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Workshop

Regulatable ML: Towards Bridging the Gaps between Machine Learning Research and Regulations

Jiaqi Ma · Chirag Agarwal · Sarah Tan · Himabindu Lakkaraju · Usha Bhalla · Zana Bucinca · Zixi Chen · Junwei Deng · Xudong Shen · Varshini Subhash

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Abstract

This workshop brings together ML and policy experts to identify and address various technical and policy challenges that arise when regulating ML models.

Video

Chat is not available.

Schedule

Timezone: America/Los_Angeles

6:55 AM

Opening Remarks Opening Remarks

Video

7:00 AM

Rayid Ghani: Designing ML Systems that can be Regulated: Challenges and Opportunities Keynote Talk

Video

7:30 AM

Sandra Wachter: Regulating Code: What the European Union has in stock for the governance of Artificial Intelligence, foundation models, and generative AI Keynote Talk

Video

8:00 AM

Coffee Break

8:15 AM

Oral Presentations Oral Talk

Video

8:55 AM

Jon Kleinberg: Fine-Tuning Games: Modeling the Ecosystem of Machine Learning Applications and their Development Keynote Talk

Video

9:25 AM

Poster Session Poster Session

10:20 AM

Lunch Break

11:10 AM

Oral Presentations Oral Talk

Video

11:35 AM

Elham Tabassi: Path to trustworthy and responsible AI Keynote Talk

Video

12:05 PM

Margaret Mitchell and Yacine Jernite: Regulating ML: Rights, Transparency, and Agency Keynote Talk

Video

12:35 PM

Oral Presentations Oral Talk

Video

1:00 PM

Coffee Break

1:15 PM

Tatsunori Hashimoto: Connecting provable guarantees and regulation of LLMs Keynote Talk

Video

1:45 PM

Panel Discussion: Deborah Raji, Elham Tabassi, Jon Kleinberg, Margaret Mitchell, Rayid Ghani Panel

Video

2:40 PM

Oral Presentations Oral Talk

Video

3:20 PM

Closing Remarks Closing Remarks

Video

Learning from Label Proportions: Bootstrapping Supervised Learners via Belief Propagation Poster

Shreyas Havaldar · Navodita Sharma · Shubhi Sareen · Karthikeyan Shanmugam · Aravindan Raghuveer

Regulation Games for Trustworthy Machine Learning Poster

Mohammad Yaghini · Patty Liu · Franziska Boenisch · Nicolas Papernot

Who Leaked the Model? Tracking IP Infringers in Accountable Federated Learning Oral

Shuyang Yu · Junyuan Hong · Yi Zeng · Fei Wang · Ruoxi Jia · Jiayu Zhou

Reading the drafts of the AI Act with a technical lens Poster

Tiphaine Viard · Melanie Gornet · Winston Maxwell

In Pursuit of Regulatable LLMs Poster

Eoin Kenny · Julie A Shah

Policy Comparison Under Confounding Poster

Luke Guerdan · Amanda Coston · Steven Wu · Kenneth Holstein

You Still See Me: How Data Protection Supports the Architecture of ML Surveillance Poster

Rui-Jie Yew · Lucy Qin · Suresh Venkatasubramanian

Advancing Clinical Trials via Real-World Aligned ML Best Practices Poster

Karen Sayal · Markus Trengove · Finnian Firth · Lea Goetz

Necessity of Processing Sensitive Data for Bias Detection and Monitoring: A Techno-Legal Exploration Oral

Ioanna Papageorgiou · Carlos Mougan

Can copyright be reduced to privacy Oral

Niva Elkin-Koren · Uri Hacohen · Roi Livni · Shay Moran

RényiTester: A Variational Approach to Testing Differential Privacy Poster

Weiwei Kong · Andres Munoz Medina · Mónica Ribero

Conformal Prediction via Regression-as-Classification Poster

Etash Guha · Shlok Natarajan · Thomas Möllenhoff · Mohammad Emtiyaz Khan · Eugene Ndiaye

A Unified Analysis of Label Inference Attacks Poster

Andres Munoz Medina · Travis Dick · Claudio Gentile · Róbert Busa-Fekete · Marika Swanberg

Detecting Pretraining Data from Large Language Models Oral

Weijia Shi · Anirudh Ajith · Mengzhou Xia · Yangsibo Huang · Daogao Liu · Terra Blevins · Danqi Chen · Luke Zettlemoyer

