Combatting Algorithmic Bias

To generate trust in AI, here are five measures to reduce algorithmic biases:

• Determine your company’s unique vulnerabilities and define bias for your specific AI systems.
• Pay special attention to issues in historical data and data acquired from third parties.
• A systematic approach to continuous management of AI should be critical to building your ongoing AI risk confidence.
• Recognizing bias is often a matter of perspective, and people from different racial and gender identities and economic backgrounds will notice different biases. Building diverse teams helps reduce the potential risk of bias falling through the cracks.
• You should continually analyze your data and algorithms for fairness. Technology tools such as Bias Analyzer can help automate this process as well as show the costs and benefits associated with a variety of possible mitigation actions.