Algorithmic bias describes systematic and repeatable errors in computer systems, including AI models, that produce unfair outcomes, often by reproducing biases contained in training data, for example in hiring or policing.
Many companies rush into AI because of market pressure and then stall when results disappoint or the gut feeling says something is wrong. In this conversation, AI strategy advisor Wiebke Apitzsch shows business leaders why responsible AI is good business…
This episode explains the real difference between automation and agents, cutting through the confusion created by marketing and buzzwords. Automation is framed as rigid and repetitive, useful for consistent, rule-based tasks but incapable of adapting when…
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