Anthropomorphization of AI: Opportunities and Risks Poster

Ameet Deshpande · Tanmay Rajpurohit · Karthik Narasimhan · Ashwin Kalyan

A Brief Tutorial on Sample Size Calculations for Fairness Audits Poster

Harvineet Singh · Fan Xia · Mi-Ok Kim · Romain Pirracchio · Rumi Chunara · Jean Feng

AnchMark: Anchor-contrastive Watermarking vs GenAI-based Image Modifications Poster

Minzhou Pan · Yi Zeng · Xue Lin · Ning Yu · Cho-Jui Hsieh · Ruoxi Jia

A new Framework for Measuring Re-Identification Risk Poster

CJ Carey · Travis Dick · Alessandro Epasto · Adel Javanmard · Josh Karlin · Shankar Kumar · Andres Munoz Medina · Vahab Mirrokni · Gabriel H. Nunes · Sergei Vassilvitskii · Peilin Zhong

An Alternative to Regulation: The Case for Public AI Poster

Nicholas Vincent · David Bau · Sarah Schwettmann · Joshua Tan

Towards Responsible Governance of Biological Design Tools Oral

Richard Moulange · Max Langenkamp · Tessa Alexanian · Samuel Curtis · Morgan Livingston

Learning to Walk Impartially on the Pareto Frontier of Fairness, Privacy, and Utility Oral

Mohammad Yaghini · Patty Liu · Franziska Boenisch · Nicolas Papernot

Video

Can LLM-Generated Misinformation Be Detected? Oral

Canyu Chen · Kai Shu

Limitations of the “Four-Fifths Rule” and Statistical Parity Tests for Measuring Fairness Poster

Manish Raghavan · Pauline Kim

Navigating Dataset Documentation in ML: A Large-Scale Analysis of Dataset Cards on Hugging Face Poster

Xinyu Yang · Weixin Liang · James Zou

Towards a Post-Market Monitoring Framework for Machine Learning-based Medical Devices: A case study Oral

Jean Feng · Adarsh Subbaswamy · Alexej Gossmann · Harvineet Singh · Berkman Sahiner · Mi-Ok Kim · Gene Pennello · Nicholas Petrick · Romain Pirracchio · Fan Xia

Is EMA Robust? Examining the Robustness of Data Auditing and a Novel Non-calibration Extension Poster

Ayush Alag · Yangsibo Huang · Kai Li

Algorithmically Mediated User Relations: Exploring Data's Relationality in Recommender Systems Poster

Athina Kyriakou · Oana Inel · Asia Biega · Abraham Bernstein

Scaling up Trustless DNN Inference with Zero-Knowledge Proofs Poster

Daniel Kang · Tatsunori Hashimoto · Ion Stoica · Yi Sun

Racial Disregard in Algorithmic Fairness Poster

Jamelle Watson-Daniels · Alexander Tolbert

Outliers Exist: What Happens if You are a Data-Driven Exception? Poster

Sarah Cen · Manish Raghavan

Membership Inference Attack on Diffusion Models via Quantile Regression Poster

Steven Wu · Shuai Tang · Sergul Aydore · Michael Kearns · Aaron Roth

PROSAC: Provably Safe Certification for Machine Learning Models under Adversarial Attacks Poster

Ziquan Liu · zhuo zhi · Ilija Bogunovic · Carsten Gerner-Beuerle · Miguel Rodrigues

Where did you learn that?: Tracing the Impact of Training Data with Diffusion Model Ensembles Poster

Zheng Dai · Rui-Jie Yew · David Gifford

Merging (EU)-Regulation and Model Reporting Oral

Danilo Brajovic · Vincent Philipp Göbels · Janika Kutz · Marco Huber

Video

Missing Value Chain in Generative AI Governance: China as an example Poster

Yulu Pi

Assessing AI Impact Assessments: A Classroom Study Poster

Nari Johnson · Hoda Heidari

SILO Language Models: Isolating Legal Risk In a Nonparametric Datastore Oral

Sewon Min · Suchin Gururangan · Eric Wallace · Weijia Shi · Hannaneh Hajishirzi · Noah Smith · Luke Zettlemoyer

Assessing the Impact of Distribution Shift on Reinforcement Learning Performance Poster

Ted Fujimoto · Joshua Suetterlein · Samrat Chatterjee · Auroop Ganguly