This is my new AI in Healthcare Highlights & Milestones Report for Summer 2022. This report includes an overview of advances made during the summer across the healthcare spectrum including important studies, regulatory clearances, fundraising, partnerships, and growth in the AI ecosystem worldwide. This summer scientists demonstrated how they successfully used AI in many areas including: to reduce sepsis deaths, to predict cardiac events, to detect breast cancer, to detect lung cancer, to detects osteoporosis, to detect Parkinson's, to monitor diabetic retinopathy, to detect heart disease, to detect bladder cancer, to enable pathology, to detect fractures, and to monitor Parkinson's using the Apple Watch. In July scientists in Germany published a large scale study demonstrating that radiologists working with AI were more accurate detecting breast cancer than radiologists working without AI, and vice versa - the AI was more accurate when working with a radiologist than when working independently. The study was led by Vara, a German company, in collaboration with radiologists at the Essen University Hospital in Germany and the Memorial Sloan Kettering Cancer Center in New York. Vara's AI is has been used by radiologists in German breast screening centers for two years and is used in 30% of Germany's breast cancer screening centers. Vara's AI software is also used to screen for breast cancer in a hospital in Mexico and in a hospital in Greece.

The nonpartisan think tank Brookings this week published a piece decrying the bloc's regulation of open source AI, arguing it would create legal liability for general-purpose AI systems while simultaneously undermining their development. Under the EU's draft AI Act, open source developers would have to adhere to guidelines for risk management, data governance, technical documentation and transparency, as well as standards of accuracy and cybersecurity. If a company were to deploy an open source AI system that led to some disastrous outcome, the author asserts, it's not inconceivable the company could attempt to deflect responsibility by suing the open source developers on which they built their product. "This could further concentrate power over the future of AI in large technology companies and prevent research that is critical to the public's understanding of AI," Alex Engler, the analyst at Brookings who published the piece, wrote. "In the end, the [E.U.'s] attempt to regulate open-source could create a convoluted set of requirements that endangers open-source AI contributors, likely without improving use of general-purpose AI."

A recently published Panel for the Future of Science and Technology (STOA) study examines the impact of biases on datasets used to support decision-making systems based on artificial intelligence. It explores the ethical implications of the deployment of digital technologies in the context of proposed European Union legislation, such as the AI act, the data act and the data governance act; as well as the recently approved Digital Services Act and Digital Markets Act. It ends by setting out a range of policy options to mitigate the pernicious effects of biases in decision-making systems that rely on machine learning. Machine learning (ML) is a form of artificial intelligence (AI) in which computers develop their own decision-making processes for situations that cannot be directly and satisfactorily addressed by available algorithms. The process is adjusted through the exploration of existing data on previous similar situations that include the solutions found at the time. The broader and more balanced the dataset is, the better the chances will be of obtaining a valid result; but there is no a priori way of knowing whether the data available will suffice to collect all aspects of the problem at hand.

North American companies are onboarding robot workers at a faster-than-ever pace. According to the Association for Advancing Automation, companies ordered a record-setting 12,305 machines in the second quarter of 2022. "The pandemic definitely highlighted some areas and shortages in resources needed to be automated, and customers had to automate just due to the fact that people weren't coming back to the workplace," FANUC North America Vice President Louis Finazzo said. "For a long time, the automotive industry accounted for 60 to 70% of robot orders," Association for Advancing Automation President Jeff Burnstein said. "And we knew that when other industries started adopting is when we would really see growth, which is finally happening now, in part due to the pandemic forcing companies to look at other options when they couldn't bring people into work."

DAPA, the Digital Asset Policy Alliance, is launching as a collaborative initiative focused on the public policy implications of web3 with initial participants from Fabric Ventures, the web3 venture contributor, Coadec, The Coalition for a Digital Economy, Project Vellir, NEAR Protocol and Unstoppable Finance. DAPA welcomes other volunteers and will progressively decentralise with'community-driven' at its heart with the upcoming DAPA DAO. DAPA's mission is to improve understanding of web3 and crypto technology and ensure that new industry regulation protects consumers and businesses, while also promoting innovation and adoption of the transformative benefits of this new technology. Decentralisation technology has the potential to transform our society for the better. There has been rapid growth in blockchain technology and consumer demand for web3 applications, which has attracted the attention of policy makers and regulators, including in the UK, EU and US.

BEIJING, Sept 6 (Reuters) - High-profile universities and state-run research institutes in China have been relying on a U.S. computing chip to power their artificial intelligence (AI) technology but whose export to the country Washington has now restricted, a Reuters review showed. U.S. chip designer Nvidia Corp (NVDA.O) last week said U.S. government officials have ordered it to stop exporting its A100 and H100 chips to China. Local peer Advanced Micro Devices Inc (AMD) (AMD.O) also said new licence requirements now prevent export to China of its advanced AI chip MI250. The development signalled a major escalation of a U.S. campaign to stymie China's technological capability as tension bubbles over the fate of Taiwan, where chips for Nvidia and almost every other major chip firm are manufactured. China views Taiwan as a rogue province and has not ruled out force to bring the democratically governed island under its control.

On August 9, at least a dozen explosions rocked a Russian military base in Crimea. Russia's defence ministry avoided assigning blame – saying the "detonation of several aviation ammunition stores" caused the blast – while, for its part, Ukraine's military played it coy. It did not claim responsibility for the damaged combat planes, nor for a subsequent drone strike on the navy headquarters in the Russian-occupied area. Instead, Ukraine's defence ministry mockingly warned on Twitter about the dangers of smoking – sardonically suggesting that Russian soldiers caused the explosions themselves by tossing lit cigarettes. Unless they want an unpleasantly hot summer break, we advise our valued russian guests not to visit Ukrainian Crimea.

BEIJING – High-profile universities and state-run research institutes in China have been relying on a U.S. computing chip to power their artificial intelligence (AI) technology but whose export to the country Washington has now restricted, a review showed. U.S. chip designer Nvidia Corp. last week said U.S. government officials have ordered it to stop exporting its A100 and H100 chips to China. Local peer Advanced Micro Devices Inc. (AMD) also said new license requirements now prevent export of its advanced AI chip MI250 to China. This could be due to a conflict with your ad-blocking or security software. Please add japantimes.co.jp and piano.io to your list of allowed sites.

In his new book The Last War: How AI Will Shape India's Final Showdown With China, Pravin Sawhney, the editor of FORCE magazine, disquietingly forebodes a grim scenario for 2024: "If India and China were to fight a war in the near future, India faces the prospect of losing the war within 10 days. China could take Arunachal Pradesh and Ladakh with a minimum loss of life, and there is very little that India could do about it." Is it the imagination of a defence analyst running wild? Far from it -- such scenarios have been predicted by other analysts too. A US military blog, Mad Scientist, which looks at the future of warfare, visualised a similar scenario for 2035 in February 2020, wherein China, in collusion with Pakistan, defeats India in Jammu and Kashmir and Ladakh.

High-profile universities and state-run research institutes in China have been relying on a U.S. computing chip to power their artificial intelligence (AI) technology but whose export to the country Washington has now restricted, a Reuters review showed. U.S. chip designer Nvidia Corp last week said U.S. government officials have ordered it to stop exporting its A100 and H100 chips to China. Local peer Advanced Micro Devices Inc (AMD) also said new licence requirements now prevent export to China of its advanced AI chip MI250. The development signalled a major escalation of a U.S. campaign to stymie China's technological capability as tension bubbles over the fate of Taiwan, where chips for Nvidia and almost every other major chip firm are manufactured. China views Taiwan as a rogue province and has not ruled out force to bring the democratically governed island under its control.