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Data Authenticity, Consent, & Provenance for AI are all broken: what
  will it take to fix them?

Data Authenticity, Consent, & Provenance for AI are all broken: what will it take to fix them?

19 April 2024
Shayne Longpre
Robert Mahari
Naana Obeng-Marnu
William Brannon
Tobin South
Katy Gero
Sandy Pentland
Jad Kabbara
ArXivPDFHTML

Papers citing "Data Authenticity, Consent, & Provenance for AI are all broken: what will it take to fix them?"

9 / 9 papers shown
Title
Consent in Crisis: The Rapid Decline of the AI Data Commons
Consent in Crisis: The Rapid Decline of the AI Data Commons
Shayne Longpre
Robert Mahari
Ariel N. Lee
Campbell Lund
Hamidah Oderinwale
...
Hanlin Li
Daphne Ippolito
Sara Hooker
Jad Kabbara
Sandy Pentland
34
34
0
20 Jul 2024
Building an Ethical and Trustworthy Biomedical AI Ecosystem for the
  Translational and Clinical Integration of Foundational Models
Building an Ethical and Trustworthy Biomedical AI Ecosystem for the Translational and Clinical Integration of Foundational Models
Simha Sankar Baradwaj
Destiny Gilliland
Jack Rincon
Henning Hermjakob
Yu Yan
...
Dean Wang
Karol Watson
Alex Bui
Wei Wang
Peipei Ping
29
5
0
18 Jul 2024
Watermarks in the Sand: Impossibility of Strong Watermarking for
  Generative Models
Watermarks in the Sand: Impossibility of Strong Watermarking for Generative Models
Hanlin Zhang
Benjamin L. Edelman
Danilo Francati
Daniele Venturi
G. Ateniese
Boaz Barak
WaLM
132
53
0
07 Nov 2023
Market Concentration Implications of Foundation Models
Market Concentration Implications of Foundation Models
Jai Vipra
Anton Korinek
ELM
16
14
0
02 Nov 2023
Pile of Law: Learning Responsible Data Filtering from the Law and a
  256GB Open-Source Legal Dataset
Pile of Law: Learning Responsible Data Filtering from the Law and a 256GB Open-Source Legal Dataset
Peter Henderson
M. Krass
Lucia Zheng
Neel Guha
Christopher D. Manning
Dan Jurafsky
Daniel E. Ho
AILaw
ELM
127
94
0
01 Jul 2022
Just What do You Think You're Doing, Dave?' A Checklist for Responsible
  Data Use in NLP
Just What do You Think You're Doing, Dave?' A Checklist for Responsible Data Use in NLP
Anna Rogers
Timothy Baldwin
Kobi Leins
102
64
0
14 Sep 2021
The Pile: An 800GB Dataset of Diverse Text for Language Modeling
The Pile: An 800GB Dataset of Diverse Text for Language Modeling
Leo Gao
Stella Biderman
Sid Black
Laurence Golding
Travis Hoppe
...
Horace He
Anish Thite
Noa Nabeshima
Shawn Presser
Connor Leahy
AIMat
236
1,508
0
31 Dec 2020
Extracting Training Data from Large Language Models
Extracting Training Data from Large Language Models
Nicholas Carlini
Florian Tramèr
Eric Wallace
Matthew Jagielski
Ariel Herbert-Voss
...
Tom B. Brown
D. Song
Ulfar Erlingsson
Alina Oprea
Colin Raffel
MLAU
SILM
264
1,798
0
14 Dec 2020
Scaling Laws for Neural Language Models
Scaling Laws for Neural Language Models
Jared Kaplan
Sam McCandlish
T. Henighan
Tom B. Brown
B. Chess
R. Child
Scott Gray
Alec Radford
Jeff Wu
Dario Amodei
220
3,054
0
23 Jan 2020
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