Pith. sign in

REVIEW 1 cited by

Towards Regulatable AI Systems: Technical Gaps and Policy Opportunities

Not yet reviewed by Pith; the record is open.

Re-run · record.json Download PDF Read on arXiv ↗

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 2306.12609 v2 pith:DFG7IXQY submitted 2023-06-22 cs.AI cs.CY

Xudong Shen , Hannah Brown , Jiashu Tao , Martin Strobel , Yao Tong , Akshay Narayan , Harold Soh , Finale Doshi-Velez This is my paper · ORCID
classification cs.AIcs.CY
keywords whattechnicalquestionrequirementssystemsadherenceapproachattention
verification ladder T0 review T1 audit T2 compute T3 formal
0 comments
read the original abstract

There is increasing attention being given to how to regulate AI systems. As governing bodies grapple with what values to encapsulate into regulation, we consider the technical half of the question: To what extent can AI experts vet an AI system for adherence to regulatory requirements? We investigate this question through the lens of two public sector procurement checklists, identifying what we can do now, what should be possible with technical innovation, and what requirements need a more interdisciplinary approach.

Discussion (0). Continue with ORCID to comment.

Forward citations

Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. AI for Regulatory Affairs: Balancing Accuracy, Interpretability, and Computational Cost in Medical Device Classification

    cs.AI 2025-05 conditional novelty 6.0 of 10

    CNN (88.3% accuracy) and XGBoost (86%) beat zero-shot LLMs (about 46%) on NMPA medical device classification, with no single model winning on accuracy, interpretability, and cost simultaneously.

Pith tools