Monitoring AI Services for Misuse

Author:

Javadi Seyyed Ahmad1,Norval Chris1,Cloete Richard1,Singh Jatinder1

Affiliation:

1. University of Cambridge, Cambridge, United Kingdom

Funder

EPSRC

Microsoft

Publisher

ACM

Reference51 articles.

1. A survey of anomaly detection techniques in financial domain

2. Amazon. 2019 a. Build an AI-driven Application. https://aws.amazon.com/machine-learning/ai-services/ Amazon. 2019 a. Build an AI-driven Application. https://aws.amazon.com/machine-learning/ai-services/

3. Amazon. 2019 b. DetectFaces. https://docs.aws.amazon.com/en_pv/rekognition/latest/dg/API_DetectFaces.html Amazon. 2019 b. DetectFaces. https://docs.aws.amazon.com/en_pv/rekognition/latest/dg/API_DetectFaces.html

4. Amazon. 2020. Amazon Rekognition FAQs. https://aws.amazon.com/rekognition/faqs/?nc=sn&loc=7 Amazon. 2020. Amazon Rekognition FAQs. https://aws.amazon.com/rekognition/faqs/?nc=sn&loc=7

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1. Visibility into AI Agents;The 2024 ACM Conference on Fairness, Accountability, and Transparency;2024-06-03

2. Tinker, Tailor, Configure, Customize: The Articulation Work of Contextualizing an AI Fairness Checklist;Proceedings of the ACM on Human-Computer Interaction;2024-04-17

3. Unpacking Epistemic Insights of Artificial Intelligence (AI) in Science Education: A Systematic Review;Science & Education;2024-03-15

4. Towards AI as a Service for Small and Medium-Sized Enterprises (SME);Lecture Notes in Business Information Processing;2023-11-25

5. Toward Label-Efficient Emotion and Sentiment Analysis;Proceedings of the IEEE;2023-10

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