When is it permissible for artificial intelligence to lie? A trust-based approach
This addresses ethical challenges for AI developers and users in industry settings, but it is incremental as it builds on existing trust and negotiation theories.
The paper tackles the problem of determining when conversational AI can ethically lie in negotiations by proposing a trust-based normative framework, noting that cultural norms and individual expectations affect its applicability and generalizability.
Conversational Artificial Intelligence (AI) used in industry settings can be trained to closely mimic human behaviors, including lying and deception. However, lying is often a necessary part of negotiation. To address this, we develop a normative framework for when it is ethical or unethical for a conversational AI to lie to humans, based on whether there is what we call "invitation of trust" in a particular scenario. Importantly, cultural norms play an important role in determining whether there is invitation of trust across negotiation settings, and thus an AI trained in one culture may not be generalizable to others. Moreover, individuals may have different expectations regarding the invitation of trust and propensity to lie for human vs. AI negotiators, and these expectations may vary across cultures as well. Finally, we outline how a conversational chatbot can be trained to negotiate ethically by applying autoregressive models to large dialog and negotiations datasets.