Module Code - Title:

IN6062 - DATA GOVERNANCE AND ETHICS

Year Last Offered:

2023/4

Hours Per Week:

Lecture

2

Lab

1

Tutorial

0

Other

3

Private

4

Credits

6

Grading Type:

N

Prerequisite Modules:

Rationale and Purpose of the Module:

This module aims to support the MSc in Business Analytics by providing a conceptual framework relating to ethics, and governance, that informs data analytics activities and research. Such frameworks are now standardised across international Data science, Business Analytics research programs. For such reasons, the module aims to build upon this rationale and provide a unique component informed by the established data ethics research, and governance research group in the KBS. The use of personal data in contexts of analytics poses serious ethical and legal questions in terms of inputs and outputs. The purpose of the module is to frame data analytics technologies as technologies that need to be developed in parallel to frameworks that are informed by ethics and governance.

Syllabus:

The module will use examples of data analytics products that present ethical tensions, such as face recognition algorithms, consumer media platforms (Facebook, Spotify, Netflix, Amazon), cloud-based services (IBM Watson, personal assistant's; Siri, Alexa and Cortona) and autonomous vehicles to interrogate how risk and governance metrics are dependent upon informed accurate conceptual frameworks. 1. The Data Society 2. Data Business and Revenue 3. Data Governance 4. Data Ethics 5. Defining the Key Concepts 6. The Ethical Framework of Principlism 7. Privacy 8. Bias

Learning Outcomes:

Cognitive (Knowledge, Understanding, Application, Analysis, Evaluation, Synthesis)

1. Identify the fundamental principles of key regulatory data/privacy regimes such as the GDPR, privacy, privacy by design, data commodification. 2. Conceptualise the challenges relating to data governance. 3. Evaluate the utility of ethical theories in the context of business analytics. 4. Demonstrate and ability to interrogate the ethical contexts of data analytics technologies. 5. Critically evaluate the concepts of data, privacy, bias and governance to support decision-making.

Affective (Attitudes and Values)

1. Appreciate the possible challenges in developing informed and accurate conceptual understanding of governance and ethics. 2. Show an awareness of the core concepts of privacy, ethics and governance. 3. Value a more informed, nuanced and pragmatic understanding of the many societal, ethical and legal challenges that data analytics innovation presents.

Psychomotor (Physical Skills)

N/A

How the Module will be Taught and what will be the Learning Experiences of the Students:

The module will be delivered using a blended learning approach using on-line lectures, labs and tutorials. The module content is very much in line with the graduate attribute of "responsibility" as key privacy, ethical and governance issues are explored.

Research Findings Incorporated in to the Syllabus (If Relevant):

Prime Texts:

Floridi, L (2009) Network ethics: information and business ethics in a networked society , Journal of Business Ethics 90: 649-659

Richterich, A (2018) The big data agenda¿: data ethics and critical data studies , London: University of Westminster Press.

Other Relevant Texts:

Lupton D (2016) Digital risk society. In: Burgess A, Alemanno A and Zinn J (eds.) The Routledge handbook of risk studies. , Routledge

Programme(s) in which this Module is Offered:

Semester - Year to be First Offered:

Module Leader:

martin.cunneen@ul.ie