Can AI be a Teaching Partner? Evaluating ChatGPT, Gemini, and DeepSeek across Three Teaching Strategies

2026-03-31T07:23:59Z4c206fb5f3707d6a6528b1341a2aabccc22bec8ec90a6345d0cea7168397f991
adversarial-useai-governanceai-safetyclimate-riskcompute-infrastructuredataset-contaminationdisinformationeducation-aifederated-architectureharmful-capability-uplifthezbollahhuman-ai-interactionincident-managementinformation-operationsmodel-evaluationmulti-agent-systemspedagogyprivacyrenewable-energysocial-media

What happened

This collection of arXiv papers (Mar 31, 2026) covers multiple AI and socio-technical topics with clear security and policy relevance. Key items: a position paper proposing "harmful capability uplift" as a human-centered metric for measuring how frontier models increase users' ability to cause harm (methodological guidance for evaluations); analyses of benchmarking risks for multi-agent scientific AI systems (contamination, tool-use, replication challenges); a federated, sector-led architecture for national AI governance and incident management (case study: India); empirical studies of LLMs as

Why it matters

A reviewed impact interpretation has not been published for this record.

Evidence and limitations

Source ID
arxiv_cs_cy
Record identifier
4c206fb5f3707d6a6528b1341a2aabccc22bec8ec90a6345d0cea7168397f991
Enrichment time
2026-03-31T07:23:59Z
AI-assisted enrichment
Yes

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