DTS 3182 units300 LevelFirst Semester

Ethics and Legal Issues in Data Science

B.Sc. Data Science, University of Uyo

DTS 318 (Ethics and Legal Issues in Data Science) is a 2-unit, 300 Level course taught in the First Semester at the University of Uyo, Akwa Ibom State, Nigeria.

The obligations that come with holding and modelling data about people: privacy law, consent, algorithmic fairness, transparency and accountability. The course that determines whether your technical skill does good or harm.

On Areté, DTS 318 comes with

  • 3 recommended textbooks
  • an AI tutor that has read this course’s outline and notes
Sign in to study DTS 318

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Course outline

  1. 01Ethical frameworks applied to data: consequentialist, deontological and virtue perspectives
  2. 02Privacy: informational self-determination, consent, purpose limitation and data minimisation
  3. 03Anonymisation, pseudonymisation and re-identification risk; k-anonymity and differential privacy in outline
  4. 04Data protection law: the Nigeria Data Protection Act, the NDPR, and the GDPR as a comparator
  5. 05Rights of data subjects: access, rectification, erasure, portability and objection
  6. 06Algorithmic bias and fairness: sources of bias, fairness metrics, and their trade-offs
  7. 07Transparency, explainability and the right to an explanation; black-box models in high-stakes decisions
  8. 08Accountability, auditing, and the governance of automated decision-making
  9. 09Professional codes of conduct and case studies of data science failures

Recommended textbooks

  • Weapons of Math Destruction — Cathy O'Neil

    The essential account of how models cause real-world harm

  • Ethics and Data Science — Loukides, Mason & Patil

    Short, free, and practical on day-to-day decisions

  • Fairness and Machine Learning — Barocas, Hardt & Narayanan

    Free at fairmlbook.org; the rigorous treatment of fairness metrics

How to pass DTS 318

  • Know the Nigeria Data Protection Act and the NDPR specifically — Nigerian law is what you are examined on and what will actually govern your work
  • Learn why the different fairness metrics are mathematically incompatible; "just make it fair" is not an available option and examiners want you to know that
  • Prepare three real case studies (e.g. COMPAS, a credit-scoring case, a facial-recognition case) in enough detail to analyse rather than merely name
  • This is the course whose content you will most often actually need after graduation — treat it as professional training, not a compliance box

DTS 318 — questions and answers

What is DTS 318 at the University of Uyo?
DTS 318 (Ethics and Legal Issues in Data Science) is a 2-unit, 300 Level course taught in the First Semester at the University of Uyo, Akwa Ibom State, Nigeria. The obligations that come with holding and modelling data about people: privacy law, consent, algorithmic fairness, transparency and accountability. The course that determines whether your technical skill does good or harm.
What topics are covered in DTS 318?
The DTS 318 outline covers 9 topics: Ethical frameworks applied to data: consequentialist, deontological and virtue perspectives; Privacy: informational self-determination, consent, purpose limitation and data minimisation; Anonymisation, pseudonymisation and re-identification risk; k-anonymity and differential privacy in outline; Data protection law: the Nigeria Data Protection Act, the NDPR, and the GDPR as a comparator; Rights of data subjects: access, rectification, erasure, portability and objection; Algorithmic bias and fairness: sources of bias, fairness metrics, and their trade-offs; Transparency, explainability and the right to an explanation; black-box models in high-stakes decisions; Accountability, auditing, and the governance of automated decision-making; Professional codes of conduct and case studies of data science failures.
What textbooks are recommended for DTS 318?
Recommended reading for DTS 318: Weapons of Math Destruction by Cathy O'Neil; Ethics and Data Science by Loukides, Mason & Patil; Fairness and Machine Learning by Barocas, Hardt & Narayanan.
How do I pass DTS 318?
Know the Nigeria Data Protection Act and the NDPR specifically — Nigerian law is what you are examined on and what will actually govern your work Learn why the different fairness metrics are mathematically incompatible; "just make it fair" is not an available option and examiners want you to know that Prepare three real case studies (e.g. COMPAS, a credit-scoring case, a facial-recognition case) in enough detail to analyse rather than merely name This is the course whose content you will most often actually need after graduation — treat it as professional training, not a compliance box
Where can I find DTS 318 lecture notes and past questions?
Areté (https://www.aretecyb.tech/courses/dts-318) carries 3 recommended textbooks for DTS 318, plus an AI tutor that has read the outline. It is free for University of Uyo students — sign in with your email, no password.

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