Impact of tech on marginalized women

As GenAI becomes more ubiquitous, research alarmingly shows that women are using these tools at lower rates than men across nearly all regions, sectors, and occupations.   A recent paper from researchers at Harvard Business School, Berkeley, and Stanford synthesizes data from 18 studies covering more than 140k individuals worldwide.   Their findings:   • Women are approximately 22% less likely than men to use GenAI tools • Even when controlling for occupation, age, field of study, and location, the gender gap remains • Web traffic analysis shows women represent only 42% of ChatGPT users and 31% of Claude users   Factors Contributing the to Gap:   - Lack of AI Literacy: Multiple studies showed women reporting significantly lower familiarity with and knowledge about generative AI tools as the largest gender gap driver. - Lack of Training & Confidence: Women have lower confidence in their ability to effectively use AI tools and more likely to report needing training before they can benefit from generative AI.   - Ethical Concerns & Fears of Judgement: Women are more likely to perceive AI usage as unethical or equivalent to cheating, particularly in educational or assignment contexts. They’re also more concerned about being judged unfairly for using these tools.   The Potential Impacts: - Widening Pay & Opportunity Gap: Considerably lower AI adoption by women creates further risk of them falling behind their male counterparts, ultimately widening the gender gap in pay and job opportunities. - Self-Reinforcing Bias: AI systems trained primarily on male-generated data may evolve to serve women's needs poorly, creating a feedback loop that widens existing gender disparities in technology development and adoption.   As educators and AI literacy advocates, we face an urgent responsibility to close this gap and simply improving access is not enough. We need targeted AI literacy training programs, organizations committed to developing more ethical GenAI, and safe and supportive communities like our Women in AI + Education to help bridge this expanding digital divide.   Link to the full study in the comments. And a link also to learn more or join our Women in AI + Education Community. AI for Education #Equity #GenAI #Ailiteracy #womeninAI

Misogyny is driving young women away from online spaces. New polling commissioned by Amnesty International UK, exposes the staggering levels of online misogyny that plague social media, driving young people, particularly women, away from spaces meant for connection and creativity. I've shared the full report which is worth a read Toxic Tech: How Misogyny is Shaping Gen Z’s Online Experience. It adds to the giant pile of evidence around the harm being caused by tech to our young people, especially women. An overwhelming 73% of Gen Z social media users have witnessed misogynistic content online with half encountering it on a weekly basis. The problem is only getting worse, as 70% believe misogynistic and divisive language has increased on social media. Alarmingly, 55% express concerns about seeing misogynistic content, and less than half (49%) feel that social media is a safe space. The polling also uncovers the shocking forms of online harassment faced by Gen Z women, including: ℹ️ 53% receiving inappropriate emojis (e.g., 🍆💦) on their posts and photos ℹ️ 44% receiving unsolicited explicit images ℹ️ 43% being body-shamed ℹ️ 40% subjected to unwanted sexually suggestive comments ℹ️ 32% experiencing hate speech ℹ️ 27% reporting online stalking. Among social media platforms, TikTok is seen as the worst offender. 70% of respondents reported encountering misogynistic content on TikTok, rising to 80% for women, followed by Instagram (61%), Twitter/X (37%), YouTube (31%), and Facebook (30%). Marginalised groups and ethnic minorities suffer these toxic effects the most: ℹ️ Gen Z women with disabilities are twice as likely as women without disabilities to spend more than 10 hours a day on social media. ℹ️ Three in ten women with disabilities who have experienced online misogyny, reported that they had received threats of violence online against one in five of those without disabilities. ℹ️ Gen Z women with ethnic minority backgrounds who have experienced online misogyny, are more likely to have experienced hate speech than their white counterparts. Online misogyny is having a severe impact on mental health: ℹ️ 55% of those who have experienced online misogyny have blocked users in response to abusive content. ℹ️ 44% of Gen Z women who had experienced online misogyny in the UK report negative mental health impacts from exposure to misogynistic content. ℹ️ 35% have switched their accounts to private. ℹ️ 30% have taken screenshots as evidence of abuse received ℹ️ 22% avoid posting certain types of content. ℹ️ 20% have avoided or left platforms altogether And sadly there are many more depressing stats in there. Until we bring in genuine accountability and consequence to these Tech companies, these issues will just continue- we need a systemic response. For young women to abandon online spaces because of men's behaviour, can't be something we just accept. Love & light, Sal. #WeRiseByLiftingEachOther

