What are the risks of using non-transparent AI systems?
Non-transparent AI systems can lead to issues like bias, lack of accountability, and erosion of trust.
Can you explain how bias occurs in these systems?
Bias in non-transparent AI often arises from biased training data or algorithms that are not properly vetted.
What are the consequences of eroded trust in AI?
Eroded trust can result in reduced adoption of AI technologies, regulatory backlash, and public skepticism.
How can we improve transparency in AI?
Improving transparency can involve clear documentation, explainable AI models, and open-source practices.
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