In recent years, the topic of ethics in artificial intelligence (AI) has sparked growing concern in academia, at tech companies, and among policymakers here and abroad. That’s not because society suddenly woke up to the need, but rather because trial and error has brought ethics to center stage. Facial recognition technology, for example, has been shown to be vulnerable to racial bias. Similarly, AI-powered tools designed to conduct objective screening of job applicants evaluated women candidates more negatively than men.One crucial question is often absent in these discussions: What is an effective model for integrating ethics into AI research and development?
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