Vladan Joler, Matteo Pasquinelli: The Nooscope Manifested: AI as Instrument of Knowledge Extractivism (2020)
Filed under essay | Tags: · algorithm, artificial intelligence, automation, data, knowledge, machine learning, statistics
“The Nooscope is a cartography of the limits of artificial intelligence, intended as a provocation to both computer science and the humanities. Any map is a partial perspective, a way to provoke debate. Similarly, this map is a manifesto — of AI dissidents.”
“The Nooscope is a visual manifesto of AI as instrument of knowledge extractivism. The Nooscope is also an experiment in academic publication and critical tools for AI studies. The large diagram and the essay can be browsed online or downloaded in PDF format and printed on a large scale.”
Publisher KIM research group, Karlsruhe University of Arts and Design, Karlsruhe, and Share Lab, Novi Sad, 1 May 2020
Diagram & Essay HTML
AI Now 2019 Report (2019)
Filed under report | Tags: · artificial intelligence, automation, data, employment, ethics, gender, governance, infrastructure, machine learning, policy, power, race, society
This report “examines new research on the risks and harms of AI, including its use by companies to aggressively manage and control workers, its climate impact, and the growing use of facial and affect recognition. We also look at the growing movements that are demanding a halt to risky and dangerous AI, and offer recommendations on what policymakers, advocates, and researchers can do to address these harms.”
By Kate Crawford, Roel Dobbe, Theodora Dryer, Genevieve Fried, Ben Green, Elizabeth Kaziunas, Amba Kak, Varoon Mathur, Erin McElroy, Andrea Nill Sánchez, Deborah Raji, Joy Lisi Rankin, Rashida Richardson, Jason Schultz, Sarah Myers West, and Meredith Whittaker
Publisher AI Now Institute, New York, 12 Dec 2019
Creative Commons BY-ND 4.0 International License
Sean Dockray: Performing Algorithms: Automation and Accident (2019)
Filed under thesis | Tags: · algorithm, art, automation, control society, generativity, governmentality, labour, lecture-performance, machine learning, neural networks
“Performing Algorithms: Automation and Accident investigates how artists might stage encounters with the algorithms driving our post-industrial, big-data-based, automatic society. Several important theories of this contemporary condition are discussed, including control societies, post-industrial societies, the automatic society, the cybernetic hypothesis, and algorithmic governmentality. These concepts are interwoven with histories of labour and automation, recent developments in machine learning and neural networks, and my own past work.
Through a series of expanded lecture performances that describe our algorithmic condition while setting it into motion, this research seeks to discover ways in which to advance new critical positions within a totalizing technical apparatus whose very design preempts it. The included creative works have been performed, exhibited, and published between 2014 and 2018. They are made available online through an artificially intelligent chatbot, a frequent figure in the research, which here extends the concerns of that research through to how the work is framed and presented.
The thesis focuses on both generative art and the lecture performance, which converge in performing algorithms but are generally not discussed in connection with one another. They emerged in parallel as artistic methods, however, at a time when management and computation were taking root in the workplace in the 1960s. Furthermore, as the Internet became widespread from the 1990s, generative art and the lecture performance each found renewed prominence.
With human language and gesture increasingly modelling itself on the language of computation and work constantly reshaped by the innovations of capital, this project identifies “not working” both in terms of the technological breakdown and also as a condition of labour under automation. A discussion of the first fatal accident involving a self-driving vehicle illustrates this dual condition. Shifting from glitch art’s preoccupation with provoking errors to a consideration of not working, this research proposes artistic strategies that learn to occupy rather than display the accident.”
Publisher Faculty of the Victorian College of the Arts and Melbourne Conservatorium of Music, The University of Melbourne, 2019