With disinformation on social media a significant problem, the ability to identify authors of malicious articles and the originators of disinformation campaigns could help reduce the threat from such information attacks. At the Black Hat Asia 2020 conference this week, three researchers from Baidu Security, the cybersecurity division of the Chinese technology giant Baidu, presented their approach to identifying authors based on machine learning techniques, such as neural networks. The researchers used 130,000 articles by more than 3,600 authors scraped from eight websites to train a neural network that could identify an author from a group of five possible writers 93% of the time and identify an author from a group of 2,000 possible writers 27% of the time. While the results are not impressive, they do show that identifying the person behind a piece of writing is possible, said Li Yiping, a researcher at Baidu Security, during his presentation on his team's work. "Most fake news is posted anonymously and lacks valid information to identify the author," he said.

Imagine that one day you're riding the train and decide to hop the turnstile to avoid paying the fare. It probably won't have a big impact on the financial well-being of your local transportation system. But now ask yourself, "What if everyone did that?" The outcome is much different -- the system would likely go bankrupt and no one would be able to ride the train anymore. Moral philosophers have long believed this type of reasoning, known as universalization, is the best way to make moral decisions. But do ordinary people spontaneously use this kind of moral judgment in their everyday lives?

In a midnight tweet, the President of the United States revealed that he and the First Lady have both tested positive for the coronavirus, raising concerns about his health and upending an already chaotic campaign season just thirty-two days before the election. The virus--which has transformed American life, killed more than two hundred thousand Americans, and devastated the U.S. economy--now threatens the health of the President and senior government officials. The White House has said that the President is experiencing mild symptoms; even so, they are signs of COVID-19, the disease caused by the coronavirus. From here, his illness might dissipate or grow much more severe. For the moment, President Trump's illness is mild.

Twitter is making changes to its photo cropping function after an investigation into racial bias in the software, the company said on Thursday. The announcement comes after users on the platform repeatedly showed that the tool -- which uses machine learning to choose which part of an image to crop based on what it thinks is the most interesting -- cuts out Black people from photos and centers on white faces instead. Tony Arcieri, a cryptography engineer, posted a series of tweets in mid-September showing how the platform's algorithm routinely chose to highlight the face of Senate Majority Leader Mitch McConnell, who is white, instead of former President Barack Obama's in multiple photos of the two. The experiment prompted others to try similar experiments with the same result, and led to the company launching an investigation into its systems shortly after. The social media company implemented its machine-learning-powered image cropping system in 2018.

The news cycle this week seemed to grab people by the collar and shake them violently. On Wednesday, Palantir went public. The secretive company with ties to the military, spy agencies, and ICE is reliant on government contracts and intent on racking up more sensitive data and contracts in the U.S. and overseas. Following a surveillance-as-a-service blitz last week, Amazon introduced Amazon One, which allows touchless biometric scans of people's palms for Amazon or third-party customers. The company claims palm scans are less invasive than other forms of biometric identifiers like facial recognition.

Four weeks ago, my last article for The AI Journal pointed out that the COVID-19 "creates data deficits … Relaxed or suspended regulatory reporting requirements deliver less data to governments for aggregation, which in turn delivers less complete data sets to markets." It did not take long before the official sector started pointing out crucial breaks in key data sets used for global macro and credit risk analysis. De Nederlandsche Bank (the Dutch central bank) recently released research showing that key inputs for HIPC inflation measures were not collected during March and April. Because the HIPC data is only updated annually, when central bankers sought to plug the gap in order to conduct monetary policy, they only alternative was to use same-month 2019 data as a proxy for 2020 prices in key sectors disrupted by the pandemic. While the data gap was resolved, actual price data diverged significantly from the estimated data.

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Sweden is set to become a leader in the global Artificial Intelligence (AI) industry by prioritizing AI-driven initiatives and opportunities in the country. Artificial Intelligence (AI), referred to as intelligence demonstrated by machines, encompasses many technologies, such as, machine learning (ML), deep learning (DL), blockchain, etc. AI Sweden launched in February, 2019 (formerly, AI Innovation of Sweden) is an initiative by the Swedish Government's Ministry of Enterprise and Innovation to harness the opportunities offered by digital transformation in automation. The government is implementing this initiative in collaboration with the European Union and several partnering agencies, such as, Lantmäteriet, Vinnova, Knut and Alice Wallenberg Foundation, universities, and research institutions. The Wallenberg AI, Autonomous Systems and Software Program (WASP) was launched in 2015 but received an additional billion Swedisn kroner grant in 2018 from the Knut and Alice Wallenberg Foundation. This funding has expanded the AI Sweden initiative under the name of the Billion kroner program for AI research.

Healthcare is an obvious sector to deploy AI in. It generates tsunamis of data, vast amounts of money are spent on it, and there are plenty of opportunities to improve the quality of its products and services by making them more intelligent and intelligible. It is a mistake to think of healthcare as a single monolithic entity. Will Smart is the former CIO for the NHS in England, and he points out that healthcare carries out the activities of numerous different industries, including hotels, catering, research, professional services, janitorial services, logistics, manufacturing, and many others. What kinds of AI should healthcare managers be looking into?

As a part of the U.S. Department of Energy's Advanced Scientific Computing Research program, Intel today inked a three-year agreement with Sandia National Laboratories to explore the value of neuromorphic computing for scaled-up AI problems. Sandia will kick off its work using a 50-million-neuron Loihi-based system recently delivered to its facility in Albuquerque, New Mexico. As the collaboration progresses, Intel says the labs will receive systems built on the company's next-generation neuromorphic architecture. Along with Intel, researchers at IBM, HP, MIT, Purdue, and Stanford hope to leverage neuromorphic computing -- circuits that mimic the nervous system's biology -- to develop supercomputers 1,000 times more powerful than any today. Chips like Loihi excel at constraint satisfaction problems, which require evaluating a large number of potential solutions to identify the one or few that satisfy specific constraints.