DSB202 Data Ethics and Society
To view more information for this unit, select Unit Outline from the list below. Please note the teaching period for which the Unit Outline is relevant.
| Unit code: | DSB202 |
|---|---|
| Prerequisite(s): | IFB104 and IFB105 |
| Credit points: | 12 |
| Timetable | Details in HiQ, if available |
| Availabilities |
|
| CSP student contribution | $1,192 |
| Domestic tuition unit fee | $4,704 |
| International unit fee | $5,640 |
Unit Outline: Semester 2 2026, Gardens Point, Internal
| Unit code: | DSB202 |
|---|---|
| Credit points: | 12 |
| Pre-requisite: | IFB104 and IFB105 |
| Coordinator: | Andrew Gibson | andrew.gibson@qut.edu.au |
Overview
In this unit you will explore ethical concerns associated with information and data, and develop a personal ethical stance which will help you approach data science tasks in an ethical way. The unit will investigate ethical problems that can arise in the use of information including issues associated with fairness and dignity, transparency and privacy, sovereignty and the law, governance and regulation, AI and emerging technologies, and balancing competing rights. The unit will use real examples from contemporary applications of data science and information technologies, analysing the practical effects of good versus poor ethical practices. You will use ethical theory to help identify your own personal stance on ethical issues, and in doing so shape your own ethical position and provide you with approaches that you can use in practice. Successful completion of this unit will prepare you to be able to face ethical issues in your future work and respond thoughtfully to them.
Learning Outcomes
On successful completion of this unit you will be able to:
- Critique data practices and information applications using a knowledge of ethical theory
- Develop ethical principles for effectively addressing social and ethical issues, including those relating to Australian Aboriginal and Torres Strait Islander peoples.
- Create an ethical stance towards data and information technology applications that is based on substantive ethical theory and accounts for contemporary social perspectives.
- Clearly articulate and defend a personal ethical stance and communicate how it may be applied in contemporary scenarios.
Content
Content will include:
- a selection of ethical philosophy and theory relevant to contemporary ethical issues in data science.
- ethical issues associated with GenAI and specific approaches to mitigation and governance of risks
- an ethical problem posed by a representative of industry or community organisation, development of response, and receiving feedback on your response.
- consideration of ethics and data governance issues specific to indigenous peoples, such as data sovereignty and data collection and analysis implications for cultural practices. In particular, issues related to Australian Aboriginal and Torres Strait Islander peoples will be examined.
- examining data ethics and governance issues related to social diversity and inclusion.
Learning Approaches
In this unit, you will learn by engaging in lectures and tutorials. The unit will take a problem based approach to learning, and will involve class discussion in both lectures and tutorials. You will be expected to actively participate in discussions and respectful debate related to the ethical and governance problems posed. Through the activities of the unit, you will be encouraged to develop your own personal ethical stance which is theoretically defendable and is compatible with relevant data governance law, policy and principles.
This unit is available to be studied on campus or online. You will be expected to spend an average of 12-15 hours per week studying the unit including scheduled classes, independent study, and competing assessment tasks.
Feedback on Learning and Assessment
You will receive feedback on your learning from the teaching team both formatively during tutorials and summatively as part of your assessment. Cohort level feedback will also be provided from industry or community organisation representative as part of your response to an ethical problem posed by industry. You will have the opportunity to engage in a formative peer review process to help improve your portfolio for assessment.
Assessment
Overview
A portfolio of work created through the unit will anchor the assessment for the unit, evidencing your understanding of the principles involved in taking an ethical stance with respect to contemporary data ethics issues. You will demonstrate the depth of understanding by defending your personal ethical stance in an interview. You will also demonstrate your understanding of the fundamental theoretical foundations presented in the unit in an ethical theory exam.
Unit Grading Scheme
7- point scale
Assessment Tasks
Assessment: Ethical development portfolio
A collection of material collated throughout the semester which demonstrate (a) your ongoing engagement with the learning tasks, including those related to GenAI; (b) evidence your engagement with an industry specific problem; and (c) contribute to the formulation of your personal ethics statement (also included in the portfolio).
This assessment is eligible for the 48-hour late submission period and assignment extensions.
Assessment: Interview
A mock job interview where you respond specifically to questions related to ethical issues in a nominated data science or information technology area of concern. Your response will be justified from the perspective of your personal ethical position together with theoretical approaches introduced throughout the unit.
Assessment: Ethical theory exam
A mix of multiple choice and short answer questions will assess your understanding of the theoretical content covered in the unit.
Threshold Assessment:
Your personal ethical stance needs to be strongly founded on well established ethical principles as articulated in ethical theory and philosophy. Therefore it is essential that you can demonstrate a satisfactory understanding of the main theories presented in the unit.
Academic Integrity
Academic integrity is a commitment to undertaking academic work and assessment in a manner that is ethical, fair, honest, respectful and accountable.
