Money, Power, and AI
Automated Banks and Automated States
$125.00 USD
- Editors:
- Zofia Bednarz, University of Sydney
- Monika Zalnieriute, University of New South Wales, Sydney
- Date Published: November 2023
- availability: This ISBN is for an eBook version which is distributed on our behalf by a third party.
- format: Adobe eBook Reader
- isbn: 9781009334280
Find out more about Cambridge eBooks
$
125.00 USD
Adobe eBook Reader
Other available formats:
Hardback
Looking for an inspection copy?
This title is not currently available on inspection
-
In this ambitious collection, Zofia Bednarz and Monika Zalnieriute bring together leading experts to shed light on how artificial intelligence (AI) and automated decision-making (ADM) create new sources of profits and power for financial firms and governments. Chapter authors—which include public and private lawyers, social scientists, and public officials working on various aspects of AI and automation across jurisdictions—identify mechanisms, motivations, and actors behind technology used by Automated Banks and Automated States, and argue for new rules, frameworks, and approaches to prevent harms that result from the increasingly common deployment of AI and ADM tools. Responding to the opacity of financial firms and governments enabled by AI, Money, Power and AI advances the debate on scrutiny of power and accountability of actors who use this technology. This title is available as Open Access on Cambridge Core.
Read more- Illustrates connections, interactions, and motivations behind the use of Artificial Intelligence and automated decision-making in private financial and public sectors
- Includes diverse perspectives on the issue of AI and ADM from researchers in legal and social sciences
- Available as Open Access on Cambridge Core
Customer reviews
Not yet reviewed
Be the first to review
Review was not posted due to profanity
×Product details
- Date Published: November 2023
- format: Adobe eBook Reader
- isbn: 9781009334280
- availability: This ISBN is for an eBook version which is distributed on our behalf by a third party.
Table of Contents
Foreword by Frank Pasquale
Introduction Monika Zalnieriute and Zofia Bednarz
1. AI in the financial sector: policy challenges and regulatory needs Teresa Rodríguez de las Heras Ballell
2. Demystifying consumer-facing fintech: transparency and accountability in automated financial advice tools Jeannie Paterson, Tim Miller and Henrietta Lyons
3. Leveraging AI to mitigate money laundering risks in the banking system Doron Goldbarsht
4. AI opacity in financial industry and how to break it Zofia Bednarz and Linda Przhedetsky
5. The automated welfare state: challenges for socio-economic rights of the marginalised Terry Carney
6. A new 'machinery of government'? the automation of administrative decision-making Paul Miller
7. The 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
8. The islamophobic consensus: datafying racism in catalonia Aitor Jiménez and Ainhoa Nadia Douhaibi
9. Law and empathy in the automated state Cary Coglianese
10. Sorting teachers out: automated performance scoring and the limit of algorithmic governance in the education sector Ching-Fu Lin
11. Supervising automated decisions Tatiana Cutts
12. Against procedural fetishism in the automated state Monika Zalnieriute.
Sorry, this resource is locked
Please register or sign in to request access. If you are having problems accessing these resources please email [email protected]
Register Sign in» Proceed
You are now leaving the Cambridge University Press website. Your eBook purchase and download will be completed by our partner www.ebooks.com. Please see the permission section of the www.ebooks.com catalogue page for details of the print & copy limits on our eBooks.
Continue ×Are you sure you want to delete your account?
This cannot be undone.
Thank you for your feedback which will help us improve our service.
If you requested a response, we will make sure to get back to you shortly.
×