Module Code - Title:

IN8032 - RESPONSIBLE DIGITALIZATION, DATAFICATION AND ARTIFICIAL INTELLIGENCE

Year Last Offered:

N/A

Hours Per Week:

Lecture

2

Lab

0

Tutorial

1

Other

0

Private

7

Credits

6

Grading Type:

N

Prerequisite Modules:

Rationale and Purpose of the Module:

The related phenomena of digitalization, datafication and AI pose a series of challenges for contemporary business practice. The purpose of this module is to interrogate what constitutes responsibility in this new domain. The rationale resides with how business can implement these new technologies whilst protecting the interests of citizens, workers and consumers. The module will facilitate participants in creating conceptual frameworks that are based on risk governance and applied ethics. The module will privilege the idea of multidisciplinary work in this domain.

Syllabus:

AI Governance, social theory and digitalization, applied ethics in technology, risk methodologies around emerging technology, current use and future trajectory.

Learning Outcomes:

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

On successful completion of this module, students will be able to: 1. Demonstrate a better understand EU Regulatory instruments 2. Show insights into the ethical issues around AI implementation 3. Show an appreciation of soft governance mechanisms around data management 4. Discuss the implications and risk around surveillance and monitoring regimes 5. Demonstrate a critical awareness of the concepts of trust and trustworthiness and evidence development of a critical engagement with the important concepts of privacy, consent and autonomy 6. Critically evaluate and reflect on ideas related to gender in this domain 7. Distinguish between use of big data in private and public sectors 8. Problematise and critically inquire into technological future(s).

Affective (Attitudes and Values)

On successful completion of this module, students will be able to: be responsible and articulate around the subject matter

Psychomotor (Physical Skills)

On successful completion of this module, students will be able to:

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

Seminar and discussions - participants will learn from faculty and peers - content will be informed by current EC funded projects in this space. Set reading will be discussed in the classroom

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

Prime Texts:

Zuboff, S (2023) The age of surveillance capitalism. In Social theory re-wired , Routledge

Miller, T (2019) Explanation in artificial intelligence: Insights from the social sciences , Artificial intelligence, 267

Salles, A., Evers, K. and Farisco, M., (2020) Anthropomorphism in AI , AJOB neuroscience

D'IGNAZIO, C. & KLEIN, L. F (2020) Data Feminism , Cambridge, Massachusetts, The MIT Press.

MORI, M., MACDORMAN, K. F. & KAGEKI, N. (2012) The Uncanny Valley , IEEE Robotics & Automation

Other Relevant Texts:

Programme(s) in which this Module is Offered:

PHBUADTPA - BUSINESS ADMINISTRATION

Semester(s) Module is Offered:

Spring

Module Leader:

Martin.Mullins@ul.ie