Art Practice Commons^™

Handouts Don’T Exist. Hustle Or You Don’T Eat., Conor Mcgarrigle Dr.

Articles

It is well established that AI has a bias problem; however, black-boxed machine learning systems render it difficult to even understand and visualize the nature and extent of the problem, let alone find solutions. This paper discusses an artistic research approach toward highlighting AI bias and explores the aesthetic potential of machine learning through a case study of an AI artwork called #RiseandGrind.The artist trained a recurrent neural network on a dataset extracted from Twitter hashtags (#Riseandgrind and #Hustle),which were selected to represent a specific filter bubble (embodied neoliberal precarity) in order to produce a biased AI that generates tweets …

Recipe For Disaster, Zac Travis

MFA Thesis Exhibit Catalogs

Today’s rapid advances in algorithmic processes are creating and generating predictions through common applications, including speech recognition, natural language (text) generation, search engine prediction, social media personalization, and product recommendations. These algorithmic processes rapidly sort through streams of computational calculations and personal digital footprints to predict, make decisions, translate, and attempt to mimic human cognitive function as closely as possible. This is known as machine learning.

The project Recipe for Disaster was developed by exploring automation in technology, specifically through the use of machine learning and recurrent neural networks. These algorithmic models feed on large amounts of data as a …