Tag: explainability
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Resource: AI Blindspot – A discovery process for spotting unconscious biases and structural inequalities in AI systems.
AI Blindspots are oversights in a team’s workflow that can generate harmful unintended consequences. They can arise from our unconscious biases or structural inequalities embedded in society. Blindspots can occur at any point before, during, or after the development of a model. The consequences of blindspots are challenging to foresee, but they tend to have…
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The Future of Artificial Intelligence Depends on Trust
To open up the AI black box and facilitate trust, companies must develop AI systems that perform reliably — that is, make correct decisions — time after time. The machine-learning models on which the systems are based must also be transparent, explainable, and able to achieve repeatable results. Source: Rao, A. & Cameron, E. (2018).…