Michelle Seng Ah Lee

University of Cambridge

15 JJ Thomson Ave

William Gates Building

Cambridge, Cambridgeshire CB3 0FD

United Kingdom

http://compacctsys.soc.srcf.net/team/

  • University of Cambridge

SCHOLARLY PAPERS

8

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13

CROSSREF CITATIONS

5

Scholarly Papers (8)

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1.

The Landscape and Gaps in Open Source Fairness Toolkits

Michelle Seng Ah Lee and Jatinder Singh. 2021. The Landscape and Gaps in Open Source Fairness Toolkits. In CHI Conference on Human Factors in Computing Systems (CHI ’21), May 8–13, 2021, Yokohama, Japan. ACM, Yokohama, Japan, 13 pages. https://doi.org/10.1145/3411764.3445261
Number of pages: 13 Posted: 23 Nov 2020 Last Revised: 21 May 2021
Michelle Seng Ah Lee and Jatinder Singh
University of Cambridge and University of Cambridge -- Dept. Computer Science & Technology (Computer Laboratory)
Downloads 638 (57,434)
Citation 1

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open source, fairness, fairness toolkits, algorithmic fairness, algorithmic auditing

2.

Formalising trade-offs beyond algorithmic fairness: lessons from ethical philosophy and welfare economics

Number of pages: 33 Posted: 12 Oct 2020 Last Revised: 08 Jun 2021
Michelle Seng Ah Lee, Luciano Floridi and Jatinder Singh
University of Cambridge, University of Oxford - Oxford Internet Institute and University of Cambridge -- Dept. Computer Science & Technology (Computer Laboratory)
Downloads 588 (63,622)
Citation 3

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algorithmic fairness, algorithmic ethics, fairness, ethical AI, machine learning, key ethics indicators, KEI

3.

Risk Identification Questionnaire for Detecting Unintended Bias in the Machine Learning Development Lifecycle

Lee, Michelle Seng Ah and Jatinder Singh. "Risk Identification Questionnaire for Detecting Unintended Bias in the Machine Learning Development Lifecycle." Proceedings of the AAAI/ACM Conference on AI, Ethics, and Society. 2021.
Number of pages: 11 Posted: 16 Feb 2021 Last Revised: 24 May 2021
Michelle Seng Ah Lee and Jatinder Singh
University of Cambridge and University of Cambridge -- Dept. Computer Science & Technology (Computer Laboratory)
Downloads 315 (131,750)
Citation 2

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algorithmic fairness, algorithmic bias, unintended bias, machine learning, bias identification, risk identification, risk management, bias questionnaire, risk methods

4.

Algorithmic Fairness in Mortgage Lending: From Absolute Conditions to Relational Trade-Offs

Lee, M.S.A., Floridi, L. Algorithmic Fairness in Mortgage Lending: from Absolute Conditions to Relational Trade-offs. Minds & Machines (2020). https://doi.org/10.1007/s11023-020-09529-4
Number of pages: 27 Posted: 06 May 2020 Last Revised: 10 Jun 2020
Michelle Seng Ah Lee and Luciano Floridi
University of Cambridge and University of Oxford - Oxford Internet Institute
Downloads 295 (141,301)
Citation 8

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algorithmic fairness, mortgage discrimination, fairness trade-offs, machine learning, ethics

5.

Centering the Rule of Law in the Digital State

(2020) IEEE Computer 53(10)
Number of pages: 20 Posted: 30 Sep 2020 Last Revised: 10 Dec 2020
Jennifer Cobbe, Michelle Seng Ah Lee, Heleen Janssen and Jatinder Singh
University of Cambridge - Computer Laboratory, University of Cambridge, University of Cambridge - Computer Laboratory and University of Cambridge -- Dept. Computer Science & Technology (Computer Laboratory)
Downloads 177 (229,559)
Citation 2

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automated decision-making, public sector automation, rule of law

6.

Reviewable Automated Decision-Making: A Framework for Accountable Algorithmic Systems

ACM Conference on Fairness, Accountability, and Transparency (FAccT ‘21), March 1–10, 2021, Virtual Event, Canada
Number of pages: 12 Posted: 12 Feb 2021
Jennifer Cobbe, Michelle Seng Ah Lee and Jatinder Singh
University of Cambridge - Computer Laboratory, University of Cambridge and University of Cambridge -- Dept. Computer Science & Technology (Computer Laboratory)
Downloads 155 (256,585)
Citation 3

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Algorithmic systems, automated decision-making, accountability, audit, artificial intelligence, machine learning

7.

Innovating with Confidence - Embedding AI Governance and Fairness in a Financial Services Risk Management Framework

Number of pages: 19 Posted: 29 Apr 2021
Michelle Seng Ah Lee, Luciano Floridi and Alexander Denev
University of Cambridge, University of Oxford - Oxford Internet Institute and University of Oxford
Downloads 114 (323,904)
Citation 2

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Artificial Intelligence, Financial Services, Auditing, Innovation

8.

Spelling Errors and Non-Standard Language in Peer-to-Peer Loan Applications and the Borrower’s Probability of Default

Lee, Michelle Seng Ah and Jatinder Singh. "Spelling Errors and Non-Standard Language in Peer-to-Peer Loan Applications and the Borrower’s Probability of Default." In Proceedings of Credit Scoring and Credit Control Conference XVII. 2021.
Number of pages: 9 Posted: 18 Jun 2020 Last Revised: 24 May 2021
Michelle Seng Ah Lee and Jatinder Singh
University of Cambridge and University of Cambridge -- Dept. Computer Science & Technology (Computer Laboratory)
Downloads 114 (323,904)

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peer-to-peer lending, discriminatory lending, alternative credit, credit risk, algorithmic bias, spelling error, non-standard language