Tech-disruption and digital transformation today, has forced the world to reimagine the future of work. Almost all industries ranging from computer sciences to e-commerce, health, and education are soon slated to face tech-disruption. Tech-enabled systems, automation, and artificial intelligence (AI) are the key drivers of the fourth industrial revolution that the 21st Century is witnessing. Multiple research pieces have hinted that the Internet of Things (IoT), Machine Learning, and Automation will change the conventional ways of working. At the same time, humans and technology would end up being closest than ever before. Although there is palpable anxiety on the huge loss of jobs that disruptive technologies would bring, AI experts have time and again assured that tech-disruption isn’t only about losing jobs to machines. It is about new jobs coming up that currently don’t even exist.
The demand for cognitive skills, creativity, and critical thinking is higher, as machines are set to automate repetitive, calculative, less creative jobs. The World Economic Forum has estimated that 65% of children who are entering primary school will be engaged in jobs that currently don’t exist. Kai-Fu Lee, a Taiwanese American computer scientist and Artificial Intelligence expert, has estimated that the future would replace a whopping 40% jobs by robots that are skilled at automating tasks.
AI Fast Booming, but Women Workforce is in Peril
While debates about how tech-disruption would change the future of work, it leads to job losses and job gains for new-skillets. The lesser-discussed concern is how genders would be affected by the tech-disruption. Would men and women be equally affected? Reports have suggested that women would McKinsey Global Institute (MGI) report has highlighted that women would have a harder time coping with this technology disruption. What is obvious is that these new jobs would demand an entirely new range of skillset. McKinsey estimated that by 2030, there would be a huge growth of social and emotional skills across the globe about 26% and 22% in the US and Europe, respectively.
On the one hand, AI is booming and set to change the world, and on the other hand, women researchers worldwide in AI are decreasing in numbers over the last decade. As of 2019, less than 14% of AI researchers are women. With no signs of improvement since the 1990s. It is even a bigger gap than the 15.5 % women in Science, Technology, Engineering, and Math (STEM). Tech-giants Google, Microsoft, and IBM have an estimated 11.3%, 11.95 %, and 15.66 %, respectively, of published women researchers in AI. Moreover, women are projected to lose 5 jobs for every job gained, whereas men would lose 3.
The International Monetary Fund (IMF) projects that 11% of jobs currently held by women (a higher percentage than those currently held by men) are at risk of elimination due to AI and other digital technologies. The higher management posts are projected to be notably safer than the lower administrative positions where women mostly dominate are at the highest risks of job loss to automation. It is a major cause of concern as women constitute 50% of the global workforce.
As per International Labour Organisation, 2018, 56% of employees will face job displacement in manufacturing hubs of Cambodia, Thailand, Phillipines, Vietnam and Indonesia. Aproximately 76% of women will lose their in the Garment, Textile and Foodwear industries. This comprise of 2.6million vietnamese women and 600,000 Cambodian women will lose their jobs to machine in GTF industries.
Gender Bias continues for Women in AI
The gender-inequity in AI is no different from the age-old gender bias that has existed since time immemorial, especially for women in traditionally male-dominated fields. The gender-disparity of women in AI is mostly direct out-turn of years of under-representation of women in STEM fields. Globally technology sector is still male-driven and has only 22% of female representation. In Singapore, it is slightly higher than the global average. 28% Women form the AI talent pool.
More often than not, the female AI-powered digital assistants are projected as passive and amenable while their male counterparts are made to be authoritative and mighty. Research has estimated 67 percent of submissive digital assistants meant for menial work are female. We have witnessed that declining percentage of women have graduated from computer science degree and resulting in scarcity of women in Machine learning research sector.
Gender biases are prevalent even in Natural Language Processing (NLP) tools. The tech-to-speech and speech-to-text technology show errors due to insufficient data inputs from the female category. Many computer vision systems show errors when it comes to recognizing women. AI depends on quality data for the fair working of algorithms. When it comes to women, there is much less data, and AI always runs the risks of picking up existing biases and prejudices against women. The only way to eliminate this is to work proactively in feeding unbiased, equitable data to AI to receive the desired prejudice-free outcome.
