Grid of 70 averaged faces for different face attribute categories, with overlaid heatmaps indicating significant regions.
Grid of 70 averaged faces for different face attribute categories, with overlaid heatmaps indicating significant regions.

A journey into the art of face analysis and classification.

Congrats on becoming a Faceworker! Our AI finds the perfect face for every job. Audition for each job by showing us you can make your face fit what the job needs. Ready to try out for your first job?

Facework is a game that imagines a world where face analysis is key to the latest gig economy app. As a Faceworker, the player is given an opportunity to interrogate in realtime how computer vision and machine learning tools work — to playfully grow an intuition for what it means to see like a machine, and to understand how machines can…

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The use of mugshots in research, and the shift from face recognition to face attribute classification.

In 2018 I read a research paper about estimating body mass index from face photos, written by an insurance company. The paper had a diagram, a mosaic of photos of mostly Black men showing that the training data was built on mugshots taken by the Florida department of corrections. I’ve been making art about face analysis since 2009, and I was generally familiar with the long history connecting it to policing, and that it is deployed in a way that reinforces systemic racism and mass incarceration. I knew mugshots were easily accessible. But I didn’t know that mugshots were used…

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In the late 1960s, scientist Roger Payne popularized underwater recordings of humpback whales, with the goal of ending the extinction-level threat of commercial whaling.

“I felt that unless people got interested in whales there was no hope of saving them and I realized that I might be able to help change that. […] I spent two years recording whales and lecturing about them and going around playing whale songs for anyone who’d listen. My aim was to try to build whale songs into human culture.”
Roger Payne

In 1969 he released “Songs of the Humpback Whale” on a flexi-disc…

In 2014 machine learning researcher Ian Goodfellow introduced the idea of generative adversarial networks or GANs. “Generative” because they output things like images rather than predictions about input (like “hotdog or not”); “adversarial networks” because they use two neural networks competing with each other in a “cat-and-mouse game”, like a cashier and a counterfeiter: one trying to fool the other into thinking it can generate real examples, the other trying to distinguish real from fake.

The first GAN images were easy for humans to identify. Consider these faces from 2014.

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Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks” (2014) by Radford et al, also known as DCGAN.

But the latest examples of GAN-generated faces, published in October…

Update: I have found a studio manager, but I will leave this post up in the hope it will help others ask for the help they need.

Hi! I’m an artist based in Los Angeles working with code, and I’m looking to hire a part-time studio manager.

My work takes a variety of forms including interactive installations, sneaky interventions, playful websites, workshops, and toolkits for other artists working with code. I love exploring the possibilities of new technologies, understanding how they affect society, and building alternative futures with friends. …

Creating new datasets and exploring new algorithms in the context of the dance performance “discrete figures”

In February 2018 Daito Manabe wrote me an email with the subject “Dance x Math (ML)”, asking if I’d be interested in working on a new project. I have some background working in the context of dance in the past, including 3d scanning with Lisa Parra in 2010, Reactor for Awareness in Motion with YCAM in 2013, and Transcranial with Daito and Klaus Obermaier in 2014–2015.

[Video description: screen recording of software showing a motion captured dancer rendered with basic shapes, and augmented by additional geometric and abstract extensions.]

I was very excited for the possibility of working with Mikiko

Disclaimer: I am not a doctor, this is not medical advice.

In 2013 around the age of 28, I stopped feeling rested when I woke up each morning. It happened gradually and never really disappeared, but in the process of trying to fix it I learned a lot about sleep, and about myself. Today, my worst nights are much more manageable than those from a few years ago. If you’re an analytical person and you’re having trouble feeling rested, this is for you. Read through to follow my journey, or skip to the end for a summary.

My trouble began…

Algorithmic music composition has developed a lot in the last few years, but the idea has a long history. In some sense, the first automatic music came from nature: Chinese windchimes, ancient Greek wind-powered Aeolian harps, or the Japanese water instrument suikinkutsu. But in the 1700s automatic music became “algorithmic”: Musikalisches Würfelspiel, a game that generates short piano compositions from fragments, with choices made by dice.

An example session of Musikalisches Würfelspiel.

Markov chains, formalized in the early 1900s to model probabilistic systems, can also be used to generate new musical compositions. They take the motivations behind the dice game…

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Photo Credit

This short tutorial describes a few methods for gaining access to the internet, a basic human right, from public wireless networks.

This tutorial has been tested on Mac, should work on Linux, and hasn’t been tested on Windows.


Make sure you do this step before you are stuck without Internet access.

  1. Install Python pip.
  2. Make a copy of this repository and install dependencies for the script we will be using:
git clone
cd FreeWifi && pip install -r requirements.txt

How to get additional time

If you had free internet access but your time has run out, the first thing to try is open an…

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This post is aimed at artists and other creative people who are interested in a survey of recent developments in machine learning research that intersect with art and culture. If you’ve been following ML research recently, you might find some of the experiments interesting but will want to skip most of the explanations.

The first AI that left me speechless was a chatbot named MegaHAL. I read a typical training session with its creator, Jason Hutchens:

User: Tu parles français? MegaHAL: I GUESS SO. PARLEZ-VOUS FRANÇAIS? User: In 1793 the french king was executed. MegaHAL: HA HA HA! CORRECT. ALTHOUGH…

Kyle McDonald

Artist working with code.

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