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<h1 class="title toc-ignore">BINF 4008-02</h1>
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<p><font size="+2"><strong>INTERROGATING ETHICS AND JUSTICE IN DIGITAL
HEALTH</strong></font><br />
<strong>Spring 2024 - Thursdays, 2:00-4:00PM</strong><br />
<a href="https://www.dbmi.columbia.edu/" target="_blank">Department of
Biomedical Informatics, Columbia University</a> |
<a href="https://www.mhe.cuimc.columbia.edu/" target="_blank">Department
of Medical Humanities and Ethics, Columbia University</a><br />
<strong>Classroom Location:</strong> Columbia University Irving Medical
Center, Presbyterian Hospital, 20th Floor, Room 200<br />
<strong>Office Hours:</strong> by appointment</p>
<p><strong>Course Directors:</strong></p>
<div class="clearfix" >
<div class="img-container">
<img src="assets/img/elhadad_noemie.jpeg" style="float:left;height: 150px;width: 150px"
alt="Avatar" class="avatar" />
</div>
<div class="bio-container">
<p>
<a href="https://people.dbmi.columbia.edu/noemie/" target="_blank">Noémie
Elhadad, PhD</a><br />
<a href="mailto:[email protected]?subject=BINF 4008-02" target="_blank">[email protected]</a>
<table style="font-size:80%;">
<td>
Chair, Department of Biomedical Informatics Associate Professor of
Biomedical Informatics Affiliated with Computer Science<br />
Data Science Institute<br />
Columbia University
</p>
</td>
</table>
</div>
<div class="img-container">
<img src="assets/img/lee_sandra.jpeg" style="float:left;height: 150px;width: 150px" alt="Avatar" class="avatar" />
</div>
<div class="bio-container" float:left>
<p>
<a href="https://www.mhe.cuimc.columbia.edu/profile/sandra-s-lee-phd" target="_blank">Sandra
Soo-Jin Lee, PhD</a><br />
<a href="mailto:[email protected]?subject=BINF 4008-02" target="_blank">[email protected]</a><br />
<table style="font-size:80%;">
<td>
Chief, Division of Ethics<br> Professor of Medical Humanities and
Ethics<br />
Co-Director, Center for ELSI Resources and Analysis (CERA) &
ELSIhub<br> Director, Team Science Program & Resource, Columbia
University Irving Institute for Clinical and Translational
Research<br />
</p>
</td>
</table>
</div>
</div>
<br> <strong>Teaching Assistants:</strong><br />
<div class="clearfix" >
<div class="img-container">
<img src="assets/img/idnay_betina.jpg" style="float:left;height: 150px;width: 150px" alt="Avatar" class="avatar" />
</div>
<div class="bio-container" float:left>
<p>
Betina Idnay, PhD, RN</a><br />
<a href="mailto:[email protected]?subject=BINF 4008-02" target="_blank">[email protected]</a><br />
<table style="font-size:80%;">
<td>
Postdoctoral Research Fellow<br> Department of Biomedical Informatics
</p>
</td>
</table>
<br> <br>
</div>
<div class="img-container">
<img src="assets/img/zheng_elise.jpg" style="float:left;height: 150px;width: 150px"
alt="Avatar" class="avatar" />
</div>
<div class="bio-container">
<p>
Elise Li Zheng, PhD</a><br />
<a href="mailto:[email protected]?subject=BINF 4008-02" target="_blank">[email protected]</a>
<table style="font-size:80%;">
<td>
Postdoctoral Research Scientist<br />
Division of Ethics, Department of Medical Humanities and Ethics
</p>
</td>
</table>
<br> <br>
</div>
</div>
<!-- <div class="img-container"> -->
<!-- <img src="assets/img/reyesnieva_harry.png" style="float:left;height: 150px;width: 150px" alt="Avatar" class="avatar" /> -->
<!-- </div> -->
<!-- <div class="bio-container2"> -->
<!-- <p><a href="https://www.harryreyesnieva.com" target="_blank">Harry Reyes Nieva, MPhil, MAS, MA</a> -->
<!-- <a href="mailto:[email protected]?subject=BINF 4008-02" target="_blank">[email protected]</a> -->
<!-- <table style="font-size:80%;"><td> -->
<!-- PhD student in Biomedical Informatics, -->
<!-- Columbia University -->
<!-- Visiting Postgraduate Research Fellow, -->
<!-- Harvard Medical School</p></td></table> -->
<!-- <br> -->
<!-- <br> -->
<!-- </div> -->
<div id="course-description" class="section level2">
<h2>Course Description</h2>
<p>Engaging with data is a civic requirement. Technical expertise must
include engagement with the ethical issues and policy implications
related to emerging data-driven techniques. The biomedical, health, and
