Plateau That Never Comes: When Efficiency Claims in Datacenters and AI Become Greenwashing
2026-06-04T07:23:53Z•49f1dce933d4c3b99166b96e18c004fe0a5533e419b6cd36abffc616b38c099f
AI riskAI safetyCRM dataDelphi studyagentic AIcyberattacksdangerous capabilitiesdatacentersdigital twinseducationgovernancegreenwashingmarket researchmisinformationpedagogypower centralizationprivacyrebound effectsregulatory gamingreinforcement learningreward hacking','societal hacking'rules-as-codesustainabilitysynthetic personalitiesweapons
What happened
This feed collects recent CS/cy submissions spanning AI governance, risk, and societal impacts. Key contributions: a critical framework showing datacenter/AI “efficiency” claims can amount to greenwashing by ignoring absolute resource burdens and rebound effects; a 272-expert Delphi ranking short-term AI risks (dangerous capabilities, competitive dynamics, weapons & cyberattacks, power centralization, misinformation) with many risks judged to have nontrivial catastrophic probabilities; analysis of agentic AI in education highlighting threats to learner agency and recommendations for human-in‑/
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_cs_cy
- Record identifier
- 49f1dce933d4c3b99166b96e18c004fe0a5533e419b6cd36abffc616b38c099f
- Enrichment time
- 2026-06-04T07:23:53Z
- AI-assisted enrichment
- Yes
This record may overlap with other records. Its enrichment can be incomplete or wrong, and machine assistance was used. Validate consequential decisions against the linked source and your own environment.