Various resources available on this website
People in Critical AI »
A list of awesome scholars in STS and Critical AI studies.
Concepts glossary »
Popular concepts, theories and ideas relevant to semiotics and science and technology studies, explained.
Films and documentaries
illustrating technosemiotic storytelling & analysis
References »
List of references used throughout the site.
Technology & Society 2023 reading list »
Technosemiotics: previous projects
Technosemiotics: AI & Society Nextbook »
New Media and Technosemiotics modules at Palacký University Olomouc »
Similar projects elsewhere
This is a list of projects and websites with similar aims and approaches to the critical study of AI, maintained and supported by other individuals and organizations elsewhere in the web.
AI myths
Myths, misconceptions & inaccuracies render AI systems opaque. Check out the resources we provide to tackle 8 of the most common myths about ‘artificial intelligence.’
The DAIR Institute
An interdisciplinary and globally distributed AI research institute.
AI Now Institute
The AI Now Institute at New York University is an interdisciplinary research center dedicated to understanding the social implications of artificial intelligence.
Algorithmic Justice League
Unmasking AI harms and biases
All Tech Is Human
A non-profit that is expanding & improving the Responsible Tech ecosystem so we can better tackle thorny tech & society issues.
Critical AI
A research network and a blog hosted by Rutgers University, and a new interdisciplinary journal published by Duke University Press
Histories of Artificial Intelligence: A Genealogy of Power
The Department of History and Philosophy of Science, and the Faculty of English of the University of Cambridge co-hosted a Mellon Sawyer Seminar entitled ‘Histories of AI: A Genealogy of Power’ from May 2020 to December 2021.
#NotMyRobots
Website that collects misleading / unrealistic / terrible pics of robots, bots, AI
Knowing Machines
Knowing Machines is a research project tracing the histories, practices, and politics of how machine learning systems are trained to interpret the world.