clinical domains are going through in-depth changes as artificial
intelligence and data-driven thinking are becoming inherent to routine
processes. How will knowledge production in health data science
determine what counts as healthy, normal or disease in individuals and
groups? Who will get access to what care and at what price when
treatment recommendations are guided by artificial intelligence?</p>
<p>The purpose of this course is to engage students in thinking about
the ethical issues and social implications of the creation, analysis and
application of data in health. This multidisciplinary course will teach
students to situate data technologies within their socio-political
contexts and to examine the social life of data and its impact on
society. Students will become adept at identifying and analyzing how the
management and interpretation of data impacts and is impacted by social,
economic and political processes.</p>
<p>This collaborative course will provide innovative materials and
hands-on experience to students through:</p>
<ol style="list-style-type: decimal">
<li><p>a series of use cases that reflect ongoing themes in ethics and
justice in digital health, and corresponding simulated datasets &
computational tools for students to engage with;</p></li>
<li><p>collaborative, multidisciplinary work on a research project at
the intersection of ethics and digital health for students to synthesize
their skills and knowledge acquired during the course; and</p></li>
<li><p>mentoring for students to write an op-ed on a specific topic in
ethics for digital health targeted at the general public.</p></li>
</ol>
</div>
<div id="learning-objectives" class="section level2">
<h2>Learning Objectives</h2>
<p>When students complete this course, they will be able to:</p>
<ul>
<li><p>Engage with fundamental concepts in the social study of science
and technology and analyze historical, social, and political issues
(e.g., construction of categories, co-production, expertise, public
engagement, and structural inequality);</p></li>
<li><p>Identify ethical issues in data science techniques applied in
biomedical research, clinical care, and wellbeing technology, including
fairness, equity and justice, and issues such as privacy, autonomy,
discrimination, and accountability;</p></li>
<li><p>Critically analyze and identify how and to what extent values are
embedded in technical artifacts and systems through implicit and
explicit technological design and user experience, and how to prioritize
values for individuals and groups and their implications for
tradeoffs;</p></li>
<li><p>Carry out analyses of complex health and healthcare datasets to
identify types of potential biases;</p></li>
<li><p>Engage and critically analyze computational approaches proposed
in the recent machine-learning and biomedical literature for bias
detection and mitigation;</p></li>
<li><p>Communicate the on-going problematics and debates of data-driven
digital health from an ethical and justice standpoint.</p></li>
</ul>
</div>
<div id="registration" class="section level2">
<h2>Registration</h2>
<p>Registration for the course is with instructor’s permission. The
course is open to Columbia University graduate students as well as
undergraduate seniors. As you register, please send an email to Drs
Elhadad and Lee with the following information:<br />
* Your name, uni, department, and year in degree<br />
* In a few sentences, why are you interested in taking the course?<br />
* Do you have experience with coding?<br />
* Do you have a background in ethics?</p>
</div>
<div id="prerequisites" class="section level2">
<h2>Prerequisites</h2>
<p>Students must have foundational programming concepts (Python or R
concepts) including data types and basic operations, and are able to
effectively navigate the RStudio interface. The course is open to
graduate students as well as undergraduate seniors. Permission from the
course directors is required to enroll.</p>
</div>
<div id="course-requirements-and-grading" class="section level2">
<h2>Course Requirements and Grading</h2>
<p>Attendance to class is required unless otherwise pre-approved.
