Woman Are The Key That AI And Data Science Need

In light of International Womens Day celebrations this past weekend, we acknowledged the beauty, essence and power of women to achieve and thrive in the global ecosystem. Yet in our modern digital age, women continue to be neglected on multiple fronts, especially that of the new workforce. It is societys role to ensure that all females are given equal opportunities to grow in this new age workforce, and we must understand that all of us have a stake in this mission. Women are the key piece to the puzzle of realizing the highest maturity levels of digital enterprises, but unless we realize this, our progress in AI and technology will remain stagnant. In order to close the gender gap in science, technology, engineering and math (STEM), and to accelerate advances in artificial intelligence and the sciences, we must encourage and support women on all levels, from government to enterprise, and establish equal employment opportunities for all.

AI is one of the fields in which women can experience tremendous success, especially with the right push towards female participation in the industry. Women are a necessary force that organizations must integrate in order to accelerate the AI maturity of enterprises. In specific, a heavy emphasis on the female workforce within the artificial intelligence setting can help alleviate some of the biggest problems that enterprises face in the eyes of machine learning technologies, such as selection bias. Therefore, in order for organizations to achieve the highest AI maturity levels, it is necessary to mobilize women on a mass scale and include them as part of all enterprise endeavors in artificial intelligence, from research to product launch.

The above remarks indicate that there has been a global push to involve more women in science and technology careers. Towards the end of 2019, the World Economic Forum urged more female role models to join accelerator programs focused on promoting women in STEM careers. International campaigns to involve more females in STEM, AI and data science have launched in multiple nations, championed by such entities like IBM, IPsoft and Microsoft as well as the US Chamber of Commerce. From Australia to Saudi Arabia to Canada, strong female leaders in STEM and AI have begun to inspire girls and young women around the world to dream big and chase career opportunities in engineering, artificial intelligence and the sciences. The White House has also made an effort to make women in STEM a top priority: the Womens Global Development and Prosperity Initiative, spearheaded by Ivanka Trump, is a new level of female empowerment in STEM. The project seeks to, Reach 50 million women in the developing world by 2025 through U.S. government activities, private-public partnerships, and a new, innovative fund, and equip them with all possible tools to succeed in the new digital world.

It is evident that steps have been taken to boost female participation in STEM, artificial intelligence and data science. Moreover, this article serves as a first glimpse into the current situation, how to combat it, and ends with several recommendations that seek to accelerate progress for all women in STEM, AI and data science. The mass mobilization of women in STEM careers is the secret that will unleash the fullest potential of our technological abilities, as well as the grand capacities that our digital world has to offer. Without females, this global mission is destined to fail.

STEM, data science and AI are fields in which women are vastly underrepresented, and the numbers make it clear. Females compose just 28% of the science and engineering workforce, and that number drops when observing the number of women pursuing university degrees in said fields. About 55% of university graduates are females, but only a little over one-third of those degrees are in STEM. For example, research from the World Economic Forum shows that a measly 3% of females take coursework for information communication technology (ICT), with just 5% choosing to pursue studies math and statistics, and a slightly better 8% when it comes to engineering.

The current situation with AI careers also fails to play in favor of women. Just 13.8% of women have authored artificial intelligence related research papers, and less than a quarter of females are considered to be AI professionals. This information should be more than disquieting to enterprises wishing to scale-up their AI maturity levels. According to BCG GAMMA, Interpreting causal relationships and correlations in large data sets requires subtlety, and both humans and machine learning algorithms can occasionally see patterns that lead to spurious, biased, or even downright dangerous conclusions. This ultimately means that organizations will always fail to harness the fullest capacity of their digital innovations without including women, as machine learning technologies will be fed a constant stream of biased data, producing junk results that are not reflective of the full picture, causing potentially catastrophic harm to organizations.

And when it comes to data science, the news still remains uneventful for women. Females comprise some 15% of the career population, and just 18% of leadership positions at premier technology companies. Despite this fact, according to a poll conducted by LivePerson, 91.7% of 1000 survey respondents said that they could name just one female leader in STEM.

With over 90% of the population oblivious to the female presence in STEM, data science and AI, clearly, the globe clearly faces an uphill battle on the pursuit to resolve this issue.

What is keeping women out of STEM and STEM related occupations? A number of factors must be considered when attempting to answer this question. Lets break these elements down first, and then briefly go over each one in more depth in order to understand the crux of the matter.

