๐ค AI Summary
Current AI evaluation frameworks predominantly emphasize proxy metrics such as capability, safety, and efficiency, while overlooking the actual impact on the holistic well-being of humanity and the planet. This work proposes a human flourishingโcentric paradigm, introducing a multidimensional indicator system that integrates physical, psychological, social, spiritual, and ecological dimensions. It pioneers the "Return on Flourishing" (RoF) as a value-based assessment and decision-making framework for AI systems and post-AGI economic institutions. RoF synthesizes validated measurement instruments from psychology, sociology, and environmental science, combined with counterfactual causal inference, dynamic systems modeling, and value-sensitive design methodologies. Feasibility is demonstrated through corporate pilots applying RoF to AI-enabled job redesign, institutional evaluation, and post-deployment monitoring, offering an actionable, well-being-oriented pathway for AI-driven societal transformation.
๐ Abstract
Current evaluation frameworks for artificial intelligence focus mainly on capability, safety, and proxies such as adoption, engagement, efficiency, productivity, and financial return. These criteria are necessary but insufficient because they do not establish whether increasingly powerful systems improve or degrade human and planetary well-being. Through an integrative conceptual synthesis, we argue that human flourishing should serve as a primary success criterion for artificial intelligence, the global race to develop increasingly capable AI systems, and prospective post-AGI economic systems. We make three contributions. First, Flourishing Metrics provides an extensible framework spanning physical, emotional, financial, relational, spiritual, and planetary well-being, combining validated subjective measures with representative behavioural, organisational, community, and environmental indicators. Second, Return on Flourishing (RoF) extends return on investment by evaluating the counterfactual contribution of interventions, policies, and AI systems to flourishing relative to their resources, risks, and opportunity costs. Third, we develop distribution-sensitive safeguards and show how RoF could guide AI-enabled work redesign, institutional appraisal, assurance, and post-deployment monitoring through business pilots. We formalise flourishing as a dynamic system variable while emphasising the need for democratic specification, empirical calibration, independent validation, and protection against unacceptable losses within particular dimensions or stakeholder groups. RoF is proposed not as a universal reward function, but as a value-accounting and decision architecture for assessing whether intelligence, automation, and economic transformation generate durable human and planetary progress.