Generative AIs are the talk of the town these days. But the more we rely on GenAIs, the greater the need to ensure these models are free from bias.
LLMs are trained on large amounts of data, which may allow bias to creep in. For example, a model trained using datasets predominantly generated by white men will offer responses likely reflecting the perspectives of white men. This is not intentional but a byproduct of underlying data used to train the AI.
Platforms cannot completely eliminate bias. But platforms also realise that mitigating bias to the extent possible is critical for the widespread acceptance, reliability and utility of AI models.
I share my perspective on the challenges associated with bias in AI, in an article by the Financial Express (India).
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