What baboons, babies and Tetris players tell us about interaction: a biosocial view of norm-based social learning

Abstract

Could androids use movements to build relationships? For people, relationships are created with the help of behaviour-shaping norms, which infants begin to discover and manipulate by the third month. To build relationships, MAchines can also learn to exploit human reactions in real-time decision-making. In the video game Tetris, for example, affect co-opts computer-generated patterns to simplify cognitive tasks: norms mediate what Kirsh and Maglio (Cognitive Sci., 18, pp. 513–549, 1994) term epistemic actions, which allow implicit knowledge to shape key pressing in ways that, given past games, are likely to be informative and valuable. Expert players act to change their cognitive states by allowing the game's higher-level states to constrain their lower-level actions. Since this process enables the development of expertise, we might expect it to be widespread; but it seems marginal in hamadryas baboons, although they use affect and complex norms. In humans, by contrast, infants use adults as cognitive resources in developing their epistemic abilities. This has engineering implications for android designers. Since androids can elicit epistemic actions, engineers need to develop an affect–sensitive interface. If successful at this, even rudimentary co-action may prompt people to report experiencing androids as both making choices and violating expectations.