The Triangles of Dishonesty:Modelling the Evolution of Lies, Bullshit, and Deception in Agent Societies

Misinformation and disinformation in agent societies can be spread due to the adoption of dishonest communication. Recently, this phenomenon has been exacerbated by advances in AI technologies. One way to understand dishonest communication is to model it from an agent-oriented perspective. In this paper we model dishonesty games considering the existing literature on lies, bullshit, and deception, three prevalent but distinct forms of dishonesty. We use an evolutionary agent-based replicator model to simulate dishonesty games and show the differences between the three types of dishonest communication under two different sets of assumptions: agents are either self-interested (payoff maximizers) or competitive (relative payoff maximizers). We show that:(i) truth-telling is not stable in the face of lying, but that interrogation helps drive truth-telling in the self-interested case but not the competitive case;(ii) that in the competitive case, agents stop bullshitting and start truth-telling, but this is not stable;(iii) that deception can only dominate in the competitive case, and thattruth-telling is a saddle point in which agents realise deception can provide better payoffs

The evolution of deception.

Funder: MIT Media LabFunder: King's College LondonFunder: Ethics and Governance of AI FundDeception plays a critical role in the dissemination of information, and has important consequences on the functioning of cultural, market-based and democratic institutions. Deception has been widely studied within the fields of philosophy, psychology, economics and political science. Yet, we still lack an understanding of how deception emerges in a society under competitive (evolutionary) pressures. This paper begins to fill this gap by bridging evolutionary models of social good-public goods games (PGGs)-with ideas from interpersonal deception theory (Buller and Burgoon 1996 Commun. Theory 6, 203-242. (doi:10.1111/j.1468-2885.1996.tb00127.x)) and truth-default theory (Levine 2014 J. Lang. Soc. Psychol. 33, 378-392. (doi:10.1177/0261927X14535916); Levine 2019 Duped: truth-default theory and the social science of lying and deception. University of Alabama Press). This provides a well-founded analysis of the growth of deception in societies and the effectiveness of several approaches to reducing deception. Assuming that knowledge is a public good, we use extensive simulation studies to explore (i) how deception impacts the sharing and dissemination of knowledge in societies over time, (ii) how different types of knowledge sharing societies are affected by deception and (iii) what type of policing and regulation is needed to reduce the negative effects of deception in knowledge sharing. Our results indicate that cooperation in knowledge sharing can be re-established in systems by introducing institutions that investigate and regulate both defection and deception using a decentralized case-by-case strategy. This provides evidence for the adoption of methods for reducing the use of deception in the world around us in order to avoid a Tragedy of the Digital Commons (Greco and Floridi 2004 Ethics Inf. Technol. 6, 73-81. (doi:10.1007/s10676-004-2895-2))