Algorithmic Justice in Precision Medicine

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Overview

We are excited to share the final report from the Toward Algorithmic Justice in Precision Medicine workshop held in November 2023. 

Read the full report here
 

Feedback needed

We are thankful to workshop participants for their insights, which informed the report. We would value your feedback on the subject matter and the report, regardless of your role, perspective, or whether you participated in the workshop. 

Comments

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You will be given the option of having your comments included on this web page (see below) and if so, whether they should include your name or be shared anonymously. Members of the workshop Steering Committee will review and post comments periodically. Thank you for engaging with us on this critical issue.

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Workshop Videos

View the captioned workshop videos by session:

Welcome - Chancellor Hawgood; Goals and Framing w/ Keith Yamamoto; Keynote w/ Alondra Nelson; Workshop topics w/ Ida Sim
Panel 1 - Advance toward transparency and explainability in healthcare algorithms and their use
Panel 3 - Ensure accountability, equity, and justice in outcomes from healthcare algorithms
Breakout Groups Report back
Concluding Remarks

Photos

Sponsors

• UCSF Precision Medicine (PM)

• UCSF Research Development Office (RDO)

• UCSF Office of the Chief Informatics Officer (CRIO)

• UCSF Bakar Computational Health Sciences Institute (BCHSI)

• UCSF UC Berkeley Joint Program in Computational Precision Health (CPH)

• UCSF Clinical and Translational Science Institute (CTSI) Community Engagement Program (CE)

• UCSF Clinical and Translational Science Institute (CTSI) Research Action Group for Equity (RAGE)

• UCSF Office of the Associate Vice Chancellor for Research – Inclusion, Diversity, Equity, and Anti-Racism (VC-IDEA)

 

Related

Precision medicine seeks to fundamentally alter current policy and practice of biomedical research, public health, and healthcare. It aims to leverage algorithms, including artificial intelligence (AI) tools, to aggregate, integrate, and analyze vast amounts of data from basic science, clinical, personal, environmental, social, and population health settings. It would define biological processes and determine disease mechanisms; develop and deliver precise diagnostics, therapeutics and prevention measures in a manner that advances equity; and advise and treat all people based on their individual conditions, needs, and values.

However, public health and social science research have shown that certain data collection methods and analyses, constructed datasets, and analytical algorithms carry biases that perpetuate or exacerbate structuralized racism, gender inequities, inaccessibility, and other harms. Therefore, altering current practices and advancing toward precision medicine will require acknowledging and addressing these harms. As part of this workshop, we will consider systemic flaws in data collection efforts, datasets, and AI tools, and how resultant algorithmic injustices can be uncovered and addressed.

This gathering convened community members along with health system professionals, biomedical investigators, and AI tool developers to discuss key issues, identify and prioritize specific challenges, and propose actionable recommendations.

Agenda

Glossary