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These visualizations are experimental and still being refined. Designs and data presentation may change.

Emerging Risks

Which subdomains have both high academic risk coverage and real-world incidents, and are experts predicting worsening? Each dot is a subdomain plotted by risk count vs incident count, with expert BAU severity encoded via dot size or color intensity.

Severity:
r = 0.44
Discrimination & Toxicity
Privacy & Security
Misinformation
Malicious Actors & Misuse
Human-Computer Interaction
Socioeconomic & Environmental
AI System Safety, Failures & Limitations
Dot size = BAU severitysmall = lowlarge = high

Key Takeaways

  • 1.Risk-incident correlation is r = 0.44 (moderate), suggesting academic risk coverage has moderate alignment with real-world incidents.
  • 2.4.3 Fraud, scams, and targeted manipulation is the top hotspot (394 incidents, severity 3.1/5).
  • 3.7.2 AI possessing dangerous capabilities has the most risks relative to incidents (77 risks, 0 incidents) — not yet materialized.
  • 4.24 of 24 subdomains have expert severity data. 0 shown without severity encoding.

Risk counts from the MIT AI Risk Repository. Incidents from the AI Incident Database. Expert severity from Delphi survey BAU expectations.