Humans have many cognitive skills not possessed by their nearest primate relatives. The cultural intelligence hypothesis argues that this is mainly due to a species-specific set of socialcognitive skills, emerging early in ontogeny, for participating and exchanging knowledge in cultural groups. We tested this hypothesis by giving a comprehensive battery of cognitive tests to large numbers of two of humans' closest primate relatives, chimpanzees and orangutans, as well as to 2.5-year-old human children before literacy and schooling. Supporting the cultural intelligence hypothesis and contradicting the hypothesis that humans simply have more "general intelligence," we found that the children and chimpanzees had very similar cognitive skills for dealing with the physical world but that the children had more sophisticated cognitive skills than either of the ape species for dealing with the social world.

Most studies of animal cognition focus on group performance and neglect individual differences and the correlational structure of cognitive abilities. Moreover, no previous studies have compared the correlational structure of cognitive abilities in nonhuman animals and humans. We compared the structure of individual differences of 106 chimpanzees and 105 two-year-old human children using 15 cognitive tasks that posed problems about the physical or social world. We found a similar factor of spatial cognition for the two species. But whereas the chimpanzees had only a single factor in addition to spatial cognition, the children had two distinct additional factors: one for physical cognition and one for social cognition. These findings, in combination with previous research, support the proposal that humans share many cognitive skills with nonhuman apes, especially for dealing with the physical world, but in addition have evolved some specialized skills of social cognition.

Abstract. Comparing humans and machines is one important source of information about both machine and human strengths and limitations. Most of these comparisons and competitions are performed in rather specific tasks such as calculus, speech recognition, translation, games, etc. The information conveyed by these experiments is limited, since it portrays that machines are much better than humans at some domains and worse at others. In fact, CAPTCHAs exploit this fact. However, there have only been a few proposals of general intelligence tests in the last two decades, and, to our knowledge, just a couple of implementations and evaluations. In this paper, we implement one of the most recent test proposals, devise an interface for humans and use it to compare the intelligence of humans and Q-learning, a popular reinforcement learning algorithm. The results are highly informative in many ways, raising many questions on the use of a (universal) distribution of environments, on the role of measuring knowledge acquisition, and other issues, such as speed, duration of the test, scalability, etc.