Women are less convinced of AI’s benefits than men are, and less likely to think that generative AI will enable them to develop new skills, according to a survey by Cognizant.francescoridolfi.com/iStockPhoto / Getty Images
David Silverberg is a Toronto-based journalist and editor who has reported on digital culture and Silicon Valley for the past 17 years.
If you’re using AI tools like ChatGPT, you most likely identify as male. That’s not just an observation about the male-dominated discourse and leadership in the booming AI space – it’s borne out by data.
A Harvard University report found a staggering gender chasm in how men and women use AI, with a gap of 25 per cent. The study’s author, Harvard Business School associate professor Rembrand Koning, said the lack of adoption could relate to how women appear to be more worried about the potential costs of relying on computer-generated information, particularly if it’s perceived as unethical or cheating. “Women face greater penalties in being judged as not having expertise in different fields,” he said. A joint American-Danish study pointed to another possible cause: Women who said they faced an adoption barrier to ChatGPT use pointed to a dearth of proper training.
But whatever the reason, this gap could spell disaster for the majority of women around the world who aren’t adopting to AI tech as quickly as men.
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If there’s any demographic that needs to upskill with AI tech, it’s women, whose median full-time wages are 17 per cent lower than men in Canada, according to the most recent OECD data. Research showed that women, who are overrepresented in entry-level office jobs, are three times more likely to have their job replaced by AI in the future.
Women have to catch up to men if they want to compete in the job market of the present, too. Among AI-friendly companies, executives are moving past AI infatuation and focusing on upskilling or re-skilling employees, while adjusting their hiring practices; college graduates with AI skills are almost twice as likely to receive an interview offer after applying for a job. The more AI capital someone accumulates, the higher the chance they will be rewarded with job prospects or bigger salaries. The tech-industry research group Lightcast scanned more than 1.3 billion job ads in the U.S. and found that jobs requiring AI skills advertised a 28-per-cent premium, working out to roughly US$18,000 per year – a premium that surged to 43 per cent when listings specified seeking two or more AI skills.
Some of us, regardless of gender, are still wary of the AI hype, predicting a bubble on the verge of bursting. That might yet be on the horizon. But at least for now, AI should be viewed as one of the most revolutionary advances in modern society.
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But women remain skeptical. According to a survey carried out by Cognizant, women are less convinced of AI’s benefits than men are, and less likely to think that generative AI will enable them to develop new skills (40 per cent, compared with 51 per cent of men) or create new opportunities (33 per cent, compared with 40 per cent of men).
What’s concerning is that even when women have the opportunity to delve deep into innovative tools like AI, they might not keep up with it. Studies show that men tend to be early adopters of new technologies, and that while young girls may show initial interest in similar sectors, they often lose interest over time.
The AI adoption gender gap will also affect how the technology is developed. As the work force becomes more automated, humans will still need to develop, monitor and curate technologies for their intended audience – and it has been mainly men at the controls. Such an unbalanced scale means these tools are being created and fine-tuned without input from women, even though it’s critical that AI products work to reverse this trend. As Prof. Koning’s study says, this lack of input from women could result in AI systems that reinforce gender stereotypes. “If it is learning predominantly from men, does that cause these tools to potentially respond differently or be biased in ways that could have long-term effects?” he asks.
Under-representation in the boardroom and the engineering table has already given us biased technologies. Facial recognition, for example, has long performed poorly when trying to recognize Black faces, and efforts to address the fact that women disproportionately experience nausea while using virtual-reality devices have moved slowly.
Women don’t need to become specialists or spend hours a day reading about neural networks. But they should enroll and feel empowered to participate in training programs, experiment with their favourite tools, use generative AI in savvy ways, and figure out how it can help them both at work and at home, much like men are doing.
Inequalities in the workplace are already commonplace in Canada. The last thing we need is another labour challenge that women have to hurdle to achieve the quality of life and employment income they deserve.