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In support of our mission to benefit people and society, the Partnership on AI intends to conduct research, organize discussions, share insights, provide thought leadership, consult with relevant third parties, respond to questions from the public and media, and create educational material that advances the understanding of AI technologies including machine perception, learning, and automated reasoning.

"In an exclusive interview, a top Google exec says the AI could eventually recognize if you're frustrated or pick up conversations where you left off."

These principles were developed in conjunction with the 2017 Asilomar conference

Guard is a site that uses AI to read epically long privacy policies and then highlight any aspects of them that might be problematic.

Object detection kit, scanning objects for a cleaner city

Build your own smart speaker and learn AI literacy at the same time

Living under permanent surveillance and what that means for our freedom

Open source, privacy aware Google Home & Amazon Alexa iot device and much more

"Nearly three years after the company was called out, it hasn't gone beyond a quick workaround"

An algorithm deduced the sexuality of people on a dating site with up to 91% accuracy, raising tricky ethical questions

"Have you noticed that news stories and marketing material about Artificial Intelligence are typically illustrated with clichéd and misleading images ?"

"Tripling as a feat of engineering, a social commentary on homelessness, and an interactive puppet show, [Ables] causes us to pause on the issue of homelessness and human-robot interaction. For a more whimsical interaction, a robot ball that follows you around is a pleasant way to get used to the presence of robots in society."

If you searched for "three white teenagers" on Google Images earlier this month, the result spat up shiny, happy people in droves - an R.E.M. song in JPG format. The images, mostly stock photos, displayed young Caucasian men and women laughing, holding sports equipment or caught whimsically mid-selfie. If you searched for "three black teenagers," the algorithm offered an array of mug shots.

Search term brings back mainly results of black women, which some say is evidence of bias. But algorithms may just be reflecting the wider social landscape

Algorithms used in American criminal justice is found to be biased against blacks

Google came under fire this week after its new Photos app categorized photos in one of the most racist ways possible. On June 28th, computer programmer Jacky Alciné found that the feature kept tagging pictures of him and his girlfriend as "gorillas."

The blind application of machine learning runs the risk of amplifying biases present in data. Such a danger is facing us with word embedding, a popular framework to represent text data as vectors which has been used in many machine learning and natural language processing tasks. We show that even word embeddings trained on Google News articles exhibit female/male gender stereotypes to a disturbing extent. This raises concerns because their widespread use, as we describe, often tends to amplify these biases. Geometrically, gender bias is first shown to be captured by a direction in the word embedding. Second, gender neutral words are shown to be linearly separable from gender definition words in the word embedding. Using these properties, we provide a methodology for modifying an embedding to remove gender stereotypes, such as the association between between the words receptionist and female, while maintaining desired associations such as between the words queen and female. We define metrics to quantify both direct and indirect gender biases in embeddings, and develop algorithms to "debias" the embedding. Using crowd-worker evaluation as well as standard benchmarks, we empirically demonstrate that our algorithms significantly reduce gender bias in embeddings while preserving the its useful properties such as the ability to cluster related concepts and to solve analogy tasks. The resulting embeddings can be used in applications without amplifying gender bias.

"CARS-SPYING: A new generation of cars is on the way - and they will know all your driving secrets"

"A trove of internal documents sheds light on the algorithms that Facebook's censors use to differentiate between hate speech and legitimate political expression."