We Need to Retool Higher Ed to Defeat Robots

Thousands of years ago, the agricultural revolution led our foraging ancestors to take up the scythe and plough. Hundreds of years ago, the Industrial Revolution pushed farmers out of fields and into factories. Just tens of years ago, the technology revolution ushered many people off the shop floor and into the desk chair and office cube.

Today, we are living through yet another revolution in the way that human beings work for their livelihoodsand once again, this revolution is leaving old certainties scrapped and smoldering on the ash heap of history. Once again, it is being powered by new technologies. But instead of the domesticated grain seed, the cotton gin, or the steam engine, the engine of this revolution is digital and robotic.

We live in a time of technological marvels. Computers continue to speed up while the price of processing power continues to plummet, doubling and redoubling the capabilities of machines. This is driving the advance of machine learningthe ability of computers to learn from data instead of from explicit programmingand the push for artificial intelligence. As economists Erik Brynjolfsson and Andrew McAfee note in their book The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies, we have recently hit an inflection point in which our machines have reached their full force to transform the world as comprehensively as James Watts engine transformed an economy that once trundled along on ox carts. Labor experts are increasingly and justifiably worried that computers are becoming so adept at human capabilities that soon there will be no need for any human input at all.

The evidence for this inflection point is everywhere. Driverless cars are now traversing the streets of Pittsburgh, Pennsylvania, and other cities. New robots can climb stairs and open doors with ease. An advanced computer trounced the human grandmaster of the intricate Chinese strategy game Go. Moreover, it is not only the processing power of machines that has skyrocketed exponentially but also the power of their connectivity, their sensors, their GPS systems, and their gyroscopes. Today, we are giving computers not only artificial intelligence but, in effect, artificial eyes, ears, hands, and feet.

Consequently, these capacities are enabling computers to step into rolesand jobsonce held exclusively by members of our species. Robots now analyze stocks, write in deft and informative prose, and interact with customers. Semi-autonomous machines may soon join soldiers on the battlefield. In China, co-botsmachines that can work in factories safely alongside human beingsare upending that countrys vaunted manufacturing sector, allowing fewer laborers to be vastly more productive. In 2015, sales of industrial robots around the world increased by 12 percent over the previous year, rising to nearly a quarter of a million units.

At the same time, Big Data is revolutionizing everything from social science to business, with organizations amassing information in proportions that flirt with the infinite. Algorithms mine bottomless troves of data and then apply the information to new functions, essentially teaching themselves. Machine learning now powers everything from our spam filters to our Amazon shopping lists and dating apps, telling us what to watch, what to buy, and whom to love. Deep learning systems, in which artificial neural networks identify patterns, can now look at an image and recognize a chair or the face of a human individual or teach themselves how to play a video game without ever reading the instructions.

In many ways, these new technologies are an astonishing boon for humanity, giving us the power to mitigate poverty, hunger, and disease. For example, Stanley S. Litow, vice president of corporate citizenship and corporate affairs at IBM, is overseeing an initiative between Memorial Sloan Kettering Hospital in New York City and Watson, the computer that famously beat the human champions of the television game show Jeopardy! A doctor who had watched the show approached IBM with the idea to collaborate. Thus, Watson was reborn as an oncology adviser. Computer scientists at IBM embedded it with information from the hospitals clinical trials (not just some, all of them, said Litow) and trained it through data analytics to respond to oncologists questions.

So it proceeds as if talking to a potential patient, said Litow. On a mobile device I can say, She has the following characteristics. Do we have any information on clinical trials that would help me figure out whether this is the problem or that is the problem? Watson then analyzes the data and responds to the oncologists question in normal English. Theres a lot of clinical trial information, but a lot of doctors dont have access to it, said Litow. It is actually helping some of the best oncologists in the United States make a better, faster diagnosis and move toward a treatment plan quickly. In treating cancer, thats critical.

Automation long has been considered a threat to low-skilled labor, but increasingly, any predictable work is now within the purview of machines.

