Tech-Driven Workforce Diversity

AI isn’t just a powerful tool for accelerating sustainability work. It can also help us move faster in advancing human rights - and we’re piloting AI models that do just that. Amazon has hundreds of thousands of suppliers worldwide - that’s a massive scope. So we’re harnessing AI to keep pace, prevent, and respond to human rights risks in our network. Here are two examples of how that’s taking shape: 🔍 Smarter Risk Prediction: We developed an AI model that can analyze tens of thousands of historical social audits to identify patterns, spot warning signs, and flag high-risk suppliers - essentially helping us zoom in on what matters. The testing results were impressive - the tool successfully identified about 9 out of every 10 high-risk sites, with 85% overall accuracy. ⏱Faster insights: It can take a human rights manager up to four hours to manually review a supplier audit report. But we developed an AI tool that processes a report in just minutes - identifying risks, rating the seriousness, and suggesting next steps. Early versions helped us process audit reports 65% faster - a remarkable difference! It’s important to note - these AI tools aren’t replacing human decision-making. They’re designed to support, enhance and accelerate our work. Every AI recommendation gets reviewed by our experts - and their input actually helps improve the system over time. We’re still in early stages, but I’m inspired by the potential. On this #HumanRightsDay, I invite you to learn more about our work from Devex’s comprehensive interview with Leigh Anne DeWine, our Director of Human Rights & Social Impact, who is making a great impact every day here at Amazon. Thanks to Leigh Anne and our entire Human Rights and Social Impact team for the incredibly critical work you do. 🙏 https://lnkd.in/gSWZAWFB

One simple hack for every software agency to train their people and keep up with the AI revolution: Get engaged in social impact projects, pro bono. Seriously, I get this question so often when talking to software vendors: “I'd love to use our skills for good, but what do we get if we get involved?” There’s a lot to say – building a portfolio, go-to-market strategies, retaining talent. Did you know that 86% of Gen Zs and 89% of millennials say a sense of purpose is important to overall job satisfaction? But one golden use case has emerged recently – a true win-win-win. What we’ve seen at Tech To The Rescue over the past five years is simple: Social impact work isn’t charity. It’s how companies sharpen their edge. When tech teams partner with nonprofits tackling crises – like Mercy Corps or ACAPS – they’re not just donating skills. They’re learning in ways no corporate client could teach them. They’re designing for chaos, building for the underserved, and stretching their creativity to the limit. For small and mid-sized companies, this work is a goldmine of tactical insight: - Designing systems for low-bandwidth environments - Creating tools for users with limited digital literacy - Adapting platforms for multilingual emergency contexts These aren’t side projects. They’re previews of the challenges companies will face as they scale into new markets. We call it R&D with purpose. That’s why every week, more than 10 software agencies join Tech To The Rescue. Today, three out of four of them treat AI upskilling as the key business driver for their engagement. It’s also why top minds join the movement to power up nonprofits with their expertise – just like Werner Vogels, Amazon’s CTO, who mentors nonprofit CTOs directly, giving them access to the same leadership and technical playbook that powers Amazon Web Services (AWS) (all done under the Now Go Build CTO Fellowship, created in partnership with our AI for Changemakers program). My op-ed on this has just been published by Fast Company (thanks to magnificent Jean Ekwa!). I’d love to hear your thoughts – please drop them below. 👏 Lars Peter Nissen, Alicia Morrison, Yevhen B.

Access to justice organizations present unique opportunities for technology companies. Some thoughts on effectively engaging with this impactful sector: 1. Prioritize affordability: Develop flexible pricing models, including sliding scales based on organizational size or client volume. Consider offering pro bono licenses to qualifying nonprofits. 2. Streamline intake processes: Demonstrate how your case management system can reduce initial client screening time by 50% or how your chatbot can triage inquiries, freeing up staff for complex cases. 3. Emphasize data privacy: Highlight robust anonymization features and compliance with domestic violence shelter confidentiality requirements. Detail your approach to handling sensitive immigration status information. 4. Design for accessibility: Create interfaces optimized for users with limited digital literacy. Ensure compatibility with screen readers and offer multilingual support for common languages in underserved communities. 5. Form community partnerships: Collaborate with bar associations and law schools to gather insights on unmet legal needs. This informs product development and builds credibility with potential clients. 6. Develop social impact metrics: Invest in analytics that quantify your technology's effect on case outcomes, time saved, or number of additional clients served. This data supports grant applications and impact reporting. 7. Address specific legal domains: Tailor solutions for high-need areas like eviction defense, debt collection, or public benefits appeals. Offer modules that incorporate relevant local laws and court procedures. 8. Facilitate knowledge sharing: Implement features that allow easy creation and distribution of know-your-rights materials or pro se resources, amplifying the reach of limited legal staff. The stakes in this market extend far beyond profit margins. By developing tools that expand access to justice, tech companies have the potential to reduce inequality, prevent homelessness, protect domestic violence survivors, and strengthen the very fabric of civil society. Those who successfully navigate the unique challenges of this sector won't just capture market share – they'll play a pivotal role in fulfilling the promise of equal justice under law. #legaltech #innovation #law #business #learning

