IB9SY-15 Augmenting Knowledge Work with AI
Introductory description
This module aims to equip students with the theories and frameworks needed to successfully collaborate with AI in knowledge work. The module draws on leading research about human-AI collaboration to illuminate the benefits and drawbacks of predictive, generative, and agentic AI for individuals, organizations and society, preparing students to use AI responsibly and effectively in their careers. Learning is assessed in an individual essay that critically examines how a certain form of knowledge work can be augmented with AI.
Module aims
- Critically Analyse AI Technologies: The module aims to equip students to assess cutting-edge AI technologies, their strategic importance, industry impact, and adoption implications. Students will learn how to distinguish between predictive, generative, and agentic AI, and critically analyse the differences between AI and prior technological advancements.
- Develop Strategic AI Use Skills: The module will enable students to navigate the use of AI (predictive, generative, agentic) tools in their career through engaged augmentation by illuminating research-backed best practices, benefits and risks of AI use in knowledge work across accuracy, creativity, and persuasiveness, drawing on key frameworks from human-AI collaboration research. These skills are in high demand in organizations across industries.
- Foster Responsible AI Transformation in organizations: The module will prepare students to understand organizational benefits and risks of AI use and how to balance benefits (e.g., productivity gains from automation) with risks and societal implications (e.g., labour displacement, deskilling). Enable students to be critical actors in AI transformations in organizations.
Outline syllabus
This is an indicative module outline only to give an indication of the sort of topics that may be covered. Actual sessions held may differ.
The AI disruption: What is the changing nature of knowledge work with AI?
Automation vs. Augmentation?
AI adoption in organizations: The hype vs. the current reality
Human and AI interaction: Three types of human- AI interactions: Centaurs, Cyborgs and Self automators.
Reciprocal learning of humans &AI: How both humans and machines learn in the joint knowledge work
Responsible AI: What does “Human in the loop” really means? who is accountable for mistakes? What can we do as
professionals?
Generating new knowledge and innovating with AI
Context work and context engineering: Decontextualizing and recontextualizing
AI in teams: AI the cybernetic teammate
Reimagining knowledge work and possible futures of knowledge work with AI and Agents
Learning outcomes
By the end of the module, students should be able to:
- Demonstrate advanced understanding of theoretical and empirical approaches to working and collaborating with AI in knowledge work
- Develop (ideate and communicate) and critically evaluate the potential of AI to augment and transform knowledge work
- Analyse real-world case studies to identify opportunities and challenges in leveraging AI technologies for strategic business goals, while also recognising societal implications
Indicative reading list
Reading lists can be found in Talis
Research element
Apply appropriate theories, concepts and research to an AI augmentation idea.
Subject specific skills
Propose an AI augmentation model for a form of knowledge work, demonstrating its benefits, risks, and societal implications.
Apply appropriate theories, concepts and research to an AI augmentation idea. Demonstrate developed capabilities to work with AI in different modes, as a potential 'peer' or 'assistant' or 'tool'.
Transferable skills
Demonstrate communication skills
Demonstrate critical thinking skills
Demonstrate problem solving skills
Study time
| Type | Required |
|---|---|
| Lectures | 9 sessions of 1 hour (6%) |
| Other activity | 18 hours (12%) |
| Private study | 49 hours (33%) |
| Assessment | 74 hours (49%) |
| Total | 150 hours |
Private study description
Private study to include preparation for lectures and workshops and own reading
Other activity description
9 x 2 hrs F2F workshops
Costs
No further costs have been identified for this module.
You do not need to pass all assessment components to pass the module.
Assessment group A
| Weighting | Study time | Eligible for self-certification | |
|---|---|---|---|
Assessment component |
|||
| Individual Assignment | 100% | 74 hours | Yes (extension) |
Reassessment component is the same |
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Feedback on assessment
via myWBS
There is currently no information about the courses for which this module is core or optional.