The Shepherd Test: How Will Super Intelligent Agents Balance Care and Control in Asymmetric Relationships?

This paper introduces the Shepherd Test, a new conceptual test for assessing the moral and relational dimensions of su- perintelligent artificial agents. The test is inspired by human interactions with animals, where ethical considerations about care, manipulation, and consumption arise in contexts of asym- metric power and self-preservation. We argue that AI crosses an important, and potentially dangerous, threshold of intelli- gence when it exhibits the ability to manipulate, nurture, and instrumentally use less intelligent agents, while also manag- ing its own survival and expansion goals. This includes the ability to weigh moral trade-offs between self-interest and the well-being of subordinate agents. The Shepherd Test thus chal- lenges traditional AI evaluation paradigms by emphasizing moral agency, hierarchical behavior, and complex decision- making under existential stakes. We argue that this shift is crit- ical for advancing AI governance, particularly as AI systems become increasingly integrated into multi-agent environments. We conclude by identifying key research directions, including the development of simulation environments for testing moral behavior in AI, and the mathematical formalization of ethical manipulation within multi-agent systems