Watsons next challenge is to improve teaching in the New York City public school system, advising educators on effective teaching practices by using the same data analytics and communication techniques it is deploying with such success at Sloan Kettering. Technologies like Watson are helping people save lives, teach fractions, andin their less sophisticated iterationsfind the nearest parking space. They are helping people work better.

Or they are, for the moment. Automation long has been considered a threat to low-skilled labor, but increasingly, any predictable workincluding many jobs considered knowledge economy jobsis now within the purview of machines. This includes many high-skill functions, such as interpreting medical images, doing legal research, and analyzing data.

As advanced machines and computers become more and more proficient at picking investments, diagnosing disease symptoms, and conversing in natural English, it is difficult not to wonder what the limits to their capabilities are. This is why many observers believe that technologys potential to disrupt our economyand our civilizationis unprecedented.

Over the past few years, my conversations with students entering the workforce and the business leaders who hire them have revealed something important: to stay relevant in this new economic reality, higher education needs a dramatic realignment. Instead of educating college students for jobs that are about to disappear under the rising tide of technology, 21st century universities should liberate them from outdated career models and give them ownership of their own futures. They should equip them with the literacies and skills they need to thrive in this new economy defined by technology, as well as continue providing them with access to the learning they need to face the challenges of life in a diverse, global environment. Higher education needs a new model and a new orientation away from its dual focus on undergraduate and graduate students. Universities must broaden their reach to become engines for lifelong learning.

There is a great deal of evidence that we need such an educational shift. An oft-quoted 2013 study from Oxford University found that nearly half of U.S. jobs are at risk of automation within the next twenty years. In many cases, that prediction seems too leisurely. For example, new robotic algorithmic trading platforms are now tearing through the financial industry, with some estimates holding that software will replace between one-third and one-half of all finance jobs in the next decade. A 2015 McKinsey report found that solely by using existing technologies, 45 percent of the work that human beings are paid to do could be automated, obviating the need to pay human employees more than $2 trillion in annual wages in the United States.

This is not the first time we have faced a scenario like this. In past industrial revolutions, the ploughmen and weavers who fell prey to tractors and spinning jennies had to withstand a difficult economic and professional transition. However, with retraining, they could reasonably have expected to find jobs on the new factory floors. Likewise, as the Information Age wiped out large swaths of manufacturing, many people were able to acquire education and training to obtain work in higher-skilled manufacturing, the service sector, or the office park. Looking ahead, education will remain the ladder by which people ascend to higher economic rungs, even as the jobs landscape grows more complex. And it undoubtedly is getting knottier. One of the reasons for this is that the worldwide supply of labor continues to rise while the net number of high-paying, high-productivity jobs appears to be on the decline. To employ more and more people, we will need to create more and more jobs. It is not clear where we will find them.

Certainly, the emergence of new industriessuch as those created in the tech sectorwill have to step up if they are going fill this gap. According to the U.S. Bureau of Labor Statistics, the computer and information technology professions are projected to account for a total of 4.4 million jobs by 2024. In the same period, the labor force, age 16 and older, is expected to reach 163.7 million. Adding to the disjoint is the remarkable labor efficiency of tech companies. For instance, Google, the standard bearer for the new economy, had 61,814 full-time employees in 2015. At its peak in 1979, in contrast, General Motors counted 600,000 employees on its payroll. To address the deficit, well need creative solutions.

Apart from automation, many other factors are stirring the economic pot. Globalization is the most apparent, but environmental unsustainability, demographic change, inequality, and political uncertainty are all having their effects on how we occupy our time, how we earn our daily bread, and how we find fulfillment. Old verities are melting fast. The remedies are not obvious.

Some observers have been encouraged by the growth of the gig economy, in which people perform freelance tasks, such as driving a car for Uber, moving furniture through TaskRabbit, or typing text for Amazon Mechanical Turk. But earnings through these platforms are limited. Since 2014, the number of people who earn 50 percent or more of their income from gig platforms has actually fallen. In general, these platforms give people a boost to earnings and help to pay the monthly bills. But as an economic engine, they have not emerged as substitutes for full-time jobs.

