Governing Artificial Intelligence in Scientific Research: The ARCHON Framework — Ethical Requirements Derived from Technical Architecture
TL;DR
This paper proposes the ARCHON framework, a set of ten requirements derived from the technical architecture of AI systems, to facilitate ethical compliance of scientific research for experts and practicioners engaging in roles such as proposal evaluators, project officers, ethics board members, or research administrators.
Abstract
Artificial Intelligence (AI) is rapidly entering scientific research programmes on the assumption that the established ethical frameworks are enough to address failure risks. But that assumption is wrong: AI systems are structurally different from the tools that conventional research ethics was designed to govern. As illustrated by mainstream models, AI systems can be characterized by being stochastic, opaque, resource-intensive, and operate at population scale, meaning that ethical breaches can extend far beyond individual research projects, with potential consequences for public trust in democratic institutions. Taking the case of EU research as reference, this paper proposes the ARCHON framework,a set of ten requirements derived from the technical architecture of AI systems, to facilitate ethical compliance of scientific research for experts and practicioners engaging in roles such as proposal evaluators, project officers, ethics board members, or research administrators. The paper includes a mapping table intended to facilitate the application of the framework to evaluate ethical compliance, both for specific projects and general research programmes. Applied consistently, the ARCHON framework enables substantive rather than merely declarative AI ethical compliance, contributing this way for scientific research policy to continue addressing societal needs while remaining democratically accountable.