April 15
8am-10am (EDT/Boston Time)
In this session, participants will approach and learn about the chances and challenges of digital self-determination in health from a multidisciplinary angle – technology, medicine, law and policy.
From a technical perspective, participants will learn, which problems in medicine can and cannot be solved with artificial intelligence (AI). Using the COVID tracing app as an example, the clinical utility of AI shall be explored from a medical perspective. Within a legal and policy analysis, participants will explore how individual and public interests can be balanced adequately in order to foster innovation while also protecting individual rights.
“What Artificial Intelligence Can and Can’t Do Right Now”, Harvard Business Review, by Andrew Ng
“AI Recognizes COVID-19 in the Sound of a Cough”, IEEE Spectrum, by Megan Scudellari
8am: Reflections and Report Back from Previous Session (Lance)
8:10am: Introduction to digital self-determination in medicine
Each speaker gives a 3-minutes pitch about their specialty/research areas and their question they would like to explore with the students
Prof. Stefan Feuerriegel (technology): Which problems in medicine can be solved with AI?
Prof. Satchit Balsari (medicine): Clinical utility of AI (COVID tracing app)
Prof. Kerstin N Vokinger (law/policy): Legal challenges of AI and self-determination
8:25am: Sparks Session 1 & 2 (20 minutes each)
Students will break into 3 groups. Each group will meet for 20 minutes and then rotate to the next speaker. The objective is a direct conversation between the groups and the lecturer and to discuss the pitch/case with different perspectives (technology, medicine, law/policy).
9:05am: 5 Minute Break
9:10am: Breakout Session 3
Students will break into 3 groups. Each group will meet for 20 minutes and then rotate to the next speaker. The objective is a direct conversation between the groups and the lecturer and to discuss the pitch/case with different perspectives (technology, medicine, law/policy).
9:30am: Debrief
Lecturers and students conversation (power over medical decisions in the age of AI)
Answers and highlights from the conversations are shared
9:50am: Summary, Assignment, Next Steps
Resources referenced in this session
“What can machine learning do? Workforce implications”, Science, Vo. 358 (3670), by Erik Brynjolfsson and Tom Mitchell
Paper:
Supplementary Materials
Digital tools against COVID-19: taxonomy, ethical challenges, and navigation aid, The Lancet Digital Health Vo. 2, August 2020, by Urs Gasser et al.
Resources for Further Consideration
“Machine Learning in Medicine”, New England Journal of Medicine, Vol. 380 (14), by Alvin Rajkomar, Jeffrey Dean, Isaac Kohane
Based upon the session, find an interesting current example of some of the questions, challenges, or elements from Session 5 as relates to digital self-determination and the intersection of technology, medicine, policy and law in your country, region, state, or city. Research it a bit and try to produce an artifact that addresses or raises some of the questions and concerns from the session.
Ideally, these will be case studies that will highlight what is happening, what are some of the challenges and solutions possible in the situation, and what are some of the additional questions raised through the lens of digital self-determination. Ideally, the artifact would include a set of questions to push the audience to think more deeply about the example or to compare it/connect it to other examples (e.g. “What could be changed to enhance the peoples/communities’ abilities to take more control of their health data?”)
Due Tuesday, April 20 by 2pm (EDT/Boston time).
Strong Recommendations
Try a format that you have not tried before (if you’ve done text, try image or video; if you’ve done video, try audio, text, or another format).
Collaborate with someone else (especially if you haven’t yet)
Share on Slack with others what you plan on doing. This might help ideas for collaboration or find opportunities to align or differentiate from one another.
Please submit your artifact using this form: https://forms.gle/EsCanYoVyys6Zx3dA
Participants had a robust discussion about the outline of what a Wikipedia entry on “Digital Self-Determination” would look like. We’d like to start developing that entry in full over the next three sessions. Drawing upon the various research and materials you found when developing the Bibliography from Week 2, we would like you to begin to draft out the actual Wikipedia entry. This week, there are a few steps to get there.
Revisit the outline and finalize (for now) what the exact sections are going to be for the entry as best as possible.
Synthesize and finalize these great ideas in the comments and where relevant, add them as notes in the relevant section of the outline
Resolve the comment threads that focus on the outline, once the comments have been meaningfully incorporated (resolve; don’t delete--press the check mark).
For the rest of this activity, develop about 3-5 sentences for every Level 1 section and at least 1-3 sentences for subsections.
This will be a collaborative efforts so you might create a table above the outline to identify who is taking on what section (collaboration is encouraged)
By next Thursday (4/22/2021), all sections and make sure that there is coverage of all the sections
In starting to write this entry, please review and keep in mind these resources as they highlight important considerations about creating a Wikipedia article:
Satchi Balsari
Dr. Satchit Balsari is a Professor in emergency medicine at Harvard Medical School and Beth Israel Deaconess Medical Center. Since 2009, he has been affiliated with the FXB Center for Health and Human Rights at Harvard University, where his research has contributed to advocacy on behalf of vulnerable populations affected by disasters and humanitarian crises.
His interdisciplinary interests in mobile technology, disaster response, and population health have been informed by his clinical practice in the United States and his field work around the world. His research has resulted in innovative applications of mobile, cloud-based technology to address public health challenges in mass gatherings, disasters, and humanitarian crises.
Dr. Balsari received his medical degree from Grant Medical College in Mumbai, India and his public health degree from Harvard; he completed his emergency medicine residency at Columbia and Cornell’s New York-Presbyterian Hospital. In March 2017, he was awarded the Dr B.C. Roy National Award by the President of India, for “outstanding services in the field of sociomedical relief.” Dr. Balsari is an Aspen Ideas Scholar, and Asia 21 Young Leader at the Asia Society.
Stefan Feuerriegel
Stefan is a Professor of management information systems in the Department of Management, Technology, and Economics at ETH Zurich. His group develops, implements, and evaluates new Artificial Intelligence (AI) tools to solve real-world challenges and to make a profound impact in our daily lives. Examples include AI tools for monitoring the COVID-19 epidemic, for managing global development aid flows, for identifying and mitigating fake news, and for effectively detecting health risks in diabetes patients. In his research, Stefan partnered with global industry players such as Foursquare, Thomson Reuters, ABB Hitachi, or Siemens to bring AI into practice. Stefan has further been an advisor of the SDG Financing Lab of the OECD, and a member of a COVID-19 working group of the World Health Organization (WHO).
After obtaining a PhD from the University of Freiburg, he was a strategy consultant with McKinsey, and a visitor at Carnegie Mellon University, Pittsburgh; the University of Texas at Austin; the University of New South Wales, Sydney; and the National Institute of Informatics, Tokyo.
Kerstin N Vokinger
Kerstin N Vokinger is a Professor at the University of Zurich, Faculty Associate at the Berkman Klein Center (Harvard University), and Affiliated Faculty at Harvard Medical School (Program on Regulation, Therapeutics, and Law). In her research, she focuses with her team on interdisciplinary questions at the intersection of law, medicine, and technology, with the goal to improve access to medicine and technology. In her areas of expertise, she also advises governmental authorities and international organizations.
Kerstin studied in parallel law (JD) and medicine (MD), and conducted a PhD at the University of Zurich. She also completed a Masters of Law (LLM) at Harvard Law School, was a Visiting Fellow at the Berkman Klein Center, and a Postdoc Fellow at Harvard Medical School.