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Archive for the ‘employment’ category: Page 30

Jul 16, 2022

Firm managers may benefit from transparency in machine-learning algorithms

Posted by in categories: business, education, employment, information science, robotics/AI

In today’s business world, machine-learning algorithms are increasingly being applied to decision-making processes, which affects employment, education, and access to credit. But firms usually keep algorithms secret, citing concerns over gaming by users that can harm the predictive power of algorithms. Amid growing calls to require firms to make their algorithms transparent, a new study developed an analytical model to compare the profit of firms with and without such transparency. The study concluded that there are benefits but also risks in algorithmic transparency.

Conducted by researchers at Carnegie Mellon University (CMU) and the University of Michigan, the study appears in Management Science.

“As managers face calls to boost , our findings can help them make decisions to benefit their firms,” says Param Vir Singh, Professor of Business Technologies and Marketing at CMU’s Tepper School of Business, who coauthored the study.

Jul 16, 2022

X-energy’s TRISO-X Fuel Fabrication Facility to Produce Fuel for Advanced Nuclear Reactors

Posted by in categories: economics, employment, nuclear energy

The TRISO-X, LLC Fuel Fabrication Facility (TF3) will be the nation’s first High-Assay, Low-Enriched Uranium (HALEU) fuel fabrication facility. TRISO-X is a wholly owned subsidiary of advanced reactor designer X-energy, LLC. TF3 will use uranium enriched between 5% and 20% to produce fuel for advanced and small modular reactors of the future. TF3 will manufacture TRi-structural ISOtropic (TRISO) fuel, an advanced fuel that is tough enough to handle the higher operating temperatures of several advanced reactors under development.

The U.S. Department of Energy (DOE) is supporting the development of TF3 through an award with X-energy, LLC under the Advanced Reactor Demonstration Program (ARDP) 0, which aims to speed the demonstration of advanced reactors through cost-shared partnerships with the U.S. nuclear industry. The design and license application development of TF3 was also supported through an $18M (federal cost share) industry FOA that was awarded to X-energy in 2018. TF3 will initially provide the TRISO fuel for X-energy’s Xe-100 high-temperature gas reactor.

“The TRISO-X Fuel Fabrication Facility represents the intersection of some of DOE’s hard work to bring advanced reactors to commercialization,” said Alice Caponiti, DOE’s Deputy Assistant Secretary for Reactor Fleet and Advanced Reactor Deployment. “We’ve been investing in R&D on TRISO fuels for decades. Now, with funding through ARDP, TF3 will bring the next evolution of nuclear fuel to reality, advancing new nuclear technology, creating new jobs, and supporting the clean energy economy.”

Jul 9, 2022

13 percent of U.S. adults report serious psychological distress during COVID-19

Posted by in categories: biotech/medical, employment, finance, health

Serious psychological distress among U.S. adults remained fairly steady between April and July 2020, according to a research letter published online Nov. 23 in the Journal of the American Medical Association.

Emma E. McGinty, Ph.D., from the Johns Hopkins Bloomberg School of Public Health in Baltimore, and colleagues conducted two waves of the Johns Hopkins COVID-19 Civic Life and Public Health Survey (April 7 to April 13, 2020, and July 7 to July 22, 2020). Changes in during the COVID-19 pandemic was evaluated among 1,337 U.S. adults.

The researchers found that 13 percent of respondents reported serious in July 2020 versus 14.2 percent in April 2020, with 72 percent of adults reporting serious distress in both waves. The prevalence of serious distress was highest among adults aged 18 to 29 years (25.4 percent in April versus 26.5 percent in July), those with income less than $35,000 (20.2 percent in April versus 21.2 percent in July), and Hispanic individuals (17.9 percent in April versus 19.2 percent in July) at both time points. Among those with serious distress, the most common stressors were concerns about contracting COVID-19 (65.9 percent) and pandemic effects on employment (65.1 percent) and finances (60.6 percent). Educational interruptions were a stressor among adults with serious distress attending college and/or with (69 percent).

Jul 9, 2022

Coronavirus lockdown made many of us anxious. But for some people, returning to ‘normal’ might be scarier

Posted by in categories: biotech/medical, employment, neuroscience

Many Australians have welcomed the gradual easing of coronavirus restrictions. We can now catch up with friends and family in small numbers, and get out and about a little more than we’ve been able to for a couple of months.

All being well, restrictions will continue to be lifted in the weeks and months to come, allowing us slowly to return to some kind of “normal”.

