Module overview
In this module you will examine the intersection of AI with technologically induced harms ‘techno harms’ such as extremism, discrimination, and mis and disinformation in the context of international criminal justice. You will explore AI’s dual role in both causing and combating these harms, as well as its potential for predicting future threats. Drawing from multiple disciplines, the module equips you with the tools to critically analyse AI’s impact on online harms and its use in prevention and mitigation strategies. Understanding AI-enabled cyber harms helps in developing effective countermeasures and policies, while also raising important ethical questions about surveillance, privacy, and civil liberties.
Aims and Objectives
Learning Outcomes
Learning Outcomes
Having successfully completed this module you will be able to:
- Evaluate the application of AI-focused theories and approaches to analyse real-life technoharms and predict future scenarios in criminal justice work.
- Reflect on the implications of AI for contemporary and future criminal justice themes across a broad time frame.
- Examine critically the impact of AI on the formation of online discourses and group identities relevant to criminal justice, and project future trends.
- Critically analyse current policies and laws on AI-related technoharms as a basis for developing feasible reforms and future-proofing strategies in criminal justice.
- Produce coherent and persuasive written arguments on AI, technoharms, and future threat assessment using a range of theoretical and empirical material.
- Understand the evolution of AI-driven technoharms and the role of legitimate actors in the criminal justice system in addressing current and future threats.
- Compare key theories and methodological approaches relating to AI, technoharms, and future threat assessment in criminal justice.
- Identify and analyse complex technoharms facilitated by AI, assessing their current and potential future impact on criminal justice processes.
- Apply advanced analytical tools to reveal and evaluate AI's role in underlying structures of current and emerging technoharms.
- Explain how AI-driven technoharms are developed and perpetuated by various actors and institutions, and how they might evolve in the future.
- Engage in the formation of interdisciplinary arguments about AI's use in online spaces within criminal justice contexts, including its application in future threat assessment.
Syllabus
Typically:
- Introduction to Module: AI, Techno Harms and Future Threat Assessment in Criminal Justice
- Theoretical Perspectives on AI and Social Harm: Present and Future Implications
- AI-driven Methodological Approaches in Criminal Justice and Threat Prediction
- AI and the Acceleration of Memetic Warfare: Current Implications and Future Scenarios for Law Enforcement
- AI and Cyberwarfare: From International Organised Crime to Cyberterrorism
- Machine Learning and Digital Propaganda: Evolving Challenges in Criminal Contexts
- AI-powered Extremism and Radicalisation Online: Trends and Future Projections
- Artificial Intelligence in Human Trafficking and Border Control: Current and Emerging Threats
- The relationship between AI, Video Gaming and Violent Extremism: The Current Landscape, Trends and Threats
- AI Tools for Disrupting, Preventing, and Predicting Online Harms
- Ethical Considerations of AI Use in Criminal Justice and Future Threat Assessment
- AI and Predictive Surveillance: Promises, Pitfalls, and Future Developments
- The Future of AI in Criminal Justice: Anticipating Opportunities and Challenges
Learning and Teaching
Teaching and learning methods
The programme employs a range of teaching and learning methods tailored to online delivery and the needs of working professionals. One of the primary methods used is asynchronous learning, where students can access materials on their own schedule. This includes multimedia resources - but not just video lectures, but also podcasts, animations, and interactive simulations; and reading materials like PDFs or e-books. These resources allow learners to engage with content at their own pace. In addition, discussion forums provide a space for students to ask questions and participate in debates with their peers without the need for everyone to be online at the same time. The asynchronous learning is complemented by synchronous components, such as webinars. These sessions, typically held via Microsoft Teams, give students the opportunity to interact with instructors in real-time, asking questions or participating in discussions. All of these methods are designed to accommodate different learning approaches and ensure that students can apply theoretical knowledge to practical scenarios relevant to their professional contexts. With a strong emphasis on self-paced learning, supported by ongoing instructor guidance.
| Type | Hours |
|---|---|
| Independent Study | 90 |
| Guided independent study | 34 |
| Online Course | 26 |
| Total study time | 150 |
Assessment
Summative
This is how we’ll formally assess what you have learned in this module.
| Method | Percentage contribution |
|---|---|
| Coursework | 100% |
Referral
This is how we’ll assess you if you don’t meet the criteria to pass this module.
| Method | Percentage contribution |
|---|---|
| Coursework | 100% |
Repeat
An internal repeat is where you take all of your modules again, including any you passed. An external repeat is where you only re-take the modules you failed.
| Method | Percentage contribution |
|---|---|
| Coursework | 100% |
Repeat Information
Repeat type: Internal & External