This week we spotlight the ninth risk framework included in the AI Risk Repository:
The paper uses a literature review, thematic analysis, and PEST analysis to examine the ethical and risk implications of AI and propose actionable management strategies.
The results present the most common ethical issues associated with AI, and categorizes them along three axes—type of AI (Domain-Specific AI vs. AGI), focus areas (effects on humans vs. issues related to AI itself), and risk severity (existential vs. non-existential risks).
Uses a macro-level Political, Economic, Social, and Technological (PEST) framework to analyze AI's ethical and risk implications in a broader context.
Provides actionable management strategies, including establishing ethics committees, enhancing AI security, and embedding ethics in technology management processes.
Identifies several pressing gaps in the AI and AI Ethics literature.
This summary highlights a paper included in the MIT AI Risk Repository. We did not author the paper and credit goes to Meek, T., Barham, H., Beltaif, N., Kaadoor, A., & Akhter, T. (2016). For the full details, please refer to the original publication: 10.1109/PICMET.2016.7806752
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