Fixing “Same Name” Confusion in AI Search Results Risk
Same-Name Confusion Risk in AI Search Results As generative AI systems increasingly influence public perception, identity overlap has become a measurable governance risk. When two individuals share identical names, AI systems may transfer claims across entities. This creates what is known as knowledge graph contamination. The risk is not limited to confusion. It introduces reputational harm when incorrect achievements, affiliations, or allegations are attributed to the wrong person. AI misattribution liability exposure arises when generative systems present blended information as authoritative output. Because these systems rely on probabilistic retrieval and knowledge graph clustering, weak signal separation can cause structural identity contamination. Key risk vectors include: • Improper semantic clustering • Cross-source attribute blending • Weak disambiguation protocols AI search identity integrity risk escalates when zero-click summaries or automated answers disp...