He believed that eventually we will have computers that achieve Artificial Intelligence, but we do not know how long this will take. He whimsically suggested it could be between "10 or 500" years. Fortunately we do not have to despair in the interim period, because we can still have intelligent assistant computers that work not through artificial intelligence, but Man-Computer Symbiosis.
Symbiosis is a well known concept borrowed from biology - something like the "interaction between two different organisms living in close physical association, typically to the advantage of both." The important point is that they are different organisms, that nevertheless find a way to interact in mutually beneficial ways. When applied to computers, the key point is that the computers don't have to run the same program as the human. We don't need to worry about troublesome concepts like Artificial Intelligence or Cognitive Systems if we can instead achieve Symbiotic Systems which don't carry the same philosophical and emotional baggage. So what is it about?
It turns out that there is a simple way to think about what a symbiotic computer might be, and how it differs from other beneficial programs like spreadsheets and search engines. The main insight behind symbiotic computing is that the interaction between a human and a machine can sometimes hit unforeseen alternatives that requires an action which has not been anticipated by the designer of the application. That is, the solution requires some steps that have not been specifically programmed into the execution of the program. It is in this situation that the program needs to adapt in a way that is helpful to the human user, where the program takes the sort of initiative that is simply not a part of the operation of normal software tools. An example might be the need to generate novel hypotheses while categorizing large volumes of novel information, to help the human user make sense of the data. This is largely what Watson does while answering questions in Jeopardy!, where each novel questions requires the formulation of hypotheses from the large volume of assimilated data. The Watson system is usually presented as a question answering program, but in fact it generates a large number of alternative hypotheses from which it picks one answer based on a number of heuristics. If instead Watson presented several hypotheses in a collaborative problem solving session, then this would be an example of symbiotic computing, which would possibly achieve close to 100% accurate performance. If we think about such systems in this way we can avoid unnecessarily loaded terms like Cognitive Computing, and still have clever programs that help us carry out cognitively demanding tasks.
Still, it is not easy to create such systems. As Licklider says: "To think in interaction with a computer in the
same way that you think with a colleague whose competence
supplements your own will require much tighter
coupling between man and machine than is suggested by
the example and than is possible today."
In order to achieve coupling we need to understand important aspects of cognition, even if we don't need to reproduce it. But much more about this in future posts.