Of the new full-time jobs that are appearing, many are so-called hybrid jobs that require technological expertise in programming or data analysis alongside broader skills. Fifty years ago, no one could have imagined that user-experience designer would be a legitimate profession, but here we are. Clearly, work is changing. All these factors create a complex and unexplored terrain for job seekers, begging some important questions: How should we be preparing people for this fast-changing world? How should education be used to help people in the professional and economic spheres?

As a university president, this is no small question for me. As a matter of fact, the university I lead, Northeastern, is explicitly concerned with the connections between education and work. As a pioneer in experiential learning, grounded in the co-op model of higher education, Northeasterns mission has always been to prepare students for fulfillingand successfulroles in the professional world. But lately, as I have observed my students try to puzzle out their career paths, listened to what employers say they are looking for in new employees, and take stock of what I read and hear every day about technologys impact on the world of professional work, I have come to realize that the existing model of higher education has yet to adapt to the seismic shifts rattling the foundations of the global economy.

Machines will help us explore the universe, but human beings will face the consequences of discovery.

I believe that college should shape students into professionals but also creators. Creation will be at the base of economic activity and also much of what human beings do in the future. Intelligent machines may liberate millions from routine labor, but there will remain a great deal of work for us to accomplish. Great undertakings like curing disease, healing the environment, and ending poverty will demand all the human talent that the world can muster. Machines will help us explore the universe, but human beings will face the consequences of discovery. Human beings will still read books penned by human authors and be moved by songs and artworks born of human imagination. Human beings will still undertake ethical acts of selflessness or courage and choose to act for the betterment of our world and our species. Human beings will also care for our infants, give comfort to the infirm, cook our favorite dishes, craft our wines, and play our games. There is much for all of us to do.

To that end, this book offers an updated model of higher educationone that will develop and empower a new generation of creators, women and men who can employ all the technological wonders of our age to thrive in an economy and society transformed by intelligent machines. It also envisions a higher education that continues to deliver the fruits of learning to students long after they have begun their working careers, assisting them throughout their lives. In some ways, it may seem like a roadmap for taking higher education in a new direction. However, it does not offer a departure as much as a continuity with the centuries-old purpose of colleges and universitiesto equip students for the rigors of an active life within the world as it exists today and will exist in the future. Education has always served the needs of society. It must do so now, more than ever. That is because higher education is the usher of progress and change. And change is the defining force of our time.

A UNIQUELY HUMAN EDUCATION

Education is its own reward, equipping us with the mental furniture to live a rich, considered existence. However, for most people in an advanced society and economy such as ours, it also is a prerequisite for white-collar employment. Without a college degree, typical employees will struggle to climb the economic ladder and may well find themselves slipping down the rungs.

When the economy changes, so must education. It has happened before. We educate people in the subjects that society deems valuable. As such, in the 18th century, colonial colleges taught classics, logic, and rhetoric to cadres of future lawyers and clergymen. In the 19th century, scientific and agricultural colleges rose to meet the demands of an industrializing world of steam and steel. In the 20th century, we saw the ascent of professional degrees suited for office work in the corporate economy.

Today, the colonial age and the industrial age exist only in history books, and even the office age may be fast receding into memory. We live in the digital age, and students face a digital future in which robots, software, and machines powered by artificial intelligence perform an increasing share of the work humans do now. Employment will less often involve the routine application of facts, so education should follow suit. To ensure that graduates are robot- proof in the workplace, institutions of higher learning will have to rebalance their curricula.

A robot-proof model of higher education is not concerned solely with topping up students minds with high-octane facts. Rather, it refits their mental engines, calibrating them with a creative mindset and the mental elasticity to invent, discover, or otherwise produce something society deems valuable. This could be anything at alla scientific proof, a hip-hop recording, a new workout regimen, a web comic, a cure for cancer. Whatever the creation, it must in some manner be original enough to evade the label of routine and hence the threat of automation. Instead of training laborers, a robot-proof education trains creators.

