How Iranian immigrants can be role models for diversity in STEM

Of interest:

When I first came to the United States from Iran in 2007 for a doctorate in computer science and machine learning, I was surprised by how few women attended industry conferences. Those I did meet were usually fellow immigrants.

Diversity and gender equality drive creativity and spur innovation across the globe. It’s why the United Nations has declared Feb.11 the International Day of Women and Girls in Science and why the U.S. House of Representatives just launched the first-ever Women in STEM Caucus. The bipartisan initiative, started by four female congresswomen, now has 13 members from both sides of the aisle. The caucus aims to increase the presence of women and underrepresented minorities in STEM across the country.

In Tehran, where I grew up, it’s considered normal for girls to study computer programming from an early age. That culture has opened the door for new generations of female engineers. In fact, in Iran, nearly 70 percent of university graduates in science, technology, engineering and mathematics (STEM) are women.

That’s a sharp contrast with the United States, where women are vastly underrepresented in STEM fields. Data by the Council of Graduate Schools found that in 2018 U.S. women earned only about a quarter of PhDs in engineering, math and computer science. This is at a time when the United States is facing a critical shortage of STEM workers; in 2015, 14 states advertised 20 STEM jobs for every unemployed STEM worker, according to New American Economy. That demand is projected to grow over the next decade.

Today, I’m the executive vice president and chief algorithms officer for Overstock.com, a tech-driven online retailer committed to diversity. As an immigrant and a woman, I bring a wealth of experiences that help me see problems differently. Plenty of data shows women bring skill sets, strategic thinking and creativity valued by businesses. Women also take women’s needs to heart when creating products and services for them, whether it’s heart medication, seat belts or air bags designed for our physiques. Simply put, women are an essential part of the talent pool.

American companies should strive for increased diversity and inclusivity throughout their organizations. Teachers need to create inclusive classrooms that value girls’ and women’s opinions. Those of us in the field can create better representation by hiring and championing female colleagues or requesting female-friendly policies inside the companies where we work. Leaders in our communities also need to do more to encourage women, immigrants and minorities to enter STEM fields. I applaud the Congressional Women in STEM Caucus, whose mandate is to improve access to hands-on learning, technical training and real-world application of skills required in these jobs.

But we also need to remember the value of our personal stories in influencing young lives. If young American women and girls, including immigrants and minorities, are going to embrace STEM, they’re going to need more support and role models. As Caucus Co-Chair Rep. Chrissy Houlahan of West Chester, Pa., said, she was one of 10 women in her engineering major and doesn’t think the numbers have changed much in 30 years.

A 2018 study of 6,000 American young women conducted by Microsoft and KRC Research found that girls who know a woman in STEM are more than 70 percent more likely to know how to pursue a STEM career and what types of specific jobs might utilize a STEM skillset.

The study said parents’ encouragement was particularly influential in whether girls cultivated a love for science and technology and stuck with these fields over time. Likewise those of us already working in these industries can also serve as mentors for them, whether it’s volunteering at coding camps or sharing our enthusiasm for AI and robotics over ice cream.

Or we can simply raise our hands high in our communities and say: “This is what a female coder, engineer, biotech founder, mathematician or science professor looks like. You can be one, too.” That’s especially important, because 30 percent of girls and 40 percent of women described a man when asked what a “typical” scientist or engineer looked like.

As a woman in STEM, an Iranian American citizen and an immigrant, I want to encourage new generations to realize their potential. With any luck, I’ll see many more female faces at industry conferences to come.

Dr. Kamelia Aryafar is executive vice president and chief algorithms officer for Overstock.com.

Source: How Iranian immigrants can be role models for diversity in STEM

Canada must look beyond STEM and diversify its AI workforce

From a visible minority perspective, based on STEM graduates, representation reasonably good as per the chart above except for engineering and particularly strong in math and computer sciences, the closest fields of study to AI.

With respect to gender, the percentage of visible minority women is generally equivalent to that on non-visible minority women or stronger (but women are under-represented in engineering and math/computer sciences):

Artificial intelligence (AI) is expected to add US$15.7 trillion to the global economy by 2030, according to a recent report from PwC, representing a 14 percent boost to global GDP. Countries around the world are scrambling for a piece of the pie, as evidenced by the proliferation of national and regional AI strategies aimed at capturing the promise of AI for future value generation.