The UK government just acknowledged something most digital transformation programmes quietly ignore. Technology is not the constraint anymore. Access is. Published on 24 March 2026, the Digital Inclusion Action Plan One Year On outlines progress on the government’s commitment to digital access. It aims to ensure everyone, regardless of their circumstances, can get connected and go online safely and with confidence. But 1.6 million people have no internet connection at all, and many more do not have the right device or the skills to use the internet at work and in life. People who are not online are often also disabled, older, or have lower incomes. Without internet access and digital skills, they end up paying more for bills, trapped earning less, or unable to easily get the support they need. That is a structural inequality being reinforced by every service that moves exclusively online without asking who gets left behind. The plan is doing something other digital strategies rarely do. It explicitly commits to ensuring online services are simple to use with offline options too, and to putting in place more trusted local help. That second part matters enormously. Most digital transformation programmes treat non digital access as a temporary concession until everyone catches up. This plan treats it as a permanent design requirement. The plan highlighted groups more likely to struggle, including low income households, older people, disabled people, unemployed people, and some young people not in employment, education or training. These are precisely the groups who most depend on government services. Building services that work beautifully for connected, confident users whilst excluding the most vulnerable is not digital transformation. It is digital displacement. The real test of this plan is not whether it reaches the people already online. It is whether it changes how departments design services for the people who are not. How many of your services assume digital access that your most vulnerable users do not have? #DigitalInclusion #GovTech #PublicSector

Amazon’s hiring AI once rejected qualified women and preferred men. Here’s why: Paola Cecchi-Dimeglio, a Harvard lawyer and Fortune 500 advisor, has a warning for HR: If you ignore AI bias, you scale discrimination because it learns our prejudice and amplifies it in hiring and performance decisions. Remember Amazon's hiring algorithm? It systematically favored male candidates because it learned from historical hiring data that was already biased. The tool was discontinued, but the lesson remains relevant for every organization using AI today. Dimeglio identifies three critical sources of bias: 1. Training data bias: When AI learns from unrepresentative data, it produces skewed outcomes. For example, generative AI models underrepresent women in high-performing roles and overrepresent darker-skinned individuals in low-wage positions. 2. Algorithmic bias: Flawed data leads to biased algorithms. Recruitment tools may favor keywords more common on male resumes, perpetuating gender disparities in hiring. 3. Cognitive bias: Developers' unconscious biases influence how data is selected and weighted, embedding prejudice into the system itself. Paola's solution framework for HR leaders: ✅ Ensure diverse training data – Invest in representative datasets and synthetic data techniques  ✅ Demand transparency – Require clear documentation and regular audits of AI systems  ✅ Implement governance – Establish policies for responsible AI development  ✅ Maintain human oversight – Integrate human review in AI decision-making  ✅ Prioritize fairness – Use methods like counterfactual fairness to ensure equitable outcomes  ✅ Stay compliant – Follow regulations like the EU's AI Act and NIST guidelines As Paola emphasizes: "HR leaders, as the gatekeepers of talent and culture, must take the lead on avoiding and mitigating AI biases at work." This isn't just about fairness, it's about achieving better outcomes, building trust, and protecting your organization from legal and reputational risks. The question isn't whether AI has bias. It's whether you're doing something about it. How is your organization addressing AI bias in HR processes? Let's discuss.

