HR researchers discovered the real reason why stressful jobs are killing us

Arianne Cohen
fastcompany.com
Originally posted 20 May 20

Your job really might kill you: A new study directly correlates on-the-job stress with death.

Researchers at Indiana University’s Kelley School of Business followed 3,148 Wisconsinites for 20 years and found heavy workload and lack of autonomy to correlate strongly with poor mental health and the big D: death. The study is titled “This Job Is (Literally) Killing Me.”

“When job demands are greater than the control afforded by the job or an individual’s ability to deal with those demands, there is a deterioration of their mental health and, accordingly, an increased likelihood of death,” says lead author Erik Gonzalez-Mulé, assistant professor of organizational behavior and human resources. “We found that work stressors are more likely to cause depression and death as a result of jobs in which workers have little control.”

The reverse was also true: Jobs can fuel good health, particularly jobs that provide workers autonomy.

The info is here.

Rebuilding the Economy Around Good Jobs

Zeynep Ton
Harvard Business Review
Originally posted 22 May 20

One thing we can predict: Customers who are struggling economically will be looking more than ever for good value. This will give the companies that start building a good jobs system a competitive advantage over those that don’t. After the financial crisis of 2008, Mercadona — Spain’s largest grocery chain and a model good jobs company — reduced prices for its hard-pressed customers by 10% while remaining profitable and gaining significant market share. Hard work and input from empowered front lines had a lot to do with it.

The pandemic is likely to accelerate the ongoing shakeup of U.S. retailing. The United States has 24.5 square feet of retail space per person versus 16.4 square feet in Canada and 4.5 square feet in Europe. This is almost certainly too much and the mediocre — the ones that don’t make their customers want to keep coming back — will not survive.

The pandemic is likely to speed up the adoption of new technologies. Although typically seen as a way to reduce headcount, adopting, scaling, and leveraging new technologies require a capable and motivated (even if smaller) workforce.

There is an alternative: A good jobs system that has already proven successful. Long before the pandemic, there were successful companies — including Costco and QuikTrip — that knew their frontline workers were essential personnel and treated and paid them as such. Even in very competitive, low-cost retail sectors, these companies adopted a good jobs system and used it to win.

There’s a strong financial case for good jobs. Offering good jobs lowers costs by reducing employee turnover, operational mistakes, and wasted time. It improves service, which increases sales both in the short term and — through customer loyalty — in the long term.

The info is here.

BlackRock’s New Morality Marks the End for Coal

Nathaniel Bullard
Bloomberg News
Originally posted 17 Jan 20

Here is an excerpt:

In the U.S., the move away from coal was well underway before the $7 trillion asset manager announced its restrictions. Companies have been shutting down coal-fired power plants and setting “transformative responsible energy plans” removing coal from the mix completely, even in the absence of robust federal policies. 

U.S. coal consumption in power generation fell below 600 million tons last year. This year, the U.S. Energy Information Administration expects it to fall much further still, below 500 million tons. That’s not only down by more than 50% since 2007, but it would also put coal consumption back to 1978 levels.

That decline is thanks to a massive number of plant retirements, now totaling more than 300 since 2010. The U.S. coal fleet has not had any net capacity additions since 2011. 2015 is the most significant year for coal retirements to date, as a suite of Obama-era air quality standards took effect. 2018 wasn’t far behind, however, and 2019 wasn’t far behind 2018.

The base effect of a smaller number of operational coal plants also means that consumption is declining at an accelerating rate. Using the EIA’s projection for 2020 coal burn in the power sector, year-on-year consumption will decline nearly 15%, the most since at least 1950.

Coal’s decline doesn’t exist in isolation. Most coal in the U.S. travels from mine to plant by rail, so there’s a predictable impact on rail cargoes. A decade ago, U.S. rail carriers shipped nearly 7 million carloads of coal. Last year, that figure was barely 4 million.

The info is here.

Robots in Finance Could Wipe Out Some of Its Highest-Paying Jobs

Lananh Nguyen
Bloomberg.com
Originally poste 6 Dec 19

Robots have replaced thousands of routine jobs on Wall Street. Now, they’re coming for higher-ups.

That’s the contention of Marcos Lopez de Prado, a Cornell University professor and the former head of machine learning at AQR Capital Management LLC, who testified in Washington on Friday about the impact of artificial intelligence on capital markets and jobs. The use of algorithms in electronic markets has automated the jobs of tens of thousands of execution traders worldwide, and it’s also displaced people who model prices and risk or build investment portfolios, he said.

“Financial machine learning creates a number of challenges for the 6.14 million people employed in the finance and insurance industry, many of whom will lose their jobs -- not necessarily because they are replaced by machines, but because they are not trained to work alongside algorithms,” Lopez de Prado told the U.S. House Committee on Financial Services.

