- Eric D. Brown, D.Sc.
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- Trust but Verify: The Need for Critical Thinking with AI
Trust but Verify: The Need for Critical Thinking with AI
In the rush to adopt artificial intelligence, many leaders have forgotten the importance of critical thinking and validation. While AI offers tremendous potential for business transformation, its true value comes from thoughtful implementation and rigorous verification. Here's why trust in AI starts with trusting the humans using it.
Eric Brown
January 09, 2025
A stark reminder that trust requires verification - whether in traditional business or AI implementation. Photo by Bernard Hermant on Unsplash
I'm a huge advocate for AI. Every company should explore and implement AI where it makes sense. The technology is impressive and offers immense potential for innovation and efficiency.
But I'm seeing something concerning: leaders blindly trusting AI outputs without applying critical thinking. This isn't just worrying - it's dangerous for businesses rushing to adopt AI without proper validation processes.
We've spent decades building controls, checks and balances, and validation steps into our business processes. From financial reporting to software development, we've created rigorous verification systems. Yet, with AI, leaders are throwing all that rigor out the window.
Look at Google's search summaries or AI-generated news briefs. They're often inaccurate or missing crucial context. But because AI created them, people accept them without question. How do you know your LLM isn't just making stuff up? You don't - unless you verify.
When you present AI-generated work to stakeholders, you're not asking them to trust the AI - you're asking them to trust your judgment. The technology is a tool like Excel or PowerBI. The real value comes from applying our experience to validate and enhance its outputs.
Companies are rushing to replace existing processes with AI without considering the critical thinking baked into their current approaches. They're so focused on automation that they ignore the risks of unverified outputs.
Forget "trust but verify" - with AI, you verify. Every output needs validation.
This doesn't mean AI isn't valuable—it absolutely is. Companies should explore and implement it. But it's a tool, not a replacement for human judgment. The best leaders approach AI outputs with the same rigor they'd apply to any analysis: questioning assumptions, validating sources, and applying business judgment.
We need to be honest about where AI stands today. These tools can enhance our capabilities but are not ready to replace human judgment or existing business controls. Some use cases are production-ready, but many need careful consideration and validation.
The future of AI in business isn't about blind trust - it's about thoughtful integration. It's about combining AI capabilities with human wisdom. Most importantly, it's about maintaining the healthy skepticism that good business leaders apply to any new technology.
Before implementing AI, establish your validation approach. How will you verify outputs? What controls need to be in place? What does accurate and reliable mean for your specific use case?
Your stakeholders aren't trusting the AI - they're trusting you. That trust must be earned through demonstrated competence and rigorous validation. Don't let the need for validation stop you from implementing AI - but do it thoughtfully, with proper controls in place.
If you found this tech tip helpful, consider sharing it with another executive grappling with AI implementation costs. If you want to explore AI and other Technology strategies, feel free to reach out.
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