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AIPF Health Wide Reach Sessions

January 18 & January 21, 2022

In 2019, the Massachusetts Institute of Technology launched the Stephen A. Schwarzman College of Computing to address the global opportunities and challenges presented by the prevalence of computing and the rise of artificial intelligence. As a part of this mission, the College created the AI Policy Forum (AIPF)—its vehicle to move the global conversation about the impact of AI from principles to practical policy implementation. The Forum is an ongoing initiative focused on cultivating global, inclusive and science-based discussions on AI policy, aiming to become a conversation partner, sounding board, and matchmaker for policymakers and anyone thinking about AI policy.
 

The AIPF Wide Reach is an effort to assemble governmental officials devoted to AI policy from around the world to discuss these important issues. This specific event will focus on health data access and privacy. Advancing AI technology in healthcare is critically dependent on access to large health datasets. Through this event we seek to better understand what can be done to decrease barriers to access to high-quality health data to advance more innovative, robust and inclusive research results while being respectful of patient privacy. 

The workshop will highlight successes in data sharing and examples of the type of AI technology development we hope to accelerate, and will discuss advantages & disadvantages of approaches that policy makers are grappling with around de-identification, creation of synthetic data, and access control. From these we aim to understand how to scale successful data sharing models and identify legal, institutional and regulatory solutions and barriers to be addressed. The program is as follows:

Organizers

  • Marzyeh Ghassemi, MIT

  • David Sontag, MIT

  • Ziad Obermeyer, UC Berkeley

 

Participants

  • International policymakers dedicated to AI policy in their respective countries

  • MIT & external faculty 

  • AIPF team members

 

Goals

  • Bi-directional learning on AI policy, i.e., exchange of knowledge/perspectives between scientists and a variety of policymakers from around the world

  • Focus on concrete AI policy challenges and specific policy tradeoffs 

  • Increase engagement and continue building an “AIPF community”

  • Gather input that will inform the direction of future AIPF work and events

  • Establish connections and contacts between attendees for ongoing international collaboration

 

Format

  • Virtual meetings (Zoom), under Chatham House Rule

  • Target number of participants: ~40 policymakers + faculty + AIPF team

  • Dates: January 18 and January 21, 2022

  • For each Wide Reach session, a speaker will be asked to present on a topic of expertise.

  • Live Q/A session participants will be tasked with proposing concrete policy approaches to the challenge being discussed. Some sessions may  include breakout groups for different areas.

  • After each session, the AIPF team will prepare a written summary of the discussion and the policy proposals.

Workshop Part 1

January 18, 2022 
10:00 am - 4:30 pm EST

SESSION 1

10:00 - 10:15 am

Introductions and AIPF process
Barzilay and Weitzner

Workshop goals
Ghassemi, Obermeyer, Sontag

Non-Profit / Gov’t
Success Stories

10:15 - 10:30 am

10:30 - 10:45 am

10:45 - 11:00 am

MIMIC/PhysioNet
Leo Celi, MIT

11:00 - 11:15 am

11:15 - 11:30 am

Break

Limited Access
Models

11:30 - 11:45 am

11:45 - 12:00 pm

Q/A with
all panelists

12:00 - 1:00 pm

Session 1 panelist discussion (1 hour, live)

1:00 - 1:15 pm

Break

SESSION 2

Upside
Demonstrations

1:15 - 1:30 pm

1:30 - 1:45 pm

Covid testing in Greece
Hamsa Bastani, UPenn

1:45 - 2:00 pm

Breast Cancer Screening
Regina Barzilay, MIT

2:00 - 2:15 pm

Data holes in biomedical research
Anna Goldenberg, University of Toronto

2:15 - 2:30 pm

Integrating Real-time EWS in deployed Models
Dimitris Bertsimas, MIT

2:30- 2:45 pm

Using Truven and CMS data to identify & address health bias
Sherri Rose, Stanford

Q/A with
all panelists

2:45 - 3:45 pm

Session 2 panelist discussion (1 hour, live)

3:45 - 4:30 pm

Discussion Summary and Close
Ghassemi, Obermeyer, Sontag

SESSION 3

10:00 - 10:30 am

Introductions and AIPF process
Barzilay and Weitzner

Workshop goals and Summary of Day 1
Ghassemi, Obermeyer, Sontag

Legal frameworks, 
regulation, and
funding

10:30 - 10:55 am

NIH’s vision and initiatives to enable health data access
Susan Gregurick, NIH

11:00 - 11:15 am

HIPAA and Health Regulation
Marcy Wilder, HoganLovells

11:15 - 11:30 am

Reconceptualizing privacy tradeoffs
Arti Rai, Duke Law School

Q/A with
all panelists

11:30 - 12:30 pm

Session 3 panelist discussion (1 hour, live)

12:30 - 12:45 pm

Break

SESSION 4

Technical
Approaches to
Privacy

12:45 - 1:00 pm

De-identification approaches
Doug Fridsma, Datavant

1:00 - 1:15 pm

Synthetic data generation and use
Carmela Troncoso, EPFL (Synthetic Data, A Mirage)

1:15 - 1:30 pm

Privacy-preserving ML in clinical records
Steven Wu, CMU 

1:30 - 1:45 pm

Federated learning
Rui Duan, Harvard

Q/A with
all panelists

1:45 - 2:15 pm

Session 4 panelist discussion (30 min, live)

SESSION 5

Infrastructure for
Data Sharing

2:15 - 2:30 pm

Dandelion Infrastructure
Elliott Green, Dandelion Health

2:30 - 2:45 pm

Secure computing and decentralized data science
Dawn Song, UC Berkeley

2:45 - 3:00 pm

Ethical Implications
of Shared Health Data

3:00 - 3:15 pm

Ethical data use and sharing
Kadija Ferryman, JHU

3:15 - 3:30 pm

Patient data advocacy
Nell Luo, Folia Health

Q/A with
all panelists

3:30 - 4:15 pm

Session 5 panelist discussion (30 min, live)

4:15 - 4:30 pm

Summary and Close
Ghassemi, Obermeyer, Sontag

Workshop Part 2

January 21, 2022 
10:00 am - 4:30 pm EST