Recent surveys, studies, forecasts and other quantitative assessments of the progress and impact of AI highlight the precarious nature of the future of work (long after the coronavirus pandemic ends), the continuing mixed attitudes of consumers about data privacy, and the possible resilience of this year's investments in AI. The IT department's need for AI talent has tripled between 2015 and 2019, but the number of AI jobs posted by IT is still less than half of that stemming from other business units; departments recruiting AI talent in high volumes include marketing, sales, customer service, finance, and research and development. By 2025, at least two of the top 10 global retailers will establish robot resource organizations to manage nonhuman workers; 77% of retailers plan to deploy AI by 2021, with the deployment of robotics for warehouse picking as the No. 1 use case [Gartner] By 2024, AI, virtual personal assistants, and chatbots will replace almost 69% of the manager's workload [Gartner] "Supervised machine learning doesn't live up to the hype. It isn't actual artificial intelligence akin to C-3PO, it's a sophisticated pattern-matching tool… Rather than seeing exponential improvements in the quality of AI performance (a la Moore's Law), we're instead seeing exponential increases in the cost to improve AI systems"--Stefan Seltz-Axmacher, founder, Starsky Robotics "…why are we holding our hands behind our back trying to build AI without mechanisms that infants have?"--Gary "We haven't really gone to great depth with deep learning yet. We've had a limited amount of training data so far. We've had limited structures with limited compute power. But the key point is that deep learning learns the concept, it learns the features. "…such capabilities [as "deepfake" transformation of the human face] were called image processing 15 years ago, but are routinely termed AI today.

The health care sector has increasingly turned to artificial intelligence to aid in everything from performing surgeries to helping diagnose and predict outcomes of patient illnesses. But as the coronavirus crisis ramps up, and hackers turn their eyes toward the health sector, experts warn these systems and the patients they support are increasingly at risk. "Obviously any disruption or denial of service of any type of medical health technology which interrupts patient care is definitely a significant issue," said John Riggi, the senior adviser for cybersecurity and risk at the American Hospital Association (AHA). "Worst-case scenario, life-saving medical devices may be rendered inoperable." AI systems have gradually been integrated into health care in the United States, often used to help speed diagnoses, such as reading X-rays, and for determining risks to patients.

Artificial Intelligence (AI) is developing fast. It will change our lives by improving healthcare (e.g. At the same time, AI entails a number of potential risks, such as opaque decision-making, gender-based or other kinds of discrimination, intrusion in our private lives or being used for criminal purposes. In order to foster an active dialogue between multiple stakeholders and set out policy options to tackle these challenges, the European Commission has just released a White Paper entitled "On Artificial Intelligence -A European approach to excellence and trust" which is available for download. Interested to learn more on the implications of AI for intellectual property and the themes relevant for legal practice in this field? Take a look at our IP Special on the topic!

Artificial intelligence (AI) often raises concerns about privacy and deception apropos of facial recognition and forged entities. However, the massive outbreak of the novel coronavirus is now driving most of the technology companies and experts to look for AI's abet. Since the first report of coronavirus (COVID-19) in Wuhan, China – the virus has now spread to at least 100 other countries. Nevertheless, the undisclosed information holds the key to the certainty that the artificial intelligence warning system, run by Toronto startup "BlueDot" flagged a news report from China about enigmatic pneumonia distressing the residents of Wuhan, back in December 2019. As China leans on its strong technology sector, specifically artificial intelligence and data science to track and combat this pandemic, tech leaders like Alibaba, and Huawei chose to accelerate their company's healthcare initiatives. Consequently, tech startups are integrally involved with medics and government officials on the global level to trigger technology as the virus continues to feast on many other countries.

The Radiological Society of North America (RSNA) has received numerous inquiries seeking access to COVID-19 related imaging data, both from radiology sites interested in sharing such data for use in research and education and from researchers. RSNA is committed to accelerating open source collaborative research on the uses of medical imaging in addressing the COVID-19 pandemic, including the use of new tools like artificial intelligence (AI). This form will enable institutions with COVID-19 data to express interest in participating in a planned open data repository for international COVID-19 imaging research and education efforts. Please complete this form if your institution has COVID-19 data that you may be willing and able to share for research purposes. Completing this brief survey does not represent a final commitment to collaborate with us or to share your data.

It's a common frustration--software updates intended to make our applications run faster inadvertently end up doing just the opposite. These bugs, called performance regressions in the field of computer science, are time-consuming to fix because locating software errors normally requires substantial human intervention. To overcome this obstacle, researchers at Texas A&M University, in collaboration with computer scientists at Intel Labs, developed a completely automated way of identifying the source of the errors. Their algorithm, based on a specialized form of machine learning called deep learning, is not only turnkey, but also quick. It finds performance bugs in a matter of a few hours instead of days.

According to Deltec Bank, Bahamas - 'The presence of AI produces several specific benefits that banks can use to generate new revenue streams through individualization.' We all understand that artificial intelligence and data analytics are excellent teammates. Over the next several years, the banking sector will use the power of this combination to create and deliver essential products and strategies that can help consumers and businesses grow their wealth through new and unique methods. The success of this process depends on where the industry focuses its energy, and AI enables institutions to concentrate its initiatives on crucial tasks instead of bureaucratic responsibilities. The banking sector already uses a standardized analytics report to understand the reasons why specific behaviors and actions happen.

COVID-19 has gripped the world for the past month as it brought global industries to a screeching halt and overwhelmed healthcare systems. From AI and big data to supercomputing, tech has been fighting back by leveraging complex data analysis to aid in diagnosis, epidemiology and treatment. Now, DarwinAI, a Canadian AI startup, has announced a new tool to fight back against the pandemic: COVID-Net. The news was announced in a blog post by Sheldon Fernandez, CEO of DarwinAI. "The global crisis brought on by COVID-19 has affected us all," Fernandez wrote.

Scientists have developed an artificial intelligence system that can translate a person's thoughts into text by analysing their brain activity. Researchers at the University of California, San Francisco, developed the AI to decipher up to 250 words in real time from a set of between 30 and 50 sentences. The algorithm was trained using the neural signals of four women with electrodes implanted in their brains, which were already in place to monitor epileptic seizures. The volunteers repeatedly read sentences aloud while the researchers fed the brain data to the AI to unpick patterns that could be associated with individual words. The average word error rate across a repeated set was as low as 3 per cent.

Kaitlin Ugolik Phillips Kaitlin Ugolik Phillips is a journalist and editor who lives in Raleigh, North Carolina. Her writing on law, finance, health, and technology has appeared in the Establishment, VICE, Quartz, Institutional Investor magazine, Law360, Columbia Journalism Review, and Narratively, among others. She writes a blog and newsletter about empathy featuring reportage, essays, and interviews. Her book The Future of Feeling is available from Little A.