When AI Gets It Wrong—Veterans Know Why and How to Fix It

Hey there, I’m Ambika—welcome to the 12th edition of Jai Jawan Jai Kisan (Hail the Soldier, Hail the Farmer)! 🚜🌱

🌟 A heartfelt thanks to everyone who’s been supporting this newsletter by sharing ideas and references for topics to cover every week. You all rock! 🤩 I'm absolutely hooked on anything that dives deep into algorithmic biases and training large language models (LLMs). This topic fascinates me because we’re right on the brink of defining the next 50 years of human progress! 🚀

We’re living in a time when corporations are releasing updated LLMs faster than smartphone manufacturers roll out their operating system updates 📱✨. Recently, I took a super insightful course called "Avoiding AI Harm" via Coursera, designed by the brilliant minds at Fred Hutchinson Cancer Centre. It was a game-changer! 💡🎓

🤔 This got me thinking—what happens when AI goes wrong in high-stakes environments? The consequences are massive! 🚨 In 2025 alone, we’ve seen AI biases cause wrongful arrests, discriminatory hiring practices, and even life-threatening medical errors. But guess what? These blunders aren’t new—the military has been dealing with AI failures on the battlefield for years. 💥

In warfare, a single algorithmic error can literally mean life or death. ⚠️ While corporate companies are still scratching their heads trying to fix AI biases, it’s high time we bring in battle-tested veterans 💪. These experts could audit current AI systems and rigorously test them against biases—the same ones that caused catastrophic model failures in warfare. 🎯

It’s all about learning from those who’ve faced the chaos firsthand. 🌍✨ What do you think? 🔎

In modern battlefields, AI powers everything from drone targeting to logistics. But when algorithms fail to distinguish civilians from combatants, the consequences can be devastating. 💥 In late 2024, an autonomous surveillance system in the Middle East misclassified humanitarian workers as insurgents, leading to a lethal drone strike with 12 civilian casualties and global condemnation. The root cause? Wait, before you say AI… the real culprit was biased data that overemphasized specific behavioral patterns. Similarly, corporate AI faces comparable risks—misclassifying customers, rejecting qualified candidates, and delivering biased outcomes. 📉 A major tech firm recently faced legal trouble after its recruitment AI disproportionately rejected women and older candidates.

This is where military veterans come in! 💪 Trained to assess complex, high-stakes situations where lives are on the line, veterans bring a critical edge. Their situational awareness allows them to spot subtle biases that others might miss—whether in law enforcement AI, where facial recognition systems have a 34% higher error rate for non-white faces, or in the tech sector, where recruitment tools recently disqualified 200 qualified applicants due to biased data. Veterans’ human-in-the-loop approach is invaluable for ensuring algorithmic transparency. 🤖✨

The military’s diverse environment encourages cross-cultural collaboration, creating a unique advantage in spotting data blind spots. 🧠Military personnel represent one of the most diverse professional cohorts—spanning ethnicities, socioeconomic backgrounds, and global perspectives. In February 2025, an AI surveillance tool misidentified minority climate activists in London, echoing the same flaws seen in defense systems. Veterans, with their real-world expertise, flagged such biases, applying their insights to mitigate AI harm to underrepresented communities. Another example that is worth sharing is of a healthcare AI —- in 2025 this AI model underdiagnosed heart disease in women due to male-biased training data—a gap veterans trained in triage decision-making could have effectively flagged.

The world of AI is racing ahead faster than we ever imagined! 🚀 More and more companies are diving into this field, bringing disruptive AI models that are shaping the future of technology. But amidst all the excitement, we must not overlook the looming danger of AI bias. ⚠️ Without proper audits, biased AI can cause significant harm—not just by infringing on human rights but by threatening the livelihoods of countless people. 💔

We need forward thinkers—people who can truly think out of the box. 🌟 Battle-tested wisdom is what we need to fix the error-prone data that is fed to these AI models. It’s their expertise that can bring algorithmic transparency, uphold AI ethics, and uncover the blind spots that today’s developers and corporate decision makers often miss. 🔎✨

On the battlefield, decisions are made quickly, accurately, and under uncertain conditions. 🎯 This same mindset is critical for improving AI’s ability to handle edge cases and adapt to real-world complexities.

The future of human-AI symbiosis depends on such outside-the-box thinking. 🌍💡 Hiring top-notch AI devs and data scientists alone isn’t enough. We need experts from diverse sectors—especially the military—who can bring their pragmatic wisdom into the mix. 🛡️ By hiring more veterans into corporate AI teams, companies can bridge the gap between innovation and real-world problems. Defense organizations are already partnering with private-sector AI teams to test algorithms in battlefield scenarios. It’s time companies across industries adopt similar strategies, recruiting more and more veterans to review and refine AI systems to eliminate unintended biases. 🙌

Veterans, with their experience, understand that no system works in isolation. 🤝 AI oversight also requires ongoing collaboration between human expertise. No innovation gets refined by operating in silos. It’s time we give a chance to our war heroes to fine tune and improve the machine efficiency—together, we can create a safer, fairer future for AI. 🤖✨

Shoutout to incredible thought leaders like Timnit Gebru (a trailblazer in Ethical AI), Fei-Fei Li (Godmother of AI) and Andrew Ng (Visionary in AI education and innovation) who are driving the conversation around fairness, accountability and inclusivity of AI, ensuring that tech serves humanity equitably. You have been a source of inspiration to me. ❤️

I hope you enjoyed this week’s edition! If you found value in it, I’d love for you to share it with your friends—it truly fuels my passion to bring you more insightful and inspiring content every week.

Can’t wait to connect again next week! Until then, keep championing sustainability and resilience in everything you do. 🌱✨

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