Source: SSRN SSRN presents the abstract for the academic paper "Beyond the Black Box: AI, Transparency, and Corporate Social Responsibility" by Sarah H. Dadush. The paper addresses the critical issue of opacity in artificial intelligence systems used by corporations. It argues that the lack of transparency in how these "black box" algorithms make decisions poses significant risks, not only to consumers and the public but also to the companies themselves, exposing them to legal, reputational, and financial liabilities. The author contends that existing legal frameworks may be insufficient to compel the necessary level of transparency from corporations deploying AI.

The core argument of the paper is that the principles of Corporate Social Responsibility (CSR) can be effectively leveraged to fill this regulatory gap. Dadush proposes that CSR initiatives and reporting standards should be expanded to include meaningful disclosures about the use of AI. By reframing AI transparency as a fundamental component of corporate responsibility and ethical conduct, stakeholders—including investors, consumers, and civil society—can exert pressure on companies to adopt more transparent practices. This approach seeks to create a market-driven incentive for corporations to open up their AI black boxes, thereby fostering greater accountability and mitigating the societal harms associated with opaque algorithmic decision-making.