The field of robotics is yielding the most advanced generation of machines in history, so we need a disciplinary field that can do the same for human beings. In the pages that follow, I lay out a framework for a new disciplinehumanicsthe goal of which is to nurture our species unique traits of creativity and flexibility. It builds on our innate strengths and prepares students to compete in a labor market in which brilliant machines work alongside human professionals. And much as todays law students learn both a specific body of knowledge and a legal mindset, tomorrows humanics students must master specific content as well as practice uniquely human cognitive capacities.

In the chapters ahead, I describe both the architecture and the inner workings of humanics, but here I begin by explaining its twofold nature. The first side, its content, takes shape in what I call the new literacies. In the past, literacy in reading, writing, and mathematics formed the baseline for participation in society, while even educated professionals did not need any technical proficiencies beyond knowing how to click and drag through a suite of office programs. That is no longer sufficient. In the future, graduates will need to build on the old literacies by adding three moredata literacy, technological literacy, and human literacy. This is because people can no longer thrive in a digitized world using merely analog tools. They will be living and working in a constant stream of big data, connectivity, and instant information flowing from every click and touch of their devices. Therefore, they need data literacy to read, analyze, and use these ever-rising tides of information. Technological literacy gives them a grounding in coding and engineering principles, so they know how their machines tick. Lastly, human literacy teaches them humanities, communication, and design, allowing them to function in the human milieu.

As noted earlier, knowledge alone is not sufficient for the work of tomorrow. The second side of humanics, therefore, is not a set of content areas but rather a set of cognitive capacities. These are higher-order mental skillsmindsets and ways of thinking about the world. The first is systems thinking, the ability to view an enterprise, machine, or subject holistically, making connections between its different functions in an integrative way. The second is entrepreneurship, which applies the creative mindset to the economic and often social sphere. The third is cultural agility, which teaches students how to operate deftly in varied global environments and to see situations through different, even conflicting, cultural lenses. The fourth capacity is that old chestnut of liberal arts programs, critical thinking, which instills the habit of disciplined, rational analysis and judgment.

Together, the new literacies and the cognitive capacities integrate to help students rise above the computing power of brilliant machines by engendering creativity. In doing so, they enable them to collaborate with other people and machines while accentuating the strengths of both. Humanics can, in short, be a powerful toolset for humanity.

This book also explores how people grasp these tools. To acquire the cognitive capacities at a high level, students must do more than read about them in the classroom or apply them in case studies or classroom simulations. To cement them in their minds, they need to experience them in the intensity and chaos of real work environments such as co-ops and internships. Just as experiential learning is how toddlers puzzle out the secrets of speech and ambulation, how Montessori students learn to read and count, and how athletes and musicians perfect their jump shots or arpeggios, it also is how college students learn to think differently. This makes it the ideal delivery system for humanics.

A new model of higher education must, however, account for the fact that learning does not end with the receipt of a bachelors diploma. As machines continue to surpass their old boundaries, human beings must also continue to hone their mental capacities, skills, and technological knowledge. People rarely stay in the same career track they choose when they graduate, so they need the support of lifelong learning. Universities can deliver this by going where these learners are. This means a fundamental shift in our delivery of education but also in our idea of its timing. It no longer is sufficient for universities to focus solely on isolated years of study for undergraduate and graduate students. Higher education must broaden its view of whom to serve and when. It must serve everyone, no matter their stage in life.

By 2025, our planet will count eight billion human inhabitants, all of them with human ambition, intelligence, and potential. Our planet will be more connected and more competitive than the one we know today. Given the pace of technologys advance, we can predict that computers, robots, and artificial intelligence will be even more intricately intertwined into the fabric of our personal and professional lives. Many of the jobs that exist now will have vanished. Others that will pay handsomely have yet to be invented. The only real certainty is that the world will be differentand with changes come challenges as well as opportunities. In many cases, they are one and the same.

Education is what sets them apart.

Excerpted from Robot Proof: Higher Education in the Age of Artificial Intelligence by Joseph E. Aoun. Copyright 2017 by Joseph E. Aoun. Published by MIT Press.

