The United Nations Educational, Scientific, and Cultural Organization (UNESCO) today unveiled its latest Science Report. The massive undertaking -- this year's report totals 762 pages, compiled by 70 authors from 52 countries over 18 months -- is published every five years to examine current trends in science governance. This latest edition includes discussion of the rapid progress toward Industry 4.0 and, for the first time, a deep analysis of AI and robotics research around the globe. Going beyond just the global leaders, it offers an overview of almost two dozen countries and global regions, examining AI research, funding, strategies, and more. Overall, the report determines "it is the field of AI and robotics that dominated scientific output" in recent years.

The conundrum is one that many governments face: how do you make the most of technological advances in areas such as artificial intelligence (AI) while protecting people's rights? This applies to government as both a user of the tech and a regulator with a mandate to protect the public. Australia's Human Rights Commission recently undertook an exercise to consider this very question. Its final report, Human Rights and Technology, was published recently and includes some 38 recommendations – from establishing an AI Safety Commissioner to introducing legislation so that a person is notified when a company uses AI in a decision that affects them. We have rounded up some of the report's recommendations for governments about how to ensure greater use of AI-informed decision-making does not result in human rights disaster.

Deep learning is gaining increasing popularity for spatiotemporal forecasting. However, prior works have mostly focused on point estimates without quantifying the uncertainty of the predictions. In high stakes domains, being able to generate probabilistic forecasts with confidence intervals is critical to risk assessment and decision making. Hence, a systematic study of uncertainty quantification (UQ) methods for spatiotemporal forecasting is missing in the community. In this paper, we describe two types of spatiotemporal forecasting problems: regular grid-based and graph-based. Then we analyze UQ methods from both the Bayesian and the frequentist point of view, casting in a unified framework via statistical decision theory. Through extensive experiments on real-world road network traffic, epidemics, and air quality forecasting tasks, we reveal the statistical and computational trade-offs for different UQ methods: Bayesian methods are typically more robust in mean prediction, while confidence levels obtained from frequentist methods provide more extensive coverage over data variations. Computationally, quantile regression type methods are cheaper for a single confidence interval but require re-training for different intervals. Sampling based methods generate samples that can form multiple confidence intervals, albeit at a higher computational cost.

They would also look to make available computing power to analyze the data, with the goal of allowing access to researchers across the country. "This is a moment that is calling us to be strengthening our speed and scale" when it comes to advances in AI technology, said National Science Foundation Director Sethuraman Panchanathan in an interview. "It is also calling us to make sure that innovation is everywhere." The task force, which Congress mandated in the National Artificial Intelligence Initiative Act of 2020, is part of an effort across the government to ensure the U.S. remains at the vanguard of technological advancements. The Senate this week approved a bipartisan bill to invest $250 billion in technology research and development, and the House is considering similar legislation.

The modern business world is littered with examples where organisations hastily rolled out artificial intelligence (AI) and machine learning (ML) solutions without due consideration of ethical issues, which has led to very costly and painful learning lessons. Internationally, for example, IBM is getting sued after allegedly misappropriating data from an app while Goldman Sachs is under investigation for using an allegedly discriminatory AI algorithm. A closer homegrown example was the Robodebt debacle, in which the federal government deployed ill-thought-through algorithmic automation to send out letters to recipients demanding repayment of social security payments dating back to 2010. The government settled a class action against it late last year at an eye-watering cost of $1.2 billion after the automated mailouts system targeted many legitimate social security recipients.

AutoX, Momenta and WeRide took the stage at TC Sessions: Mobility 2021 to discuss the state of robotaxi startups in China and their relationships with local governments in the country. They also talked about overseas expansion -- a common trajectory for China's top autonomous vehicle startups -- and shed light on the challenges and opportunities for foreign AV companies eyeing the massive Chinese market. Worldwide, regulations play a great role in the development of autonomous vehicles. In China, policymaking for autonomous driving is driven from the bottom up rather than a top-down effort by the central government, observed executives from the three Chinese robotaxi startups. Huan Sun, Europe general manager at Momenta, which is backed by the government of Suzhou, a city near Shanghai, said her company had a "very good experience" working with the municipal governments across multiple cities.

Asif Khan has been chosen for a DARPA Young Faculty Award. Khan is an assistant professor in the Georgia Tech School of Electrical and Computer Engineering (ECE), where he has been on the faculty since 2017. Khan is receiving this award for his research on ferroelectric field-effect transistors for embedded non-volatile memory applications. Ferroelectric field-effect transistors is one of the most-promising device technologies for artificial intelligence (AI) and machine learning (ML) hardware, due to its energy efficiency and compatibility with high-volume semiconductor manufacturing. The project will focus on solving the critical voltage problem of this device technology, by identifying and implementing new strategies for interface defect reduction in and the downscaling of the ferroelectric gate-dielectric stack.

To understand the promise and peril of artificial intelligence for food safety, consider the story of Larry Brilliant. Brilliant is a self-described "spiritual seeker," "social change addict," and "rock doc." During his medical internship in 1969, he responded to a San Francisco Chronicle columnist's call for medical help to Native Americans then occupying Alcatraz. Then came Warner Bros.' call to have him join the cast of Medicine Ball Caravan, a sort-of sequel to Woodstock Nation. That caravan ultimately led to a detour to India, where Brilliant spent 2 years studying at the foot of the Himalayas in a monastery under guru Neem Karoli Baba. Toward the end of the stay, Karoli Baba informed Brilliant of his calling: join the World Health Organization (WHO) and eradicate smallpox. He joined the WHO as a medical health officer, as a part of a team making over 1 billion house calls collectively. In 1977, he observed the last human with smallpox, leading WHO to declare the disease eradicated. After a decade battling smallpox, Brilliant went on to establish and lead foundations and start-up companies, and serve as a professor of international health at the University of Michigan. As one corporate brand manager wrote, "There are stories that are so incredible that not even the creative minds that fuel Hollywood could write them with a straight face."[1]

As drones become a bigger part of modern warfare, fighting forces are devising creative ways to disable them. The U.S. military recently demonstrated a drone interceptor that fires pink'Silly String'-like streamers at unmanned craft, gumming up their rotors and bringing them crashing down to Earth. The goal is to devise anti-drone technology that doesn't cause as much collateral damage as explosives, according to the Defense Advanced Research Projects Agency (DARPA), and would be used in populated areas. DARPA began developing the interceptor, known as Counter-Unmanned Air System (C-UAS), four years ago as a means to stop small self-guided unmanned aircraft without the kind of major collateral damage caused by gunfire or explosives. In a video posted this week, DARPA demonstrated C-UAS at Eglin Air Force Base outside Valparaiso, Florida.

Fox News Flash top headlines are here. Check out what's clicking on Foxnews.com. Yellowstone National Park announced Wednesday that it is testing its first autonomous electric shuttle. T.E.D.D.Y., or The Electric Driverless Demonstration in Yellowstone, is a small vehicle with a big job. Annual visitation to the park has increased by almost 40% since 2008 – by 1 million people in the last decade, causing issues like parking lot overflow, traffic jams, unsanitary conditions, roadside soil erosion and vegetation trampling.