Artificial intelligence (AI) is no longer the stuff of science fiction. AI determines what news you get served up on the internet. It plays a key role in online matchmaking, which is now the way most romantic couples get together. It will tell you how to get to your next meeting, and what time to leave home so you're not late. AI often appears both omniscient and neutral, but on closer inspection we find AI learns from and adopts human biases.

Fox News contributor Karl Rove reacts to Trump blasting the media and Big Tech for being'massively corrupt.' WASHINGTON – Congressman-elect Jay Obernolte, a 50-year-old who is a video game developer by trade, will be a bit of an outlier in Congress. That's because members of Congress are not necessarily known as a technologically savvy bunch. This reputation has been earned by many awkward moments and stumbles by members when discussing tech, including in a 2018 hearing when Rep. Steve Cohen, D-Tenn., told Alphabet CEO Sundar Pichai, "I use your apparatus often," referring to Google, the search engine. But Obernolte – whose company FarSight Studios creates games for a variety of platforms ranging from PlayStation to iOS – said that, with the right approach, Congress can and should effectively address major tech issues ranging from net neutrality to Section 230. "I actually think that sometimes we get caught up in jargon from a technological standpoint, which is not helpful because I don't think the technology is unapproachable," he told Fox News in an interview.

The Living Planet Index produced by WWF estimates that wildlife population sizes have dropped by 68 per cent since 1970. The charity advocates the use of artificial intelligence (AI) as a tool of conservation technology to monitor and curb this alarming rate of decline. One of the most useful applications is in acoustic monitoring, recording the sounds of wildlife ecosystems on weatherproof sensors. Many animals, from birds and bats to mammals and even invertebrates, use sound for communication, navigation and territorial defence, providing reams of rich data on how a species population is doing. AI provides a fast and cost-effective way to analyse hours of recordings for patterns of behaviour.

Beijing – Muslims in China's Xinjiang were "arbitrarily" selected for arrest by a computer program that flagged suspicious behavior, activists said Wednesday, in a report detailing big data's role in repression in the restive region. The U.S.-based Human Rights Watch said leaked police data that listed over 2,000 detainees from Aksu prefecture was further evidence of "how China's brutal repression of Xinjiang's Turkic Muslims is being turbocharged by technology." Beijing has come under intense international criticism over its policies in the resource-rich territory, where rights groups say as many as 1 million Uighurs and other mostly Muslim minorities have been held in internment camps. China defends the camps as vocational training centers aimed at stamping out terrorism and improving employment opportunities. Surveillance spending in Xinjiang has ballooned in recent years, with facial recognition, iris scanners, DNA collection and artificial intelligence deployed across the province in the name of preventing terrorism.

Artificial intelligence is growing ever more powerful and entering people's daily lives, yet often we don't know what goes on inside these systems. Their non-transparency could fuel practical problems, or even racism, which is why researchers increasingly want to open this'black box' and make AI explainable. When decisions are made by artificial intelligence, it can be difficult for the end user to understand the reasoning behind them. In February of 2013, Eric Loomis was driving around in the small town of La Crosse in Wisconsin, US, when he was stopped by the police. The car he was driving turned out to have been involved in a shooting, and he was arrested.

Spotify is currently working on an algorithm that could let musicians know whether their latest compositions copy parts of existing songs, reports the specialist magazine, Music Business Worldwide. Patent applications were apparently filed at the end of November in the US and in Europe, for a new technology named "Plagiarism Risk Detector and Interface." The invention is said to analyze so-called "lead sheets" -- a kind of musical score for songs denoting melody, chords and sometimes more -- to detect whether they copy any elements of any other tracks featured on the Spotify platform. These could be harmonies, sequences of chords or fragments of melody, for example. It could also provide a link to the track resembling the creation analyzed by the AI in order to facilitate rewriting.

Now calculate cosine similarity between each document and each query. For each query sort the cosine similarity scores for all the documents and take top-3 documents having high scores.

Growing applications of machine learning in policy settings have raised concern for fairness implications, especially for racial minorities, but little work has studied the practical trade-offs between fairness and accuracy in real-world settings. This empirical study fills this gap by investigating the accuracy cost of mitigating disparities across several policy settings, focusing on the common context of using machine learning to inform benefit allocation in resource-constrained programs across education, mental health, criminal justice, and housing safety. In each setting, explicitly focusing on achieving equity and using our proposed post-hoc disparity mitigation methods, fairness was substantially improved without sacrificing accuracy, challenging the commonly held assumption that reducing disparities either requires accepting an appreciable drop in accuracy or the development of novel, complex methods.

Banks and other financial firms are investing in "explainable" artificial intelligence that lets auditors and analysts trace how decisions about loans and other services are made by financial technologies, experts say. The increasing use of software with AI capabilities such as machine learning and data mining has automated banking operations, increasing efficiency and providing more services. But privacy and civil liberties groups contend that has come at a cost, with bias in the AI systems' algorithms leading to discrimination in the form of loans or other services denied based on sex or ethnicity. This perception of algorithmic bias is a big problem for banks, which are investing in technical solutions to solve the problem, Moutusi Sau, an analyst at research and advisory company Gartner Inc., told CQ Roll Call. That issue is known as the black box problem with AI systems: software decision-making processes that often are opaque to humans, making it difficult or impossible to determine how a decision was made.

Joy Buolamwini from the MIT Media Lab says facial-recognition software has the highest error rates for darker-skinned females. New applications powered by artificial intelligence (AI) are being embraced by the public and private sectors. Their early uses hint at what's to come. In June 2020, IBM, Amazon and Microsoft announced that they were stepping back from facial-recognition software development amid concerns that it reinforces racial and gender bias. Amazon and Microsoft said they would stop selling facial-recognition software to police until new laws are passed in the United States to address potential human-rights abuses.