister beat that perception, and shortly thereafter, once he showed it was possible, many other runners were able to achieve this also.
Not long after Sir Roger’s historic achievement, In June 1956, at Dartmouth, New Hampshire, four young scholars: John McCarthy, Marvin Minsky, Nathaniel Rochester, and Claude Shannon jointly initiated and organized the Dartmouth Symposium, which lasted for two months, the goal of the Symposium was simulating human intelligence using a machine.
Four events are frequently cited as outcomes of the Dartmouth Symposium: the neural network simulator demonstrated by Marvin Minsky, the searching method proposed by John McCarthy, and the “Logic Theorist” presented by Herbert Simon and Allen Newell and the founding of the term: “Artificial Intelligence.”
The work of Simon and Newell towards AI was especially highly considered and regarded as a major breakthrough in computer simulation of human intelligence – just like Bannister’s record breaking performance that no one thought was possible, Simon and Newell presented a program able ‘to mimic the problem solving skills of a human being.’
Whilst the Dartmouth Symposium is often considered the first significant event in AI and its participants received much recognition (for example John McCarthy, Allen Newell and Herbert Simon all are recipients of Turing Awards), Simon was also awarded a Nobel Prize in Economics “for his pioneering research into the decision-making process within economic organizations.”
Herbert Simon Professor of Computer Science and Psychology at Carnegie Mellon and researcher at the RAND Corporation, wrote a pair of articles that could be considered to be the seminal articles for the founding paradigm of Artificial Intelligence (AI) research and Behavioral Economics. The two articles are: Behavioral Theory of Rational Choice and Rational Choice and the Structure.
These two papers are the foundation of the work that led to Herb Simon’s Nobel Prize in Economics: ‘that omniscient Economic Man’, the decision-maker, with his immense (assumed) information processing power and prowess was an implausible fiction.
Simon proposes a model of the decision-maker characterized by limited information processing and information gathering capabilities; ‘who therefore must be satisfied with decisions less than optimal; who uses strategies and tactics of thought (what we now term heuristics) to achieve behaviors that are ‘good enough’. This led to bounded rationality, which Simon maintains, dealt with the limits of ‘information processing capacities’ – something he applied to both human intelligence and helped his and others work on AI.
Simon’s research on “human problem solving” became the core of a wide-ranging theoretical project in which AI, economics, and cognitive psychology were closely intertwined and led to his discovery that: “Economics is one of the sciences of the artificial.” (Simon, 1976, p. 441)
Simon and Heuristics
Daniel Kahneman, often thought of as the founder of Behavioral Economics and like Simon a recipient of the Noble Prize in Economics, credits Simon’s work on bounded rationality and heuristics (rules of thumb and shortcuts in thinking) as being hugely influential on his work with Amos Tversky.
In fact so dominant was the concept of the heuristic from Simon on AI that in Computer Science and Operations Research AI was sometimes called “heuristic programming.” See for example this paper by Minsky (Some methods of Artificial Intelligence and Heuristic Programming) and this article on heuristics in computer science.
The word “heuristic” is derived from the Greek verb heuriskein, meaning “to find” or “to discover.” Archimedes is said to have run naked down the street shouting “Heureka” (I have found it) after discovering the principle of flotation in his bath. Authors later changed this to Eureka.
The Logic Theorist program developed by Simon and Newell was “capable of discovering proofs for theorems in elementary symbolic logic, using heuristic techniques similar to those used by humans.” (Newell, Shaw, Simon, 1962, p. 146)
AI improving irrational thinking and behavior
A core theme of Behavioral Economics is that we act irrationally or make sub-optimal decisions. In Maps of bounded rationality: psychology for behavioral economics; Kahneman points out there is a conflict between the two systems we us for thinking. System 1 (perception and intuition) and System 2 (reasoning) can engender inconsistent preferences: “we cannot take it for granted that preferences that are controlled by emotion of the moment will be internally coherent, or even reasonable by the cooler criteria of reflective reasoning. In other words, the preferences of System 1 are not necessarily consistent with the preferences of System 2.”
James G. March a long term collaborator of Herb Simon on Organization Theory and Bounded Rationality writes: “Human beings have unstable, inconsistent, incompletely evoked, and imprecise goals.” (March, 1987, p. 598)
Through AI, machines are gaining in logic and ‘rational’ intelligence and there is no reason to believe that they cannot become smarter than humans. As we use these machines, or Cognitive Assistants they will nudge us to make better decisions in personal finance, health and generally provide solutions to improve our circumstances.
Bounded Rationality, AI and our modern economy
Herbert Simon said: “The principle of bounded rationality is the capacity of the human mind for formulating and solving complex problems is very small compared with the size of the problems whose solution is required for objectively rational behavior in the real world.”
Simon’s work has had a significant impact on the economy and AI is becoming more and more available throughout our world to solve real problems.
Google’s search uses AI and bounded rationality, as Peter Norvig Director of Research at Google has written: Simon’s work on AI and Bounded Rationality: “led to the establishment of search algorithms as perhaps the primary tools in the armory of early AI researchers, and the establishment of problem solving as the canonical AI task.”
AI is already improving how we communicate, analyze data, make financial decisions and trades. It is being put to work in hospitals to improve health diagnosis and soon we will be wearing AI programmed smart watches to monitor our wellbeing.
In the last interview he gave before he passed away Herb Simon reflected on how computers will continue to shape our world and can improve our rationality.
AI technologies will soon be pervasive in solutions that could in fact be the answer to help us overcome irrational behavior and make optimal economic decisions. The more we understand the depth of Herbert Simon’s work the more we will be prepared to take advantage of the great opportunities AI offers us.
Picture credit: Creative Commons Wikipedia