Executives need to manage the reputational, regulatory, and legal risks of AI-led ethical decisions.
If the developers who identify the data to be used for training an AI system aren't looking for bias, how can they prevent an ethical dilemma? For example, suppose a company has historically hired more men than women. In that case, a bias is likely to exist in the resume data. Men tend to use different words than women in their resumes. If the data is sourced from men's resumes, then women's resumes may be viewed less favorably, just based on word choice.
While each company is addressing these principles differently, we can learn a lot by examining their commonalities. Here are some fundamental principles they address.
While these tech giants are imperfect, they are leading the way in addressing ethical AI challenges. What are your board and senior management team doing to address these issues?Make the ethics of AI a board-level discussionEnsure senior executives understand how and where AI-based systems are being considered and implementedBy addressing these issues now, your company will reduce the risks of having AI make or recommend decisions that imperil the company.
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