AI, Digital and Innovation Policy (996N1)
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AI, Digital and Innovation Policy
Module 996N1
Module details for 2026/27.
15 credits
FHEQ Level 7 (Masters)
Module Outline
This module examines industrial and innovation policies for managing radical technical change, with a specific focus on Artificial Intelligence. It frames the aims, rationale and tools of industrial and innovation policy, recognising that industrial development and competitiveness are greatly affected by policy actions at multiple levels, from local to international. It explores how governments create innovation incentives, address sectoral and spatial polarisation, and navigate global trade contexts. It places particular focus on AI and digital technologies, using concepts from innovation studies. The module combines both historical and forward-looking insights to identify commonalities and differences among radical changes and their implications for energy, information and goods and services production and distribution. Seminars critically discuss policy development, rationale and limitations in emerging and developing countries.
Module learning outcomes
Critically analyse the theoretical foundations and practical implications of industrial and innovation policy responses to radical technological change.
Evaluate the effectiveness of industrial and innovation policy interventions across different institutional, sectoral and developmental contexts.
Synthesise understanding of how radical technologies reshape economic and social systems, institutions and labour markets.
Critically evaluate policy trade-offs in governing radical innovation and formulate evidence-based policy recommendations.
| Type | Timing | Weighting |
|---|---|---|
| Coursework | 30.00% | |
| Coursework components. Weighted as shown below. | ||
| Group Presentation | T2 Week 11 | 100.00% |
| Computer Based Exam | Semester 2 Assessment | 70.00% |
Timing
Submission deadlines may vary for different types of assignment/groups of students.
Weighting
Coursework components (if listed) total 100% of the overall coursework weighting value.
| Term | Method | Duration | Week pattern |
|---|---|---|---|
| Spring Semester | Seminar | 2 hours | 01010101010 |
| Spring Semester | Lecture | 2 hours | 11111111111 |
How to read the week pattern
The numbers indicate the weeks of the term and how many events take place each week.
Dr Xiangming Tao
Convenor, Assess convenor
/profiles/559903
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