AI: Robot Overlord, Replacement or Colleague?

AI, or Artificial Intelligence, plays an increasingly important role in our modern world due to its transformative impact across various sectors.

The ‘AI: Robot Overlord, Replacement or Colleague’ unit explores the science behing the headlines, the mechanisms of machine learning algorithms, AI benefits, implications and ethics.

It’s an undergraduate unit available to all students at The University of Manchester across disciplines and faculties. It’s delivered entirely online following an Agile-inspired pedagogical framework, where learners explore AI concepts through real-world case studies, interviews with experts, cross-discipline debates, group discussions, forums, etc.


By completing this unit, learners work together to develop informed opinions on the complexities of AI in our society, explore the strengths and opportunities of current AI technologies, and most importantly its weaknesses and limitations. Learners also investigate and reflect on the benefits of embedding AI in our society, and any potential threats that can bring on our future jobs and lives.

The unit consists of 10 learning modules and covers topics on:

  • Robots in our lives
  • Social ethics and dilemmas of AI
  • Learning from data, what is AI and what is ML?
  • AI a threat to the workforce?
  • AI effect on the society
  • AI and legal issues
  • AI ethics and governance
  • ML classification algorithms

Pedagogy model

Online learning

The module has been designed to be delivered entirely online through the Blackboard virtual learning environment. Blackboard contains all the learning modules, assessment information, and contact details. The unit has no powerpoint slides, instead we filmed case studies and recorded interviews with domain experts, collected relevant articles and created interactive and engaging activities for the learners.

Robot Overlord structure

Iterative and incremental learning

Learning is structured in an iterative manner where we introduce and revisit concepts to get a more in-depth knowledge through time.

Assessment has 3 components:

  • Group case studies - 30%
  • Individual essay - 50%
  • Individual project - 20%

The learners explore weekly group case studies to incrementally develop their critical evaluation skills in the form of pros and cons analysis, for and against analysis, mini-SWOT analysis, critical reflection, blog posts, etc. These weekly group assignments prepare learners for the end-of-unit bigger assessment, the individual essay, in which learners will conduct a longer in-depth SWOT (Strengths, Weaknesses, Opportunities, and Threats) analysis on the impact of AI.

More information on Agile-inspired iterative and incremental pedagogy models to deliver online group work can be found here: Moving to online teaching: models to deliver group work

Structured flexibility

To accommodate the interdisciplinary nature of our learners and their varied skillset, the Robot Overlord unit provides a structured flexibility where learners have the opportunity to tailor their learning. The academic team provides the tools and platforms and sets the structure of activities to guide the learning process, and the learners choose the topics and analysis to pave their future.

Every week, the group chooses an AI-relevant topic from a pre-defined list to explore and build their critical skills. At the end of the unit, each learner will pick a topic of their interest to conduct the in-depth SWOT analysis. In the past we had essays on a big variety of topics including: The impact of AI in healthcare, space exploration, fashion industry, religion, legal profession, self-driving cars, education, and many more.

At the end of the unit, every learner has an basic understanding of the impact of AI in the areas of business, law, health and manufacturing, and an in-depth understanding of the area of their choice.

Hands-on experience

The unit provides an introduction to computational thinking and explores the opportunities and limitations of AI algorithms. Learners get hands-on experience with popular classification machine learning algorithms through digital notebooks called Jupyter Notebooks.

More information on how the team uses Jupyter Notebooks in the students learning journey: Using interactive digital notebooks for bioscience and informatics education, Davies et al

Personal environment

We partnered with 3rd year computer science students to develop an in-house infrastructure to host Jupyter Notebooks. Each learner has its own personal environment with a copy of the notebooks and can access them through a web browser without having to install or download any software. This was vital given the wide range of backgrounds of our learners and their varied technical experience. Learners can interact with code and the provided datasets, and explore parameters and features. They can make and save changes, extract the notebooks, or create their own.

Robot Overlord on Medium

AI is a fast-paced domain, where a textbook will be outdated the minute will get published. Instead we use the Medium blogging site to collect relevant articles and papers.

Visit the Robot Overlord site on Medium here.