AIxDESIGN Bookmark Library

Fingerspelling.xyz uses your webcam and machine learning to analyze your hand shapes so you can learn to sign the American Sign Language alphabet.

The Universal Hip Hop Museum is coming to New York City, and an MIT team led by D. Fox Harrell has designed for it unique creative experiences at the intersection of art, learning, and technology.

I was on a panel tonight discussing Ethics in Design Research. I’m on a lot of panels about design and ethics because I’ve worked in AI…

A year in workshops

Viraj Joshi is a designer, technologist, and futurist based in London. He designd curious objects and fiction with great affinity towards our technological and social futures. Viraj is also the Creator of Eliza. Eliza is a series of cartoons that personifies

Rudy van Belkom is a futures researcher at the Netherlands Study Centre for Technology Trends (STT). He recently published his book about ethics in the design process (‘AI no longer has a plug’) that offers developers, policymakers, philosophers and basically anyone with an interest in AI, tools for integrating ethics into the AI design process. The main question of his research is always: what future do we want? We need to ask ourselves what purpose we want to use technology for, rather than seeing it as purpose in itself. How can we use technology to create a better world? And what exactly is a better world? Currently Rudy is focusing on the impact of technology on the future of Democracy. In addition he developed an ethical design game for AI, inspired by the scrum process, that can be used to translate ethical issues into practice. The essence of the game is based on the position paper that he wrote together with the HU research group on AI and was accepted for ECAI 2020: ‘An Agile Framework for Trustworthy AI’. Van Belkom also investigated the role of AI in the future of his own field.

A new online tool can automatically detect, rig, and animate semi-abstract drawings of people.

AI DeMoS Lab, with a focus on developing AI for democracy, has 4 PhD positions.

We are a non-profit creating more realistic and inclusive images of artificial intelligence. Visit our growing repository available for anyone to use for free under CC licences, or just to use as inspiration for more helpful and diverse representations of AI.

Data-Driven Exploitation in the Gig Economy

The latest news headlines as seen through a generative image AI. All images are created using real-time New York Times data combined with Big Sleep, VQGAN+CLIP and CLIP Guided Diffusion. Text-to-image generation techniques built on machine learning.

Type of employment: Full time.

Type of employment: Full time.

Image Generation with 0 code

At Random Studio, we create brand and service experiences that trigger a sense of wonder. Our work comes to life in the space where the digital meets the physical. As a studio, we value new ideas, new insight, new ways of seeing the world — and we are currently searching for a User Experience Designer to

A fast, dataset-agnostic, deep visual search engine for digital art history

The role of a designer is to intentionally shape the world around us with the resources we have available. That world is increasingly shaped by data sets, algorithms, and pre-trained models.

The value of a shared understanding of AI models. Model cards: a proposed first step

The Most Likely Machine is an interactive learning prototype by Artefact designed to help pre-teens develop algorithmic literacy through play.

Learn about bias and variance in our second animated data visualization.

Bust writer's block and be more creative with our magical writing AI.

Making Friends with Machine Learning was an internal-only Google course specially created to inspire beginners and amuse experts. Today, it is available to e...

AI Think Tank - Connect, Discuss, Innovate

26-27 November, Amsterdam / Online

Visit https://www.aiaaic.org/aiaaic-repository for information on what this resource is, and how it may be used

When it was first published in 1972, Hubert Dreyfus's manifesto on the inherent inability of disembodied machines to mimic higher mental functions caused an uproar in the artificial intelligence community. The world has changed since then. Today it is clear that "good old-fashioned AI," based on the idea of using symbolic representations to produce general intelligence, is in decline (although several believers still pursue its pot of gold), and the focus of the Al community has shifted to more complex models of the mind. It has also become more common for AI researchers to seek out and study philosophy. For this edition of his now classic book, Dreyfus has added a lengthy new introduction outlining these changes and assessing the paradigms of connectionism and neural networks that have transformed the field.At a time when researchers were proposing grand plans for general problem solvers and automatic translation machines, Dreyfus predicted that they would fail because their conception of mental functioning was naive, and he suggested that they would do well to acquaint themselves with modern philosophical approaches to human beings. What Computers Can't Do was widely attacked but quietly studied. Dreyfus's arguments are still provocative and focus our attention once again on what it is that makes human beings unique.