Over the past several years, concerns around AI ethics have gone mainstream. The concerns, and the outcomes everyone wants to avoid, are largely agreed upon and well documented. No one wants to push out discriminatory or biased AI. No one wants to be the object of a lawsuit or regulatory investigation for violations of privacy. But once we’ve all agreed that biased, black box, privacy-violating AI is bad, where do we go from here? The question most every senior leader asks is: How do we take action to mitigate those ethical risks?
Ethics and AI: 3 Conversations Companies Need to Have
Move from abstract concerns to actionable plans.
March 21, 2022
Summary.
While concerns about AI and ethical violations have become common in companies, turning these anxieties into actionable conversations can be tough. With the complexities of machine learning, ethics, and of their points of intersection, there are no quick fixes, and conversations around these issues can feel nebulous and abstract. Getting to the desired outcomes requires learning to talk about these issues differently. First, companies must decide who needs to be part of these conversations. Then, they should: 1) define their organization’s ethical standards for AI, 2) identify the gaps between where you are now and what your standards call for, and 3) understand the complex sources of the problems and operationalize solutions.
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Avoid integrity traps in the workplace.
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New!
HBR Learning
Ethics at Work Course
Accelerate your career with Harvard ManageMentor®. HBR Learning’s online leadership training helps you hone your skills with courses like Ethics at Work. Earn badges to share on LinkedIn and your resume. Access more than 40 courses trusted by Fortune 500 companies.
Avoid integrity traps in the workplace.