E238: The diagnostic room: The Fifteen Failures Only Human Judgement Catches

<p>In this solo episode of AI For Pharma Growth, Dr Andree Bates explores one of the biggest blind spots in pharma AI: the failures that can survive a normal review process even when the output sounds polished, plausible and well grounded.</p><p>Dr Andree explains why better models and better retrieval do not remove the need for human judgement. In fact, as AI systems improve, people often scrutinise them less. Fluent prose can create a false sense of reliability, while automation bias and anchoring make reviewers less likely to challenge the underlying frame.</p><p>The episode introduces three broad families of failure: invented, distorted and misdirected. These include fabricated or misattributed citations, silent interpolation, dropped qualifiers, hedge-to-claim escalation, manufactured consensus, stale guidance and planted instructions. Many of these are harder to catch because the output reads better than the truth.</p><p>Dr Andree also shares practical checks teams can use, including tracing claims back to source, checking what is unsupported, looking for missing qualifiers, regenerating outputs for stability and deliberately testing the opposite case.</p><p>The key message is that prompting is only half the skill. In a regulated industry, teams also need to be trained to judge what comes back.</p><p>Topics Covered</p><ul><li><p>Why better AI can lead to less scrutiny</p></li><li><p>Automation bias and anchoring</p></li><li><p>Invented, distorted and misdirected failures</p></li><li><p>Fabricated and misattributed citations</p></li><li><p>Dropped qualifiers and strengthened claims</p></li><li><p>Manufactured consensus</p></li><li><p>Prompt injection and planted instructions</p></li><li><p>Claim-by-claim verification</p></li><li><p>Why review methods must change for AI</p></li><li><p>The growing importance of the judgement layer</p></li></ul><p><strong>About Eularis</strong><br>Eularis builds AI capability inside pharma and biotech — over 20 years applying AI to real pharmaceutical problems, inside real pharmaceutical and biotech companies.</p><p>Keynotes and live sessions — Working sessions for pharma teams where nobody leaves with notes. They leave with working prompts and real capability they&#39;ve already run on their own work.</p><p>The AI Enablement Institute — Strategy and a workshop get you started; neither stays current. Most pharma companies already have a generic AI course library. None of it is written for a regulatory writer, an MSL or a