Data and AI

Our world is becoming entangled - so much of our consensus reality is being created by the software we hardly understand – financial markets where bots endlessly trade with other bots, social media algorithms that control what narrative we see, even AI deep fakes that make us doubt our own ears and eyes.

Kyung Jin Jeong has created a GAN that shows just how easy it is to take a photograph of any room and change it into an ‘attractive advertisement image’, calling to question perhaps this ease in which it is possible to transform images using machine learning.

As it becomes harder and harder to sort out where the human influence is in the process of AI, it is perhaps important to unpick and make legible how these processes work such as in Celeste Camilleri’s 'Datafields' which explores the complexity of dataset creation and the inherent biases that are part of the process through her online experience.

It is also important to remember, as Erik Lintunen does in his writing and project 'Cloudy Logic' how complex and brittle these systems are – how they are ‘precise, intricate and sensitive to contextual change’ – and how hard it discuss and explore the nuances of how they actually work without a background in digital technologies or data practises. But these projects, and the other work across IED, open up and build a vocabulary and language around artificial intelligence for other creative practitioners and the wider general public and present an alternative way of engaging with machine learning.

Anna Riddler