This article maps bias across the full lifecycle of medical AI: training data (who is in the dataset and what’s missing) --> labels (how “ground truth” encodes human bias) --> model development and evaluation --> real-world implementation --> which models get published and from where. It illustrates concrete clinical risks, from melanoma models that underperform on dark skin to ICU mortality models with recall as low as 25% in underrepresented groups, and shows how biased systems can drive substandard decisions for the very patients who most need better care. The authors argue that mitigation must go beyond technical fixes, combining diverse datasets, fairness-aware modeling, interpretability, stronger standards, and clinical trials that explicitly test for unbiased performance. Key takeaways - Bias enters early: imbalanced cohorts, nonrandom missing data, and the absence of social determinants of health all push models to work best for already advantaged groups. - “Ground truth” is not neutral: labels reflect provider behavior, misclassification, and structural inequities, so models can learn and amplify existing clinical biases rather than correct them. - Whole-cohort metrics like AUC can hide harm; subgroup performance, fairness metrics, and interpretability tools are essential to detect and mitigate inequity in model outputs. - Real-world deployment introduces new bias: models can fail on populations unlike the training data (Epic sepsis model is a key example), and clinician use/override patterns can themselves be inequitable. - Publication and funding ecosystems skew what gets built and validated, with over half of clinical AI models using US or Chinese data, and radiology dominating the literature. Dipu’s Take If AI in medicine isn’t explicitly designed and governed for equity, it will quietly operationalize our worst blind spots at scale. Accuracy alone is a distraction metric; the harder questions are “for whom, in which contexts, and at what clinical cost?” The leadership opportunity here is to treat debiasing as core safety and quality work: mandate diverse data, require subgroup reporting and fairness metrics, bake bias monitoring into post-deployment oversight, and tie reimbursement and approvals to demonstrated equitable performance in trials.

India’s digital revolution has already changed how we pay, transact and borrow. #Aadhaar, #UPI, #DigiLocker, #AccountAggregators, and #OCEN, have made the India Stack the backbone of financial inclusion. Yet, for millions in #RuralIndia, credit remains a missing piece. Documentation, rigid eligibility criteria, and credit scores leave many farmers, shopkeepers, and entrepreneurs out of the formal financial system, despite their clear need and potential. This is where #AIforRuralIndia (AIR) can be a game changer. - Imagine a farmer applying for credit in his local dialect, guided by a simple voice interface. - Imagine repayment plans that match harvest cycles, not rigidly fixed EMIs. - Imagine trust built through alternative data, like mobile usage or cash-flow behaviour, when formal history is absent. When #AIR meets #IndiaStack, credit is no longer about transactions, it leads to #transformation. It’s about creating financial solutions that are intelligent, inclusive, and empathetic. In my latest piece for Analytics Insight®, I dive into how this convergence can unlock a new era of rural credit, scalable, sustainable, and built for #Bharat. Read the full article here: https://lnkd.in/duEDkhv8 #FinancialInclusion #AI #RuralCredit #IndiaStack #TechForBharat

What does a fair go look like in 2025? Increasingly, it means access to a digital device, reliable internet and the skills to use them. New data from the Australian Digital Inclusion Index shows 1 in 5 Australians remain digitally excluded or highly excluded. For the first time, the Index also measured generative AI uptake – because the dimensions of digital inclusion are evolving fast, and so are the risks of being left behind. At The Smith Family, we see firsthand the impact digital exclusion has on students experiencing poverty and disadvantage. It doesn’t just affect academic achievement, but well-being, career readiness and the opportunities that shape a young person’s future. Once, literacy was about reading and writing. Today, it’s also digital fluency. Next, it will demand the ability to navigate AI critically and safely. A fair go in 2025 is about equitable access to the digital world – for everyone. For young people, digital inclusion means the chance to thrive at school and step into all kinds of future jobs. For Australia, it means making the most of everyone’s potential, which leads to stronger communities and a more competitive economy. https://bit.ly/4nPdbSw RMIT University, Swinburne University of Technology, Telstra, ARC Centre of Excellence for Automated Decision-Making and Society

Technology's greatest impact happens when it's placed in the hands of people solving the world's toughest challenges.   The Lenovo AI for Social Impact Lab, in partnership with Tech To The Rescue, is supporting remarkable nonprofits using AI combined with deep local knowledge and insights to help their communities with solutions that are scalable, inclusive, and urgently needed.   One example that continues to inspire me: WeRobotics Brazil Flying Labs. Their solution involves using satellite imagery, drone technology, and AI-powered algorithms to monitor wildfires near São Paulo, Brazil. It enables real-time fire monitoring, rapid damage assessment, and smarter planning for future events, reducing risk to personnel and helping conservation units act faster and safer.   Here's one example from the team's workflow: to process massive amounts of data, they use high-end Lenovo Legion laptops to run demanding AI-based software, helping transform thousands of raw images into meaningful insights on the ground. They were kind enough to share these photos with us of the work in action.   This is just one of several incredible organizations in the program using AI, local knowledge, and Lenovo tech to do good. Their work is the definition of #TechForGood. It makes me super proud that Lenovo is playing a role in this space! More on these powerful stories https://bit.ly/3TxHEYB