I was delighted to be interviewed by John Leonard at Computing – a source for end-user IT news, analysis and insight around the world – about my talk Automated out of work: AI’s impact on the female workforce at the Women in Tech Festival on Tuesday October 31st in London.
I reproduce below the interview. You’ll find at the end additional reflections framed as Q&A.
Interview
Patricia Gestoso, is an award-winning technologist and inclusion strategist with over 20 years of experience in digital transformation with a focus on client service, artificial intelligence, and inclusive and ethical design of technology and workplaces.
Patricia will be giving a talk about the impact of AI on the workplace and workers at the Women in Tech Festival in October. We do hope you’ll be able to join us.
In the meantime, we caught up with Patricia and asked her to give us a taster.
How did you become interested in the topic of AI?
As a Director of Support for a scientific and engineering software corporation, I see how AI helps our customers every day to accelerate drug discovery, clinical trials, and research on new materials.
On the flip side, as an inclusion strategist and collaborator on initiatives such as the Race and AI toolkit and Better Images of AI, I’m also aware of the different ways in which AI helps encode and automate biases.
That’s the reason why in the last three years I’ve been actively fostering discussion about the benefits and challenges that AI brings to inclusion, equity, and sustainability on social media as well as through keynotes and articles.
Your talk is titled: “Automated out of work: AI’s impact on the female workforce”. Are women likely to be disproportionately affected in the next wave of automation?
It’s important to take a step back and see where those predictions of women more likely to be negatively affected in the next wave of automation. They come from several assumptions.
First, that there are certain sectors that will be more impacted than others. Then, that the impact on those sectors will be negative on the less skilled workers, next that those workers are women, and finally, that people prefer to interact with machines than with humans.
On the flip side, we have other studies that tell us that the most impacted will be white-collar workers like software engineers – who are overwhelming men – or lawyers – where which gender is overrepresented depends on the practice area.
In case this was not contradictory enough, we’re also told that the roles that AI won’t displace will be those that are related to soft skills and studies show that women are great at those – collaboration, listening, and championing a common plan.
The reality is that when we see how’s already impacted by automation, it’s easy to argue that it’s mostly men. Workers at Amazon’s warehouses, Uber drivers, or Deliveroo riders. Their work is scheduled and constantly monitored by AI. Moreover, when we look at who’s raising the alarm about generative AI stealing their jobs right now, we see book authors, screenwriters, and actors. Again, professions that are far from failing in the “female job” category.
For me, talking about the next wave of automation disproportionately affecting women is to deflect from the reality that AI is already affecting the workforce dramatically right now. And it’s not fortuitous. It’s the old strategy of “divide and conquer”. By saying “it’ll be worse in the future and women’s jobs will be the most affected,” it aims to keep men quiet with the false premise that they should conform because their jobs are “safe”.
Are there ways that women and other underrepresented groups can harness the technology to their advantage to mitigate some of these scenarios? If so what do they need to do and where should they start?
I’ll go into more detail in my talk, but there are three obvious areas where women and underrepresented groups can harness technology to their advantage.
First, increasing their negotiation power. If we look at the industrial revolution, the disruption was massive. Loss of jobs, exhausting work schedules, child labour. What’s changed the game? Unions. This is no different now with Amazon workers and screenwriters. Social platforms and digital tools such as apps are powerful means to organise resistance.
Next, learning about AI. Ignoring new technology is not the answer because AI is not going away anytime soon. However, when I said learning, I’m not necessarily suggesting to become an AI software developer. I’m talking about following the major trends in AI, understanding how they impact your industry – what are the major risks and possible rewards – and getting involved in projects aimed at exploring the capabilities that AI can bring to your business.
Finally, discovering how AI can augment you as a professional. We see a lot in the media about the need to learn about how to work “for” or “with” AI. For me, the key is to learn how you can use AI tools to strengthen your capabilities.
Tech has a tendency to concentrate power and wealth in the hands of the already rich and powerful. Is AI likely to continue or even exacerbate this tendency?
