Fall 2026

Introductory Artificial Intelligence (ai) and Data Ethics

PHILOS 244 introduces contemporary moral and political issues in AI and Data Ethics, integrating technical concepts with case studies on privacy, automation, and algorithmic justice.

offering recorded3–4 credits
Recorded instructors · Fall 2026 Edvard Aviles MezaHenry CurcioKenneth Quek +4 more

Summary

1 / 7

Historical reviews of Burgandy Basulto: Reviewers characterize the workload as easy with lenient grading and extension policies, though one notes a final essay project requiring a choice between argumentative or media connection formats.

Grade history

average GPA
letter grades
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All recorded terms · compare terms & instructors

Prerequisites

Course map

Sophomore standing

  • Sophomore standing
PHILOS 244

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

Prerequisite text tree
  • Sophomore standing

Professors

Fall 2026

No course-specific feedback yet.

Historical instructors & teaching patterns

Historical reviews for Burgandy Basulto describe her as nice, knowledgeable, and a generous grader who is lenient with extensions. However, one reviewer found the class unengaging and the material self-explanatory, while another appreciated her helpfulness and the final project options.

BURGANDY BASULTO is recorded teaching in Fall 2025. Recorded history may be incomplete and does not establish a future schedule.

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

Calendar & sections

Fall 2026

Schedule loads here as you scroll.

SectionModeEnrolled / capacityWaitlist
LEC 001Classroom Instruction141 / 14111
DIS 301Classroom Instruction23 / 231
DIS 302Classroom Instruction22 / 233
DIS 303Classroom Instruction24 / 232
DIS 304Classroom Instruction26 / 263
DIS 305Classroom Instruction23 / 232
DIS 306Classroom Instruction23 / 230
LEC 002Classroom Instruction69 / 7013
DIS 321Classroom Instruction23 / 2310
DIS 322Classroom Instruction22 / 232
DIS 323Classroom Instruction24 / 241
LEC 003Classroom Instruction68 / 6920
DIS 331Classroom Instruction23 / 233
DIS 332Classroom Instruction23 / 237
DIS 333Classroom Instruction22 / 2310

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

Meeting source records

Student experience

the class

Historical reviews for Burgandy Basulto describe the course as easy and lenient, though some find the material unengaging and basic, while others praise her knowledge and helpfulness.

Recent recorded grades — Fall 2025: 3.96 GPA, 98.3% A/AB (n=121 letter grades); Spring 2026: 3.94 GPA, 97.8% A/AB (n=138 letter grades).

difficulty & workload

Historical reviews of Burgandy Basulto: Reviewers characterize the workload as easy with lenient grading and extension policies, though one notes a final essay project requiring a choice between argumentative or media connection formats.

Historical reviews of Burgandy Basulto: Students report mixed experiences, with some finding the class unengaging and the professor's participation style annoying, while others appreciate her generosity and care for student learning.

Topics

  • Moral and political issues in AI and Data Ethics
  • Technical concepts: bias/variance tradeoff, reference class problem, inductive risk
  • Data and privacy
  • Impacts of automation on society
  • Use of algorithms in medicine and criminal law

Skills

  • Understanding technical AI concepts like bias/variance and inductive risk
  • Analyzing societal impacts of automation and algorithmic use in specific domains

Grades

Latest available · Spring 2026— not enough history to project Fall 2026.

average GPA
A / AB grades
letter grades
Instructor

Grade distribution · % of letter grades

A
AB
B
BC
C
D
F

Grades over time

Through Spring 2026

More grade details Grade mix, volume & source data

Where this course fits relative to

Latest available grades · Spring 2026 · all course levels

GPA

Higher than % of other courses in this group.

Course GPAs · red marks this course’s range

letter grades

More recorded grades than % of other courses in this group.

Typical course in this group: letter grades.

About this comparison

1283 courses over the same term, each with at least 30 recorded letter grades. Cross-listed courses count once. GPA is not a measure of difficulty or teaching quality. The typical course is the median by recorded grade count; tied values are not counted as lower. Grade counts describe course scale, not unique students or typical section size.

Descriptions compare GPA with this group’s average: at least 0.20 higher or lower; otherwise close to average. Section size uses median recorded enrollment: small up to 30, mid-sized 31–99, large 100+. Lectures and discussion/lab sections are described separately.

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.

Selected offering source records
PHILOS 244 · Fall 2026

Introductory Artificial Intelligence (AI) and Data Ethics

Recorded 2026-09-07
Raw records
[
  {
    "run_id": "20260907T155543-ce3781c4",
    "semester": "1272",
    "observed_at": "2026-09-07 15:55:43.033547+00:00",
    "offering_id": "1272:736:027102",
    "course_id": "PHILOS 244",
    "course_uid": "course_d271e7d703bce2000629b9ba",
    "term_id": "1272",
    "source_course_id": "027102",
    "source_subject_id": "736",
    "title": "Introductory Artificial Intelligence (AI) and Data Ethics",
    "credits_min": 3,
    "credits_max": 4,
    "typically_offered": "Not Applicable"
  }
]
Rate My Professors

Student reviews

Original comments behind the course and instructor summaries.

Read original reviews
Madgrades

Grade history

Recorded grade distributions by term, section, and instructor.

Explore recorded grades
Model 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": "b9d5cb3d127b6bdd0bdce07742c945f36d2ab4d49922a69c1c679fb9db3ec6af",
  "requirements_status": "valid",
  "dataset_revision": "e243353dcb7d79b7247ced91d69443ef4c2a6349",
  "observed_at": "2026-09-07 15:55:43.033547+00:00"
}