Canada has benefited from an early lead in AI, which is often attributed to the Canadian Institute for Advanced Research (CIFAR) having had the foresight to invest in Geoffrey Hinton’s research on deep learning shortly after the turn of the century. As a result, Canada can now tout Montreal as having the highest concentration of researchers and students of deep learning in the world and Toronto as being home to the highest concentration of AI start-ups in the world.

But the market for AI is approaching maturity. A report from McKinsey & Co. suggests that the public and private sectors together have captured only between 10 and 40 percent of the potential value of advances in machine learning. If Canada hopes to maintain a competitive advantage, it must both broaden the range of disciplines and diversify the workforce in the AI sector.

Looking beyond STEM

Strategies aimed at capturing the expected future value of AI have been concentrated on innovation in fundamental research, which is conducted largely in the STEM disciplines: science, technology, engineering and mathematics. But it is the application of this research that will grow market share and multiply value. In order to capitalize on what fundamental research discovers, the AI sector must deepen its ties with the social sciences.

To date the role of social scientists in Canada’s strategy on AI has been largely limited to areas of ethics and public policy. While these are endeavours to which social scientists are particularly well suited, they could be engaged much more broadly with AI. Social scientists are well positioned to identify and exploit potential applications of this research that will generate both social and economic returns on Canada’s investment in AI.

Social scientists take a unique approach to data analysis by drawing on social theory to critically interpret both the inputs and outputs of a given model. They ask what a given model is really telling us about the world and how it arrived at that result. They see potential opportunities in data and digital technology that STEM researchers are not trained to look for.

A recent OECD report looks at the skills that most distinguish innovative from non-innovative workers; chief among them are creativity, critical thinking and communication skills. While these skills are by no means exclusively the domain of the social sciences, they are perhaps more central to social scientific training than to any other discipline.

The social science perspective can serve as a defence mechanism against the potential folly of certain applications of AI. If social scientists had been more involved in early adaptations of computer vision, for example, Google might have been spared the shame of image recognition algorithms that classify people of colour as animals (they certainly would have come up with a better solution). In the same vein, Microsoft’s AI chatbots would have been less likely to spew racist slurs shortly after launch.

Social scientists can also help meet a labour shortage: there are not enough STEM graduatesto meet future demand for AI talent. Meanwhile, social science graduates are often underemployed, in part because they do not have the skills necessary to participate in a future of work that privileges expertise in AI. As a consequence, many of the opportunities associated with AI are passing Canada’s social science graduates by. Excluding social science students from Canada’s AI strategy not only reduces their career paths but restricts their opportunities to contribute to fulfilling the societal and economic promise of AI.

Realizing the potential of the social sciences within Canada’s AI ecosystem requires innovative thinking by both governments and universities. Federal and provincial governments should relax restrictions on funding for AI-related research that prohibit applications from social scientists or make them eligible only within interdisciplinary teams that include STEM researchers. This policy has the effect of subordinating social scientific approaches to AI to those of STEM disciplines. In fact, social scientists are just as capable of independent research, and a growing number are already engaged in sophisticated applications of machine learning to address some of the most pressing societal challenges of our time.

Governments must also invest in the development of undergraduate and graduate training opportunities that are specific to the application of AI in the social sciences, using pedagogical approaches that are appropriate for them.

Social science faculties in universities across Canada can also play a crucial role by supporting the development of AI-related skills within their undergraduate and graduate curriculums. At McMaster University, for example, the Faculty of Social Sciences is developing a new degree: master of public policy in digital society. Alongside graduate training in the fundamentals of public policy, the 12-month program will include rigorous training in data science as well as technical training in key digital technologies that are revolutionizing contemporary society. The program, which is expected to launch in 2021, is intended to provide students with a command of digital technologies such as AI necessary to enable them to think creatively and critically about its application to the social world. In addition to the obvious benefit of producing a new generation of policy leadership in AI, the training provided by this program will ensure that its graduates are well positioned for a broader range of leadership opportunities across the public and private sectors.

Increasing workplace diversity

A report released in 2019 by New York University’s AI Now Institute declared that there is a diversity crisis in the AI workforce. This has implications for the sector itself but also for society more broadly, in that the systemic biases within the AI sector are being perpetuated via the myriad touch points that AI has with our everyday lives: it is organizing our online search results and social media news feeds and supporting hiring decisions, and it may even render decisions in some court cases in future.

