Systemic exclusion of women in tech training

"This report developed by UNESCO and in collaboration with the Women for Ethical AI (W4EAI) platform, is based on and inspired by the gender chapter of UNESCO’s Recommendation on the Ethics of Artificial Intelligence. This concrete commitment, adopted by 194 Member States, is the first and only recommendation to incorporate provisions to advance gender equality within the AI ecosystem. The primary motivation for this study lies in the realization that, despite progress in technology and AI, women remain significantly underrepresented in its development and leadership, particularly in the field of AI. For instance, currently, women reportedly make up only 29% of researchers in the field of science and development (R&D),1 while this drops to 12% in specific AI research positions.2 Additionally, only 16% of the faculty in universities conducting AI research are women, reflecting a significant lack of diversity in academic and research spaces.3 Moreover, only 30% of professionals in the AI sector are women,4 and the gender gap increases further in leadership roles, with only 18% of in C-Suite positions at AI startups being held by women.5 Another crucial finding of the study is the lack of inclusion of gender perspectives in regulatory frameworks and AI-related policies. Of the 138 countries assessed by the Global Index for Responsible AI, only 24 have frameworks that mention gender aspects, and of these, only 18 make any significant reference to gender issues in relation to AI. Even in these cases, mentions of gender equality are often superficial and do not include concrete plans or resources to address existing inequalities. The study also reveals a concerning lack of genderdisaggregated data in the fields of technology and AI, which hinders accurate measurement of progress and persistent inequalities. It highlights that in many countries, statistics on female participation are based on general STEM or ICT data, which may mask broader disparities in specific fields like AI. For example, there is a reported 44% gender gap in software development roles,6 in contrast to a 15% gap in general ICT professions.7 Furthermore, the report identifies significant risks for women due to bias in, and misuse of, AI systems. Recruitment algorithms, for instance, have shown a tendency to favor male candidates. Additionally, voice and facial recognition systems perform poorly when dealing with female voices and faces, increasing the risk of exclusion and discrimination in accessing services and technologies. Women are also disproportionately likely to be the victims of AI-enabled online harassment. The document also highlights the intersectionality of these issues, pointing out that women with additional marginalized identities (such as race, sexual orientation, socioeconomic status, or disability) face even greater barriers to accessing and participating in the AI field."

My recent research, which examines the adoption of emerging technologies through a gender lens, illuminates continued disparities in women's experiences with Generative AI. Day after day we continue to hear about the ways GenAI will change how we work, the types of jobs that will be needed, and how it will enhance our productivity, but are these benefits equally accessible to everyone? My research suggests otherwise, particularly for women. 🕰️ The Time Crunch: Women, especially those juggling careers with care responsibilities, are facing a significant time deficit. Across the globe women spend up to twice as much time as men on care and household duties, resulting in women not having the luxury of time to upskill in GenAI technologies. This "second shift" at home is increasing an already wide divide. 💻 Tech Access Gap: Beyond time constraints, many women face limited access to the necessary technology to engage with GenAI effectively. This isn't just about owning a computer - it's about having consistent, uninterrupted access to high-speed internet and up-to-date hardware capable of running advanced AI tools. According to the GSMA, women in low- and middle-income countries are 20% less likely than men to own a smartphone and 49% less likely to use mobile internet. 🚀 Career Advancement Hurdles: The combination of time poverty and tech access limitations is creating a perfect storm. As GenAI skills become increasingly expected in the workplace, women risk falling further behind in career advancement opportunities and pay. This is especially an issue in tech-related fields and leadership positions. Women account for only about 25% of engineers working in AI, and less than 20% of speakers at AI conferences are women. 🔍 Applying a Gender Lens: By viewing this issue through a gender lens, we can see that the rapid advancement of GenAI threatens to exacerbate existing inequalities. It's not enough to create powerful AI tools; we must ensure equitable access and opportunity to leverage these tools. 📈 Moving Forward: To address this growing divide, we need targeted interventions: Flexible, asynchronous training programs that accommodate varied schedules Initiatives to improve tech access in underserved communities. Workplace policies that recognize and support employees with caregiving responsibilities. Mentorship programs specifically designed to support women in acquiring GenAI skills. There is great potential with GenAI, but also risk of leaving half our workforce behind. It's time for tech companies, employers, and policymakers to recognize and address these gender-specific barriers. Please share initiatives or ideas you have for making GenAI more inclusive and accessible for everyone. #GenderEquity #GenAI #WomenInTech #InclusiveAI #WorkplaceEquality