Grading is based on class participation (10%), Use Case Responses and
Experiments (35%), a Group Project (35%), and an Op-Ed (20%).</p>
</div>
<div id="assignments" class="section level2">
<h2>Assignments</h2>
<p><strong>Use Case Responses and Experiments.</strong> Short response
papers (1-2 pages) to readings discussed in class and the use case
described in class, discuss potential solutions and how you would
implement them, and programming notebooks compiling experiments on use
cases (e.g., assess degree of missing information of different data
elements in given datasets and resulting biases). The primary competency
of these assignments will relate to comprehension of material discussed
in class and application of computational tools to specific use
cases.</p>
<p><strong>Group project.</strong> Small teams of students with
interdisciplinary background will select a particular issue (e.g.,
predictive modeling for resource allocation in a pandemic), identify
gaps in knowledge (e.g., racial and economic disparities), propose a
comprehensive plan for addressing the knowledge gap, and provide
preliminary work towards addressing the identified gaps. The primary
competencies of this assignment will pertain to synthesis of the
different ethical frameworks and the algorithmic approaches discussed in
class. Furthermore, the project will provide experience for students to
work closely across their discipline boundaries and experience
first-hand the challenges and rewards of such collaborations.</p>
<p><strong>Op-Ed.</strong> Students will write op-eds (650-800 words)
that communicate the complexity of a chosen topic at the intersection of
ethics, justice, and digital health to a general audience. The primary
competency for this assignment pertains to the importance of
communication and civic engagement on current policy and technological
issues. To support students with this assignment, students will
participate in a workshop on writing to the general public. Students
will writeOpEds for a selected venue and will have the opportunity to
publish their pieces on the course’s blog and other outlets. <em>Final
Due: April 18, 2024.</em></p>
</div>
<div id="academic-integrity" class="section level2">
<h2>Academic Integrity</h2>
<p>Columbia’s intellectual community relies on academic integrity and
responsibility as the cornerstone of its work. Graduate students are
expected to exhibit the highest level of personal and academic honesty
as they engage in scholarly discourse and research. In practical terms,
you must be responsible for the full and accurate attribution of the
ideas of others in all of your research papers and projects; you must be
honest when taking your examinations; you must always submit your own
work and not that of another student, scholar, or internet source.
Graduate students are responsible for knowing and correctly utilizing
referencing and bibliographical guidelines. When in doubt, consult your
professor. Citation and plagiarism-prevention resources can be found at
the GSAS page on
<a href="https://gsas.columbia.edu/student-guide/research/academic-integrity-and-responsible-conduct-research" target="_blank">Academic
Integrity and Responsible Conduct of Research</a>.</p>
<p>Failure to observe these rules of conduct will have serious academic
consequences, up to and including dismissal from the university. If a
faculty member suspects a breach of academic honesty, appropriate
investigative and disciplinary action will be taken following
<a href="https://www.gsas.columbia.edu/content/deans-discipline" target="_blank">Dean’s
Discipline</a> procedures. Your grade should reflect your own work. If
you believe you are going to have trouble completing an assignment,
please talk to one of the instructors or TA in advance of the due
date.</p>
</div>
<div id="course-schedule" class="section level2">
<h2>Course Schedule</h2>
<table>
<colgroup>
<col width="15%" />
<col width="84%" />
</colgroup>
<thead>
<tr class="header">
<th>Date</th>
<th>Topic</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td>Jan 18</td>
<td>Ethics: Principles and Fundamentals</td>
</tr>
<tr class="even">
<td>Jan 25</td>
<td>AI in Digital Health</td>
</tr>
<tr class="odd">
<td>Feb 1</td>
<td>Observational Health Data Sciences and Informatics
(OHDSI)/Observational Medical Outcomes Partnership (OMOP) Primer / R and
SQL Access Lab</td>
</tr>
<tr class="even">
<td>Feb 8</td>
<td>Sociotechnical systems, stakeholders and politics of technology</td>
</tr>
<tr class="odd">
<td>Feb 15</td>
<td>Data Ownership</td>
</tr>
<tr class="even">
<td>Feb 22</td>
<td>Whose Data; Which Data are Collected; Data Harmonizations and
Standardizations</td>
</tr>
<tr class="odd">
<td>Feb 29</td>
<td>Privacy and Safety</td>
</tr>
<tr class="even">
<td>Mar 7</td>
<td>Writing Op-Ed Workshop</td>
</tr>
<tr class="odd">
<td>Mar 14</td>
<td>No class</td>
</tr>
<tr class="even">
<td>Mar 21</td>
<td>Algorithmic Fairness and Justice: from infrastructure to
application</td>
</tr>
<tr class="odd">
<td>Mar 28</td>
<td>GenAI: epistemological challenge</td>
</tr>
<tr class="even">
<td>Apr 4</td>
<td>Trust, Trustworthiness and Transparency</td>
</tr>
<tr class="odd">
<td>Apr 11</td>
<td>Designing ethical technology through inclusive and participatory
design</td>
</tr>
<tr class="even">
<td>Apr 18</td>
<td>Op-Ed discussions</td>
</tr>
<tr class="odd">
<td>Apr 25</td>
<td>Group Presentations</td>
</tr>
</tbody>
</table>
</div>
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