What Is the Responsibility of Developers Using Generative AI?
Spend enough time around generative AI projects and a pattern becomes obvious. The technical conversation moves fast. Capabilities, benchmarks, integrations, model comparisons. What moves much slower is the conversation about what developers are actually accountable for when something goes wrong. And things do go wrong. A hiring tool trained on historical data quietly filters out candidates from certain backgrounds. A healthcare chatbot confidently gives wrong medical information. A content system produces outputs that nobody tested for because the edge cases seemed unlikely at the time. These are not hypothetical scenarios. They have already happened, and in every case a developer made choices during the build that contributed to the outcome. That is the conversation this guide is built around. Why Developer Responsibility Matters More in Generative AI With traditional software, the relationship between input and output is something a developer can trace, test, and predict with ...