A Fair Objective for Human-Empowerment-Preserving AI: Desiderata, Design, and Likely Behavioral Consequences
Jobst Heitzig, Ram Potham
Why It Matters
What makes this one worth your time
Understanding how to balance power dynamics in human-AI interactions is crucial for developing safe and beneficial AI systems.
This research introduces a new objective function aimed at balancing power between humans and AI.
Summary
The paper proposes a framework for designing AI systems that prioritize human empowerment and manage power dynamics through a parametrizable objective function, while considering human bounded rationality and social norms.
Key contributions
- Development of a parametrizable and decomposable objective function for AI systems.
- Proof of how specific desiderata enforce functional forms and restrict parameter ranges.
- Exemplification of the consequences of maximizing the proposed metric in various scenarios.
Notable insights
- The approach incorporates human bounded rationality and social norms into the design of AI objectives, which is often overlooked.
- The use of a parametrizable and decomposable objective function allows for flexibility in addressing diverse human goals.
Possible limitations
- Not stated in the abstract.
Abstract
arXiv:2608.08240v1 Announce Type: new Abstract: This paper explores the idea of promoting well-being and safety in human-AI interactions by forcing AI agents explicitly to empower humans and to manage the power balance between humans and AI agents in a desirable way. Using a principled, partially axiomatic approach based on desirable properties, we design a parametrizable and decomposable objective function for AI systems that represents an inequality- and risk-averse long-term aggregate of human power. It can take into account models of human bounded rationality and social norms, and crucially, considers a wide variety of possible human goals. We prove how certain desiderata enforce particular functional forms and restrict parameter ranges. We exemplify the consequences of softly maximizing this metric in several paradigmatic situations and describe what instrumental sub-goals it will likely imply.