Housing Secretary Robert Jenrick still has questions to answer over his role in a planning case involving a Tory donor, Sir Keir Starmer has said. The Labour leader told the BBC the matter was "far from closed" but stopped short of calling for the minister's resignation. Mr Jenrick is under fire after granting permission for a luxury housing development to donor Richard Desmond. Downing Street said the PM had full confidence in the minister. Mr Jenrick says he was motivated by a desire to see more homes built when he overruled government inspectors to give the green light to Mr Desmond's plans for a 1,500 home development at the former Westferry printing works, in London's Isle of Dogs.

The journal Earth and Space Science identifies AI technologies as key for reducing human forecasters' workloads while delivering more accurate and timely predictions. The US National Oceanic and Atmospheric Administration (NOAA) also says incorporating AI and machine learning significantly increases the prediction ability of extreme weather such as thunderstorms and hurricanes. Google is an industry pioneer. The tech giant presented new research into the development of deep learning models for precipitation forecasting in December, 2019. The team treated forecasting as an image-to-image translation problem and leveraged the power of the ubiquitous UNET convolutional neural network.

A diver examines one of the coral nurseries on the coral reefs of the Society Islands in French ... [ ] Polynesia. While scientists have succeeded at restoring some coral reefs, humans alone can't save all the reefs that are dying across the globe, a NOAA reef restoration manager said this month. Even in the best of conditions, human divers can spend only three or four hours per day working under water, said Tom Moore, coral reef restoration program manager for the National Oceanic And Atmospheric Administration. And those best conditions are rare. That's not enough to halt the collapse of one of the planet's most crucial ecosystems, Moore said at the EarthxOcean conference: half the world's coral reefs have died and the rest are expected to perish in this century.

When we're first learning to make music, most of us don't worry about an A.I. stealing our flow. They say imitation is the sincerest form of flattery. But when Jay-Z heard himself on the internet spitting iambic pentameter -- Hamlet's "To Be, or Not to Be" soliloquy, to be exact -- "flattered" is hardly the word for how he responded. It was produced by a well-trained computer speech synthesis program using artificial intelligence. An anonymous YouTube artist named Vocal Synthesis has created a library of popular voices mismatched with unexpected famous texts, including George Bush reading "In Da Club" by 50 Cent, Barack Obama reading "Juicy" by Notorious B.I.G, and, yes, Jay-Z reading Hamlet (and Billy Joel's "We Didn't Start the Fire").

McCarthy et al [1] organized the Dartmouth workshop in 1956 to initiate artificial intelligence (AI) as a research field with a lofty goal to simulate, enhance, or even surpass human intelligence. Given the tremendous potentials and challenges, the excitements and frustrations are equally remarkable. Their interactions lead to alterations of AI springs and winters, through which the AI field has been developed step by step, and elevated to today's level, and we believe that this field will have an even brighter future. Currently, AI is in a new spring, especially its sub-field machine learning (ML) which enjoys rapid development and constant innovations featured by deep neural networks, also known as deep learning. On August 30, 2019, the White House issued a memorandum on the Fiscal Year 2021 Administration Research and Development Budget Priorities [2], underlining that'departments and agencies should prioritize basic and applied research investments that are consistent with the 2019 Executive Order on Maintaining American Leadership in Artificial Intelligence and the eight strategies detailed in the 2019 update of the National Artificial Intelligence Research and Development Strategic Plan.'

From a technical standpoint, machine learning is a field where absolute cybersecurity is impossible! It does not promise to completely protect the confidentiality, integrity, and availability of data and networks but instead offers practical ways to reduce the scale of attacks and improve the security level to a great extent. One reason why we cannot entirely prevent cybersecurity threats in machine learning is that cyber attackers themselves are adopting the same technology for attacks, which include malware and phishing, spam, DDoS, ransomware, spyware, etc. Besides, the offensive capabilities are much cheaper and easier to develop and deploy than the necessary defensive measures. The use of AI-powered malicious apps in massive cyberattacks increases the speed, adaptability, agility, coordination, and even sophistication of the attacks on a large population of networks and devices. By using supervised and unsupervised learning, these malicious programs can hide within a victim's system, and generate credentials to infiltrate devices by automatically cycling through password and username options at a speed faster than a human could test. They can self-learn how and when to attack their target system and be able to evade defensive measures through self-initiated changes in signature and behavior at the event of a counterattack.

Boston has become the second-largest city in the US to bar police and other local agencies from using facial recognition software (via WBUR). The city's 13-member council voted unanimously to ban the technology outside of use in specific criminal cases. The bill also prevents any city official from obtaining the technology through a third-party. The bill was put forward in part to protect the city's minority residents. "Boston should not use racially discriminatory technology that threatens the privacy and basic rights of our residents," said councilor Michelle Wu, who co-sponsored the bill alongside councilor Ricardo Arroyo.

Talking about racism and it's impact on robotics and roboticists was the first conversation in our new biweekly online discussion series "Society, Robots and Us" on alternate Tuesdays at 6pm PDT. It was a generous, honest and painful discussion that I hope has left a lasting impact on everyone who listened. There is systemic racism in America, and this does have an impact on robotics and roboticists in many many ways. The US Senator Elizabeth Warren in conversation today with Alicia Garza from Black Futures Lab said, "America was founded on principles of liberty and freedom, but it was built on the backs of enslaved people. This is a truth we must not ignore. Racism and white supremacy have shaped every crucial aspect of our economy, and our political system for generations now."

Boston City Councilors voted unanimously to ban the use of facial-recognition technology by police -- technology the Boston Police Department currently doesn't use anyway due to its unreliability. All 13 councilors voted in favor of the order authored by Councilors Ricardo Arroyo and Michelle Wu to ban the city from using technology that matches people's faces. Mayor Marty Walsh's office said the mayor would review the legislation, not committing to whether he'd sign it or not. "It puts Bostonians at risk for misidentification," Arroyo said. A recent MIT study found that the technology was wrong more often when trying to identify darker-skinned people.

These past few months have been especially challenging, and the deployment of technology in ways hitherto untested at an unrivalled pace has left the internet and technology watchers aghast. Artificial intelligence has become the byword for technological progress and is being used in everything from helping us combat the COVID-19 pandemic to nudging our attention in different directions as we all spend increasingly larger amounts of time online. It has never been more important that we keep a sharp eye out on the development of this field and how it is shaping our society and interactions with each other. With this inaugural edition of the State of AI Ethics we hope to bring forward the most important developments that caught our attention at the Montreal AI Ethics Institute this past quarter. Our goal is to help you navigate this ever-evolving field swiftly and allow you and your organization to make informed decisions. This pulse-check for the state of discourse, research, and development is geared towards researchers and practitioners alike who are making decisions on behalf of their organizations in considering the societal impacts of AI-enabled solutions. We cover a wide set of areas in this report spanning Agency and Responsibility, Security and Risk, Disinformation, Jobs and Labor, the Future of AI Ethics, and more. Our staff has worked tirelessly over the past quarter surfacing signal from the noise so that you are equipped with the right tools and knowledge to confidently tread this complex yet consequential domain.