The Academic Integrity Policy sets out the range of conduct that can be a failure to maintain the standards of academic integrity. This includes, cheating in exams, plagiarism, self-plagiarism, collusion and contract cheating. It also includes providing fraudulent or altered documentation in support of an academic concession application, for example an assignment extension or a deferred exam.
You are encouraged to make use of QUT’s learning support services, resources and tools to assure the academic integrity of your assessment. This includes the use of text matching software that may be available to assist with self-assessing your academic integrity as part of the assessment submission process.
Breaching QUT’s Academic Integrity Policy or engaging in conduct that may defeat or compromise the purpose of assessment can lead to a finding of student misconduct (Code of Conduct – Student) and result in the imposition of penalties under the Management of Student Misconduct Policy, ranging from a grade reduction to exclusion from QUT.
Resources
There are no specific resources that need to be purchased to study this unit. All learning materials and resources will be made available via Canvas.
Course Learning Outcomes
This unit is designed to support your development of the following course/study area learning outcomes.DS01 Bachelor of Data Science
- Demonstrate a broad and coherent knowledge of the principles, concepts and techniques of the data science discipline, with depth of knowledge in at least one area developed through a major.
Relates to: Ethical development portfolio, Interview, Ethical theory exam - Demonstrate critical thinking and problem-solving skills, as well as adaptivity in applying learned techniques in new and unfamiliar contexts.
Relates to: Ethical development portfolio, Interview, Ethical theory exam - Communicate effectively in a variety of modes, to expert and non-expert audiences, including in a professional context.
Relates to: Interview - Apply awareness of the relevant social and ethical frameworks, including Australian indigenous perspectives, concerning the collection, storage and use of data in informing decision-making.
Relates to: Ethical development portfolio, Interview, Ethical theory exam
IN01 Bachelor of Information Technology
- Demonstrate a broad theoretical and technical knowledge of well-established and emerging IT disciplines, with in-depth knowledge in at least one specialist area aligned to multiple ICT professional roles.
Relates to: ULO1, Ethical theory exam - Critically analyse and conceptualise complex IT challenges and opportunities using modelling, abstraction, ideation and problem-solving to generate, evaluate and justify recommended solutions.
Relates to: ULO2, ULO3, Ethical development portfolio - Communicate professionally and effectively in written, verbal and visual formats to a diverse range of stakeholders, considering the audience and explaining complex ideas in a simple and understandable manner in a range of IT-related contexts.
Relates to: ULO4, Interview - Critically reflect, using a human-centric approach, on the social, cultural, ethical, privacy, legal, sustainability, and accessibility issues shaping the development and use of IT, including respecting the perspectives and knowledge systems of Aboriginal and Torres Strait Islander peoples, ensuring IT solutions empower and support people with disabilities, and fostering inclusive and equitable digital technologies that serve diverse communities.
Relates to: ULO2, ULO3, ULO4, Ethical development portfolio, Interview
Unit Outline: Semester 2 2026, Online
| Unit code: | DSB202 |
|---|---|
| Credit points: | 12 |
| Pre-requisite: | IFB104 and IFB105 |
Overview
In this unit you will explore ethical concerns associated with information and data, and develop a personal ethical stance which will help you approach data science tasks in an ethical way. The unit will investigate ethical problems that can arise in the use of information including issues associated with fairness and dignity, transparency and privacy, sovereignty and the law, governance and regulation, AI and emerging technologies, and balancing competing rights. The unit will use real examples from contemporary applications of data science and information technologies, analysing the practical effects of good versus poor ethical practices. You will use ethical theory to help identify your own personal stance on ethical issues, and in doing so shape your own ethical position and provide you with approaches that you can use in practice. Successful completion of this unit will prepare you to be able to face ethical issues in your future work and respond thoughtfully to them.
Learning Outcomes
On successful completion of this unit you will be able to:
- Critique data practices and information applications using a knowledge of ethical theory
- Develop ethical principles for effectively addressing social and ethical issues, including those relating to Australian Aboriginal and Torres Strait Islander peoples.
- Create an ethical stance towards data and information technology applications that is based on substantive ethical theory and accounts for contemporary social perspectives.
- Clearly articulate and defend a personal ethical stance and communicate how it may be applied in contemporary scenarios.
Content
Content will include:
- a selection of ethical philosophy and theory relevant to contemporary ethical issues in data science.
- ethical issues associated with GenAI and specific approaches to mitigation and governance of risks
- an ethical problem posed by a representative of industry or community organisation, development of response, and receiving feedback on your response.
- consideration of ethics and data governance issues specific to indigenous peoples, such as data sovereignty and data collection and analysis implications for cultural practices. In particular, issues related to Australian Aboriginal and Torres Strait Islander peoples will be examined.
- examining data ethics and governance issues related to social diversity and inclusion.
Learning Approaches
In this unit, you will learn by engaging in lectures and tutorials. The unit will take a problem based approach to learning, and will involve class discussion in both lectures and tutorials. You will be expected to actively participate in discussions and respectful debate related to the ethical and governance problems posed. Through the activities of the unit, you will be encouraged to develop your own personal ethical stance which is theoretically defendable and is compatible with relevant data governance law, policy and principles.
