Last summer, Microsoft’s Japan office tried an experiment. For one month, the office closed on Fridays, giving workers an extra day off, while paying them a full-time salary. Management also decided that no meetings would last more than 30 minutes and urged employees to cut down the amount of time they spent responding to emails.
Jobs play a central role in the lives of most adults.
As forces like globalization and automation reshape the labor market, it is clear that some people and places are positioned to do well while others risk becoming collateral damage. The well-educated and technically savvy find ample employment opportunities, while those with lower levels of education face a labor market that is decidedly less welcoming, with lower wages and less potential for career growth.
Meanwhile, some regions dramatically outpace others in job growth, incomes, and productivity, raising disquieting questions about how best to promote broad-based economic growth.
Against this backdrop, we provide in a new report extensive demographic and occupational data on low-wage workers nationally and in more than 350 metropolitan areas. It is a large and diverse group of people, and they play a major role in our economy.
Let’s say that on average you are in better shape than other people of your age. You are more able than them: quicker, sprightlier, livelier. You feel and identify as younger than your official age. However, despite all your youthful energy, you are also discriminated against because of your greater age.
You cannot get a job – or, if you do, you might earn less than some of your younger coworkers simply due to your advanced years.
The question is, should you be allowed to change your ‘official’ age in order to avoid this discrimination and to better match how you identify and feel?
“We know that all organisms are capable of some form of learning, we just weren’t sure how those abilities first evolved. Now we can watch these major evolutionary events unfold before us in a virtual world,” says lead author Anselmo Pontes, a computer science researcher at Michigan State University.
“Understanding how learning behavior evolved helps us figure out how it works and provides insights to other fields such as neuroscience, education, psychology, animal behavior, and even AI. It also supplies clues to how our brains work and could even lead to robots that learn from experiences as effectively as humans do.”
According to coauthor Fred Dyer, a professor of integrative biology, these findings have the potential for huge implications.
In the aftermath of the fatal Apollo 1 launchpad fire in January 1967 — among the most egregious examples of sacrificing safety and reliability to schedule — NASA learned the hard lessons of the avoidable tragedy, pulled up its socks and built some of the most reliable machines ever devised by engineers.
Among them was the one component of the American lunar landing that lacked redundancy, a design imperative for manned spaceflight: the ascent engine that would lift moon walkers off the lunar surface to rendezvous with the orbiting mother ship, the Apollo command module.
Virtually every component of the Apollo Saturn V and spacecraft had redundant systems, often multiple redundancy. Space is deadly, the engineers and astronauts were always looking for ways to reduce the inevitable risks.
Boston Dynamics raised a lot of eyebrows earlier this year when it announced it would be making one of its robots commercially available by the end of this year. But this week the company officially announced that its dog-like robot, Spot, is now available for order via the company website.
Spot is a four-legged, animal-like robot that the company is pushing less as a singular-use machine and more as a customizable platform that can be adapted to a range of tasks. The base unit has sensors and cameras allowing for 360-degree vision for navigation (including rough terrain and climbing stairs) and obstacle avoidance. It can move at a speed of 1.6 m/s, carry a payload of up to 14 kg (about 31 lbs), and run for 90 minutes on one charge of its swappable battery. It can be operated via remote control or function autonomously.
Where Boston Dynamics hopes the value for Spot will be found is in its level of customization.
Spot can be customized with the addition of hardware, such as an articulating grabber arm, or with specialized sensors. The company has also released two software development kits (SDKs) along with Spot.
The goal to create industrial networks that are fully interoperable, completely secure, and cloud connected while communicating in real time poses some major challenges for Industry 4.0
The widespread push to increase network connectivity, machine productivity, and security for interconnected devices on the factory floor has forced hardware companies to adapt to the increasing advancement toward the industrial internet of things (IIoT), better known as Industry 4.0.
In theory, the ultimate goal of Industry 4.0 is to make networks that are fully interoperable, completely secure, cloud connected, and able to communicate in real time. However, these aims pose some major technology challenges for Industry 4.0 in the near term.
How will Industry 4.0 designers address interoperability, security, and the growing trend for IIoT gateways?
Artificial intelligence (AI) experts at SRI International in Menlo Park, Calif., are helping U.S. military researchers determine if autonomous machines are self-aware of their own competencies and limitations to carry out assigned tasks.
How does a person know if he’s smart enough to do the job … if he has a skill set that’s adequate for the task at hand? It sounds simple, but it’s a fundamental ability necessary for trust and team building.
Now apply the same question to artificial intelligence technology and machine learning? How does a machine know if it’s smart enough to do the job? That’s what DARPA and SRI International are aiming at.
Hungary has signed a deal with China to modernize the railway link between Budapest and Belgrade. The project – the first major Chinese infrastructure deal inside the EU – aims to facilitate the distribution of goods arriving at the Chinese-owned port of Piräus, but critics say it might be a waste of taxpayer money.
.. the line will mostly operate cargo transport of Chinese goods.
Yes, and it will touch only one Hungarian city between Budapest and the Serbian border. And the transportation route between Belgrade and the port of Piräus has not even been planned yet.
Also, China did not only buy the port of Piräus but is also holding substantial shares of other ports in Europe – so it has plenty of entrance points to Europe. So I think the transportation line, of which Budapest-Belgrade will be part of, is actually not in a privileged position from the Chinese perspective.
How do behavioral science approaches fit into the broader ecosystem of government improvement efforts? More specifically, what is being done to foster organic growth in the understanding and use of these approaches in the public sector? And how do we bridge their use between academics and practitioners?
David Yokum, a pioneer in the field, says: “Applied research can be remarkably difficult, as theories often fail to work in practice. We need scientists shoulder to shoulder with practitioners in those moments, co-designing fresh ideas and iteratively experimenting to optimize solutions.”
A critical mass of talent has evolved in recent years among government practitioners, commercial and non-profit entities, and academia. There is also substantial sharing among them.
As I’ve noted in previous pieces on this topic, there are pockets of talent and experience in using behavioral insights across the government, at all levels.
What follows is a brief overview of some of the resources available.