Lily McCraith


Index
+++++
  1. Becoming-with Proteus 
  2. AI Pedagogies
  3. Master Pondkeeper Digital Twin
  4. The All Rivers and Species Act
  5. DIY LIDAR
  6. Potential Energies
  7. Lost Notes
  8. Soft//Quest

Archive
2017-2021
  1. We go in a circle and end up writing a book residency
  2. Pre-enacting Predictions
  3. Knowledges of Novichok
  4. Cold Water Club
  5. Midge Press

Mark

AI Pedagogies // AI School


Research project, publication and workshops
AI Who’s Looking After Me? Science Gallery London 2023
Commissioned by Science Gallery & Kings College London



https://london.sciencegallery.com/toolkit-area/teaching-ai
           
AI PEDAGOGIES is a critical look at how we teach AI.

‘How we teach AI’ in both senses of the phrase: how we train the AIs themselves, and how we train those who will interface with them: engineers, consumers, researchers and ‘decision makers’.

What datasets are used to nurture these technologies? How are certain pedagogies and certain biases algorithmically encoded within systems? Who gets to design the curricula AIs learn from? And how are the curricula of those who go on to teach AI shaped? How is AI taught in learning environments, and how does this in turn feed back into the teaching of AI?

We believe this to be a critical space of enquiry which requires urgent attention and solidification in academic, public and technical discourses.

Through conversations with a wide range of King’s College London researchers exploring AI through the lens of philosophy, computer science, ethics, medicine and digital humanities, Teaching AI offers a handbook of structured experiences: sets of instructions which explore alternative lessons for teaching AI.






Mark