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DRPS : Course Catalogue : School of Philosophy, Psychology and Language Sciences : Philosophy

Undergraduate Course: Algorithmic Bias (PHIL10235)

Course Outline
SchoolSchool of Philosophy, Psychology and Language Sciences CollegeCollege of Arts, Humanities and Social Sciences
Credit level (Normal year taken)SCQF Level 10 (Year 4 Undergraduate) AvailabilityAvailable to all students
SCQF Credits20 ECTS Credits10
SummaryThis course covers the major conceptual, ethical, and legal questions concerning algorithmic bias.
Course description This course covers a range of questions about algorithmic bias. Questions that may be covered in a given semester include: What is bias? What are the sources of bias in algorithms? How can algorithmic bias be combatted? Which fairness metrics, which attempt to quantify fairness in algorithmic systems, genuinely capture fairness? What are the limits of such metrics? How does replacing human decision-makers with algorithms change our understanding of discrimination?
Entry Requirements (not applicable to Visiting Students)
Pre-requisites Students MUST have passed: Knowledge and Reality (PHIL08017) AND Mind, Matter and Language (PHIL08014)
Co-requisites
Prohibited Combinations Other requirements Students studying on MA Cognitive Science (Humanities) are permitted to take this course without having met the pre-requisite. However, it is advisable that students discuss the suitability of the course with their Student Adviser and the Course Organiser before enrolling
Information for Visiting Students
Pre-requisitesVisiting students should have completed at least 3 Philosophy courses at grade B or above. We will only consider University/College level courses. Applicants should note that, as with other popular courses, meeting the minimum does NOT guarantee admission. **Please note that Philosophy honours courses are in high demand, meaning that they have a very high number of students wishing to enrol in a very limited number of spaces.** These enrolments are managed strictly by the Visiting Student Office, in line with the quotas allocated by the department, and all enquiries to enrol in these courses must be made through the CAHSS Visiting Student Office. It is not appropriate for students to contact the department directly to request additional spaces.
High Demand Course? Yes
Course Delivery Information
Academic year 2025/26, Available to all students (SV1) Quota:  0
Course Start Semester 1
Timetable Timetable
Learning and Teaching activities (Further Info) Total Hours: 200 ( Seminar/Tutorial Hours 22, Programme Level Learning and Teaching Hours 4, Directed Learning and Independent Learning Hours 174 )
Assessment (Further Info) Written Exam 0 %, Coursework 100 %, Practical Exam 0 %
Additional Information (Assessment) Essay (75%)
Algorithmic bias analysis report (25%)
Feedback Not entered
No Exam Information
Learning Outcomes
On completion of this course, the student will be able to:
  1. Demonstrate knowledge of philosophical issues involved in algrotihmic bias
  2. Demonstrate familiarity with relevant examples of algorithmic systems
  3. Demonstrate ability to bring philosophical considerations to bear in practical contexts
  4. Demonstrate skills in research, analysis and argumentation
Reading List
A representative list of readings is:

Safiya Noble, Algorithms of oppression
Batya Friedman and Helen Nissenbaum, Bias in computer systems
Solon Barocas and Andrew Selbst, Big data's disparate impact
Anya Prince and Daniel Schwarcz, Proxy discrimination in the age of artificial intelligence and big data
Gabrielle Johnson, The hard proxy problem
Lily Hu, What is 'race' in algorithmic discrimination on the basis of race?
Thomas Kelly, Bias: a philosophical study
Brian Hedden, On statistical criteria of algorithmic fairness
Deborah Hellman, Big data and compounding injustice
Seth Lazar and Jake Stone, On the site of predictive injustice
Additional Information
Graduate Attributes and Skills Mindsets: Enquiry and lifelong learning; Outlook and engagement.
Skills: Personal and intellectual autonomy; Communication.
KeywordsNot entered
Contacts
Course organiserDr Milo Phillips-Brown
Tel:
Email: milopb@ed.ac.uk
Course secretaryMs Joan MacKenzie
Tel:
Email: jmacken8@ed.ac.uk
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