2.4 Preschool as a View into Human-like General Intelligence 27
specific goals, will have a tendency to solve other problems in creative ways, thus fulfilling its novelty goal along with its other goals. This can be seen at the level of childlike behaviors, and also at a much more advanced level. Salvador Dali wanted to depict his thoughts and feelings, but he also wanted to do so in a striking and unusual way; this combination of aspirations spurred him to produce his amazing art. A child who is asked to draw a house, but has a goal of novelty, may draw a tower with a swimming pool on the roof rather than a typical Colonial structure. A physical motivated by novelty will seek a non-obvious solution to the equation at hand, rather than just applying tried and true methods, and perhaps discover some new phenomenon. Novelty can be measured formally in terms of information-theoretic surprisingness based upon a given basis of knowledge and experience [Sch06]; something that is novel and creative to a child may be familiar to the adult world, and a solution that seems novel and creative to a brilliant scientist today, may seem like cliche’ elementary school level work 100 years from now.
Measuring creativity is even more difficult and subjective than measuring intelligence. Qual- itatively, however, we humans can recognize it; and we suspect that the qualitative emergence of dramatic, multidisciplinary computational creativity will be one of the things that makes the human population feel emotionally that advanced AGI has finally arrived.
2.4 Preschool as a View into Human-like General Intelligence
One issue that arises when pursuing the grand goal of human-level general intelligence is how to measure partial progress. The classic Turing Test of imitating human conversation remains too difficult to usefully motivate immediate-term AI research (see [HF 95] [Fre90] for arguments that it has been counterproductive for the AI field). The same holds true for comparable alter- natives like the Robot College Test of creating a robot that can attend a semester of university and obtain passing grades. However, some researchers have suggested intermediary goals, that constitute partial progress toward the grand goal and yet are qualitatively different from the highly specialized problems to which most current AI systems are applied.
In this vein, Sam Adams and his team at IBM have outlined a so-called “Toddler Turing Test,” in which one seeks to use AI to control a robot qualitatively displaying similar cognitive behaviors to a young human child (say, a 3 year old) [AABL02]. In fact this sort of idea has a long and venerable history in the AI field — Alan Turing’s original 1950 paper on AT [Tur50], where he proposed the Turing Test, contains the suggestion that
"Instead of trying to produce a programme to simulate the adult mind, why not rather try to produce one which simulates the child’s?"
We find this childlike cognition based approach promising for many reasons, including its in- tegrative nature: what a young child does involves a combination of perception, actuation, lin- guistic and pictorial communication, social interaction, conceptual problem solving and creative imagination. Specifically, inspired by these ideas, in Chapter 16 we will suggest the approach of teaching and testing early-stage AGI systems in environments that emulate the preschools used for teaching human children.
Human intelligence evolved in response to the demands of richly interactive environments, and a preschool is specifically designed to be a richly interactive environment with the capability to stimulate diverse mental growth. So, we are currently exploring the use of CogPrime to control
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