Read more: https://www.thedailybeast.com/we-need-to-retool-higher-ed-to-defeat-robots

Collection of letters by codebreaker Alan Turing found in filing cabinet

The correspondence, dating from 1949 to 1954, was found by an academic in a storeroom at the University of Manchester

A lost collection of nearly 150 letters from the codebreaker Alan Turing has been uncovered in an old filing cabinet at the University of Manchester.

The correspondence, which has not seen the light of day for at least 30 years, contains very little about Turings tortured personal life. It does, however, give an intriguing insight into his views on America.

In response to an invitation to speak at a conference in the US in April 1953, Turing replied that he would rather not attend: I would not like the journey, and I detest America.

The letter, sent to Donald Mackay, a physicist at Kings College London, does not give any further explanation for Turings forthright views on America, nor do these views feature in any of the other 147 letters discovered earlier this year.

The correspondence, dating from early 1949 to Turings death in 1954, was found by chance when an academic cleared out an old filing cabinet in a storeroom at the University of Manchester. Turing was deputy director of the universitys computing laboratory from 1948, after his heroic wartime codebreaking at Bletchley Park.

Turing was a visionary mathematician and is regarded today as the father of modern computing who broke the Nazis second world war Enigma code. While his later life has been overshadowed by his conviction for gross indecency and his death aged 41 from cyanide poisoning, a posthumous pardon was granted by the Queen in 2013. His life was featured in the 2014 film the Imitation Game.

Prof Jim Miles, of the universitys school of computer science, said he was amazed to stumble upon the documents, contained in an ordinary-looking red paper file with Alan Turing scrawled on it.

When I first found it I initially thought: That cant be what I think it is, but a quick inspection showed it was a file of old letters and correspondence by Alan Turing, he said.

I was astonished such a thing had remained hidden out of sight for so long. No one who now works in the school or at the university knew they even existed. It really was an exciting find and it is mystery as to why they had been filed away.

The collection focuses mainly on Turings academic research, including his work on groundbreaking areas in AI, computing and mathematics, and invitations to lecture at some of Americas best-known universities including the Massachusetts Institute of Technology.

It contains a single letter from GCHQ, for whom Turing worked during the war, asking the mathematician in 1952 if he could supply a photograph of himself for an official history of Bletchley Park that was being compiled by the American cryptographer William Friedman. In his reply to Eric Jones, GCHQs then director, Turing said he would send a picture for the American rogues gallery.

The collection also contains a handwritten draft BBC radio programme on artificial intelligence, titled Can machines think? from July 1951. The documents were sorted, catalogued and stored by the University of Manchester archivist James Peters and are now available to search online.

Peters said: This is a truly unique find. Archive material relating to Turing is extremely scarce, so having some of his academic correspondence is a welcome and important addition to our collection.

There is very little in the way of personal correspondence, and no letters from Turing family members. But this still gives us an extremely interesting account and insight into his working practices and academic life whilst he was at the University of Manchester.

He added: The letters mostly confirm what is already known about Turings work at Manchester, but they do add an extra dimension to our understanding of the man himself and his research.

As there is so little actual archive on this period of his life, this is a very important find in that context. There really is nothing else like it.

Read more: https://www.theguardian.com/science/2017/aug/27/collection-letters-codebreaker-alan-turing-found-filing-cabinet

Malala Yousafzai: notes from my Girl Power trip to Nigeria

In a few months Ill be starting at university. If only more girls around the world had this opportunity

Three days ago, I returned from my second visit to Nigeria.

Nigeria is the richest country in Africa, but it has the highest number of out-of-school girls in the world. When I first visited the country in 2014, the government spent 9% of its budget on education. This year its only 6%. (The international benchmark for spending on education is 20% of the overall budget.)

When planning where I would travel on my Girl Power Trip this summer, I knew I needed to return to Nigeria and advocate again for the millions of girls fighting to go to school.

In some states, particularly in northern Nigeria, extremism terrorises communities and makes education impossible for many children, particularly girls.

