In a world where large language models (LLMs) like GPT dominate headlines, one pressing question remains:
“How do we trust something we barely understand? “
Sure, these models can generate essays, write code, and even pass the bar exam, but the “why” behind their decisions often eludes their creators.
Welcome to the Wild West of AI explainability — a world where the stakes are high, and the solutions are just beginning to take shape.
Imagine you’re using GPT to automate loan approvals. It says no to a customer.
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The natural next question: Why?
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Now imagine this refusal was due to something like an implicit bias baked into the training data. Yikes, right?
Explainability isn’t just a buzzword; it’s critical for:
- Ethics: Avoiding bias and discrimination.
- Compliance: Satisfying legal frameworks like GDPR, which demand explainable AI.
- Trust: Convincing users (and regulators) that the…