Designing a Safe Autonomous Artificial Intelligence Agent based on Human Self-Regulation
This addresses the safety issue for AI developers and users, but it is incremental as it builds on existing ideas without introducing a new method.
The paper tackles the problem of designing safe AI agents by proposing to use principles from human self-regulation and goal setting to specify initial intentions and implement redundant safety mechanisms, aiming to prevent unwanted outcomes as systems grow in complexity.
There is a growing focus on how to design safe artificial intelligent (AI) agents. As systems become more complex, poorly specified goals or control mechanisms may cause AI agents to engage in unwanted and harmful outcomes. Thus it is necessary to design AI agents that follow initial programming intentions as the program grows in complexity. How to specify these initial intentions has also been an obstacle to designing safe AI agents. Finally, there is a need for the AI agent to have redundant safety mechanisms to ensure that any programming errors do not cascade into major problems. Humans are autonomous intelligent agents that have avoided these problems and the present manuscript argues that by understanding human self-regulation and goal setting, we may be better able to design safe AI agents. Some general principles of human self-regulation are outlined and specific guidance for AI design is given.