Voice technologies like the one that Mycroft is building can be traced back more than 50 years. In fact, Mycroft is named after a voice assistant that appeared in Robert Heinlein's 1963 Hugo Award winning novel "The Moon is a Harsh Mistress". All of the underlying technologies are described in the novel and they have been broken out time and again over the past half-century in popular science fiction. "Hal" from 2001 a Space Odyssey, Star Trek's "Computer", Knight Rider's "Kitt" – all of these are examples of how voice technology might work in the real world. They've also been disclosed in real-world tech like Honda's Asimo and more than 3 decades of automotive technologies from Nuance.

In the past years we've had a growing discussion about how to reduce social bias and increase fairness, which is good. We wouldn't want our models to be discriminatory because of discriminatory historical data. However what I've noticed is that some have taken this as an opportunity to poisen the well by suggesting active discriminatory practices in seductive language and insidious framing. "Debiasing" AI is not enough. We need to proactively use computational decision making to correct for injustice.

A Dutch court has demanded that an algorithm-based system used by the government to identify and track down potential housing and benefit cheats is dropped with immediate effect. As reported by DutchNews, on Wednesday, the District Court of The Hague ruled that the system conflicts with EU human rights and privacy protections. Dubbed System Risk Indication (SyRI), the automatic, machine-learning (ML) tool was used by local Dutch authorities to draw up profiles and lists of individuals suspected of being at high risk of conducting benefits fraud. According to the publication, SyRI creates risk profiles from individuals that committed social security fraud in the past and then scans for "similar" citizen profiles, creating leads for potential investigations into others that may also be committing fraud, or be of a high risk of doing so in the future. SyRI's pooling of citizen data, otherwise kept in separate silos, gave authorities wide-ranging powers and "has been exclusively targeted at neighborhoods with mostly low-income and minority residents," according to UN human rights and poverty rapporteur Philip Alston.

Facebook scientists have proposed using watermarks to identify when online images get used to train neural networks. The proposal appears to be aimed at least in part at the rise of big data startups, such as Clearview AI, that are scraping publicly available photographs from social networks and other sites and using them for facial recognition purposes, prompting privacy concerns (see: Facial Recognition: Big Trouble With Big Data Biometrics). Neural networks are a type of machine learning that involves using a large set of training data to devise rules that can be used to identify future patterns (see: What's Artificial Intelligence? To detect if training sets have used Facebook images, a team of the company's researchers has proposed building a system that can be used to find out. "We have developed a new technique to mark the images in a data set so that researchers can determine whether a particular machine learning model has been trained using those images," say Facebook researchers Alexandre Sablayrolles, Matthijs Douze and Hervé Jégou in a blog post.

AI (Artificial Intelligence) is a revolutionary technology, which is being a part of everything we do in our life on a daily basis. If we talk about a few decades ago, there were tasks that could only be done by humans, such as playing chessboard, doing research work etc, but nowadays, AI-based Machines are capable of doing these tasks. And soon, AI will be developed to the level that it will change the way we work, study and communicate. Moreover, if we will talk about patent offices worldwide, every year the number of filings of the patent applications in patent offices is increasing exponentially and the patent examiners have limited time to work on a patent application. So due to these reasons, the quality of patents is getting compromised.

Recently enacted legislation grants individuals certain rights to decide in what fashion their personal data may be used, and in particular a "right to be forgotten". This poses a challenge to machine learning: how to proceed when an individual retracts permission to use data which has been part of the training process of a model? From this question emerges the field of machine unlearning, which could be broadly described as the investigation of how to "delete training data from models". Our work complements this direction of research for the specific setting of class-wide deletion requests for classification models (e.g. deep neural networks). As a first step, we propose linear filtration as a computationally efficient sanitization method. Our experiments demonstrate benefits in an adversarial setting over naive deletion schemes.

Jokingly dubbed "deal prevention units" by some front-office staff, compliance teams now have the third most-stressful City jobs after that of an investment banker and a trader. Pre-crisis, pre-Brexit and pre-cybercrime, compliance used to be (almost!) a stress-free job with regular hours. As regulatory pressure intensifies and personal liability mounts, compliance officers are under increased pressure do the right thing every time, personally and professionally. Our latest research, The Cost of Compliance and How to Reduce It, shows that a typical European bank, serving 10 million customers, could save up to €10 million annually and avoid growing fines by the regulator by implementing technology to improve the "Know Your Customer" (KYC) processes. Following new EU Anti-Money Laundering (AML4/5) and Counter-Terrorist Financing (CTF) rules extending the scope of KYC requirements, the cost each year of punitive non-compliance fines is now €3.5 million.

Hoan Ton-That, CEO of creepy facial recognition company Clearview AI, made the bold claim on Tuesday that his company has the right to publicly posted photos on Twitter and wielded the First Amendment as his reason. Clearview AI faced heat after it was discovered they had mined billions of publicly accessible images from Facebook and Ton-That's comments prove the company isn't backing down. EXCLUSIVE: The founder of a facial recognition company described as both "groundbreaking" and "a nightmare" is speaking out. In an interview with CBS This Morning, Ton-That was asked about Twitter's cease-and-desist order requesting that his company stop scraping it's data and delete everything Clearview AI has collected from the platform. In response, the facial recognition CEO claimed his company has a first amendment right to the data.

Claims 1 and 8 as recited are not practically performed in the human mind. As discussed above, the claims recite monitoring operation of machines using neural networks, logic decision trees, confidence assessments, fuzzy logic, smart agent profiling, and case-based reasoning. . . .

The EPO has published its decision setting out the reasons for its recent refusal of two European patent applications in which an AI system was designated as the inventor. Filed by an individual in autumn 2018, the applications EP 18 275 163 and EP 18 275 174 were refused by the EPO following oral proceedings with the applicant in November 2019, on the grounds that they do not meet the legal requirement of the European Patent Convention (EPC) that an inventor designated in the application has to be a human being, and not a machine. In both applications a machine called "DABUS", which is described as "a type of connectionist artificial intelligence", is named as the inventor. The applicant stated that he had acquired the right to the European patent from the inventor by being its successor in title, arguing that as the machine's owner, he was assigned any intellectual property rights created by this machine. In its decisions, the EPO considered that the interpretation of the legal framework of the European patent system leads to the conclusion that the inventor designated in a European patent must be a natural person.