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

2025-07-10

AI Summary

Conventional ESG frameworks lack the conceptual and operational granularity to effectively assess ethical risks and human-centered value in AI-intensive enterprises. Method: This paper introduces the first ethics-focused investment evaluation model specifically designed for AI companies. Grounded in established AI ethics principles, it constructs a quantifiable nine-dimensional scoring system covering algorithmic fairness, data governance, transparency, and other critical domains. The model integrates data-driven analytics with structured performance assessment to bridge theoretical and practical gaps in existing ESG frameworks—particularly regarding machine learning systems, large-scale data processing, and autonomous decision-making. Contribution/Results: The resulting framework demonstrates both academic rigor and real-world applicability. It provides investors with a values-aligned, decision-ready tool that embeds ethical considerations directly into investment workflows—transforming abstract normative principles into comparable, auditable, and actionable investment criteria.

Technology Category

• Philosophy and Ethics of AI: Bias, Fairness & Equity
• Machine Learning: Ethics, Bias, and Fairness
• Humans and AI: Learning Human Values and Preferences

Application Category

• Economics, Online Markets and Human Computation: Fairness and ethical considerations in crowd work and in human-in-the-loop AI systems
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• User Modeling, Personalization and Recommendation: Accountability, Transparency, and Ethics for personalization

Abstract

Does AI conform to humans, or will we conform to AI? An ethical evaluation of AI-intensive companies will allow investors to knowledgeably participate in the decision. The evaluation is built from nine performance indicators that can be analyzed and scored to reflect a technology's human-centering. The result is objective investment guidance, as well as investors empowered to act in accordance with their own values. Incorporating ethics into financial decisions is a strategy that will be recognized by participants in environmental, social, and governance investing, however, this paper argues that conventional ESG frameworks are inadequate to companies that function with AI at their core. Fully accounting for contemporary big data, predictive analytics, and machine learning requires specialized metrics customized from established AI ethics principles. With these metrics established, the larger goal is a model for humanist investing in AI-intensive companies that is intellectually robust, manageable for analysts, useful for portfolio managers, and credible for investors.

Problem

• Evaluating ethical performance of AI-intensive companies for investors
• Developing specialized metrics for AI ethics beyond conventional ESG frameworks
• Creating a humanist investment model for AI-driven firms

Innovation

• Nine performance indicators for ethical AI evaluation
• Customized metrics from AI ethics principles
• Humanist investing model for AI-intensive companies