🚨 We’re not just losing women in tech — we’re losing innovation, and future leadership. BILLIONS of £££s. Thanks to my friend Rav Bumbra for highlighting The Lovelace Report —— which launched at the House of Commons by WeAreTechWomen and Oliver Wyman. 💡 Key insights from the report: • 40,000–60,000 women exit UK tech roles every year • 80% of women in tech are currently considering leaving • 90% want to lead, yet only 1 in 4 believe it’s achievable • Over 70% hold additional qualifications, yet only 14% feel they’re progressing • Replacement and retraining alone costs another £1.4–2.2 billion As someone who has dedicated years to making cybersecurity more inclusive, this report lands with weight — but also with clarity. It’s not women who need fixing. It’s the system. This isn’t a pipeline problem. It’s a systemic failure to retain and progress women in tech — which is costing the UK £2–3.5 billion a year. That number is staggering, but it represents more than financial loss — it reflects lost innovation, stalled careers, and cultures that aren’t serving the people they claim to include. The Lovelace Report lays out a clear and urgent blueprint for change. We must: ✅ Redesign career frameworks to be inclusive by default ✅ Tackle structural barriers to progression ✅ Build cultures where women thrive — not just survive 🔗 Read and share the report: https://lnkd.in/es-235TF Let’s ensure our daughters — and every woman entering tech today — finds not just opportunity, but longevity, leadership, and equity. 📢 Please pass this on to your teams, tech leaders, and HR partners. Progress only happens when we act together. #WomenInTech #TheLovelaceReport #InclusiveLeadership #TechForGood #Cybersecurity #RetentionCrisis #EquityInTech #INSecurityMovement #JaneFrankland

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 𝗖𝗼𝘀𝘁 𝗼𝗳 𝗡𝗼𝘁 𝗛𝗮𝘃𝗶𝗻𝗴 𝗔𝗻𝘆𝗼𝗻𝗲 𝗔𝗯𝗼𝘃𝗲 𝗠𝗲 𝗪𝗵𝗼 𝗟𝗼𝗼𝗸𝗲𝗱 𝗟𝗶𝗸𝗲 𝗠𝗲 Women in Tech are in minority. But as a woman leader, an AI infrastructure expert and an ex-particle physicist, I have experienced being the only woman in the room at yet another level. Not only have I only reported to men over the course of my career: 👉 The whole chain of command above me has always only been men. 👉 I've always worked for companies where the CEO and the CTO were men. 👉 In fact, almost all my peers were men, meaning that I was practically always the only woman in all staff meetings I was part of (sometimes, that would be 20 or 30 people!) When I was younger, I felt honored just to be there, part of an elite group of technologists. But that very feeling of being "lucky to be included" shaped how I behaved. I held back disagreement, afraid that if I challenged the group, it would be attributed to me being difficult, to me being... a woman. And when I was talked over or quietly ignored, it could never identify when it was discrimination, because I thought that since I was here, it must mean that they cared about my opinion, so if they shut it down, it meant I was just wrong. But then, it started costing me more than just self-confidence, but real opportunities: ❌ I couldn't find the courage to ask for promotions because I felt I should already consider myself lucky to be the highest ranking woman in my department ❌ I didn't have anyone to advise me because no one above me had gone through the same experience ❌ Some of my managers even praised me for "doing really well for a woman", so it made me feel that I was subject to different standards, and of course, no one was there to tell me otherwise ❌ I accepted the fact that I was being passed on for cool projects and promotions as a fatality In the meantime, DEI initiatives were focusing on bringing more women onboard, not helping the ones already in place grow the ladder. So if you’re the only one in the room, or the only one on the org chart who looks like you, don’t let that become a ceiling. 🤞 You are not "lucky" to be there. 💥 You are powerful. And you have every right to keep growing… and to keep dreaming 🚀 🚀🚀 #WomenInTech #Leadership #CareerGrowth #RepresentationMatters