Philosophy (PHIL) |
211 Susan Campbell, 541-346-5547
College of Arts & Sciences
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Course Data
| PHIL 223 Data Ethics >2 |
4.00 cr. |
| This course explores central ethical challenges in data science and related fields of computational analysis. Offers both an overview of the major theoretical commitments of data ethics as well as engagement with applied contexts such as computer engineering, behavioral sciences, marketing, and surveillance. |
| Grading Options: |
Optional; see degree guide or catalog for degree requirements
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| Instructor: |
Alvarado R  |
Office:
245 Susan Campbell Hall
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| Course Materials |
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CRN |
Avail |
Max |
Time |
Day |
Location |
Instructor |
Notes |
Lecture |
24288 |
48 |
150 |
0830-0950 |
tr |
123 PAC |
Alvarado R |
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Final Exam: |
0800-1000 |
w 3/20 |
123 PAC |
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Associated Sections |
+ Dis |
24289 |
8 |
25 |
1100-1150 |
f |
242 GER |
Bagwala A |
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+ Dis |
24290 |
11 |
25 |
1200-1250 |
f |
340 TYKE |
Peres Santos D |
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+ Dis |
24291 |
6 |
25 |
1100-1150 |
f |
340 TYKE |
Peres Santos D |
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+ Dis |
24292 |
19 |
25 |
1200-1250 |
f |
195 ANS |
Waldeck M |
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+ Dis |
25807 |
3 |
25 |
1300-1350 |
f |
254 STB |
Bagwala A |
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+ Dis |
25808 |
1 |
25 |
1300-1350 |
f |
195 ANS |
Waldeck M |
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Academic Deadlines
| Deadline |
Last day to: |
| January 7: |
Process a complete drop (100% refund, no W recorded) |
| January 13: |
Drop this course (100% refund, no W recorded; after this date, W's are recorded) |
| January 13: |
Process a complete drop (90% refund, no W recorded; after this date, W's are recorded) |
| January 14: |
Process a complete withdrawal (90% refund, W recorded) |
| January 14: |
Withdraw from this course (100% refund, W recorded) |
| January 15: |
Add this course |
| January 15: |
Last day to change to or from audit |
| January 21: |
Process a complete withdrawal (75% refund, W recorded) |
| January 21: |
Withdraw from this course (75% refund, W recorded) |
| January 28: |
Process a complete withdrawal (50% refund, W recorded) |
| January 28: |
Withdraw from this course (50% refund, W recorded) |
| February 4: |
Process a complete withdrawal (25% refund, W recorded) |
| February 4: |
Withdraw from this course (25% refund, W recorded) |
| February 25: |
Withdraw from this course (0% refund, W recorded) |
| February 25: |
Change grading option for this course |
 | You can't drop your last class using the "Add/Drop" menu in DuckWeb. Go to the “Completely Withdraw from Term/University” link to begin the complete withdrawal process. If you need assistance with a complete drop or a complete withdrawal, please contact the Office of Academic Advising, 101 Oregon Hall, 541-346-3211 (8 a.m. to 5 p.m., Monday through Friday). If you are attempting to completely withdraw after business hours, and have difficulty, please contact the Office of Academic Advising the next business day. |
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Expanded Course Description
| In this course we will explore some of the ethical challenges particular to the design, development and deployment of computational methods of analysis such as the ones used in data science. This course will provide the student with an understanding of fundamental ethical questions about agency, responsibility and privacy as they relate to the practices of data science, its methodology and technology. This course begins by providing an overview of the conceptual trajectory from computer ethics, to information ethics, to data ethics. At the same time this course will provide a general overview of the main elements in ethical theory: from metaethical foundations to normative components of major theoretical frameworks. Furthermore, in this course, we will review the challenges of thorough ethical thought in applied contexts such as computer engineering and modeling, behavioral sciences, marketing and predictive algorithms. Although our contextual framework will be that of the multiple facets of data science, our focus will be on fundamental issues related to (moral and epistemic) agency, (social and individual) autonomy, and (personal and distributed) responsibility, which persist even when bias, error and transparency are accounted for in scientific practice. |
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