This is good news for the economy and employment, and will hopefully help ease the high levels of distress and mental health problems our community has been experiencing during the pandemic.

Jul 8, 2022

Fixing Shoulder Pain: Harvard Scientists Develop a Method To Restore Damaged Tendons and Muscles

Posted by in category: employment

The typical office worker often has soreness throughout their body as a result of their sedentary desk jobs. Even young individuals may develop shoulder pain, which was previously primarily an issue for elderly people. Once shoulder pain creeps in, it is difficult to dress oneself, let alone move one’s body freely. It is also difficult to fall asleep. While the rotator cuffs are often naturally harmed as we age, repairing them has shown to be difficult.

Jul 6, 2022

Computer Chips That Imitate the Brain

Posted by in categories: biotech/medical, employment, robotics/AI

A multi-institutional collaboration, which includes the U.S. Department of Energy’s (DOE) Argonne National Laboratory, has created a material that can be used to create computer chips that can do just that. It achieves this by using so-called “neuromorphic” circuitry and computer architecture to replicate brain functions. Purdue University professor Shriram Ramanathan led the team.

“Human brains can actually change as a result of learning new things,” said Subramanian Sankaranarayanan, a paper co-author with a joint appointment at Argonne and the University of Illinois Chicago. “We have now created a device for machines to reconfigure their circuits in a brain-like way.”

With this capability, artificial intelligence-based computers might do difficult jobs more quickly and accurately while using a lot less energy. One example is analyzing complicated medical images. Autonomous cars and robots in space that might rewire their circuits depending on experience are a more futuristic example.

Jun 30, 2022

FBI says people are using deepfakes to apply for remote tech jobs

Posted by in categories: employment, internet, robotics/AI

What else can deepfakes do?We’ve seen examples of deepfakes being used almost to change the course of history when a Zelensky footage emerged back in March and told the Ukrainian army to lay down arms amid the Russian invasion. Fortunately, it was sloppy, and the army didn’t buy that. And now, if you consider what happens when a post-covid world that birthed many remote job opportunities for digital nomads merges with AI, The FBI Internet Crime Complaint Center (IC3) has t… See more.


The Federal Bureau of Investigation (FBI) has warned that some people are using deepfakes to apply for remote tech jobs.

Jun 12, 2022

AI’s Threats to Jobs and Human Happiness Are Very Real

Posted by in categories: economics, education, employment, existential risks, finance, robotics/AI, transportation

There’s a movement afoot to counter the dystopian and apocalyptic narratives of artificial intelligence. Some people in the field are concerned that the frequent talk of AI as an existential risk to humanity is poisoning the public against the technology and are deliberately setting out more hopeful narratives. One such effort is a book that came out last fall called AI 2041: Ten Visions for Our Future.

The book is cowritten by Kai-Fu Lee, an AI expert who leads the venture capital firm Sinovation Ventures, and Chen Qiufan, a science fiction author known for his novel Waste Tide. It has an interesting format. Each chapter starts with a science fiction story depicting some aspect of AI in society in the year 2041 (such as deepfakes, self-driving cars, and AI-enhanced education), which is followed by an analysis section by Lee that talks about the technology in question and the trends today that may lead to that envisioned future. It’s not a utopian vision, but the stories generally show humanity grappling productively with the issues raised by ever-advancing AI.

IEEE Spectrum spoke to Lee about the book, focusing on the last few chapters, which take on the big issues of job displacement, the need for new economic models, and the search for meaning and happiness in an age of abundance. Lee argues that technologists need to give serious thought to such societal impacts, instead of thinking only about the technology.

Jun 5, 2022

Opinion We’re in the midst of a ‘great return to work.’ It’s worth celebrating

Posted by in category: employment

More than 6.5 million jobs have come back in the past year, one of the greatest employment rebounds in U.S. history.

May 28, 2022

Is diversity the key to collaboration? New AI research suggests so

Posted by in categories: biotech/medical, employment, robotics/AI

A new training approach yields artificial intelligence that adapts to diverse play-styles in a cooperative game, in what could be a win for human-AI teaming.

As artificial intelligence gets better at performing tasks once solely in the hands of humans, like driving cars, many see teaming intelligence as a next frontier. In this future, humans and AI are true partners in high-stakes jobs, such as performing complex surgery or defending from missiles. But before teaming intelligence can take off, researchers must overcome a problem that corrodes cooperation: humans often do not like or trust their AI partners.

Now, new research points to diversity as being a key parameter for making AI a better team player.

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