Module Specifications
Academic Year 2026 - 2027
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
Description This module aims to provide a flexible and grounded introduction to key questions related to contemporary and emerging Generative Artificial Intelligence (GenAI) for first year undergraduate students in the disciplinary areas within the Faculty of Humanities & Social Sciences at DCU. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
Learning Outcomes 1. Trace the historical evolution of Artificial Intelligence, situating the emergence of Generative AI within the broader trajectory of computational history and HSS discourse. 2. Explain the fundamental conceptual mechanisms of GenAI, such as Large Language Models (LLMs) and diffusion models, without requiring a deep technical background. 3. Analyse the relationship between GenAI and data, specifically focusing on the social, cultural, and political implications of data harvesting, representation, and algorithmic bias. 4. Critique the ethical dimensions of AI development, including labor practices, environmental impact, and the potential for reinforcing systemic inequalities. 5. Interrogate the shifting nature of truth, authenticity, and authority in a digital landscape increasingly mediated by synthetic media. 6. Evaluate philosophical questions regarding agency, creativity, and "the human" through the lens of machine-generated content and automated reasoning. 7. Identify and discuss emerging global regulatory frameworks (such as copyright law and AI safety governance) and their impact on civil society. 8. Assess the socio-economic implications of GenAI, particularly regarding the future of work, information ecosystems, and democratic processes. 9. Synthesise the specific opportunities and disruptions posed by GenAI within your primary field of study. 10. Formulate a reflexive stance on the use of AI tools in academic practice, balancing technological knowledge with intellectual integrity. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
All module information is indicative and subject to change. For further information,students are advised to refer to the University's Marks and Standards and Programme Specific Regulations at: http://www.dcu.ie/registry/examinations/index.shtml |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
Indicative Content and Learning Activities
Module Overview, Framing the impacts of GenAI Video and text elements on Loop, setting out the module aims and context, introducing lecturers. This first week doesn’t have an assessed element, but incorporates a practice quiz and serves to introduce how the module will be mediated and assessed. Expected engagement: 30-60 mins History of Artificial Intelligence Systems - Data & Decision-making Video lecture, readings and resources on Loop. This week addresses some initial jargon-busting and familiarisation with key concepts in the AI space - fundamentals of computing architectures, why machine learning and ANNs are different, key concepts and figures in the development of the discipline within Computer Science and key effects of earlier AI developments for society. Recommender systems and algorithms are introduced and connected with our use of the web, social media, etc. Concepts of data-gathering, data privacy and surveillance capitalism are introduced. Generative AI - Contemporary Tools & Tech Video lecture, readings and resources on Loop. This week builds directly on the previous content to distinguish the current generations of Large Language Models and other Transformer architectures from prior machine learning and broader AI. The emergence of the GPT, its relationship with Google Labs and OpenAI, and the connections to key figures in the contemporary GenAI space will be explored. Students will be able to understand and distinguish models and platforms. Philosophy of Thought - Can GenAI reason? Video lecture, readings and resources on Loop. This week provides a broad introduction to epistemology and philosophy of mind, to equip students to critically examine common tropes that GenAI is thinking or is creative in a human sense. This unit is placed after the historical and technological framing of GenAI’s emergence in general to allow a specific focus on how LLM Reasoning Models work and how this differs from human cognition. Accuracy & Hallucination - Why does GenAI make mistakes? Video lecture, readings and resources on Loop. The last week of the module’s first half is designed to allow the prior learning on GenAI mechanisms and concepts to inform a solid critical understanding of the built-in nature of hallucination in such architectures. This provides key insights that can equip students to critically question AI outputs by understanding and observing their inaccuracies. Beyond LLMs - Image, Audio, Video, and other AI models Video lecture, readings and resources on Loop. Returning after Reading Week, the second half of semester commences with a focus beyond LLMs to the range and function of diffusion models and other contemporary GenAI technologies associated with media formats like images, video, music, etc. Crucially, this unit re-engages with earlier topics and draws in critical perspectives on how data was/is used in the training of these models as well as framing social harms associated with misuse - e.g. deepfakes, CSAM, etc. Alignment & Ethics of AI - Exploring Societal Consequences Video lecture, readings and resources on Loop. Having begun to address the negative consequences of GenAI misuse in the prior unit, this week is fully focussed on the questions of AI Alignment, providing a brief history of the attempts to work on this issue, detail of key figures and experiments, and critical questions about safe use. Extending the exploration of AI Externalities, the unit also discusses ethical concerns about environmental impact and labour effects. Technology & Power - Monopolies, Control, and the Politics of AI Video lecture, readings and resources on Loop. Developing from the prior week’s critical thinking topics, this unit introduces questions of organisational control of AI, including recent history of tech monopolies, concerns about manufacturing and location of associated hardware, as well as diplomacy and politics related to AI control. Specifically, this unit provides insights on mis- and dis-information, political radicalisation, and democratic erosion related to AI. Regulation of AI - Data Protection, EU AI Act, Safe uses. Video lecture, readings and resources on Loop. Having explored the history, functionality, potential harms, social consequences, and spectrum of possible misuse, this unit focuses on critical questions of how GenAI can be regulated and how users, especially vulnerable users, may be safe-guarded. The unit provides foundational knowledge on the state of present EU legislation, as well as identifying other areas of emerging concern. | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
Indicative Reading List Books: None Articles: None | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
|
Other Resources None | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||