This unit is available to be studied on campus or online. You will be expected to spend an average of 12-15 hours per week studying the unit including scheduled classes, independent study, and competing assessment tasks.
Feedback on Learning and Assessment
You will receive feedback on your learning from the teaching team both formatively during tutorials and summatively as part of your assessment. Cohort level feedback will also be provided from industry or community organisation representative as part of your response to an ethical problem posed by industry. You will have the opportunity to engage in a formative peer review process to help improve your portfolio for assessment.
Assessment
Overview
A portfolio of work created through the unit will anchor the assessment for the unit, evidencing your understanding of the principles involved in taking an ethical stance with respect to contemporary data ethics issues. You will demonstrate the depth of understanding by defending your personal ethical stance in an interview. You will also demonstrate your understanding of the fundamental theoretical foundations presented in the unit in an ethical theory exam.
Unit Grading Scheme
7- point scale
Assessment Tasks
Assessment: Ethical development portfolio
A collection of material collated throughout the semester which demonstrate (a) your ongoing engagement with the learning tasks, including those related to GenAI; (b) evidence your engagement with an industry specific problem; and (c) contribute to the formulation of your personal ethics statement (also included in the portfolio).
This assessment is eligible for the 48-hour late submission period and assignment extensions.
Assessment: Interview
A mock job interview where you respond specifically to questions related to ethical issues in a nominated data science or information technology area of concern. Your response will be justified from the perspective of your personal ethical position together with theoretical approaches introduced throughout the unit.
Assessment: Ethical theory exam
A mix of multiple choice and short answer questions will assess your understanding of the theoretical content covered in the unit.
Threshold Assessment:
Your personal ethical stance needs to be strongly founded on well established ethical principles as articulated in ethical theory and philosophy. Therefore it is essential that you can demonstrate a satisfactory understanding of the main theories presented in the unit.
Academic Integrity
Academic integrity is a commitment to undertaking academic work and assessment in a manner that is ethical, fair, honest, respectful and accountable.
The Academic Integrity Policy sets out the range of conduct that can be a failure to maintain the standards of academic integrity. This includes, cheating in exams, plagiarism, self-plagiarism, collusion and contract cheating. It also includes providing fraudulent or altered documentation in support of an academic concession application, for example an assignment extension or a deferred exam.
You are encouraged to make use of QUT’s learning support services, resources and tools to assure the academic integrity of your assessment. This includes the use of text matching software that may be available to assist with self-assessing your academic integrity as part of the assessment submission process.
Breaching QUT’s Academic Integrity Policy or engaging in conduct that may defeat or compromise the purpose of assessment can lead to a finding of student misconduct (Code of Conduct – Student) and result in the imposition of penalties under the Management of Student Misconduct Policy, ranging from a grade reduction to exclusion from QUT.
Resources
There are no specific resources that need to be purchased to study this unit. All learning materials and resources will be made available via Canvas.
Course Learning Outcomes
This unit is designed to support your development of the following course/study area learning outcomes.DS01 Bachelor of Data Science
- Demonstrate a broad and coherent knowledge of the principles, concepts and techniques of the data science discipline, with depth of knowledge in at least one area developed through a major.
Relates to: Ethical development portfolio, Interview, Ethical theory exam - Demonstrate critical thinking and problem-solving skills, as well as adaptivity in applying learned techniques in new and unfamiliar contexts.
Relates to: Ethical development portfolio, Interview, Ethical theory exam - Communicate effectively in a variety of modes, to expert and non-expert audiences, including in a professional context.
Relates to: Interview - Apply awareness of the relevant social and ethical frameworks, including Australian indigenous perspectives, concerning the collection, storage and use of data in informing decision-making.
Relates to: Ethical development portfolio, Interview, Ethical theory exam
IN01 Bachelor of Information Technology
- Demonstrate a broad theoretical and technical knowledge of well-established and emerging IT disciplines, with in-depth knowledge in at least one specialist area aligned to multiple ICT professional roles.
Relates to: ULO1, Ethical theory exam - Critically analyse and conceptualise complex IT challenges and opportunities using modelling, abstraction, ideation and problem-solving to generate, evaluate and justify recommended solutions.
Relates to: ULO2, ULO3, Ethical development portfolio - Communicate professionally and effectively in written, verbal and visual formats to a diverse range of stakeholders, considering the audience and explaining complex ideas in a simple and understandable manner in a range of IT-related contexts.
Relates to: ULO4, Interview - Critically reflect, using a human-centric approach, on the social, cultural, ethical, privacy, legal, sustainability, and accessibility issues shaping the development and use of IT, including respecting the perspectives and knowledge systems of Aboriginal and Torres Strait Islander peoples, ensuring IT solutions empower and support people with disabilities, and fostering inclusive and equitable digital technologies that serve diverse communities.
Relates to: ULO2, ULO3, ULO4, Ethical development portfolio, Interview