[2004.07213] Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims
With the recent wave of progress in artificial intelligence (AI) has come a growing awareness of the large-scale impacts of AI systems, and recognition that existing regulations and norms in industry and academia are insufficient to ensure responsible AI development. In order for AI developers to earn trust from system users, customers, civil society, governments, and other stakeholders that they are building AI responsibly, they will need to make verifiable claims to which they can be held accountable. Those outside of a given organization also need effective means of scrutinizing such claims. This report suggests various steps that different stakeholders can take to improve the verifiability of claims made about AI systems and their associated development processes, with a focus on providing evidence about the safety, security, fairness, and privacy protection of AI systems. We analyze ten mechanisms for this purpose--spanning institutions, software, and hardware--and make recommendations aimed at implementing, exploring, or improving those mechanisms.
# link_lmofhcg96r.pdf ## Metadata - PDFFormatVersion=1.4 - IsLinearized=false - IsAcroFormPresent=false - IsXFAPresent=false - IsCollectionPresent=false - IsSignaturesPresent=false - Producer=dvips + GPL Ghostscript GIT PRERELEASE 9.22 - CreationDate=D:20200421200658-04'00' - ModDate=D:20200421200658-04'00' - Creator=LaTeX with hyperref package - xmp:modifydate=2020-04-21T20:06:58-04:00 - xmp:createdate=2020-04-21T20:06:58-04:00 ## Contents ### Page 1 arXiv:2004.07213v2 [cs.CY] 20 Apr 2020Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims∗Miles Brundage1†, Shahar
saved by
related reading
- Recommendations for Technical AI Safety Research Directionsalignment.anthropic.com
- [2312.06942] AI Control: Improving Safety Despite Intentional Subversionarxiv.org
- The Compute Verification Postfirstscattering.com
- AI Control: Improving Safety Despite Intentional Subversion — LessWronglesswrong.com
- Verifying International Agreements on AI: Six Layers of Verification for Rules on Large-Scale AI Development and Deploymentarxiv.org
- Constitutional AI: Harmlessness from AI Feedbackarxiv.org
- AI Control: Improving Safety Despite Intentional Subversion — AI Alignment Forumalignmentforum.org
- [2507.11473] Chain of Thought Monitorability: A New and Fragile Opportunity for AI Safetyarxiv.org
- Verified Machine Learning Infrastructure: Formal Methods for Trustworthy Artificial Intelligence Deployment | RANDrand.org
- [2304.04914] Regulatory Markets: The Future of AI Governancearxiv.org
- Toward A Public Science of Model Behavior | Transluce AItransluce.org
- Building Trustworthy AI Agents - Schneier on Securityschneier.com