During the almost two-hour hearing, lawmakers asked experts about racial and gender bias in AI, competition for highly skilled technology workers, and the challenges of regulating increasingly complex, data-driven financial markets.

The info is here.

What jobs are affected by AI? Better-paid, better-educated workers face the most exposure

M. Muro, J. Whiton, & R. Maxim
Brookings
Originally posted 20 Nov 19

Here is an excerpt:

AI could affect work in virtually every occupational group. However, whereas research on automation’s robotics and software continues to show that less-educated, lower-wage workers may be most exposed to displacement, the present analysis suggests that better-educated, better-paid workers (along with manufacturing and production workers) will be the most affected by the new AI technologies, with some exceptions.

Our analysis shows that workers with graduate or professional degrees will be almost four times as exposed to AI as workers with just a high school degree. Holders of bachelor’s degrees will be the most exposed by education level, more than five times as exposed to AI than workers with just a high school degree.

Our analysis shows that AI will be a significant factor in the future work lives of relatively well-paid managers, supervisors, and analysts. Also exposed are factory workers, who are increasingly well-educated in many occupations as well as heavily involved with AI on the shop floor. AI may be much less of a factor in the work of most lower-paid service workers.

Men, who are overrepresented in both analytic-technical and professional roles (as well as production), work in occupations with much higher AI exposure scores. Meanwhile, women’s heavy involvement in “interpersonal” education, health care support, and personal care services appears to shelter them. This both tracks with and accentuates the finding from our earlier automation analysis.

The info is here.

U.S. companies put record number of robots to work in 2018

Reuters
Originally published February 28, 2019


U.S. companies installed more robots last year than ever before, as cheaper and more flexible machines put them within reach of businesses of all sizes and in more corners of the economy beyond their traditional foothold in car plants.

Shipments hit 28,478, nearly 16 percent more than in 2017, according to data seen by Reuters that was set for release on Thursday by the Association for Advancing Automation, an industry group based in Ann Arbor, Michigan.

Shipments increased in every sector the group tracks, except automotive, where carmakers cut back after finishing a major round of tooling up for new truck models.

The info is here.

Can we collaborate with robots or will they take our place at work?

TU/e Research Project
ethicsandtechnology.eu

Here is an excerpt:

Finding ways to collaborate with robots

In this project, the aim is to understand how robotisation in logistics can be advanced whilst maintaining workers’ sense of meaning in work and general well-being, thereby preventing or undoing resilience towards robotisation. Sven Nyholm says: “People typically find work meaningful if they work within a well-functioning team or if they view their work as serving some larger purpose beyond themselves. Could human-robot collaborations be experienced as team-work? Would it be any kind of mistake to view a robot as a colleague? The thought of having a robot as a collaborator can seem a little weird. And yes, the increasingly robotized work environment is scary, but it is exciting at the same time. The further robotisation at work could give workers new important responsibilities and skills, which can in turn strengthen the feeling of doing meaningful work”.

The information in here.

British Public Fears the Day When "Computer Says No"

Jasper Hamill
The Metro
Originally published May 31, 2018

Governments and tech companies risk a popular backlash against artificial intelligence (AI) unless they open up about how it will be used, according to a new report.

A poll conducted for the Royal Society of Arts (RSA) revealed widespread concern that AI will create a ‘Computer Says No’ culture, in which crucial decisions are made automatically without consideration of individual circumstances.

If the public feels ‘victimised or disempowered’ by intelligent machines, they may resist the introduction of new technologies, even if it holds back progress which could benefit them, the report warned.

Fear of inflexible and unfeeling automatic decision-making was a greater concern than robots taking humans’ jobs among those taking part in a survey by pollsters YouGov for the RSA.

The information is here.

Evolving Morality

Joshua Greene
Aspen Ideas Festival
2017

Human morality is a set of cognitive devices designed to solve social problems. The original moral problem is the problem of cooperation, the “tragedy of the commons” — me vs. us. But modern moral problems are often different, involving what Harvard psychology professor Joshua Greene calls “the tragedy of commonsense morality,” or the problem of conflicting values and interests across social groups — us vs. them. Our moral intuitions handle the first kind of problem reasonably well, but often fail miserably with the second kind. The rise of artificial intelligence compounds and extends these modern moral problems, requiring us to formulate our values in more precise ways and adapt our moral thinking to unprecedented circumstances. Can self-driving cars be programmed to behave morally? Should autonomous weapons be banned? How can we organize a society in which machines do most of the work that humans do now? And should we be worried about creating machines that are smarter than us? Understanding the strengths and limitations of human morality can help us answer these questions.

The one-hour talk on SoundCloud is here.