Global efforts to curb Bias and include Women in AI
Though a lot needs to be done to bridge the gender gap in AI, all hope is not lost. A couple of years back, Amazon had scrapped one of its machine-learning tools after years of working on it, when they recognized its bias against women for developers and other technical jobs. It is a great example of how companies can work towards recruitment based on gender-neutral factors like talent, competency, and skillset.
The US Congress has even introduced legislation for companies to investigate and eliminate gender bias in their machine learning system. Some countries in the UK have followed suit. Globally efforts are being made to reengineer AI to algorithmic anti-bias training. Many universities emphasize involving women in AI to solve various global issues, from healthcare to technology to education. Some of their students have patents in AI and the Internet of Things and are credited with publishing related-papers in AI.
Singapore based SGINNOVATE are helping entrepreneurial scientists irrespective of gender in Deep Tech startups.
Men and women have noticeable differences in behavior, psychology, and even ways of leadership. These differences are not necessarily a stumbling block when it comes to performing in AI or any field of leadership but quite the opposite. Most men have shown to have a pessimistic and destructive idea of AI and the future of work. There are often dire warnings coming about AI-all of which have a common denominator — Men. Experts say the involvement of women would make the future of work a lot less scary with AI.
Women are even reckoned to surpass men in AI technologies like Natural Language Processing (NLP), speech recognition, text mining, and analytics. Women are more considerate of societal and ethical standpoint while working on AI. Naturally, the tech-world has recognized women’s role as crucial for a fair and unbiased AI future. Many data science researchers have agreed in unison that for AI to be successful, the world needs more women in AI.
Remarkable Women in AI, Leading by Example
Although the number of women in AI is way less than men, great role models for women in AI certainly exist. Some of these women are making great things happen for the world with their incredible multifarious work powered with AI-technology.
AI whiz-kid, Annabelle Kwok, 26, is Singapore’s blue-eyed girl for a reason. At such a young age, she is involved in multiple AI-based innovations like Smartcow, which creates industrial-grade AI deployment services, and Neuralbay develops vision-analytic AI software accessible by Small and Medium Enterprises. A million worth is her humanitarian motivation behind developing AI — making technology more accessible through AI, even to non-tech savvy people.
Dr. Ayesha Khanna, Co-Founder and CEO of ADDO AI achieved a remarkable feat as a strategic advisor on AI, smart cities, and fintech solutions for corporate and government, including SMRT- Singapore’s largest public transport company and Singtel-Singapore’s largest telco. She was listed in Forbes as one of South Asia’s groundbreaking woman entrepreneur in 2018.
Dr. Keelin Murphy has enabled the use of AI to detect brain damage in infants to help timely treatment.
Prof Rozen Dahyot, a statistics professor in Trinity, is the principal investigator of the AIMapIT project that can discover and detect stationary objects like trees, pillars, antennas, or anything which clearly can be of great use by utility companies.
Dr. Susan Leavy has an interesting journey from Philosophy and English Literature to an MSc in AI, followed by a Ph.D. in computer science. She has wonderfully put together her specializations by using Machine learning and NLP to examine gender bias in political media coverage.
Some other remarkable women in AI like Google engineer Carrie Grimes Bostock, Jennifer Chayes, Managing Director at Microsoft Research, Silvia Chiappa, a Research scientist at Deep Mind, are smashing gender stereotypes and are paving the way for more women in AI in the future. The extraordinary feat of the leading ladies in AI clearly shows success in AI doesn’t have to be limited to men.
It is evident that the global gender bias and underrepresentation of women in AI is unjustified, and unless it is narrowed down or dissolved, it would cost the world dearly. Though there is no sovereign remedy or an instant-fix to this, the crisis calls for stronger steps to equip women with the right skillset and digital know-how. There should be more policies and programs and proactive efforts to support and skill women while identifying and eliminating bias for a more gender-diverse future in AI.
Looking Ahead & Beyond
The onus lies on women too. Each crisis is an opportunity in disguise. Women must start taking a pro-active interest in AI-technology, changing existing mindset, looking beyond limitations, enrolling for specialized tech-enhancement courses in platforms like Udemy and Coursera, finding role models, and strengthen their resolve to excel in this career path. It is also important for women to watch out for the classic ‘Imposter Syndrome,’ fear of competition, or lack of faith in their abilities in fields like AI.
The world is inching towards huge progress with giant leaps in technology. If women want to finally get an equitable world in the age of AI by putting their foot down — now is the time!