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Fall 2026
Data and Algorithms: Ethics and Policy (communications Intensive)
Introduction to ethical, legal, and policy issues in analytics and algorithms, focusing on moral reasoning and communication.
Summary
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Lectures are large, with a median of 121 enrolled students in the recorded sections.
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Calendar & sections
Fall 2026Schedule loads here as you scroll.
| Section | Mode | Enrolled / capacity | Waitlist |
|---|---|---|---|
| LEC 001 | Classroom Instruction | 121 / 121 | 23 |
| DIS 301 | Classroom Instruction | 20 / 20 | 0 |
| DIS 302 | Classroom Instruction | 20 / 20 | 1 |
| DIS 303 | Classroom Instruction | 20 / 20 | 2 |
| DIS 304 | Classroom Instruction | 20 / 20 | 14 |
| DIS 305 | Classroom Instruction | 21 / 20 | 6 |
| DIS 306 | Classroom Instruction | 20 / 20 | 0 |
Times are Central. Select a meeting for details; export includes recorded dates for the selected sections. Enrollment reflects scan time.
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Student experience
the class
An introduction to ethical, legal and policy issues related to analytics, "big data" and algorithms to support decision making. Gain familiarity with major debates and controversies in a variety of contexts. Critically analyze course materials and apply moral reasoning and legal concepts to assess case studies and critique arguments made by others. Develop ability to write, present, and communicate complex concepts, evidence, and arguments related to data ethics and policy.
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UW–Madison
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Data and Algorithms: Ethics and Policy (Communications Intensive)
Recorded 2026-09-07Raw records
[
{
"run_id": "20260907T155543-ce3781c4",
"semester": "1272",
"observed_at": "2026-09-07 15:55:43.033547+00:00",
"offering_id": "1272:544:027319",
"course_id": "LIS 462",
"course_uid": "course_7b785ba53c69640f17bea1d6",
"term_id": "1272",
"source_course_id": "027319",
"source_subject_id": "544",
"title": "Data and Algorithms: Ethics and Policy (Communications Intensive)",
"credits_min": 4,
"credits_max": 4,
"typically_offered": "Not Applicable"
}
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Explore recorded gradesModel outputs & technical records
nvidia/Qwen3.6-35B-A3B-NVFP4
LLM outputs across runs
Full model traces
Recorded model configuration, reasoning, and tool conversations.
Model & dataset provenance
{
"model": "nvidia/Qwen3.6-35B-A3B-NVFP4",
"model_revision": "1355db6a052410cfd62085d94b58866fd0f2c3c5",
"task_version": "14",
"output_id": "6afb61ff06aed3f1f8f93fe98c216ee3594e95eaf109fdfe8b8e5ddd7f702b39",
"requirements_status": "valid",
"dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
"observed_at": "2026-09-07 15:55:43.033547+00:00"
}