‘Don’t Put Your Head in the Sand’: Stars Are Quietly Inking Deals to License Their AI Doubles
In 2008, while working with Will Smith on the set of a film that never ended up getting made, Remington Scott had an epiphany. The visual effects director was watching Smith stand in a photogrammetry booth, with dozens of cameras capturing the actor’s facial features from every possible angle. “ ...
Robin Allenson on LinkedIn: 7 years ago, 1 man caused a nationwide shortage of radiologists. Here’s… | 57 comments
7 years ago, 1 man caused a nationwide shortage of radiologists. Here’s how: 👉 Professor Geoffrey Hinton said “we should stop training radiologists”… | 57 comments on LinkedIn
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Can’t lose what you never had: Claims about digital ownership and creation in the age of generative AI
Let’s say someone walks into an old-fashioned record store looking for the Bright Eyes song “False Advertising.” Upon finding and buying the album, she’d have little reason to fear that store employees might sneak into her house later and take it back from her. She’d also have no cause to think that the album was counterfeit and not by the band at all. Now let’s say instead that the same song inspires an artist to create a mural depicting the FTC’s greatest false ad cases, and the mural gets displayed in a local gallery. The artist might be surprised if the gallery later shuts its doors and refuses to return the mural . . . or if some other company secretly reuses bits of it to make something else.
PsyArXiv Preprints | Reclaiming AI as a theoretical tool for cognitive science
The idea that human cognition is, or can be understood as, a form of computation is a useful conceptual tool for cognitive science. It was a foundational assumption during the birth of cognitive science as a multidisciplinary field, with Artificial Intelligence (AI) as one of its contributing fields. One conception of AI in this context is as a provider of computational tools (frameworks, concepts, formalisms, models, proofs, simulations, etc.) that support theory building in cognitive science. The contemporary field of AI, however, has taken the theoretical possibility of explaining human cognition as a form of computation to imply the practical feasibility of realising human(-like or -level) cognition in factual computational systems; and, the field frames this realisation as a short-term inevitability. Yet, as we formally prove herein, creating systems with human(-like or -level) cognition is intrinsically computationally intractable. This means that any factual AI systems created in the short-run are at best decoys. When we think these systems capture something deep about ourselves and our thinking, we induce distorted and impoverished images of ourselves and our cognition. In other words, AI in current practice is deteriorating our theoretical understanding of cognition rather than advancing and enhancing it. The situation could be remediated by releasing the grip of the currently dominant view on AI and by returning to the idea of AI as a theoretical tool for cognitive science. In reclaiming this older idea of AI, however, it is important not to repeat conceptual mistakes of the past (and present) that brought us to where we are today.
85. Timnit Gebru Looks at Corporate AI and Sees a Lot of Bad Science - Initiative for Digital Public Infrastructure
Timnit Gebru is not just a pioneering critic of dangerous AI datasets who calls bullshit on bad science pushed by the likes of OpenAI, or a tireless champion of racial, gender, and climate justice in computing. She's also someone who wants to build something different. This week on Reimagining, we t
How Dr. Joy Buolamwini is Working Towards Equitable and Accountable Technology - Heising-Simons Foundation
Several years ago, while still a graduate student at MIT’s Media Lab, Joy Buolamwini began to notice a troubling pattern in facial recognition technology––an inability to detect a wide range of skin tones and facial structures, even in widely available systems employed by Big Tech, government agencies, and law enforcement.