One of the main findings of the AI Now report was that the widespread strategy of focusing on “women in tech” is too narrow to counter the diversity crisis. In Canada, efforts to diversify AI generally translate to providing advancement opportunities for women in the STEM disciplines. Although the focus of policy-makers on STEM is critical and necessary, it is short-sighted. Disciplinary diversity in AI research not only broadens the horizons for research and commercialization; it also creates opportunities for groups who are underrepresented in STEM to benefit from and contribute to innovations in AI.

As it happens, equity-seeking groups are better represented in the social sciences. According to Statistics Canada, the social sciences and adjacent fields have the highest enrolment of visible minorities. And as of 2017, only 23.7 percent of those enrolled in STEM programs at Canadian universities were women, whereas women were 69.1 percent of participants in the social sciences.

So, engaging the social sciences more substantively in research and training related to AI will itself lead to greater diversity. While advancing this engagement, universities should be careful not to import training approaches directly from statistics or computer science, as these will bring with them some of the cultural context and biases that have resulted in a lack of diversity in those fields to begin with.

Bringing the social sciences into Canada’s AI strategy is a concrete way to demonstrate the strength of diversity, in disciplines as well as demographics. Not only would many social science students benefit from training in AI, but so too would Canada’s competitive advantage in AI benefit from enabling social scientists to effectively translate research into action.

Source: Canada must look beyond STEM and diversify its AI workforce

Immigrant kids in U.S. deliberately build STEM skills


Similar pattern in Canada (chart above looks at Canadian-born visible minority university and college graduates compared to Not VisMin):

U.S. immigrant children study more math and science in high school and college, which leads to their greater presence in STEM careers, according to new findings from scholars at Duke University and Stanford University.

“Most studies on the assimilation of immigrants focus on the language disadvantage of non-English-speaking immigrants,” said Marcos Rangel, assistant professor at Duke’s Sanford School of Public Policy. “We focus instead on the comparative strength certain immigrant children develop in numerical subjects, and how that leads to majoring in STEM subjects in college.”

About 20 percent of U.S.-born college students major in STEM subjects. Yet those numbers are much higher among immigrants — particularly among who arrive the U.S. after age 10, and who come from countries whose native languages are dissimilar to English, Rangel said. Within that group, 36 percent major in STEM subjects.

“Some children who immigrate to the U.S., particularly older children from a country where the main language is very dissimilar to English, quite rationally decide to build on skills they are relatively more comfortable with, such as math and science,” said Rangel.

Those older immigrant children take more math and science courses in high school, the authors found. Immigrant children arriving after age 10 earn approximately 20 percent more credits in math-intensive courses than they do in English-intensive courses.

This focus continues in college, where immigrant children are more likely to pursue science, technology, engineering and math majors. Those majors, in turn, lead to careers in STEM fields. Previous research has shown that immigrants are more highly represented in many STEM careers.

“Meaningful differences in skill accumulation … shape the consequent contributions of childhood immigrants to the educated labor force,” the authors write.

Source: Immigrant kids in U.S. deliberately build STEM skills

AI and the Automation of Jobs Disproportionately Affect Women, World Economic Forum Warns

Interesting analysis of gender and AI:

Women are disproportionately affected by the automation of jobs and development of artificial intelligence, which could widen the gender gap if more women are not encouraged to enter the fields of science, technology and engineering, the World Economic Forum warned on Monday.

Despite statistics showing that the economic opportunity gap between men and women narrowed slightly in 2018, the report from the World Economic Forum finds there are proportionally fewer women than men joining the workforce, largely due to the growth of automation and artificial intelligence.

According to the findings, the automation of certain jobs has impacted many roles traditionally held by women. Women also continue to be underrepresented in industries that utilize science, technology, engineering and mathematics (STEM) skills. This affects their presence in the booming field of AI. Currently, women make up 22% of AI professionals, a gender gap three times larger than other industries.

“This year’s analysis also warns about the possible emergence of new gender gaps in advanced technologies, such as the risks associated with emerging gender gaps in Artificial Intelligence-related skills,” the report’s authors write. “In an era when human skills are increasingly important and complementary to technology, the world cannot afford to deprive itself of women’s talent in sectors in which talent is already scarce.”

