570100 Data Ethics and Regulation
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Subject handbook information prior to 2021 is available in the Archives.
Credit points: 6 cp
Result type: Grade and marks
Requisite(s): 240729 Digital Marketing Today AND 240710 Digital Consumer Behaviour AND 240715 Data-Driven Marketing AND 570101 Branding in the Digital World
These requisites may not apply to students in certain courses.
There are course requisites for this subject. See access conditions.
This subject focuses on the regulation and ethics of data practices in the digital environment. Students gain a deeper appreciation of the moral and ethical foundations of privacy, security and accountability and apply them to topics such as the ethics and regulation of data collection activities, algorithmic accountability and the biases inherent in data analytic tools.
Subject learning objectives (SLOs)
|a.||Distinguish between the characteristics and significance of ethics versus regulation|
|b.||Analyse the ethical considerations that have arisen from the wide scale collection and processing of data from and about individuals and social groups|
|c.||Compare national and international data regulation|
|d.||Apply knowledge of ethics and regulation to understand the impact on organisations, individuals and society|
Contribution to the development of graduate attributes
This subject engages with the following Program Intended Learning Outcomes (PLOs) which are tailored to the Graduate Attributes set for all graduates of the UTS Business School’s Master of Business Analytics:
Convey information clearly and fluently in written and verbal form appropriate for the problem, data and stakeholders (3.1)
Interact with colleagues and stakeholders to work effectively towards agreed outcomes (3.2). This PLO is met in class activities related to the fifth criterion in Assessment 1: Clarity and creativity of the infographic and relevance to the content of the article. Peer collaboration takes place to inform development of individually submitted work.
Demonstrate understanding of principles of sustainability, ethical and social responsibility as well as Indigenous values relating to professional practice in data analytics (4.1)
Demonstrate technical and adaptive skills in data analytics relevant to business contexts (5.1)
Teaching and learning strategies
This unit is made up of three modules delivered online over six weeks. Students work through each 2-week module at their own pace and momentum is maintained through weekly interactive activity attached to each theme and/or concept within the modules. Over the six weeks there will be three synchronous one hour online synchronous interactive sessions that discuss the module, and provide opportunities for task-based group activity, discussion and Q & A sessions (broken up into 15min segments).
Within each online module, content will be delivered through a mixture of short video presentations, interactive worksheets, quizzes/ questionnaires and short summary/comprehension/annotation exercises for selected readings and concepts using an online UTS site (Canvas’) ‘essay’ feature. These interactive elements form the basis of weekly online discussions which are moderated by teaching staff over the six weeks.
Module 1: Key concepts. In the first module students are introduced to key concepts and definitions across the two main areas of the subject. Module one covers two key questions: (1) What is data, why is it valuable and how is “datafication” related to processes that turn data into information, knowledge and economic value. This part of the module encourages students to build a more nuanced understanding of what different types of data there are, what different forms they can take and what they can and can’t do for organisations, institutions, society and individuals; (2) What ethical precepts guide the way we might think about good data stewardship? Here students are introduced to some simple interpretations of different Western ethical traditions (utilitarianism, social contract, deontology) and make sense of them in light of current data-driven practices, problems and opportunities. This insight is then used to interpret and unpack various ethical and regulatory frameworks covered in the second module.
Module 2: Frameworks. In the second module, students are introduced to a number of legal and regulatory frameworks that govern contemporary data stewardship practice. The second module casts a wide net across the regulatory landscape covering areas including consumer rights, health, geospatial data standards, intellectual property and licencing of datasets, metadata/quality standards, Freedom of Information (FOI), open data and the data sovereignty of indigenous and minority groups. Students also examine the role of different regulatory bodies and the channels of recourse available to both consumers and institutions when there are instances of data harms or malpractice.
Module 3: Case Studies. In the third module, students are presented with a list of case studies from which they can choose and explore areas/industries/problems based on their own interests. This provides a more individualised way of consolidating learnings from modules one and two
Assessment task 1: Understanding and Situating Key Concepts in Data, Regulation, Ethics
a, b, c and d
Part 1: 250 words
Part 2: 1000 words
|Criteria linkages:|| |
Assessment task 2: Analysis of Case Study
a, b, c and d
|Criteria linkages:|| |
No minimum requirements