Let’s say that we want to understand if a certain system or phenomenon is exhibiting human-level intelligence. What would we then look for? There are multitudes of such tests, and they look for a great variety of things. One catalogue of such tests is BIG-bench, a battery of task tests that is aimed at understanding the capabilities of different systems. 1 Srivastava, Aarohi, et al. “Beyond the imitation game: Quantifying and extrapolating the capabilities of language models.” arXiv preprint arXiv:2206.04615 (2022).See here for the paper.
BIG-bench looks at a large number of tasks that are both creative and difficult, and it is a fascinating catalogue – but it does not specifically look at if the system plays. Yet, the ability to play is probably fundamental to human intelligence – not just incidental or a kind of idling mode. 2 See for example Fein, Greta G. “Skill and intelligence: The functions of play.” Behavioral and Brain Sciences 5.1 (1982): 163-164. exploring the adaptiveness of play and the setting of intrinsic limitations.
Would it then not make sense to look at if there is a way to test for play? To see if an intelligence can play? Well, you could argue that it seems quite clear that LLMs can play with us – we can ask it to play any game where we give it the rules, and we can even ask it to make up a game about something and it will do so. But that is not quite what we are looking for. What we want to see is if a system starts playing itself – if it can be, in some sense, curious enough to set intrinsic limitations and obstacles for itself and find joy in playing a game that it has invented for itself.
This notion of motivation by curiosity also seems a little trivial, you just need to build a system that has an instruction to play games when it does nothing else, right? Not quite. When we play and how we play are not random behaviours. Play is not the equivalent of a human screensaver. Instead, play is something that is related to building models of the world, planning ahead, remembering systems of rules — it is much more fundamental.
Games may play a much larger role in intelligence than we think, and the role of play is still being explored conceptually in philosophy. 3 See e.g. Nguyen, C. Thi. “Philosophy of games.” Philosophy Compass 12.8 (2017): e12426. and the same author’s subsequent book Nguyen, C. Thi. Games: Agency as art. Oxford University Press, USA, 2020. . Maybe the study of complex systems like models and their behaviour should focus not only on problem solving, but the ways in which agency is exhibited and structured in play and games.
There is an irony here – in a way – since a lot of research has focused on how to play games and to do so until the machine can beat human players. Maybe that was almost right, and the greater question is not how to play, but when and why we play and testing for that in a different way.
There is much more to be explored here – like how our narrow understanding of rationality and intelligence obscures the adaptive value and role of things like play and games, or how games – as mental models – structure the way we learn and understand the world.
Notes:
- 1Srivastava, Aarohi, et al. “Beyond the imitation game: Quantifying and extrapolating the capabilities of language models.” arXiv preprint arXiv:2206.04615 (2022).See here for the paper.
- 2See for example Fein, Greta G. “Skill and intelligence: The functions of play.” Behavioral and Brain Sciences 5.1 (1982): 163-164. exploring the adaptiveness of play and the setting of intrinsic limitations.
- 3See e.g. Nguyen, C. Thi. “Philosophy of games.” Philosophy Compass 12.8 (2017): e12426. and the same author’s subsequent book Nguyen, C. Thi. Games: Agency as art. Oxford University Press, USA, 2020.