[Techno-Patriarchy: How AI is Misogyny’s New Clothes Gender discrimination is baked into artificial intelligence by design and it’s in the interests of tech bros. In my day job, I support our clients using AI to accelerate the discovery of new drugs and materials. I can see the benefits of this technology to the people and the planet. But there is a dark side too. That’s the reason tech -       Disregards women’s needs and experiences when developing AI solutions. -       Deflects its accountability in automating and increasing online harassment -       Purposely reinforces gender stereotypes -       Operationalises menstrual surveillance -       Sabotages women’s businesses and activism I substantiate each of the points above with real examples and the impact on the lives of women.   Fortunately, not all is doom and gloom.   Because insanity is to do the same thing and expect a different outcome, I also share what we need to start doing differently to develop AI that works for women too.   #EthicalAI #InclusiveAI #MisogynisticAI #BiasedAI #Patriarchy #InclusiveTech #WomenInTech #WomenInBusiness

𝗔𝗜 𝗶𝘀 𝗼𝗻𝗹𝘆 𝗮𝘀 𝗳𝗮𝗶𝗿 𝗮𝘀 𝘁𝗵𝗲 𝘄𝗼𝗿𝗹𝗱 𝗶𝘁 𝗹𝗲𝗮𝗿𝗻𝘀 𝗳𝗿𝗼𝗺. Artificial Intelligence isn’t created in a vacuum - it’s trained on data that reflects the world we’ve built. And that world carries deep, historic inequities. If the training data includes patterns of exclusion, such as who gets promoted, who gets paid more, whose CVs are ‘successful’, then AI systems learn those patterns and replicate them. At scale and at pace. We’re already seeing the consequences: 🔹Hiring tools that favour men over women 🔹Voice assistants that misunderstand female voices 🔹Algorithms that promote sexist content more widely and more often This isn’t about a rogue line of code. It’s about systems that reflect the values and blind spots of the people who build them. Yet women make up just 35% of the US tech workforce. And only 28% of people even know AI can be gender biased. That gap in awareness is dangerous. Because what gets built, and how it behaves, depends on who’s in the room. So what are some practical actions we can take? Tech leaders: 🔹 Build systems that are in tune with women’s real needs 🔹 Invest in diverse design and development teams 🔹 Audit your tools and data for bias 🔹 Put ethics and gender equality at the core of AI development, not as an afterthought Everyone else: 🔹 Don’t scroll past the problem 🔹 Call out gender bias when you see it 🔹 Report misogynistic and sexist content 🔹 Demand tech that works for all women and girls This isn’t just about better tech. It is fundamentally about fairer futures. #GenderEquality #InclusiveTech #EthicalAI Attached in the comments is a helpful UN article.

🤖 The Gendered Impact of AI: Why Women—Especially from Marginalised Backgrounds—Are Most at Risk As artificial intelligence continues to reshape the world of work, one thing is becoming increasingly clear: the effects will not be felt equally. A new report from the United Nations’s International Labour Organization and Poland’s NASK reveals that roles traditionally held by women—particularly in high-income countries—are almost three times more likely to be disrupted by generative AI than those held by men. 📉 9.6% of female-held jobs are at high risk of transformation, compared to just 3.5% of male-held roles. Why? Many of these jobs are in administration and clerical work—sectors where AI can automate routine tasks efficiently. But while AI may not eliminate these roles outright, it is radically reshaping them, threatening job security and career progression for many women. This risk is not theoretical. Back in 2023, researchers at OpenAI—the company behind ChatGPT—examined the potential exposure of different occupations to large language models like GPT-4. The results were striking: around 80% of the US workforce could have at least 10% of their work tasks impacted by generative AI. While they were careful not to label this a prediction, the message was clear: AI's reach is widespread and accelerating. 🌍 An intersectional lens shows even deeper inequities. Women from marginalised communities—especially women of colour, older women, and those with lower levels of formal education—face heightened vulnerability: They are overrepresented in lower-paid, more automatable roles, with limited access to training or advancement. They often lack the tools, networks, and opportunities to adapt to digital shifts. And they face greater risks of bias within the AI systems themselves, which can reinforce inequality in recruitment and promotion. Meanwhile, roles being augmented by AI—like those in tech, media, and finance—are still largely male-dominated, widening the gender and racial divide in the AI economy. According to the World Economic Forum, 33.7% of women are in jobs being disrupted by AI, compared to just 25.5% of men. 📢 As AI moves from buzzword to business reality, we need more than technical solutions—we need intentional, inclusive strategies. That means designing AI systems that reflect the full diversity of society, investing in upskilling programmes that reach everyone, and ensuring the benefits of AI are distributed fairly. The question on my mind is - if AI is shaping the future of work, who’s shaping AI? #AI #FutureOfWork #EquityInTech #GenderEquality #Intersectionality #Inclusion #ResponsibleTech

