AI Code Review in Regulated Environments: What a Human Expert Still Has to Own
This story was originally published on HackerNoon at: https://hackernoon.com/ai-code-review-in-regulated-environments-what-a-human-expert-still-has-to-own. Why a name on a pull request isn't proof anyone actually reviewed it, and what AI-generated code is exposing about code review at scale. Check more stories related to finance at: https://hackernoon.com/c/finance. You can also check exclusive content about #fintech-startups, #artificial-intelligence, #ai-code-review, #ai-assisted-coding, #code-review, #ai-generated-code, #human-ai-collaboration, #human-in-the-loop, and more. This story was written by: @duycao. Learn more about this writer by checking @duycao's about page, and for more stories, please visit hackernoon.com. A landmark study found 40% of AI-generated code contained vulnerabilities, yet nearly every one of those PRs still carries a human "reviewed" stamp. Defect detection drops sharply past ~400 lines per review, exactly the size AI-generated PRs tend to land at. A named reviewer isn't proof of judgment. Three categories of decisions (regulatory intent, compliance-sensitive architecture, escalation calls) need to go to a specific accountable person, not general review.