During my trip, I travelled to Maiduguri, the birthplace of Boko Haram. In a camp for people displaced by terrorism, I met girls like 15-year-old Fatima, who have faced so much violence and fear in their young lives but are still determined to go to school.

Boko Haram abducted me and wanted to marry me, Fatima told me. I later managed to escape. I was not in school until I came to the camp here.

Malala
Inadequate government spending, corruption and poverty keep girls from getting an education and pursuing their dreams. Photograph: Tess Thomas/Malala Fund

Leaders in this area, like Borno State governor Kashim Shettima, are working against extreme challenges to keep children in school. When we met, Shettima told me hes determined to rewrite history through education for children who suffer so much under Boko Haram.

In other regions of Nigeria, inadequate government spending, corruption and poverty keep girls from getting an education and pursuing their dreams.

Kehinde and Taiwo are 14-year-old twins living in Lagos. In the poor community where they live, there is no public school. When their mother contracted a serious illness and couldnt work, the family could no longer afford to pay $70 per term for their private tuition. Today, Kehinde and Taiwo work 12 hours a day grinding peppers. They earn $2 a day or less, and use the money to feed their family.

Taiwo loves mathematics and wants to be a banker. Kehinde says shed like to be a nurse and help sick people like her mother. But neither of these sisters or millions of Nigerian girls like them can achieve their dreams without education.

Malala
I knew I needed to return to Nigeria and advocate again for the millions of girls fighting to go to school. Photograph: Tess Thomas/Malala Fund

Nigeria has the means to help these girls but the government hasnt prioritised education. Thats why I met with the acting president, Yemi Osinbajo, and asked him to declare an education state of emergency in Nigeria. I urged him, the minister of education and other leaders to triple spending on education, make budgets transparent and encourage all states in Nigeria to pass the Childs Rights Act.

Osinbajo said leaders would meet again in the next two weeks to address the education crisis and he agrees Nigeria must invest significantly in education.

Malala Fund and I will keep monitoring Nigerias progress. I hope my next visit to the country can be a celebration of many more girls going to school, learning and preparing for a brighter future.

My ambitions are high, but so are those of Fatima, Kehinde, Taiwo and all the girls I meet on my travels. I will keep speaking out until all girls can go to school. My sisters and I are fighting for a world where all girls can learn and lead without fear. I hope you will join us.

Follow Guardian Students on Twitter: @GdnStudents.

Read more: https://www.theguardian.com/education/2017/jul/21/malala-yousafzai-girl-power-trip-nigeria-women-education

Maryam Mirzakhani, first woman to win mathematics’ Fields medal, dies at 40

Stanford professor, who was awarded the prestigious prize in 2014, had suffered breast cancer

Maryam Mirzakhani, a Stanford University professor who was the first and only woman to win the prestigious Fields medal in mathematics, has died. She was 40.

Mirzakhani, who had breast cancer, died on Saturday, the university said. It did not indicate where she died.

In 2014, Mirzakhani was one of four winners of the Fields medal, which is presented every four years and is considered the mathematics equivalent of the Nobel prize. She was named for her work on complex geometry and dynamic systems.

Mirzakhani specialized in theoretical mathematics that read like a foreign language by those outside of mathematics: moduli spaces, Teichmller theory, hyperbolic geometry, Ergodic theory and symplectic geometry, the Stanford press announcement said.

Mastering these approaches allowed Mirzakhani to pursue her fascination for describing the geometric and dynamic complexities of curved surfaces spheres, doughnut shapes and even amoebas in as great detail as possible.

Her work had implications in fields ranging from cryptography to the theoretical physics of how the universe came to exist, the university said.

Mirzakhani was born in Tehran and studied there and at Harvard. She joined Stanford as a mathematics professor in 2008. Irans president, Hassan Rouhani, issued a statement praising Mirzakhani.

The grievous passing of Maryam Mirzakhani, the eminent Iranian and world-renowned mathematician, is very much heart-rending, Rouhani said in a message that was reported by the Tehran Times.

Irans foreign minister, Mohammad Javad Zarif, said her death pained all Iranians, the newspaper reported.