AI is already benefiting those who have privileges and disadvantaging those who face more challenges. The Race and AI toolkit mentioned previously showcases many examples where non-White people are consistently sidelined by AI in areas such as healthcare, education, and justice.
The reason? Garbage in, garbage out. We’re feeding AI data that is generated by narrow sectors of the population and that doesn’t reflect our diversity or values as a society.
Unfortunately, attempts to limit the reach of AI tools are seen as attempts to stop progress. No different than what happened to Luddites 200 years ago. The reality is that tech is playing to our FOMO – [fear of missing out] anxiety – telling us we either let AI run wild or we’ll miss out on new drugs and cure cancer. To me, that’s akin to saying, you either let fire run wild or you won’t have fire at all. We’ve survived because we decided that we’re happy to have fire to cook and heat ourselves but that if it goes to our curtains we’ll put it out. AI shouldn’t be treated differently.
Who do you hope to reach with your keynote at the Women in Tech Festival?
I hope my talk reassures those who are frightened that AI will take their jobs that they are not powerless. I also aim to provide actionable strategies to incorporate AI into their professional careers to those that are wondering how to jump on the AI bandwagon. Finally, I hope to reach out to those who are curious about exploring alternative futures to dystopia and utopia, where rather than humans in the loop, humans are in the driving seat and machines are in the loop.
Additional reflections on women, work, and AI
What are your concerns regarding how AI will affect the future of work for women?
The main one is deskilling. To understand the concept, it is useful to remember the Luddite movement that I mentioned above.
The Luddites were British weavers and textile workers who objected to the increased use of mechanised manufacturing at the beginning of the 19th century.
Most were trained artisans who had spent years learning their craft, and they feared that unskilled machine operators were robbing them of their livelihood. As you see, their problem was not the technology in itself but the deskilling of workers.
And I could see how that may happen to women in the future. For example, those with university degrees in computing could be offered work as “prompt engineers” when they come back from maternity leave, with the resulting career and salary demotion. Or administrative professionals may get relegated to fact-checking and improving reports produced by generative AI applications, making their contribution “invisible”.
Is technology an enemy of women?
Technology has enabled women to get financially remunerated for their work. Consider the washing machine, tap water, and electricity. In places where those technologies are not available, women spend their days making up for it – typically for free.
The problem has always been that women have only been able to benefit from technology when it suited men.
For example, during the Industrial Revolution, women and children worked for less pay, which was very profitable for companies.
Women tended to receive between one-third to one-half of a man’s average salary. As the manufacturing industries began to grow, they would take advantage of these low average salaries amongst women and children. The ability to employ these women and children for little pay proved to be very beneficiary to these companies. Many industries exploited these people’s need for money, as they would turn a major profit in exchange for very cheap labor. Tasks such as printing, spinning, and other duties commonly learned at home were easy jobs to learn and were some of the most profitable.
Foundations of Western Culture course at the University of Wisconsin-Green Bay
As we can see, both the gender pay gap and genderisation of work were already at the core of the Industrial Revolution.
Another example is the tech sector. In the 1930s, women were hired to solve mathematical problems that were considered at the time as repetitive work. Some of those calculations were as complex as determining how to get a human into space and back. When computers took off in the 1960s women became the programmers while men focused on the hardware which was regarded as the most challenging work.
However, as programming gained status during the 1980s, men pushed women out of those jobs. That prompted a sharp increase in the salaries of software developers, institutionalising patriarchy and the gender pay gap.
The same with AI. We like to anthropomorphise artificial intelligence to deflect our responsibility. We say “AI will automate jobs” or “AI will replace people” but the reality is that those decisions are and will be taken by humans.
In summary, It’s not technology the enemy of women’s paid work but other human beings that see it as “a nice to have” and not deemed to be retributed as that of men. Human beings are also those who also decide that caregiving for family members is “not a job”.
The biggest threat to women’s work is not AI. It’s patriarchy feeling threatened by AI.
Patricia Gestoso