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Command-line interfaces (CLIs) share some linear and textual features with contemporary AI-driven chatbots. This commentary considers what a prompt is in both CLIs and generative AI, arguing that the former already highlights key features of processes of ideation and execution in computation.

Despite what tech CEOs might say, large language models are not smart in any recognizably human sense of the word.

297 likes, 1 comments - thegood_list on May 28, 2025: "What it’s like to bring AI into a human creative practice, with caution and curiosity. 🌊 For ISSUE 2 of The GOODStack, Curated by the wonderful @hbomb2025, we’ve invited Philip Maughan to write about his own relationship to AI in his practice. We urgently need voices from outside the tech industry to help shape the future of AI, Philip’s essay is one of those voices. A grounded, inquisitive take on what it means to engage with AI from a creative lens. Visit thegoodstack.substack.com to subscribe and let us know how you’re integrating AI with curiosity into your own practice. 🌀💙 — @pjmaughann is a writer and researcher working on creative and commercial projects based in London. His essays on food technology, simulations, fashion, and the evolution of humanity can be read at BBC Future, Noema, Tank, Kaleidoscope and elsewhere. He has worked with a range of brands and institutions on everything from campaign copy to speculative design, some of which include Prada, MoMA, Stone Island, Antikythera, Modem and Deloitte Ventures. #thegoodlist".

The Performance Paradox: Why Adolescents Online Activism Masks Their Conservative Reality

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Artificial intelligence (AI) is often discussed as something extraordinary, a dream—or a nightmare—that awakens metaphysical questions on human life. Yet far from a distant technology of the future, the true power of AI lies in its subtle revolution of ordinary life.

Before we begin, I want you to consume this painting.

We are seeing a generation of tools built without critically rethinking the purposes they are meant to serve or their role in the broader world. Could we do it differently?

Avoidance Machines, Part 2

An investigation into how AI is enriching a powerful few by dispossessing communities that have been dispossessed before.

From disrupting Hollywood to contextualizing media.

Current research in “plural alignment” concentrates on making AI models amenable to diverse human values. But plurality is not simply a safeguard against bias or an engine of efficiency: it’s a key ingredient for intelligence itself.

By Brian Merchant In This Article Introduction OpenAI and the Generative AI Boom Silicon Valley Mythology, Distilled and Accelerated From “Safe AI” to AGI — and the Hype-Led Business Model Genesis Marketing AGI, Shipping Commercial AI The Dream of AGI and the Fully Automated Organization Acknowledgments Download the full report here INTRODUCTION In the spring of […]

"I'm trying to find holiday gifts for my sisters. I open a bunch of tabs, I want my wife's advice." That's Browser Company CEO, Josh Miller, in his

How to Fight Big Tech's Hype and Create the Future We Want

This working paper is dedicated to artistic positions that critically deal with ‘artificial intelli- gence’ and automated pattern recognition through algorithms. Using a series of examples, it shows the social struggles that results from the distortions of bias and how artists react to it. Building on analyses by Harun Farocki and Hito Steyerl, projects by Adam Harvey and Jules LaPlace, Zach Blas and Jemima Wyman, Elisa Giardina Papa, Francis Hunger and Flupke, Erika Scourti, Mimi Onuoha, Nora Al-Badri, and Jan Nikolai Nelles are presented.

Nature - A review of the literature on artificial intelligence systems to examine openness reveals that open AI systems are actually closed, as they are highly dependent on the resources of a few...

Over the past twenty years, social movements from DREAMers and the Movement for Black Lives, to queer and trans resistance, and domestic worker organizing, have helped tell a new story of America—an inclusive vision of our society that has galvanized a new and newly empowered generation. This achievement was no accident: movement leaders have honed communications techniques, political messages, and storytelling strategies in a new struggle for narrative power. Until now, these efforts have largely been piecemeal and disconnected from one another.

This briefing is intended to help people with a responsibility for AI projects understand the considerations around their direct negative environmental impact arising from AI.

For all the promise and dangers of AI, computers plainly can’t think. To think is to resist – something no machine does

Price: 20€Language: English (un)real data ☁️ – (🧊)real effects explores the inherent ambiguity of data as an opportunity to not only describe the world but strategically intervene in it. Is it possible to create specific real-world outcomes by modifying our data streams? Can we intentionally produce data to interact with an algorithmic environment that is […]

Remarks delivered in response to a question from students in Frank Shephard’s Algorithmic Sublime class at the New School for Social Research, New York City, on November 8, 2024.

Rethink Design – A vocabulary for designing with AI addresses the question of how designers can engage with AI. The book presents 17 terms that were developed through inquiries into, and explorations of, designing and living with massively interconnected, potentially autonomous, and seemingly intelligent technologies. Unlike older technologies, these do not wait for human action but engage the world proactively, making decisions, communicating, and sharing data at speeds and scales that challenge comprehension. As such they destabilise and undermine boundaries, often with disregard to moral imperatives, and reconfigure not only the material world but also our relationships with it, with each other, and with ourselves. The terms are organised into 5 sections, each oriented by a key question: How will we craft inclusive human-algorithm relations?, How will we design AI systems that benefit people and the planet?, How will we create equitable socio-economic models in the digital society?, How will we enable public deliberation on data and algorithms?, and How will we prototype responsible data-driven design practices? Taken together the terms provide a sense-making instrument, a map for navigating flexibly a complex, emergent terrain. Reflecting and responding to the dynamism of the field, the book aims to be agile and accessible, offering not the final word but a brief, critical and creative introduction – a set of complementary vistas, entry points, and insights.

OpenAI’s chatbot offers paraphrases, whereas Google offers quotes. Which do we prefer?