Artificial Intelligence and Risk Management: Insights from Fordham University

Sunday, 25 August 2024, 16:59

Artificial intelligence (AI) poses both rewards and risks, as highlighted by Fordham University's research. The analysis shows that AI systems present a greater percentage of risks than their human counterparts. Furthermore, these risks are often identified post-deployment, enhancing the urgency for effective risk management frameworks in AI development.
Forbes
Artificial Intelligence and Risk Management: Insights from Fordham University

Understanding the Risks of Artificial Intelligence

Artificial intelligence (AI) has emerged as a powerful tool in various sectors, but with its advancement comes significant risks. According to Fordham University, a comprehensive database reveals that over 51% of the risks are attributed to AI systems, compared to just 34% for humans.

What Fordham University's Research Indicates

The research highlights that a staggering 65% of these risks are observed after AI deployment rather than during its developmental stages. This statistic emphasizes the importance of proactive risk management strategies to mitigate potential hazards.

  • AI system risks outnumber human risks.
  • Post-deployment risks demand immediate attention.
  • Effective risk management is critical for AI safety.

As organizations increasingly integrate AI, the focus must shift to identifying risks early and implementing robust risk management practices.


This article was prepared using information from open sources in accordance with the principles of Ethical Policy. The editorial team is not responsible for absolute accuracy, as it relies on data from the sources referenced.


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