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From promise to concern: Public perceptions of AI in ESG frameworks over time
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References

  • 2019Content Analysis: An Introduction to Its Methodology16,055 cited
  • 2018AI4People—An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations5,876 cited
  • 2015Why Are There Still So Many Jobs? The History and Future of Workplace Automation4,467 cited
  • 2005An Examination of Differences Between Organizational Legitimacy and Organizational Reputation*1,309 cited
  • 2008Text Mining Infrastructure in R1,269 cited
  • 2020Artificial intelligence for sustainability: Challenges, opportunities, and a research agenda1,201 cited
  • 2016tidytext: Text Mining and Analysis Using Tidy Data Principles in R962 cited
  • 2019Corporate digital responsibility632 cited
  • 2020Drivers, barriers and social considerations for AI adoption in business and management: A tertiary study503 cited
  • 2022Thinking responsibly about responsible AI and ‘the dark side’ of AI462 cited
  • 2022How can artificial intelligence impact sustainability: A systematic literature review424 cited
  • 2022Corporate Digital Responsibility in Service Firms and Their Ecosystems290 cited
  • 2024Artificial Intelligence Risk Management Framework (AI RMF 1.0) - Japanese translation263 cited
  • 2024Ecological footprints, carbon emissions, and energy transitions: the impact of artificial intelligence (AI)

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260 cited
  • 2020Ethical issues in service robotics and artificial intelligence222 cited
  • 2021Towards a deliberative framework for responsible innovation in artificial intelligence220 cited
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