Spring 2027

Advanced Ethics of Data and Artificial Intelligence

Advanced course examining moral and political issues in AI and Data Ethics through contemporary case studies and applied philosophical research.

offering recorded4 credits
Recorded instructors · Spring 2027 No instructors listed

Summary

What you’ll be able to do

  • Critically evaluate ethical arguments in relation to data and AI.

  • Interpret complex texts accurately and analyze them logically by identifying explicit and implicit background assumptions, and by understanding which conclusions necessarily follow from them.

  • Communicate precisely and concisely in both writing and speech, in a way that adequately captures ethical nuances and ambiguities arising in AI design and deployment while not sacrificing technical accuracy.

  • Discuss controversial ethical and social questions respectfully and with the aim of uncovering the truth.

  • Deploy the conceptual tools and language necessary to converse with scholars and practitioners in the interdisciplinary AI and Data Ethics Community.

  • Identify and evaluate the ethical, legal, and political implications of AI, as well as their historical and societal context.

  • Communicate the distinctive value of humanistic inquiry into AI and data ethics as compared to, and in addition to, technical efforts to better understand and improve AI and other emerging technologies.

Source: UW Guide 1 UW Guide 2

Grade history

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average GPA
letter grades

No recorded grade history.

All recorded terms · compare terms & instructors

Prerequisites

Course map

Junior standing

  • Junior standing
LIS/PHILOS 544

This is a best-effort interpretation; check the catalog requirements above.

Prerequisite text tree
  • Junior standing

Professors

Spring 2027

No instructors recorded for this selection.

Historical instructors & teaching patterns

Recorded history may be incomplete and does not establish a future schedule.

Calendar & sections

Spring 2027

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SectionModeEnrolled / capacityWaitlist
LEC 001Classroom Instruction0 / 600
DIS 301Classroom Instruction0 / 300
DIS 302Classroom Instruction0 / 300
LEC 001Classroom Instruction0 / 600
DIS 301Classroom Instruction0 / 300
DIS 302Classroom Instruction0 / 300

Times are Central. Select a meeting for details; export includes recorded dates for the selected sections. Enrollment reflects scan time.

Meeting source records
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Student experience

the class

In-depth examination of contemporary moral and political issues in artificial intelligence (AI) and Data Ethics, integrating urgent problems, controversies, and continuously updated case studies. Covers topics such as the use of facial recognition technology in law and immigration enforcement, algorithmically-supported hiring processes, and the complex dynamics of human-computer interaction. Includes critical engagement with cutting-edge research in applied moral/political philosophy, such as on competing theories of justice and political legitimacy as well as on key normative concepts like trust, autonomy, privacy, explainability; and case studies drawing from work in computer sciences and applied statistics.

difficulty & workload

No workload feedback recorded.

Topics

  • Facial recognition, algorithmic hiring, and human-computer interaction.
  • Theories of justice, political legitimacy, trust, autonomy, privacy, and explainability.

Skills

  • Critical evaluation of ethical arguments in AI and data contexts.
  • Logical analysis and interpretation of complex texts.
  • Precise written and oral communication of ethical nuances.
  • Identification and evaluation of ethical, legal, and political implications of AI.

Grades

Instructor

Grade distribution · % of letter grades

No grades available yet.

More grade details Grade mix, volume & source data

Sources & history

UW–Madison

Catalog & offerings

Descriptions, prerequisites, and recorded course offerings.

Catalog observation history

Observations at scan time; dates do not imply when a catalog change took effect.

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Selected offering source records
LIS/PHILOS 544 · Spring 2027

Advanced Ethics of Data and Artificial Intelligence

Recorded 2026-10-14
LIS/PHILOS 544 · Spring 2027

Advanced Ethics of Data and Artificial Intelligence

Recorded 2026-10-14
Raw records 
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    "offering_id": "1274:544:027447",
    "course_id": "LIS/PHILOS 544",
    "course_uid": "course_a999f412ec94b04365fd2cd1",
    "term_id": "1274",
    "source_course_id": "027447",
    "source_subject_id": "544",
    "title": "Advanced Ethics of Data and Artificial Intelligence",
    "credits_min": 4,
    "credits_max": 4,
    "typically_offered": "Not Applicable"
  },
  {
    "run_id": "20261014T203208-0851c9a1",
    "semester": "1274",
    "observed_at": "2026-10-14 17:50:09.728220+00:00",
    "offering_id": "1274:736:027447",
    "course_id": "LIS/PHILOS 544",
    "course_uid": "course_a999f412ec94b04365fd2cd1",
    "term_id": "1274",
    "source_course_id": "027447",
    "source_subject_id": "736",
    "title": "Advanced Ethics of Data and Artificial Intelligence",
    "credits_min": 4,
    "credits_max": 4,
    "typically_offered": "Not Applicable"
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]
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Madgrades

Grade history

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Dataset & model

Recorded 2026-10-14

View the dataset on Hugging Face
Model outputs & technical records
Qwen/Qwen3.8-27B
LLM outputs across runs
Download part 1
Full model traces

Recorded model configuration, reasoning, and tool conversations.

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Model & dataset provenance 
{
  "model": "Qwen/Qwen3.8-27B",
  "model_revision": "1d4bf0f2ff6012fd82039f2fa52739d0dd7c60c0",
  "task_version": "17",
  "output_id": "e312e8b9afe8d4a14d615e7b7de76c7c98c4326865ac9a852ccb12096f8ce08a",
  "requirements_status": "valid",
  "dataset_revision": "fc1811fa52e581ea57a35c0cf3343f8740a8ffbf",
  "observed_at": "2026-10-14 17:50:09.728220+00:00"
}