AI News, The future of work: Will robots take my job? artificial intelligence

TechTalk ep1: Are robots really taking over our jobs?

Artificial intelligence AI has been quite the talk of the town lately, particularly for its touted capacity to take over our jobs.

What's still keeping us, let's say, from moving forward is the fact that the machine can advance only based on whatever we are teaching it.

If I give 750 images of a chair to a machine and I associate the label, the word “chair” with the images, the machine will always be able to associate the word, just the word, you know this string of characters.

So if you think how we perceive knowledge and we manipulate knowledge and information, as humans we are way more advanced.

But I need this kind of knowledge, structured knowledge in order to make sense of the information in order to put the algorithms providing improved results.

So when we talk about let's say our work you know the kind of work that we are doing here and you know I spoke to you about it… the banner that we had in the Experience Center that said “Robots are not taking over our jobs”.

And when we think about robots and about the way they manipulate information, robots they are only enablers like this table or the chair.

If the robot has, for example, a humanoid like face, we’ll build empathy and we’ll think that it's intelligent that it's more intelligent than this chair, than the table.

So in the service industry what's changed drastically is the fact that for the tools which are enabled by good encyclopaedias of knowledge, of domain knowledge, together with A.I.

for navigating this information, we will have faster services, better in predicting, as good as the information we provided.

Domain knowledge can come from manufacturing, it can come from the carpenter, it can come from the financial industry, it can come from any domain.

So we have the two pillars, one being the technical one where you need technical skills like understanding the data but also how to navigate the data.

So you just think there's magic and you put the algorithm sand you put some data which is relevant now in this moment for this environment.

We don't have generally artificial intelligence, so you need to build the tools and you can be part of the process of building that.

If we have more and more frauds, the job will shift from treating the normal to treating the abnormal and also adapting, creating tools to adapt to these new situations.

So I would say no human being can be replaced by automation because our particularity is that we adapt, we are able to adapt ourselves and we always create knowledge.

We have singularity… Where it’s said that artificial intelligence, synthetic intelligence would overpass human intelligence.

So, I would think human being has an important role in creating tools and putting controls where we think that the speed of computation or the memory capacity is over passing that of the human.

The decision is always with the human because we have the theory of computing where Vilfredo Pareto (Italian engineer, sociologist, economist), explained that whenever we are faced with a real problem we have several criteria which can be different by nature or contradictory and there is no ideal solution.

On European level or in the world that you know businesses or governments are providing to employees for them to adapt and to train for this change that's happening?

E: Yes, that's a good question because actually we were working in the national programme In Luxembourg called Skills Bridge which aims in preparing the workforce for the new skills.

It identifies what skills are necessary in order to transition to a new position, what new positions appeared and also what training is required.

E: Yes, I can think of one particular programme: Skills for Europe, which is run by the European Commission and in which we are working together and identifying what are the new skills which will be required and how education can be adapted to prepare for these new skills.

We have a background service which allows us to have fast access to information, like here with electricity, we have fast access to light.

In the olden times, we relied on books and we had this linear access to information… from left to right, from right to left.

And what we are lacking now and we need to build in order to empower ourselves is the encyclopaedias of knowledge for the machine with correlation, explaining the context, domain by domain.

So we all have valuable opinions on our specific areas and we can all contribute to these encyclopaedias of knowledge and put the control points in the encyclopaedias so that when it becomes operational and the machine crunches the data, we know that we can stop it at the critical moments or the waning moments.

So we all have a place in this industrial evolution of artificial intelligence, access to information because we are all bearers of knowledge.

Are Robots Competing for Your Job?

In a downward compression of the labor market, these jobs have been taken not so much by robots as by college graduates: as much as forty per cent of college graduates are currently working at jobs that do not require a college degree, Ellen Ruppel Shell reports, in “The Job: Work and Its Future in a Time of Radical Change” (Currency).

This is a logical inevitability—everything else will be done by globots.” The catch is that, historically, caring, sharing, understanding, and empathizing with people who are in the same room as you has been the work of women, and is therefore either unpaid, and not recognized as work, or paid very badly.

In the middle decades of the twentieth century, he argues, economic policymakers abandoned workers and the health of the labor market in favor of a commitment to over-all economic growth, with redistribution as an adjustment and consumerism as its objective.

