Mindora转发了
Three months ago, I was in a virtual workshop with my team. We were building an earlier prototype of Mindora and in that moment, I realised something was off. We had just hit an uncomfortable truth. "What if the AI learns the wrong things?" someone asked. "What if it picks up on patterns we don't want it to reinforce?" The question hung in the air. Because here's the thing about building AI for HR: you're not just writing code. You're crafting something that will influence how organizations understand and support their people. The weight of that responsibility is... heavy. I've learned more about bias in the last year building Mindora than I did in my entire previous career in tech. And not just the obvious kinds. Take this example: We were working on a feature that would use AI to generate personalised messages for employees. The idea was that our platform would identify well-being risks and automatically reach out to individuals through Slack or Teams with supportive messages and suggestions. On paper, it looked perfect. Direct intervention. Scalable support. Immediate response to well-being needs. But something felt off. The more we developed it, the more we realised we were thinking about workplace well-being through the wrong lens. We were trying to solve a systemic challenge with individual band-aids. This moment fundamentally changed how we approach AI development at Mindora. We pivoted to focus entirely on empowering HR and business leaders with insights that enable them to build holistic well-being strategies. Because real change doesn't come from an AI sending a well-crafted message to a stressed employee. It comes from leaders who understand the full picture and can create environments where well-being is woven into the fabric of how work gets done. Here are the three questions we now ask ourselves every day: 1?? Are we empowering human judgment or replacing it? I remember a conversation with an HR leader who said, "I don't want AI to tell me what to do. I want it to help me see what I might be missing." That stuck with me. 2?? Can we explain not just what the AI sees, but why it sees it? Transparency isn't a feature - it's a fundamental right when AI is involved in decisions about people's well-being. 3?? Are we building for the averages or the edges? Because the most important insights about workplace well-being often come from understanding the exceptions, not the rules. These aren't perfect principles. They're messy, often conflicting, and force us to move slower than we sometimes want to. But they help us sleep at night. I'm sharing this because I believe the future of AI in HR will be built on honest conversations about these challenges. The kind of conversations that start with "I don't know" and end with "let's figure this out together." #AIinHR #ProductDevelopment #WorkplaceWellbeing #EthicalAI