kaal:claim:4941807-015

A critical unsolved challenge for AI governance is bias mitigation, because biases enter inadvertently when algorithms incorporate discriminatory practices carried in the data used for training.

AI governance does encounter a critical challenge in mitigating biases within AI systems, where biases can inadvertently arise through algorithms incorporating discriminatory practices due to data used in training.

Wulf A. Kaal, AI Governance Via Web3 Reputation System (2024), Shortcomings in Existing AI Governance, p. 17
https://ssrn.com/abstract=4941807 · source PDF

Wulf A. Kaal, AI Governance Via Web3 Reputation System (2024). SSRN: https://ssrn.com/abstract=4941807

• where training data embeds discriminatory practices

failuresupport: evidencedfailure: training data bias propagationfamily: ai-model-and-training-failureai-and-agentseducation-and-practicegovernance-design

• restates kaal:claim:4796714-011 Bias in AI systems arises when algorithms incorporate discriminatory practices carried in their training data,...
• restates kaal:claim:4855607-003 Deep learning models inadvertently learn and amplify whatever biases exist in their training data, so the comp...

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