Oversight game with bilateral information asymmetry

In the interaction between humans and autonomous systems, a fundamental challenge arises when both parties possess private information that they do not fully share. This scenario, known as bilateral information asymmetry, occurs for example when a robot or software agent has inspected a situation that its human supervisor cannot directly evaluate, while the human knows their own preferences or reward functions. This type of dynamic is critical in the design of reliable artificial intelligence systems, especially in environments where human oversight must be effective without requiring constant intervention. Models such as the oversight game or cooperative inverse reinforcement learning have made it possible to analyze how to optimize joint decision-making when there is hidden information on both sides. A relevant finding is that, even in simplified versions such as a single-turn contextual bandit game, the existence of a gap between the team optimum and a natural myopic rule can be demonstrated. This gap represents an 'avoidable harm': situations where the agent knows the proposed action is harmful and stopping it would help, but a myopic human who trusts their prior knowledge decides not to oversee. This phenomenon reveals the price of non-credible oversight communication, and its dynamic resolution requires passive learning and active signaling over repeated rounds. For companies seeking to implement AI for businesses safely and efficiently, understanding these mechanisms is essential. At Q2BSTUDIO we develop artificial intelligence solutions that integrate adaptive oversight layers, allowing both humans and agents to share relevant information without compromising autonomy or security. Additionally, we offer custom applications that incorporate transparency and control mechanisms, ideal for environments with information asymmetries. Our services range from artificial intelligence and cybersecurity to aws and azure cloud services, business intelligence services with power bi, and the creation of AI agents that collaborate with human teams. The key lies in designing systems where oversight communication is credible and avoidable harm is minimized, a goal we pursue through custom software that adapts to the specific needs of each organization.