Here he mocks the advocates of the current economic arrangement, who are prone to note that the poor are not actually starving, “and so many people have iPhones!” Reporters are suckers for the hype, Cass maintains, pointing out that after a 2017 study by the National Bureau of Economic Research suggested that, in the next hundred years, robots might eliminate as many manufacturing jobs as were lost in 2001 (presumably, a tolerable loss), the Times ran a story with the headline “Evidence That Robots Are Winning the Race for American Jobs,” while the Washington Post titled its story “We’re So Unprepared for the Robot Apocalypse.” Cass offers a careful criticism of the robots-are-stealing-our-jobs theory.

Highly vulnerable are school-bus drivers, and, while a self-driving school bus does not seem technically too far off, Cass points out, few parents can imagine putting their kids on a bus without a grownup to make sure they don’t bash one another the whole way to school.

Cass’s own policy proposals center, very reasonably, on the importance of work and family, but he fails to demonstrate how his proposals—lowering environmental regulations and establishing academic tracking in high schools—will achieve his objectives.

The Future of Work for Women

To be sure, there are compelling reasons for policymakers to focus on the challenges facing male workers vulnerable to automation and technological change.Automation in the manufacturing sector over the last several decades has disproportionately impacted men with a high school degree or less, resulting in steep declines in wages, economic stability, and status.Many prime age men have left the labor force altogether.

Yet the overwhelming focus on male workers has obscured the reality that the next waves of automation will have a profound impact on women - perhaps even more so than on men - because women are disproportionately employed in automation-risky jobs.

Increasingly, artificial intelligence, machine learning and smart software are enabling workplace automation well beyond the factory floor, from customer service chatbots, to virtual assistants, to AI-assisted disease diagnosis.

Advanced technology will therefore impact a much wider set of tasks, jobs and skills than what we have seen to date - from food preparation, to back office work, to logistics, customer service and accounting.

This high risk work includes clerical roles like secretaries, back office and administrative staff, as well as frontline service jobs such as cashiers and fast food workers.

(The Bureau of Labor Statistics report just over 9 million people in male-dominated “production occupations” in 2017, compared to nearly 22 million workers “office and administrative roles”, the vast majority of which are women.) As a result, we find that female workers in the US are currently employed in jobs that are at higher technical risk for automation than male workers.

Looking at the US workforce as a whole, we find that women constitute 54% of workers employed in high risk occupations, despite comprising less than half of the total labor force.

This trend holds true even in our Indianapolis analysis, in a city known for transportation, logistics and other male-dominated blue-collar work -- but where 55% of high risk jobs are held by women.

These jobs include fast-growing jobs in data science, artificial intelligence, machine learning specialists, computer programming and positions that we cannot yet imagine today.

(See the next point about the rise of care jobs.) On the other hand, roles in management, leadership and advanced cognitive work are much harder to automate than more routine roles, even within the same industry or sector.

For instance, a customer service representative or a fast food worker faces a higher risk of automation than does his or her first-line manager, and faces orders of magnitude higher risk than the company’s executive leadership team.

While this growth spells good news from a job numbers perspective for women, the reality is that these jobs are very poorly paid and offer little economic security, stability, legal protections, physical security or upward mobility.

(See Claudia Goldin and Lawrence Katz’s excellent book, The Race Between Education and Technology, for a detailed history of this relationship.) As MIT economist David Autor pointed out, automation since the 1980s has contributed to the polarization of the labor market by shrinking the number of middle-paying jobs -- mainly clerical work and manufacturing roles - while increasing the number of jobs at both the low paying and high paying ends.

Buoyed by myriad social and economic factors, the percent of women in the US labor force with a college degree nearly quadrupled since 1970, from 11 percent to 40 percent in 2016.

We cannot plan and develop strategies that serve all Americans if we don’t first acknowledge the ways that women are uniquely impacted by technological change and create strategies and policies that address their specific needs.

A range of legal, logistical, business, financial, political, and social factors could lower the real rate at which businesses and employers adopt technology and automate functions.

