Not all risks posed by gen AI are the same. Organizations need to manage them accordingly.
May 31, 2024
Eugene Mymrin/Getty Images
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Many organizations are understandably hesitant to adopt gen AI applications, citing concerns about privacy and security threats, copyright infringement, the possibility of bias and discrimination in its outputs, and other hazards. Risk around using gen AI can be classified based on two factors: intent and usage. Accidental misapplication of gen AI is different from deliberate malpractices (intent). Similarly, using gen AI tools to create content is differentiated from consuming content that other parties may have created with gen AI (usage). To mitigate the risk of gen AI content misuse and misapplication, organizations need to develop the capabilities to detect, identify, and prevent the spread of such potentially misleading content.
According to a poll of 2,500 executives by Gartner last spring, approximately 70% of respondents reported that their organizations are exploring how to integrate generative AI into their organizations, and the global AI adoption rates have been reported to be higher in every surveyed region, according to the recently published Stanford AI Index Report.
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ÖI
Öykü Isik is Professor of Digital Strategy and Cybersecurity at IMD in Lausanne, Switzerland. Her research and teaching specializes in digital resilience, with a focus on cybersecurity and responsible AI. She has been recognized as a Thinkers50 Radar thought leader in 2023, and serves as a member of the WEF Global Future Councuil on Cybersecurity.
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AJ
Amit Joshi is a professor of AI, Analytics and Marketing Strategy at IMD, and specializes in helping organizations use artificial intelligence and develop for their big data, analytics and AI capabilities. An award-winning professor and researcher, he has extensive experience of AI and analytics driven transformations in industries such as banking, fintech, retail, services, automotive, telecoms, and pharma.
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Lazaros Goutas is a Research Fellow at the Global Center for Digital Business Transformation at IMD Business School. His research examines the impact of AI on decision making, and the ways in which digital sustainability capabilities drive organizational performance.
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