The hiring scenario illustrates the accountability principle in a recognizable context. The broader module — verification of AI-generated research, code review standards, and the human-in-the-loop standard — applies to every role that uses AI tools to produce work that informs decisions or gets submitted as accurate.

Under the EU AI Act, high-risk AI systems include those used in hiring and employment decisions, in critical infrastructure, in education, in law enforcement, and in certain financial services. High-risk systems require specific human oversight, transparency, and documentation obligations. If your organization uses AI in any of these areas, consult your legal or compliance team [...]

Yes. The accountability standard applies regardless of which tool generated the content. AI built into enterprise software is still capable of hallucination, bias, and error. The human review requirement does not depend on the tool's sophistication or approval status.

Using AI as a first draft is appropriate when the human editor reviews and takes responsibility for the final output — not just the edits. If an AI-generated sentence containing a fabricated citation survives into the final document because the editor didn't verify the citations, the editor is accountable for that error.

The level of verification should be proportionate to the consequences of error. AI-assisted brainstorming for internal use requires less verification than a regulatory submission. Code deployed to a customer-facing system requires more review than a personal productivity script. The standard is: Would you be comfortable defending every element of this output as accurate and appropriate [...]