The future of artificial intelligence: Insights from recent Delphi studies
Ido Alón, Hazar Haidar, Ali Haidar, José Guimón
- 发表年份
- 2024
- 引用次数
- 18
摘要
We review thirteen Delphi studies on the future of Artificial Intelligence (AI), published between 2014 and 2024. Using the Delphi method, an iterative approach that refines expert insights through multiple rounds, these studies provide foresight into AI’s technological advancements, societal impacts, and policy implications across various sectors. For example, Delphi studies in healthcare foresee significant advancements in AI-driven diagnostics and personalized medicine, while in manufacturing, AI is anticipated to enhance human-robot collaboration and supply chain optimization. AI’s impact on journalism and photography shows promise in automating processes and enriching immersive storytelling, although issues like data privacy and algorithmic bias are raised. This review emphasizes a primary focus on technology trajectories, examining anticipated developments and timelines, while also considering broader strategic foresight aspects. General challenges identified include equitable access, the need for robust data governance, and workforce upskilling to integrate AI responsibly. By synthesizing insights across these studies, we provide a structured overview of both opportunities and limitations in AI development, offering guidance for stakeholders to navigate AI's complexities and capitalize on its potential responsibly. In addition, we propose methodological recommendations, such as standardizing expert selection and diversifying perspectives to improve the quality of future Delphi studies. • Reviews recent Delphi studies on the future of AI. • Explores AI's impact in healthcare, manufacturing, photography and journalism. • Identifies key ethical, societal, and economic challenges in AI integration. • Recommends methodological improvements for future Delphi studies on AI. • Emphasizes the importance of AI regulation and interdisciplinary collaboration.
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