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Artificial intelligence (AI) is increasingly a business imperative. As AI tools propagate across nearly every industry and sector, so too do myriad ethical risks. Bias and discrimination, reputation damage and regulatory consequences, novel solutions delivering poor results that impact the bottom line--these and many other consequences can emerge from AI that falls short of ethical design, development, deployment, and use. Succeeding with AI solutions and systems requires trust in the tools and their outputs, and for AI to reach its full potential, the ethics involved must be addressed upfront. While business leaders are aware of the ethical concerns AI can prompt, less clear are the qualities of ethical AI and how to enable them across the business and in the marketplace. Indeed, while there is a lot of talk around AI ethics, there is no playbook on how to design or build it. Trustworthy AI cuts through philosophical and theoretical discussions to deliver clarity on AI ethics, its components, and how to design and implement ethical principles relevant to the organization. Readers are guided through an exploration of the pitfalls and priorities in ethical AI, exemplified with the latest research, known and potential incidences of harm due to AI, and the best practices that can help executives and data scientists alike develop trustworthy AI for business benefit. Relevant to any enterprise building and using AI, Trustworthy AI helps refine what AI ethics means for the organization in a practical way. Readers will become equipped with: Essential insight into building and implementing an ethical AI strategy; Caution areas and priorities for business leaders and other professionals working on AI initiatives; Driving ethical AI thinking and planning across the entire organization; and Operationalizing AI ethics within your organization
    Collected by
    • University of Cambridge
    • Princeton University
    • Yale University
    • Stanford University
    • Beijing Normal University at Zhuhai

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