Short course
Artificial Intelligence for Complex

Become the expert on AI in your field with an interdisciplinary approach to AI. Learn from experts in data science, linguistics, law, technology, and policy on this groundbreaking new course.

This course is no longer running.

Our approach

Complex problems require interdisciplinary solutions. Answers won’t come from one subject or specialism. Learn how to tackle the issues that matter to you.

Why interdisciplinary?

“The power of interdisciplinarity is being able to take a way of seeing the world from one area, one that’s rich in academic excellence, and then being able to transport it and map it onto something else.”

Dr Haibo E

Formerly Deepmind

“A job like mine does not ask you only to be a public speaker, data analyst, project manager, writer, or team player, but all of those thing together.”

Hassan Dalmuji

Senior Advisor, WHO

“The interesting thing about setting up a business is that it’s a series of problem-solving. What you need is an ability to focus in on a problem, pull back out, and connect the dots across the space.”

Richard Reed

Co-founder, Innocent Drinks

programme overview
Programme overview

AI is inherently interdisciplinary, but most organisations are not. This course offers a space to learn developments in the field and understand the big picture. Learners will be taught an interdisciplinary approach to AI from experts in data science, linguistics, law, technology history and policy.

Critically assess AI tools & technologies.
Develop perspectives relevant to your field.
Recognise and develop a working knowledge of AI.
Identify AI threshold concepts.
Become the organisational expert on AI.
Learning Outcomes

Develop a working knowledge of AI and communicate effectively with engineers, experts, data scientists, and leadership.

Your interdisciplinary faculty
Kestral Gaian
Faculty / Head of Digital

An author and established polymath, Kestral joined LIS after stints at tech titans like Microsoft and Twilio. An expert in how humans and computers interact, their interdisciplinary approach to technology is an essential part of building a nuanced response to the new world of AI.

Emma Ahmed-Rengers

Before joining LIS, Emma was a Lecturer in Law and Data Science at the University of Birmingham. She holds a Master of Law (LLM) from the University of Cambridge, and a BSc in Politics, Psychology, Law and Economics (PPLE) from the University of Amsterdam.

James Carney

James combines methods from machine learning, experimental psychology, and linguistics to create programmes which are both intellectually challenging and instrumentally useful; including what organisations can learn from fictional narrative.

Amelia Peterson
Faculty / Head of Teaching

Amelia is a social scientist with a background in policy and consulting.  Prior to LIS, Amelia taught courses on education policy and research methods at LSE. She received her PhD from Harvard and her BA from Oxford.

A non-technical professional.
Project or product managers.
Team leads who want to develop their knowledge of AI.
Anyone looking to become an organisational expert in AI.
Life-long learners who are looking for intellectual stimulation.
About you

This course has been designed for a non-technical audience.