As AI becomes a ubiquitous part of everyday life, people increasingly understand how it works. Whereas traditional computer programs operate on clear logic—”If A happens, then do B”—AI models, especially neural networks, make decisions that are difficult to trace back to any single rule or line of code. As a result, traditional program analysis techniques such as code review are ineffective in addressing neural networks’ vulnerabilities.
Amplifying AI’s impact by making it understandable
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