Artificial intelligence (AI) could increase global GDP by $15.7 trillion by 2030, according to PricewaterhouseCoopers. The prevalence of AI in modern society is growing at a rapid pace–and the Federal government needs to keep up. On April 24, the Brookings Institution released a deep dive report on AI. After examining the multitude of sectors AI is impacting, the report offers steps the Federal government should take to get the most out of AI while still protecting important human values. In the realm of AI, China is outspending the United States.

Artificial intelligence (AI) could increase global GDP by $15.7 trillion by 2030, according to PricewaterhouseCoopers. The prevalence of AI in modern society is growing at a rapid pace–and the Federal government needs to keep up. On April 24, the Brookings Institution released a deep dive report on AI. After examining the multitude of sectors AI is impacting, the report offers steps the Federal government should take to get the most out of AI while still protecting important human values. In the realm of AI, China is outspending the United States.

Collaborative machine learning and related techniques such as distributed and federated learning allow multiple participants, each with his own training dataset, to build a joint model. Participants train local models and periodically exchange model parameters or gradient updates computed during the training. We demonstrate that the training data used by participants in collaborative learning is vulnerable to inference attacks. First, we show that an adversarial participant can infer the presence of exact data points in others' training data (i.e., membership inference). Then, we demonstrate that the adversary can infer properties that hold only for a subset of the training data and are independent of the properties that the joint model aims to capture. We evaluate the efficacy of our attacks on a variety of tasks, datasets, and learning configurations, and conclude with a discussion of possible defenses.

For the last few years, police forces around China have invested heavily to build the world's largest video surveillance and facial recognition system, incorporating more than 170 million cameras so far. In a December test of the dragnet in Guiyang, a city of 4.3 million people in southwest China, a BBC reporter was flagged for arrest within seven minutes of police adding his headshot to a facial recognition database. And in the southeast city of Nanchang, Chinese police say that last month they arrested a suspect wanted for "economic crimes" after a facial recognition system spotted him at a pop concert amidst 60,000 other attendees. These types of stories, combined with reports that computer vision recognizes some types of images more accurately than humans, makes it seem like the Panopticon has officially arrived. In the US alone, 117 million Americans, or roughly one in two US adults, have their picture in a law enforcement facial-recognition database.

Over the past few years, Artificial Intelligence (AI) has attracted a huge amount of attention. It is anticipated to transform almost every sector including key areas such as finance, healthcare, manufacturing, logistics, automotive and aviation. The impact of this technology is so great that it has led the government and the AI sector to agree a Sector Deal to boost the UK's global position as a leader in developing AI technologies, which will see £1bn of investment put into the industry. For the legal sector and other professional services, AI is both a challenge for our clients in terms of how they will operate their businesses in future (and therefore something they will seek advice upon) and a challenge to how legal and professional services are delivered as AI replaces human review, analysis and advice. However, before businesses jump on the AI bandwagon, it's important to assess whether or not AI is the right tool to solve the problem before investing. There are countless stories of businesses being driven by marketing and media hype into implementing new technology that they don't actually need or are not ready for.

If you're unhappy with other players or the results of a raid, don't take it out on the game's servers, or you could wind up in a US jail. Take it from Calin Mateias, a 38-year-old Romanian man who was just sentenced to one year in federal prison for launching a series of distributed denial of service (DDoS) attacks against "World of Warcraft's" European servers in 2010. According to the US Department of Justice, Mateias launched the attacks between February and September 2010 after clashing with other WoW players for a variety of reasons, including the division of loot and membership in raid teams. His attacks were successful, causing WoW servers to crash and preventing some paying users from being able to access the game. Mateias was indicted in 2011 and has been in custody since Nov. 20 after being extradited from Romania. He pleaded guilty in February to one count of intentional damage to a protected computer.

Everyone from the ACLU to the Koch brothers wants to reduce the number of people in prison and in jail. Liberals view mass incarceration as an unjust result of a racist system. Conservatives view the criminal justice system as an inefficient system in dire need of reform. But both sides agree: Reducing the number of people behind bars is an all-around good idea. To that end, AI--in particular, so-called predictive technologies--has been deployed to support various parts of our criminal justice system.

When Justice Frank H. Easterbrook was asked, in 1996, to deliver a lecture on "Property in Cyberspace", he titled his talk--"Cyberspace and the Law of the Horse". His curious choice of title was his way of calling out the foolishness of trying to formulate laws to address new technologies when general principles could, just as well, suffice. There were a number of cases, he said, that dealt with the sale of horses, and even more where the courts have been approached to address the injuries suffered by people who have been kicked by horses. But this doesn't mean that one needs to "collect these strands into a course on "the Law of the Horse". All we need to do is study how the general law of property, torts and commercial transactions applies to the horse trade.

The roughly €19 billion deal would face a possibly lengthy European Union antitrust review, but if completed, would create one of the continent's biggest telecommunications operators, selling the industry's holy grail "quad-play" package: cable, internet, wireless and landline-phone service on a single bill. The Financial Times reported earlier Tuesday the two companies were nearing a deal. The deal would represent the latest in a global trend of wireless carriers acquiring cable operations, or vice versa, to offer quad-play packages. Wireless carriers need high-speed cable networks to quickly transmit data to cellular towers for 5G, the coming generation of mobile networks that promise to be fast enough to enable near-instantaneous movie downloads and innovations such as self-driving cars. Both companies have said they have engaged in various forms of merger talks with each other in recent years.

We are also privileged to have Assemblyman Clyde Vanel of New York State's Assembly join our discussion on the deployment of autonomous systems, AI, the future of organized labor, universal basic income, and more. Assembly member Vanel is recognized as one of the most tech savvy legislators in Albany with his proposed legislation on AI, Blockchain and Cybersecurity. BIOS: Andrew Yang is an entrepreneur and author running for President as a Democrat in 2020. In 2011 he founded Venture for America, a national entrepreneurship fellowship, and spent the last 6 years creating jobs in cities like Cleveland, Detroit, Baltimore, and Pittsburgh. When Andrew realized that new technology like artificial intelligence threatened to eliminate one-third of all American jobs, he knew he had to do something.