Few organizations understand the importance of women to AI enterprise maturity levels

Women make up a fraction of the artificial intelligence workforce, whether in the form of research and development or as employees at technology inclined firms. According to the World Economic Forum, Non-homogeneous teams are more capable than homogenous teams of recognizing their biases and solving issues when interpreting data, testing solutions or making decisions. In other words, diverse teams, and especially those that emphasize women at their epicenter, are a necessary provision for enterprises to adopt in order to build, realize and accelerate enterprise AI maturity levels. At present moment, unfortunately, few enterprises understand the criticality of women to boost AI maturity levels.

STEM, data science and AI fields experience a lack of female role models

Without female role models for girls to look up to, it becomes difficult for young women to envision future careers in science, technology and engineering fields. In fact, a 2018 Microsoft survey shows that female STEM role models boost the interest of girls in STEM careers from 32 percent to 52 percent. Therefore, it is imperative that we showcase the achievements of women in the sciences and engineering across the world to capture the attention of females everywhere.

Women in STEM, data science and AI face a male-dominated culture and are seen as inferior

One of the biggest pressures that females face in STEM careers is cutthroat competition amongst male counterparts, and the toxic workplace culture that it creates. An HBR article found that three-fourths of female scientists support one another in their workplace to ease tensions. Moreover, women are likely to be demoted as inferior by men holding equivalent positions, whether those jobs are in engineering, data science or AI. All of these factors contribute to females swiftly dismissing STEM jobs in order to avoid such disquieting workplace circumstances.

Women in STEM, data science and AI display different preferences

According to a survey conducted by BCG, when it comes to STEM, Women place a higher premium on applied, impact-driven work than men do: 67% of women expressed a clear preference for such work, compared with 61% of men. This finding highlights a significant fact: women are vastly more likely to pursue STEM roles that provide them with meaning, purpose and produce impactful results, but many women dont perceive this purpose and impact in STEM jobs. Therefore, without a clear high impact-driven pathway in sight, females tend to turn their heads on STEM, data science and AI related careers.

Communication about STEM, data science and AI roles is key with women, but we have been lagging in this pursuit

Studies have shown that communication is of the utmost importance when it comes to getting more women involved in STEM careers. According to BCG GAMMA, just 55% of women feel like they know enough about employment opportunities in data science. Furthermore, vague explanations of job qualifications, such as being strong in data science, and, conversely, incredibly in-depth job descriptions in search of data wizard talent, tend to steer females clear of STEM related jobs. Moreover, an HBR study found that female engagement with STEM employers falls far behind men, and that this should come at no surprise as, Given the selection bias that accompanies personal work networks, especially in a young and still male-dominated field.

Retention of women in the STEM, data science and AI jobs is another challenge

It isnt enough to pique the interest of girls and young women to pursue STEM careers: the goal is to maintain, foster and grow that interest. A study published in the Social Forces journal found that women in STEM are much more likely to abandon their jobs than if they held other careers. More precisely, the study highlights that some 50% of women holding STEM careers left after 12 years on the job, whereas that number dropped to 20% for women in other fields. On average, females tend to distance themselves from STEM after 5 years of industry involvement. But why? According to the same study, Women with engineering degrees said they left engineering because of lack of advancement or low salary, along with other working conditions. These facts show that retention of women in the STEM, data science and AI workforce is chief among challenges to address.

A number of initiatives have been launched in order to combat the gender gap problem in STEM and STEM related fields. At their core, these campaigns emphasize the promotion of women, artificial intelligence, and special educational and reskilling programs to solve the problem.

Campaigns Focused on Promoting Women in STEM, AI and Data Science

IPSoft, IBM and the US Chamber of Commerce are examples of organizations that are leading the way to get more women involved with STEM, AI and data science. IPSofts Women in AI initiative has been recently launched in order to shine a light on prominent female figures in STEM, showcasing the incredible work that these professionals have accomplished in adopting and promoting AI technologies in their companies and organizations. The objective of the Women in AI initiative is to not only inspire girls and young women to pursue careers in artificial intelligence, but to also inform the world of the amazing feats that female pioneers in AI have achieved. In addition to IPsoft, IBMs #SheCanStem campaign and the US Chamber of Commerce #LightaSpark campaign have both worked to highlight the gender gap in STEM, AI and data science fields by utilizing workshops and educational initiatives across the globe in order to effectively translate the critical, rewarding, and beneficial STEM message to girls and young women. Overall, these campaigns are the right step forward on the path to closing the gender gap and promoting females in STEM and STEM related careers. The more vigorous the effort, the more females will begin to see sizeable results in these fields.

