AI Human Impact: Toward a Model for Ethical Investing in AI-Intensive Companies

AI ethics requires specialized investment metrics beyond traditional ESG frameworks. The paper argues that conventional Environmental, Social, and Governance (ESG) investing criteria are inadequate for evaluating AI-intensive companies, necessitating customized metrics specifically designed to assess how well AI systems are centered on human values and needs.

Nine performance indicators can measure whether AI serves human interests. The paper proposes a structured evaluation system with nine specific indicators that investors can use to score and analyze whether AI technologies are designed to conform to human values or whether they risk forcing humans to adapt to AI systems instead.

Investors can align financial decisions with their ethical values regarding AI. By using this human-centered evaluation model, investors gain "objective investment guidance" that empowers them to make portfolio decisions consistent with their personal values about responsible AI development and deployment.

Current AI systems require scrutiny on data practices and algorithmic decision-making. The framework specifically addresses concerns about "big data, predictive analytics, and machine learning"—highlighting that investors need tools to evaluate how AI-intensive companies handle data collection, algorithmic transparency, and automated decision-making that affects people's lives.

Ethical AI investing is both intellectually sound and practically feasible. The paper positions humanist investing in AI companies as "intellectually robust, manageable for analysts, useful for portfolio managers, and credible for investors"—suggesting that responsible AI investment doesn't require choosing between financial viability and ethical principles.