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CSC-10082 - Module Specification
School of Computer Science and Mathematics
Faculty of Natural Sciences

For academic year: 2026/27 Last Updated: 16 September 2026

CSC-10082 - Data Ethics, Governance and Professionalism
Coordinator: Baidaa Al-Bander
Lecture Time:
Level: Level 4
Credits: 30
Study Hours: 300
School Office: 01782 733075

Programme/Approved Electives for 2026/27

None

Available as a Free Standing Elective

No

Co-requisites

None

Prerequisites

None

Barred Combinations

None

Description for 2026/27

The rise of AI and Data Science and AI within society has been filled with potential but has also come with increasing risk and harms. This includes
risks to personal privacy and freedoms, impact of discriminatory algorithms due to algorithmic bias and online harms. As a result we see a
mixture of over-confidence in the value and accuracy of AI systems resulting in tech solutionism in juxtaposition to increasing criticism and lack of public trust. In response to this the need for ethically aligned design of AI and data science projects has grown. This module will outline the risks and harms associated with data science and AI by utilising a case study approach and will explore the body of regulation, governance
frameworks and techniques. This will provide the students the opportunity to develop the skills and knowledge required by employers for ethically aware data scientists.
It will help the students evaluate the digital services provided by service providers for accurate requirements gathering and professionalism.
Furthermore, It will help develop appropriate communication skills, study skills, and report writing.

Aims
This module will provide the students with an understanding of Data Ethics, Governance and Professionalism. They will explore relevant
regulations, governance frameworks and standards required for ethically aligned design and how these relate to different aspects of the data
science lifecycle. The students will apply this knowledge via techniques and tools that can be applied to areas such as data anonymisation,
debiasing, and fairness testing. It will also enable students to understand the basis and practice of professional software and systems engineering
as applicable to data science; to understand the fundamentals of requirements, evaluation, and professionalism; and to develop appropriate communication and study skills.

Intended Learning Outcomes

Evaluate the role of professional and ethical responsibilities in the development and deployment of data-driven technologies.: 1,2
Communicate ethical risks, governance concerns, and professional obligations clearly to both technical and non-technical
audiences.: 1,2
Explain key ethical principles in data science and AI, including fairness, accountability, transparency, and respect for privacy.: 1,2
Identify and apply relevant legal and regulatory frameworks (e.g. GDPR, Data Protection Act) to data collection, processing, and
sharing.: 1,2
Recognise common sources of bias in datasets and algorithms, and describe basic techniques for identifying and reducing bias.: 1,2
Articulate data governance principles, including data quality, anonymisation, and secure data handling practices.: 1,2

Study hours

28 Online Lectures
36 Active Practical Learning
200 Private Study
36 Completing Coursework

School Rules

None

Description of Module Assessment

1: Assignment weighted 50%
Case Study 1
The word count for this piece of work is 1000 words. Case Study 1 (Individual) Ethical Issues in Data Governance — Transparency, Accountability, and Compliance: In this case study, students will critically examine how data governance frameworks shape ethical practice in computing. The focus will be on transparency (making data use clear and accessible to stakeholders), accountability (ensuring responsibility for decisions and outcomes), and compliance (adhering to legal and regulatory standards such as GDPR). Students will be asked to: - Analyse a real‑world scenario where poor governance led to ethical concerns (e.g., unclear consent, hidden data sharing, or lack of oversight). - Evaluate how governance structures could have prevented or mitigated risks. - Propose improvements to policies, processes, or technical safeguards that enhance transparency and accountability. - Reflect on the balance between institutional compliance requirements and ethical responsibility to individuals and society. The case study will encourage students to connect theory to practice, demonstrating how governance failures can erode trust and how strong governance can support fairness, integrity, and sustainable digital innovation.

2: Assignment weighted 50%
Case Study 2
The word count for this piece of work is 1000 words. Case Study 2 (Individual) Ethical Challenges in Data Handling — Privacy, Consent, Bias, and Security: In this case study, students will critically evaluate the ethical implications of how data is collected, processed, and used. The focus will be on privacy (safeguarding personal information), consent (ensuring individuals understand and agree to data use), bias (preventing unfair or discriminatory outcomes in algorithms and analytics), and security (protecting data against breaches and misuse). Students will be asked to: - Analyse a scenario where poor data handling led to ethical concerns, such as breaches of privacy, inadequate consent mechanisms, or biased decision‑making. - Evaluate the risks posed by weak security practices or untested algorithms. - Propose strategies to strengthen ethical data handling, including technical safeguards, clearer consent processes, and bias‑mitigation techniques. - Reflect on how ethical failures in data handling can undermine trust in institutions and technology, and how proactive measures can restore confidence.

The University undertakes a continuous review of its teaching and research provision to ensure programmes are of a high quality and changes may be made to modules where it is necessary and reasonable to do so. Please be aware that minor changes to modules, such as a change to an individual assessment, can occur up until enrolment, although we endeavour to give you as much notice as possible of any changes. Details about the circumstance in which changes are made to programmes can be found in the Student Agreement, available at: https://www.keele.ac.uk/legalgovernancecompliance/governance/actcharterstatutesordinancesandregulations/studenttermsconditions/

Last Updated: 16 September 2026