The news of young Iranian genius and math professor Maryam Mirzakhanis passing has brought a deep pang of sorrow to me and all Iranians who are proud of their eminent and distinguished scientists, Zarif posted in Farsi on his Instagram account.

I do offer my heartfelt condolences upon the passing of this lady scientist to all Iranians worldwide, her grieving family and the scientific community.

Mirzakhani originally dreamed of becoming a writer but then shifted to mathematics. When she was working, she would doodle on sheets of paper and scribble formulas on the edges of her drawings, leading her daughter to describe the work as painting, the Stanford statement said.

Mirzakhani once described her work as like being lost in a jungle and trying to use all the knowledge that you can gather to come up with some new tricks, and with some luck you might find a way out.

Stanford president Marc Tessier-Lavigne said Mirzakhani was a brilliant theorist who made enduring contributions and inspired thousands of women to pursue math and science.

Mirzakhani is survived by her husband, Jan Vondrk, and daughter, Anahita.

Read more: https://www.theguardian.com/us-news/2017/jul/15/maryam-mirzakhani-mathematician-dies-40

College-educated women earn $8,000 less a year than men as gap widens

The gender wage gap among 2016 graduates has increased, as men make about $4 more an hour than women, according to Economic Policy Institute study

The gender wage gap is not shrinking its growing. Female college graduates now earn $8,000 a year less than their male contemporaries, a gap that has widened in the past 16 years, according to a new report published by the Economic Policy Institute.

Young male college graduates earned 8.1% more in 2016 than in 2000, while young female college graduates earned 6.8% less than in 2000, according to Elise Gould, senior economist at EPI and one of the reports authors.

That gender wage gap has increased in a meaningful way, Gould said. If you just look at their wages in 2016, on average young men who are college graduates are making $20.94 compared to $16.58 for women. Thats a difference of more than $4. Over the year, thats more than $8,000.

According to Gould, this is due to the fact that men in higher positions are driving up wages for men lower on the totem pole as well. For women, however, the wage gap gets wider as they move further up the pay scale.

Overall, women earn less than men. According to the US census, women were still earning just 79% of mens wages in 2014.

Critics of the gender wage gap theory point out that the discrepancy in pay between men and women is due to the types of careers women opt for. Meaning that women are more likely to work in lower-paying jobs like retail, fast food, teaching or nursing.

Its an interesting idea when you say that out loud: Women chose lower paying jobs. Who would chose a lower paying job? How does that even make sense? said Gould. She added that its true women might be likely to select different majors than men and that men tend to end up in higher professions.

Its still remains a fact that even within occupations, even within lets say finance, women are making less than men. So some of it is because of the major or occupation that somebody chose, but those could also be driven by discrimination at younger ages.

According to her, there is a lack of encouragement for women to go into Stem fields science, technology, engineering and math. These fields, which tend to be dominated by men, are associated with higher paid positions.

Some say there isnt really a gender pay gap. Well, that is just wrong, said former secretary of state Hillary Clinton, when she appeared on a panel discussing equal pay last week. She, too, conceded that higher paying fields like engineering, science and mathematics can often be unwelcoming to women.

Gould also pointed out that the economy is filled with people who do not have a college degree. A strong economy caters to these workers usually high-school graduates and provides them with good jobs in which they can build a stable career, she said.

College graduates make up less than a third of US population. In 2014, 29.9% of men and 30.2% of women had graduated college. According to the US Census Bureau, it was the first year that womens college attainment was statistically higher than mens college attainment. Similarly, 65.8% of Americans aged 24 to 29 do not have a college degree, according to EPIs report.

However, female high school graduates are faced with narrower gender wage gap.

Gender wage gap among high school grads has been closing over the last several years. Thats due to the fact that women have been bolstered by minimum wage increases in cities and states, explained Gould, pointing out that women account for 55.9% of workers earning minimum wage. Its growing among college grads.

Read more: http://www.theguardian.com/business/2016/apr/21/gender-wage-gap-college-graduates-women-men