Mobilizing AI to Help Close the Gender Gap

Utilizing AI to solve the problem of the gender gap is a feasible and necessary solution. According to a report Whats Keeping Women Out of Data Science? by BCG GAMMA, AI has the potential to mitigate the corporate gender and leadership gaps by removing bias in recruiting, evaluation, and promotion decisions; by helping improve retention of women employees; and, potentially, by intervening in the everyday interactions that affect employees sense of inclusion. To elaborate, machine learning technologies can help employers assess candidates based on skills rather than gender, and talent-based qualification assessments have the potential to ameliorate bias in the selection/recruitment process, thus vastly benefiting women. Moreover, according to the program director of employment and earnings at the Institute for Womens Policy Research, Ariane Hegewisch, involving more females in STEM, AI and data science is vital to eliminating biased algorithms, which can also help address the gender gap. Ultimately, less bias in the workplace will lead to more females entering the STEM workforce, and can help boost retention rates.

Placing a media emphasis on female trailblazers in AI and STEM is one of the most powerful, fast and effective ways that we can reach out to the women of the world about the opportunities that lie in the sciences and engineering. Some prominent names that are role models that come to mind include: Global GAMMA CTO and BCG Gamma Partner Andrea Gallego, Strategy Leader at IBM Saudi Arabia Deema Alathel, Co-founder of the Women in Machine Learning Conference Hanna Wallach, Founding CTO at NukkAI Veronique Ventos, Director of the MIT Computer Science & Artificial Intelligence Laboratory (CSAIL) Daniela Rus and ChairWoman and CTO at Diagnostic Robotics Dr. Kira Radinsky.

Andrea Gallego

Andrea Gallego has accomplished tremendous feats: Gallego is the founder of GAMMA X, BCGs innovation and engineering team, as well as the founder of BCG GAMMAs premier artificial intelligence and machine learning software. Her work focuses on scaling-up AI implementations across industries, and most importantly, serving as a role model for all female employees at BCG.

Deema Alathel

Deema Alathel of IBM Saudi Arabia is also a leading female voice that is worth mentioning. She has been instrumental to data science and AI efforts in Saudi Arabia, serving as part of the National Digital Transformation Unit of her country, as well as implementing top artificial intelligence strategies and plans at IBM. Alathel has also engaged with the Saudi delegation from the UN Human Rights Commission.

Hanna Wallach

Hanna Wallach is the Co-founder of the Women in Machine Learning Conference as well as Senior Researcher at Microsoft. Wallach has previously received a best paper award for her work at the Artificial Intelligence and Statistics Conference in 2010, and was named as Glamour magazines 35 Women Under 35 Who Are Changing the Tech Industry in 2014. She serves as a prominent role model in AI for women around the world.

Veronique Ventos

Veronique Ventos is the Founding CTO of NukkaAI (a paris-based AI firm), and is considered to be one of the most prominent voices in AI research in all of France. Ventos is among the top female STEM and AI leaders in France paving the countrys way to international prominence in artificial intelligence research and innovation.

Daniela Rus

Daniela Rus is currently the Director of the MIT Computer Science & Artificial Intelligence Laboratory (CSAIL). Rus works in all areas of AI and computer science, from robotics to data science to mobile computing. Rus is also a part of the National Academy of Engineering, and is an accomplished member of the science and technology communities.

Dr. Kira Radinsky

Dr. Kira Radinsky is the former head of Data Science at Ebay as well as ChairWomen and CTO at Diagnostic Robotics. Radinsky is an accomplished woman in STEM, one of her biggest achievements being the acquisition of her AI company SalesPredict by Ebay for $40 million. Radinsky is a top female voice in AI across the world.

Hundreds of more role models like the exception ones mentioned above exist around the world, and can serve as beacons of empowerment for women thinking about entering the STEM, data science and AI workforce.To learn more about the women pioneering the 21st century AI movement and creating an impact in artificial intelligence, check out this article The Women Defining The 21st Century AI Movement: Part 1 of 2.

In addition to the many initiatives set forth to combat the gender gap in STEM, the following list provides feasible and implementable efforts and campaigns that can be mobilized to further the female cause in science, technology, engineering, data science and AI. Moreover, a greater emphasis is placed on the importance of women and the maturity of enterprise AI initiatives.

Some of the recommendations below were covered extensively in a previous Entrepreneur Magazine Publication entitled Why We Need More Women in STEM and How AI Could Help Us Get There.

These recommendations combined with already implemented efforts to combat the gender gap in STEM, data science and artificial intelligence are ways in which we can encourage females and ensure that women will receive equal employment opportunities in our new digital age. Moreover, digital organizations must integrate a mass emphasis on women if they will ever achieve their highest artificial intelligence maturity levels. Now more than ever is the time for us to tap into this global mass of female potential, and channel it in the form of incredible technological feats and advancements, one STEM career at a time.

Originally posted here:

Women Are The Key To Scaling Up AI And Data Science - Forbes