The Rise of the Machines

A website called, which calculates the probability of certain jobs being automated, puts lawyers at a relatively safe 4% risk of being replaced by automation, while paralegals and legal assistants are at 94%—“Automation Risk Level: You Are Doomed” is the site’s deadpan prognosis for these professionals.

But lawyers who are resistant to technology as a whole might need to be reminded that employment anxiety is only the tip of the iceberg: law’s relationship to artificial intelligence promises to grow in scope and complexity in the coming years, as a February 15 conference at Fordham Law confirmed.

The conference, titled Rise of the Machines: Artificial Intelligence, Robotics, and the Reprogramming of Law, brought together a diverse and interdisciplinary array of professionals, including attorneys, neuroscientists, and technologists, to explore current and near-future developments in robotics, artificial intelligence, law, and policy.

Instead of asking, “Who is responsible?” when a weapons system malfunctions and harms innocent people, Crootof suggested we ask “What is the appropriate liability?” Indeed, allocating full blame on a software engineer for unintended deaths caused by an AI malfunction could be a troubling precedent to set.

The fourth and final panel of the day was “Protecting Consumers’ Privacy and Ensuring Ethical Data Practices.” Panelist Oliver Round ’07, counsel and vice president at BNY Mellon, talked about the day-to-day challenges of dealing with new technology while working at a law firm.

Reskilling for Robots: AI and the future of jobs

By David Leaser Just five years ago, the late scientist Stephen Hawking made a dire prediction: The “development of full artificial intelligence (AI) could spell the end of the human race.”  These ideas are not new.

So, let’s get this out-of-the-way now:  Robots are not going to spell the end of the human race, but AI technology has the potential to transform the labor market by eliminating some jobs, creating new jobs and making most jobs better.

Just as the combine harvester supplanted the scythe, clocks replaced the sundial and electric lights extinguished the candle, the personal computer recently replaced the ledger book.

According to a new report from the World Economic Forum, machines and algorithms in the workplace are expected to create 133 million new roles, but cause 75 million jobs to be displaced by 2022.

The research states that while AI could displace roughly 7 million jobs in the country, it could also create 7.2 million jobs, resulting in a modest net boost of around 200,000 jobs.

The researchers looked at the relationship between productivity growth and employment and found industry-level employment falls as industry productivity rises, implying that technically progressive sectors tend to shrink.

The Autor/Salomons study also showed that wages of less-educated workers in the United States and Germany have fallen sharply over the last two to three decades despite a steep reduction in the non-college share of the working age population.

An American study supports this: Two years ago, a US Government report titled “Artificial Intelligence, Automation, and the Economy” predicted 83% of United States  jobs in which people make less than $20 per hour are now, or soon will be, subject to automation.

The advent of computers and the Internet raised the productivity of highly skilled workers, but it had a negative impact on predictable tasks and roles like  travel agents, bookkeepers, and telephone switchboard operators, not to mention manufacturing assembly line jobs.  So what will AI automation do to the labor market?

These AI-driven business and technology jobs will require human beings to complement the tasks performed by cognitive technology and ensure the work of machines is effective, fair and transparent: Trainers — Trainers will help natural-language processors and language translators make fewer errors..

Of these, about 35% are expected to require additional training of up to six months, about 10% will require reskilling lasting six to 12 months, while 10% will require additional skills training of more than a year.

Most companies are adopting three strategies to manage the coming skills gap created by emerging technologies: However, nearly a quarter of companies are undecided or unlikely to pursue the retraining of existing employees.

Programs must start early and ensure children can develop relevant skills and continue through lifelong reskilling programs for people who must transition to new roles.

The board brings together 25 prominent Americans, including Ginny Rometty, CEO, President and Chairman of IBM, promising to create more than 6.5 million education, training and skill-building opportunities over the next five years.

“I look forward to finding new ways for all Americans to participate in this digital era by building the job skills that are already in demand in our economy.” As AI becomes more prominent in the workforce, human capital can be unleashed to focus on less manual and more innovative tasks.

In addition to the new technical jobs which will emerge because of AI, distinctly human skills, like creativity, originality, analytical thinking and innovation will rise in importance while memory-related tasks and manual work will be performed by robots.

These systems rely on inference by developing profiles based on skills developed in learning activities, articles written and questions answered in online communities.

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