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ai-resilience

topic2 events
papersSEP 12 04:00 UTC

arXiv paper proposes evaluating AI agents on resilience across repeated interactions

A new arXiv preprint argues that measuring whether an agent completes a single task is insufficient for judging fitness in long-running deployments. The authors propose evaluating agents on how well they hold up as challenges accumulate, including shifting conditions, repeated interactions, and reliance on human collaborators in shared workflows. The work frames resilience and considerate participation as dimensions that need dedicated benchmarks.

agents/evaluation/benchmarks/arxiv
papersSEP 12 04:00 UTC

arXiv Paper Proposes Two-Axis Framework for AI Exposure and Resilience in Software

A new arXiv preprint introduces a framework that rates software and software-based business models along two dimensions: how exposed they are to AI disruption and how well they can adapt. The authors argue that traditional technical due diligence, which focuses on architecture, scalability, and technical debt, misses these AI-specific risks. The work targets investors and analysts evaluating technology companies.

research/due-diligence/software/risk-assessment