Conclusion:

Biases in artificial intelligence (AI) often lead to discrimination at the expense of particular segments of society. When organisations leverage new technologies that demonstrate inequality and inaccuracy from AI and machine learning, the impact of under-representation and human prejudice – once detected or uncovered when a faulty decision is realised – can result in financial losses and reputational damage. Furthermore, bias in algorithms can result in less effective automation by further reinforcing flawed assumptions and processes.

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