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Experiential AI is proposed as a new research agenda in which artists and scientists come together to dispel the mystery of algorithms and make their mechanisms vividly apparent. It addresses the challenge of finding novel ways of opening up the field of artificial intelligence to greater transparency and collaboration between human and machine. The hypothesis is that art can mediate between computer code and human comprehension to overcome the limitations of explanations in and for AI systems. Artists can make the boundaries of systems visible and offer novel ways to make the reasoning of AI transparent and decipherable. Beyond this, artistic practice can explore new configurations of humans and algorithms, mapping the terrain of inter-agencies between people and machines. This helps to viscerally understand the complex causal chains in environments with AI components, including questions about what data to collect or who to collect it about, how the algorithms are chosen, commissioned and configured or how humans are conditioned by their participation in algorithmic processes.

It’s difficult to predict the negative impacts of an idea or invention, but certain frameworks can help entrepreneurs see a little bit further.

Thoughts on prompts and search boxes

A new device allowed a paralyzed patient to "speak," spelling out full sentences in real-time with an error rate of about 8%.

Blog about survival in the world of technology and all this cyberpunk around

Onomatopee

While machine learning—computer programming designed for taxonomic patterning—offers useful insights into racism and racist behavior, a gap is present in the relationship between machine learning and its connection to the racial history of science and the Black lived experience.

A radical pedagogy notebook that parses the “experiments in study, collective learning, and unlearning” at JUNGE AKADEMIE’s AI Anarchies Autumn School.

# 32 - Generative AI: The rapid evolution of digital creation Labs Report © 2022 MediaMonks. All rights reserved. Any sharing of this information is wholeheartedly encouraged. This deck is probably outdated by the time we hit share

Unsurprisingly, the artistic and ethical shortcomings of AI image generators are tied to their dependence on capital and capitalism.

Voice assistants like Siri and Alexa display a pseudo-humanity that is heavily scripted by humans. What does that mean for our AI literacy?

This essay explore what infrastructures are needed to cultivate a more feminist, caring digital society.

Artists work for years on their portfolios but people can now make copycat images using programs like DALL-E, Stable Diffusion and Midjourney.

On Spurious Content and Visual Synonyms

The Datafication of a Kiss

A new project to identify sites and vocabularies of digital IDs and AI

Bas van de Poel, co-founder of hybrid design studio and think tank Modem, discusses how design can shape a better future using technology

This article explores the conditions and modalities under which a state can incur responsibility in relation to violations of international law involving milita

The algorithm can recreate both the object's geometry and material.

Machines as a complementary lens

Verso Books is the largest independent, radical publishing house in the English-speaking world.

Consumers need transparency about how such systems are used, says professor of linguistics Emily M Bender

The long read: From ancient Egyptian cubits to fitness tracker apps, humankind has long been seeking ever more ways to measure the world – and ourselves. But what is this doing to us?

Mutual learning has been explicitly stated as a core tenet in the canon of participatory design, socially engaged art and other community-oriented and -driven “making” processes. Yet, what is mutual learning and how does it concretize in the world?

Every dataset communicates a different perspective. When you shift your perspective, your conclusions can shift, too.