Evan Greer from Fight for the Future writes, "Facial recognition might be the most invasive and dangerous form of surveillance tech ever invented. While it's been in the headlines lately, most of us still don't know whether it's happening in our area. My organization Fight for the Future has compiled an interactive map that shows everywhere in the US (that we know of) facial recognition being used -- but also where there are local efforts to ban it, like has already happened in San Francisco, Oakland, and Somerville, MA. We've also got a tool kit for local residents who want to get an ordinance or state legislation passed in their area." Read the rest

The Googler Uprising was a string of employee actions within Google over a series of issues related to ethics and business practices, starting with the company's AI project for US military drones, then its secretive work on a censored/surveilling search tool for use in China; then the $80m payout to Android founder Andy Rubin after he was accused of multiple sexual assaults. Read the rest

In Q2 2018, Chinese investors sank $2.87b into AI startups; in Q2 2019, it was $140.7m. Read the rest

I used to be on the program committee for the O'Reilly Emerging Technology conferences; one year we decided to make the theme "magic" -- all the ways that new technologies were doing things that baffled us and blew us away. Read the rest

Instagram launched a new feature today, Restrict, intended to help vulnerable users avoid abuse. Facebook's Head of Instagram Adam Mosseri says the company will also be focusing on new uses for AI to crack down on bullying. Read the rest

Bruce Sterling republishes the acronyms in a recent Daimler white-paper on self-driving cars: Read the rest

In the latest Adafruit video (previously) the proprietors, Limor "ladyada" Friend and Phil Torrone, explain the basics of machine learning, with particular emphasis on the difference between computing a model (hard) and implementing the model (easy and simple enough to run on relatively low-powered hardware), and then they install and run Tensorflow Light on a small, open-source handheld and teach it to distinguish between someone saying "No" and someone saying "Yes," in just a few minutes. It's an interesting demonstration of the theory that machine learning may be most useful in tiny, embedded, offline processors. (via Beyond the Beyond) Read the rest

Joël Franusic became obsessed with Krazy Kat, but was frustrated by the limited availability and high cost of the books anthologizing the strip (some of which were going for $600 or more on Amazon); so he wrote a scraper that would pull down thumbnails from massive archives of pre-1923 newspapers and then identified 100 pages containing Krazy Kat strips to use as training data for a machine-learning model. Read the rest

Rob Smith is an eminent computer scientist and machine learning pioneer whose work on genetic algorithms has been influential in both industry and the academy; now, in his first book for a general audience, Rage Inside the Machine: The Prejudice of Algorithms, and How to Stop the Internet Making Bigots of Us All, Smith expertly draws connections between AI, neoliberalism, human bias, eugenics and far-right populism, and shows how the biases of computer science and the corporate paymasters have distorted our whole society. Read the rest

The EU Commission's High-Level Expert Group on AI (AI HLEG) has tabled its Policy and investment recommendations for trustworthy Artificial Intelligence, recommending a ban on the use of machine learning technologies to generate Chinese-style Citizen Scores and limits on the use of the technology in monitoring and analyzing mass surveillance data. Read the rest

In The Next Generation of Deep Learning Hardware: Analog Computing *Sci-Hub mirror), a trio of IBM researchers discuss how new materials could allow them to build analog computers that vastly improved the energy/computing efficiency in training machine-learning networks. Read the rest

One of the griftiest corners of late-stage capitalism is the "public safety" industry, in which military contractors realize they can expand their market by peddling overpriced garbage to schools, cities, public transit systems, hospitals, etc -- which is how the "aggression detection" industry emerged, selling microphones whose "machine learning" backends are supposed to be able to detect "aggressive voices" (as well as gunshots) and alert cops or security guards. Read the rest

Laanlabs's showreel for 6d.ai meshing technology is an augmented reality demo in which virtual cockroaches crawl all over a very real kitchen. It's the best use of augmented reality I've ever seen. (via Beyond the Beyond) Read the rest

A new study from Facebook AI Research evaluates common machine-learning classifiers' ability to label photos of objects found in households in rich countries versus household objects from poor countries and finds that the models' performance lags significantly when being asked to classify the possessions of poor people. Read the rest

In Energy and Policy Considerations for Deep Learning in NLP, three UMass Amherst computer science researchers investigate the carbon budget of training machine learning models for natural language processing, and come back with the eyepopping headline figure of 78,468lbs to do a basic training-and-refinement operation. Read the rest

Military research and Chinese firms had access to the data Microsoft scraped under Creative Commons licenses.

For 17 years, I've been writing about the possibilities of "cognitive radio", in which radios sense which spectrum is available from moment to moment and collaborate to frequency-hop (and perform other tricks) to maximize the efficiency of wireless communications. Read the rest