50% of women abandon their tech career by age 35 And what do companies offer in response? Good intentions: ❌ Speaker panels (especially unpaid) ↳ Women don't need another panel to hear how resilient they are (hint: they know). ❌ Mentoring (without sponsorship) ↳ Mentorship offers advice to women, but rarely shifts career outcomes. ❌ Branded merchandise (“You Go Girl” swag) ↳ Tote bags and water bottles feel patronising when real problems go unaddressed. ❌ Imposter Syndrome Training ↳ Teaching women to 'fix' imposter syndrome shifts the blame off the workplace. ❌ One-Off Diversity Events ↳ Diversity breakfasts are feel-good gestures unless backed by real change. The best way to stop women leaving tech? Change what actually matters: 1/ Equal Pay 💡 Women are paid on average 16% less than men for the same roles → Run regular pay audits and share the results. → Put budget behind programs that fix pay equity. → Tie executive bonuses to closing the gender pay gap. 2/ Bias Free Environments 💡 48% of women experience gender discrimination at work → Enforce zero-tolerance policies for harassment and discrimination. → Report volumes of discrimination complaints and resolutions. → Track hidden bias, like who gets key projects and leadership exposure. 3/ Flexible Work Arrangements 💡 67% of women say work-life policies hurt their leadership prospects → Offer flexible hours, remote options, and parental leave for all. → Design roles for job-share and part-time, including senior levels. → Provide on-site childcare or offer childcare subsidies. 4/ Leadership Pathways 💡 Only 11% of executive roles in tech are held by women → Set KPIs to track women’s progression at every level. → Require diverse candidate slates and transparent promotion processes. → Fund retention programs for mid-career women with leadership potential. 5/ Sponsorship & Role Models 💡 58% of women say they don’t have equal access to networking → Pair women with senior leaders accountable for their progression. → Hold networking events during work hours, not after hours. → Track sponsorship impact through promotion outcomes. 6/ Return To Work Programs 💡 40% of women leave tech due to caring responsibilities → Offer paid returnships with training and meaningful work. → Re-hire for transferable skills, not just linear career paths. → Set targets for returner hiring and publish progress. Tech hasn’t just lost women, it’s pushed them out. The way back? Leadership that wants to fix it. Ditch the slogans. Start changing what matters. 👉 What would make more women stay in, or come back to, tech? _____________ ♻️ Repost to help your network ➕ Follow Maryann (MJ) for daily career posts

At the Bill & Melinda Gates Foundation office earlier sharing my experience and learnings from the field working on increasing access to digital connectivity and digital public platforms, closing the digital gender divide and the role of the national broadband policy in closing the connectivity gap in Nigeria. The digital divide is a technological problem, with layers of challenges including cost of broadband, issues with rights of way across state governments etc, while the digital gender gap is a human one with barriers including affordability, device ownership gap, gender pay gap, literacy skills, privacy and security concerns with respect to targeted harassment, sexual harassment, bullying etc. All these cumulatively account for the cost of exclusion. The cost of exclusion is not just economic but also has financial, technological, educational and social implications. Policymakers and stakeholders must make it a priority to address these challenges by developing gender responsive broadbands policies that factor in the multifaceted challenges faced by women in the digital space. #digitaldevelopment #digitaldivide #digitalgendergap #broadbandpolicy #digitalinfrastructure

Equipping young women with digital skills is not just a development goal—it’s a foundation for jobs, resilience, agency, and inclusive growth. In Northern Nigeria, the Gina Mata, Gina Al-Umma program, meaning “Building Women, Empowering Communities,” has trained close to 1,300 young women to build skills and access opportunities in the digital economy. With support from the World Bank's Digital Development Partnership, participants are gaining practical skills in digital marketing, online safety, financial literacy, and remote freelancing, creating new pathways to economic opportunity in fragile contexts. This is the kind of impact we aim for: when access to technology translates into access to dignity, independence, and a stronger voice in shaping one’s future. Watch video: https://lnkd.in/g9j9kdwY Read the story: https://lnkd.in/gCARXTvg

This International Women’s Day, new research from LinkedIn's Economic Graph shows that while AI is transforming industries and creating new opportunities, women are more exposed to its disruptions and remain underrepresented in AI-driven roles. Our data show: 💼 Women hold less than one-third of top management positions, and progress toward leadership is slowing. 👩💻 Women are more likely to work in roles at high risk of AI disruption and less likely to move into AI-augmented roles. 🌐 Women make up less than one-third of the AI engineering workforce and an even smaller share of those with AI literacy skills. Without the skills to use these tools, women in these roles face a double disadvantage: job disruption + limited access to new opportunities created by these technologies. What are the opportunities? ✅ Invest in AI upskilling to equip women with the skills needed for AI-driven jobs. ✅ Rethink hiring practices by focusing on skills-based recruitment to create more opportunities. ✅ Use data to drive action and ensure AI is a force for empowerment—not exclusion. 📢 Read my full article below #IWD25 #InternationalWomensDay #AI #FutureOfWork #WomenInLeadership Huge shout out to Matthew Baird, Mar Carpanelli, Kory Kantenga, Ph.D., Silvia Lara for this pivotal research!