Automation on our own terms

Benedict Dellot and Fabian Wallace-Stephens
Medium.com
Originally published September 17, 2017

Here is an excerpt:

There are three main risks of embracing AI and robotics unreservedly:

1. A rise in economic inequality — To the extent that technology deskills jobs, it will put downward pressure on earnings. If jobs are removed altogether as a result of automation, the result will be greater returns for those who make and deploy the technology, as well as the elite workers left behind in firms. The median OECD country has already seen a decrease in its labour share of income of about 5 percentage points since the early 1990s, with capital’s share swallowing the difference. Another risk here is market concentration. If large firms continue to adopt AI and robotics at a faster rate than small firms, they will gain enormous efficiency advantages and as a result could take excessive share of markets. Automation could lead to oligopolistic markets, where a handful of firms dominate at the expense of others.
2. A deepening of geographic disparities — Since the computer revolution of the 1980s, cities that specialise in cognitive work have gained a comparative advantage in job creation. In 2014, 5.5 percent of all UK workers operated in new job types that emerged after 1990, but the figure for workers in London was almost double that at 9.8 percent. The ability of cities to attract skilled workers, as well as the diverse nature of their economies, makes them better placed than rural areas to grasp the opportunities of AI and robotics. The most vulnerable locations will be those that are heavily reliant on a single automatable industry, such as parts of the North East that have a large stock of call centre jobs.
3. An entrenchment of demographic biases — If left untamed, automation could disadvantage some demographic groups. Recall our case study analysis of the retail sector, which suggested that AI and robotics might lead to fewer workers being required in bricks and mortar shops, but more workers being deployed in warehouse operative roles. Given women are more likely to make up the former and men the latter, automation in this case could exacerbate gender pay and job differences. It is also possible that the use of AI in recruitment (e.g. algorithms that screen CVs) could amplify workplace biases and block people from employment based on their age, ethnicity or gender.

The article is here.

The Data Scientist Putting Ethics In AI

By Poornima Apte
The Daily Dose
Originally published SEPT 25 2017

Here is an excerpt:

Chowdhury’s other personal goal — to make AI accessible to everyone — is noble, but if the technology’s ramifications are not yet fully known, might it not also be dangerous? Doomsday scenarios — AI as the rapacious monster devouring all our jobs — put forward in the media may not be in our immediate futures, but Alexandra Whittington does worry that implicit human biases could make their way into the AI of the future — a problem that might be exacerbated if not accounted for early on, before any democratization of the tools occurs. Whittington is a futurist and foresight director at Fast Future. She points to a recent example of AI in law where the “robot-lawyer” was named Ross, and the legal assistant had a woman’s name, Cara. “You look at Siri and Cortana, they’re women, right?” Whittington says. “But they’re assistants, not the attorney or the accountant.” It’s the whole garbage-in, garbage-out theory, she says, cautioning against an overly idealistic approach toward the technology.

The article is here.

Why we must teach morality to robots: Podcast

Daniel Glaser

The Guardian

Originally published February 27, 2017

Every week comes a new warning that robots are taking over our jobs. People have become troubled by the question of how robots will learn ethics, if they do take over our work and our planet.

As early on as the 1960s Isaac Asimov came up with the ‘Three Laws of Robotics’ outlining moral rules they should abide by. More recently there has been official guidance from the British Standards Institute advising designers how to create ethical robots, which is meant to avoid them taking over the world.

From a neuroscientist’s perspective, they should learn more from human development. We teach children morality before algebra. When they’re able to behave well in a social situation, we teach them language skills and more complex reasoning. It needs to happen this way round. Even the most sophisticated bomb-sniffing dog is taught to sit first.

If we’re interested in really making robots think more like we do, we can’t retrofit morality and ethics. We need to focus on that first, build it into their core, and then teach them to drive.

The 30-minute podcast is here.

The Simple Economics of Machine Intelligence

Ajay Agrawal, Joshua Gans, and Avi Goldfarb
Harvard Business Review
Originally published November 17, 2016

Here are two excerpts:

The first effect of machine intelligence will be to lower the cost of goods and services that rely on prediction. This matters because prediction is an input to a host of activities including transportation, agriculture, healthcare, energy manufacturing, and retail.

When the cost of any input falls so precipitously, there are two other well-established economic implications. First, we will start using prediction to perform tasks where we previously didn’t. Second, the value of other things that complement prediction will rise.

(cut)

As machine intelligence improves, the value of human prediction skills will decrease because machine prediction will provide a cheaper and better substitute for human prediction, just as machines did for arithmetic. However, this does not spell doom for human jobs, as many experts suggest. That’s because the value of human judgment skills will increase. Using the language of economics, judgment is a complement to prediction and therefore when the cost of prediction falls demand for judgment rises. We’ll want more human judgment.

The article is here.