Promoting the Transparency of AI-Generated Inferences

Many businesses today use artificial intelligence to generate inferences from the personal data they collect. This practice allows companies to better understand individual consumer preferences. However, it often occurs secretly, without consumers being aware of it. Consumers’ privacy may be compromised as they lack control over the accuracy, flow, and use of the generated inferential data. Although current data protection regulations, like the General Data Protection Regulation (GDPR), provide data subject rights, access to these inferences is not guaranteed. Businesses can deny inference access requests by exploiting the broad scope of trade secrecy law, citing their interest in protecting such data as trade secrets. This Essay deems it essential to re-examine the scope and application of trade secrets law in this context. After providing a descriptive analysis of the underlying legal frameworks in the USA and EU that empower businesses to categorize consumer inferences as trade secrets, the Essay suggests that data protection or consumer protection authorities should carefully examine the scope of trade secrets law in their respective jurisdictions and issue guidelines to limit potential abuse of the law.