The World Economic Forum report ranked the the United States 51st worldwide for gender equality — above average, but below many other developed countries, as well as less-developed nations like Nicaragua, Rwanda and the Philippines. Women in the U.S. had better economic opportunities than those in Austria, Italy, South Korea and Japan, according to the World Economic Forum.

The U.S. fell two spots from its ranking 2017. While the gender gap improved slightly in economic opportunity and participation, the gap between men and women regarding access to education and political empowerment reversed, in part due to a decline in gender equality in top government positions.

The World Economic Forum, which is known for its annual conference in Davos, Switzerland, measured the gender gap around the world across four factors – political empowerment, economic opportunity, educational attainment and health and survival – to find that the gap has closed 68%, a slight improvement from 2017, which marked the first year since 2006 that the gender gap widened.

As the gender gap stands now, it will take about 108 years to close completely and 202 years to achieve total parity in the workplace.

Source: AI and the Automation of Jobs Disproportionately Affect Women, World Economic Forum Warns

Why Immigrants Do Better At Science And Math : NPR

Intuitively makes sense but nice to have more evidence that it is so:

Seventeen-year-old Indrani Das just won the top high school science prize in the country. Das, who lives in Oradell, N.J., took home $250,000 from the former Intel Science Talent Search, now the Regeneron Science Talent Search, for her study of brain injuries and neuron damage. In her spare time, she’s already working with patients as a certified EMT.

As the Times of India pointed out, Das was one of five Indian Americans among the competition’s top ten finishers. In last year’s contest, according to one study, more than 80 percent of finalists were the children of immigrants.

What is it that spurs so many recent arrivals to the United States to excel in science, technology, engineering and math, or STEM disciplines? Some invoke cultural stereotypes, like that of the “Tiger Mother,” for an explanation.

Not Marcos Rangel. For a new study published in the journal Demography, Rangel, an economist at Duke University, and his co-author, Marigee Bacolod of the U.S. Naval Postgraduate School, looked at U.S. Census data for young adults who arrived in the United States before age 18. The data covers in detail the relative skills required for different occupations, such as physical strength, communication skills, social skills, math and reasoning. For those who went to college, they were also able to see what major they chose.

“If it were just as easy for me to write with my left hand as with my right, I would be using both. But no, I specialize,” Rangel says. In the same way, academically motivated students who have to play catch-up in English class may prefer to zoom ahead in the universal language of mathematics.

(By the way, Das, not a late arrival, is a former spelling bee champion as well as a science whiz.)

Rangel, who came here from Brazil as a young father, has seen this dynamic play out in his own family. “The younger one, who went to Pre-K in English, is different from my kid who came at five already reading Portuguese,” he says. The older one is more inclined toward math.

To be clear, Rangel doesn’t discount the notion that cultural values may also influence immigrants’ career choices. But he is out to tell a more nuanced story — “a movie, not just a photograph,” he says — of how people develop different skills and talents.

Source: Why Immigrants Do Better At Science And Math : NPR Ed : NPR

Sex differences in academia: University challenge | The Economist

Interesting analysis of the some of the unconscious beliefs and habits that may undermine efforts to increase diversity within STEM disciplines:

All this raises interesting and awkward questions. It may be unpalatable to some, but the idea that males and females have evolved cognitive differences over the course of many millions of years, because of the different interests of the sexes, is plausible. That people of different races have evolved such differences is far less likely, given the youth of Homo sapiens as a species. Prejudice thus seems a more plausible explanation for what Dr Leslie and Dr Cimpian have observed. But prejudice can work in subtle ways.

It could indeed be that recruiters from disciplines which think innate talent important are prejudiced about who they select for their PhD programmes. It could instead, though, be that women and black people themselves, through exposure to a culture that constantly tells them (which research suggests it does) that they do not have an aptitude for things like maths and physics, have come to believe this is true.

If that is the case (and Dr Leslie and Dr Cimpian suspect it is), it suggests that a cultural shift in schools and universities, playing down talent and emphasising hard work, might serve to broaden the intake of currently male-dominated and black-deficient fields, to the benefit of all.

Sex differences in academia: University challenge | The Economist.