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Contents

Published online by Cambridge University Press:  16 November 2023

Edited by
Zofia Bednarz  and
Monika Zalnieriute
Zofia Bednarz
Affiliation:
University of Sydney
Monika Zalnieriute
Affiliation:
University of New South Wales, Sydney

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Money, Power, and AI
Automated Banks and Automated States
 , pp. v - viii
Publisher: Cambridge University Press
Print publication year: 2023
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This content is Open Access and distributed under the terms of the Creative Commons Attribution licence CC-BY-NC-ND 4.0 https://creativecommons.org/cclicenses/

Contents

  1. List of Contributors

  2. Foreword by Frank Pasquale

  3. Acknowledgements

  4. List of Abbreviations

  5. Introduction: AI at the Intersection of Money and Power

    Monika Zalnieriute and Zofia Bednarz

  6. Part IAutomated Banks

    1. 1AI in the Financial Sector: Policy Challenges and Regulatory Needs

      Teresa Rodríguez de las Heras Ballell

      1. 1.1Setting the Scene: AI in the Financial Sector

      2. 1.2Concept and Taxonomy: AI System and ADM

      3. 1.3An Initial Review of the Policy and Regulatory Framework in the European Union

      4. 1.4Concluding Remarks: Principles for the Responsible Use of AI in Decision-Making

    2. 2Demystifying Consumer-Facing Fintech: Accountability for Automated Advice Tools

      Jeannie Paterson, Tim Miller, and Henrietta Lyons

      1. 2.1Introduction: Money, Power, and AI

      2. 2.2Aspiration and Application in Consumer-Facing Fintech

      3. 2.3Regulation and Risk in Consumer-Facing Fintech

      4. 2.4New Regulatory Responses to the Risks of Automated Financial Advice

      5. 2.5Conclusion

    3. 3Leveraging AI to Mitigate Money Laundering Risks in the Banking System

      Doron Goldbarsht

      1. 3.1Introduction

      2. 3.2Enforcement and Detection: The Cost of Non-compliance

      3. 3.3Leveraging AI for AML

      4. 3.4The Shift to a Risk-Based Approach

      5. 3.5Advantages and Challenges

      6. 3.6Conclusion

    4. 4AI Opacity in the Financial Industry and How to Break It

      Zofia Bednarz and Linda Przhedetsky

      1. 4.1Introduction

      2. 4.2Rules That Allow Corporate Secrecy to Exist

      3. 4.3Rules That Incentivise the Use of ADM Tools by Financial Entities

      4. 4.4Can Corporate Secrecy Coexist with Consumer Rights? Possible Regulatory Solutions

      5. 4.5Conclusions

  7. Part IIAutomated States

    1. 5The Automated Welfare State: Challenges for Socioeconomic Rights of the Marginalised

      Terry Carney

      1. 5.1Introduction

      2. 5.2Issues Posed by Automation and ADM

      3. 5.3Responding to the ‘Power’ of AI

      4. 5.4Towards AI Trust and Empathy for Ordinary Citizens

    2. 6A New ‘Machinery of Government’? The Automation of Administrative Decision-Making

      Paul Miller

      1. 6.1Introduction: ADM and the Machinery of Government

      2. 6.2Context

      3. 6.3Administrative Law and ADM Technologies

      4. 6.4Designing ADM Tools to Comply with the Law and Fundamental Principles of Good Government

      5. 6.5Conclusion

    3. 7A Tale of Two Automated States: Why a One-Size-Fits-All Approach to Administrative Law Reform to Accommodate AI Will Fail

      José-Miguel Bello y Villarino

      1. 7.1Introduction: Two Tales of the Automated States

      2. 7.2The Administrative Law of AI Systems That Replace Bureaucrats

      3. 7.3Regulating the Unseen Automated State

      4. 7.4Preparing for the Two Tales of the Automated State

    4. 8The Islamophobic Consensus: Datafying Racism in Catalonia

      Aitor Jiménez and Ainhoa Nadia Douhaibi

      1. 8.1Introduction

      2. 8.2Datafying Islamophobia

      3. 8.3Southern European Neoliberalism Fundamentals

      4. 8.4Conclusion

  8. Part IIISynergies and Safeguards

    1. 9Law and Empathy in the Automated State

      Cary Coglianese

      1. 9.1Introduction

      2. 9.2Implementation of the Automated State

      3. 9.3US Administrative Law and the Automated State

      4. 9.4AI and Good Governance in an Automated State

      5. 9.5Conclusion: The Need for Human Empathy

    2. 10Sorting Teachers Out: Automated Performance Scoring and the Limit of Algorithmic Governance in the Education Sector

      Ching-Fu Lin

      1. 10.1Introduction

      2. 10.2The Contested Algorithmization of Worker Performance Evaluation

      3. 10.3Sorting Teachers Out? Unpacking Houston Federation of Teachers v Houston Independent School District

      4. 10.4Judicial Review as Algorithmic Governance? Controversies, Ramifications, and Critical Reflections

      5. 10.5Conclusion

    3. 11Supervising Automated Decisions

      Tatiana Cutts

      1. 11.1Introduction

      2. 11.2The Determinative Factor

      3. 11.3Individualism and Relevance

      4. 11.4Statistical Rules and Relevance

      5. 11.5Choice

      6. 11.6Group One: Predictions about Facts Other Than What the Decision-Subject Will Do

      7. 11.7Group Two: Predictions about What the Decision-Subject Will Do

      8. 11.8Safeguards

    4. 12Against Procedural Fetishism in the Automated State

      Monika Zalnieriute

      1. 12.1Introduction

      2. 12.2Existing Efforts to Tame AI Power

      3. 12.3Procedural Fetishism

      4. 12.4The New Social Contract for the Age of AI

      5. 12.5Conclusion

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