Nathaniel Reed, MA, MBA’s Post

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Senior Labor Relations Specialist, Chicago Department of Aviation (CDA)

Sound advice from EY's Andy Baldwin (in Harvard Business Review, Jan. 2024) on how to embed DEI into your company's AI strategy: 1. Advancing diversity, equity, and inclusion (DEI) is a business imperative when deploying AI systems, not just a "nice to have". 2. To create well-designed AI systems with minimal bias, involve a wide range of stakeholders from different demographic groups, train the AI on diverse and representative data, and employ diverse development and testing teams. **3. Organizations should prioritize DEI in their workforce upskilling and training programs related to AI, ensuring underrepresented groups gain critical AI skills to access new career opportunities. 4. When used ethically and responsibly, AI can boost DEI by identifying patterns of bias or inequality within organizations, such as pay gaps or unfair promotion processes. 5. AI systems can improve workplace accessibility for people with disabilities through tools like speech recognition and image recognition. 6. Companies should use AI to collect and analyze data on employee engagement, satisfaction, and feedback to better tailor and customize DEI initiatives based on specific needs and experiences. https://lnkd.in/dGg3aa52 #AI #DEI #aistrategy #innovation

3 Ways to Embed DEI Into Your Company’s AI Strategy

3 Ways to Embed DEI Into Your Company’s AI Strategy

hbr.org

Nathaniel Reed, MA, MBA

Senior Labor Relations Specialist, Chicago Department of Aviation (CDA)

7mo

"A good example of a context where a poorly designed AI system can amplify bias is health care. Research by Imperial College London has highlighted that because the data that is used to train algorithms tends to be unrepresentative of minority ethnic groups, there is a risk that AI systems could exacerbate existing health inequities. So, in the case of skin cancer, for instance, if images of white patients are used to train algorithms to spot melanoma, Black patients may experience missed diagnoses that lead to them suffering more life-threatening health outcomes" (Baldwin, 2024).

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