Scope and Topics

The availability of massive amounts of data, coupled with high-performance cloud computing platforms, has driven significant progress in artificial intelligence and, in particular, machine learning and optimization. It has profoundly impacted several areas, including computer vision, natural language processing, and transportation. However, the use of rich data sets also raises significant privacy concerns: They often reveal personal sensitive information that can be exploited, without the knowledge and/or consent of the involved individuals, for various purposes including monitoring, discrimination, and illegal activities.
The third AAAI Workshop on Privacy-Preserving Artificial Intelligence (PPAI-22) held at the Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI-22) builds on the success of previous years AAAI PPAI-20 and AAAI PPAI-21 to provide a platform for researchers, AI practitioners, and policymakers to discuss technical and societal issues and present solutions related to privacy in AI applications. The workshop will focus on both the theoretical and practical challenges related to the design of privacy-preserving AI systems and algorithms and will have strong multidisciplinary components, including soliciting contributions about policy, legal issues, and societal impact of privacy in AI.

PPAI-22 will place particular emphasis on:
  1. Algorithmic approaches to protect data privacy in the context of learning, optimization, and decision making that raise fundamental challenges for existing technologies.
  2. Social issues related to tracking, tracing, and surveillance programs.
  3. Algorithms and frameworks to release privacy-preserving benchmarks and data sets.

Topics

The workshop organizers invite paper submissions on the following (and related) topics:
  • Applications of privacy-preserving AI systems
  • Attacks on data privacy
  • Differential privacy: theory and applications
  • Distributed privacy-preserving algorithms
  • Human rights and privacy
  • Privacy and Fairness
  • Privacy policies and legal issues
  • Privacy preserving optimization and machine learning
  • Privacy preserving test cases and benchmarks
  • Surveillance and societal issues

Finally, the workshop will welcome papers that describe the release of privacy-preserving benchmarks and data sets that can be used by the community to solve fundamental problems of interest, including in machine learning and optimization for health systems and urban networks, to mention but a few examples.

Format

The workshop will be a one-day meeting. The workshop will include a number of technical sessions, a poster session where presenters can discuss their work, with the aim of further fostering collaborations, multiple invited speakers covering crucial challenges for the field of privacy-preserving AI applications, including policy and societal impacts, a number of tutorial talks, and will conclude with a panel discussion.

Reviewer Self-nomination form

Please, fill in the form at the following link https://forms.gle/WQR8XfGzP2XYVs696 if you wish to self-nominate yourself for reviewing submission for PPAI-22.
Reviewers from all levels of seniority are invited to self-nominate. Their expertise will be assessed based on previous publications in the field of privacy preserving technologies as well as their participation to program committees for other events.

Important Dates

  • November 23, 2021 – Submission Deadline [Extended]
  • December 5, 2021 – NeurIPS/AAAI Fast Track Submission Deadline
  • December 16, 2021 December 23, 2021 – Acceptance Notification
  • December 31, 2021 – AAAI Early registration deadline
  • February 28 or March 1, 2022 – Workshop Date

Submission Information

Submission URL: https://cmt3.research.microsoft.com/PPAI2022

Submission Types

  • Technical Papers: Full-length research papers of up to 7 pages (excluding references and appendices) detailing high quality work in progress or work that could potentially be published at a major conference.
  • Short Papers: Position or short papers of up to 4 pages (excluding references and appendices) that describe initial work or the release of privacy-preserving benchmarks and datasets on the topics of interest.

NeurIPS/AAAI Fast Track (Rejected AAAI papers)

Rejected NeurIPS/AAAI papers with *average* scores of at least 4.5 may be asubmitted directly to PPAI along with previous reviews. These submissions may go through a light review process or accepted if the provided reviews are judged to meet the workshop standard.

All papers must be submitted in PDF format, using the AAAI-22 author kit. Submissions should include the name(s), affiliations, and email addresses of all authors.
Submissions will be refereed on the basis of technical quality, novelty, significance, and clarity. Each submission will be thoroughly reviewed by at least two program committee members.
Submissions of papers rejected from the AAAI 2022 technical program are welcomed.

For questions about the submission process, contact the workshop chairs.

Registration

Registration in each workshop is required by all active participants, and is also open to all interested individuals. Early registration deadline is on December 31th. For more information please refer to AAAI-22 Workshop page.

Invited Speakers

Adam Smith

Boston University

Talk details

Claire McKay Bowen

Urban Institute

Talk details

Damien Desfontaines

Tumult Labs

Talk details

Ilya Mironov

Facebook

Tutorial details

Program Committee

  • Amrita Roy Chowdhury (University of Wisconsin-Madison)
  • Aurélien Bellet (INRIA)
  • Carsten Baum (Aarhus University)
  • Catuscia Palamidessi (Laboratoire d'informatique de l'École polytechnique)
  • Christine Task (Knexus Research)
  • Cuong Tran (Syracuse University)
  • Di Wang (KAUST)
  • Elette Boyle (IDC H)
  • Fatemeh Mireshghallah (University of California, San Diego)
  • Graham Cormode (University of Warwick)
  • Hanieh Hashemi (University of Southern California)
  • Hao Wang (Rutgers University)
  • Ivan Habernal (Technical University of Darmstadt)
  • Jan Ramon (INRIA, FR)
  • Jianfeng Chi (University of Virginia)
  • Keyu Zhu (Georgia Tech)
  • Kobbi Nissim (Georgetown University)
  • Marco Romanelli (CentraleSupélec - CNRS - L2S )
  • Mark Bun (Boston University)
  • Michael Hay (Colgate University)
  • Mohamed Ali Kaafar (Macquarie University and CSIRO-Data61)
  • Mohammad Mahdi Khalili (University of Delaware)
  • Olga Ohrimenko (The University of Melbourne)
  • Paritosh P Ramanan (Georgia Institute of Technology)
  • Rakshit Naidu (Carnegie Mellon University)
  • Ranya Aloufi (Imperial College London)
  • Raouf Kerkouche (CISPA – Helmholtz Center for Information Security)
  • Santiago Zanella-Beguelin (Microsoft Research)
  • Terrence WK Mak (Georgia Institute of Technology)
  • Vikrant Singhal (Northeastern University )
  • Xi He (University of Waterloo)
  • Yunwen Lei (University of Birmingham)
  • Zhiqi Bu (University of Pennsylvania)

Workshop Chairs

Ferdinando Fioretto

Syracuse University

ffiorett@syr.edu

Aleksandra Korolova

University of Southern California

korolova@usc.edu

Pascal Van Hentenryck

Georgia Institute of Technology

pvh@isye.gatech.edu