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You don't have to like AI. You don't have to use ChatGPT. And you definitely don't have to like AI-generated content.

But if we're going to criticize a technology, we should probably understand what we're actually criticizing.

In this episode, we dig into some of the arguments surrounding AI, data centers, water consumption, and the environmental impact of modern technology. We talk about how deeply AI is already embedded in everyday life, from social media and Google searches to fraud detection, GPS, streaming, shopping, and delivery apps, and why the statement “I won't support companies that use AI” quickly becomes complicated.

We also look at data centers: what they actually do, why they existed long before the current generative-AI boom, why they use water, the difference between water withdrawal and consumption, and why enormous numbers need context before they're useful.

Then we bring the conversation back to business. Todd explains how he actually uses AI at Hello and on this podcast, why AI should amplify your thinking rather than replace it, and why the amount of verification you do should increase with the consequences of getting something wrong. 

Big Idea

You don't need to support every new technology. But skepticism is more useful when it's built on understanding instead of assumptions.

Key Takeaways

•  AI is much broader than ChatGPT, image generators, and generative video. 
•  AI is already embedded in many everyday technologies and services. 
•  Saying “don't use AI, use Canva” ignores Canva's own investment in AI. 
•  Data centers existed long before the current generative-AI boom. 
•  Modern banking, streaming, shopping, logistics, cloud services, maps, and countless other systems rely on data-center infrastructure. 
•  Large numbers without context can make it difficult to understand relative scale. 
•  Water withdrawal and water consumption are different concepts. 
•  Water use can create legitimate local challenges even if the broader issue isn't simply “the water disappears.” 
•  New infrastructure creates costs, tradeoffs, and potential economic benefits. 
•  AI can be extremely useful for brainstorming, organizing, editing, learning, and building workflows. 
•  The higher the consequence of being wrong, the higher your standard for verification should be. 
•  AI slop and misinformation are legitimate problems and examples of what happens when people outsource judgment rather than using the tool thoughtfully. 
•  You don't have to like AI, but at least know why you don't like it. 

Reflection

What opinion have you formed because you've actually looked into something, and what opinion have you formed because you've heard the same argument repeated enough times?

You don't have to change your mind.

But it's worth knowing why you believe what you believe.

Your business should serve you, so that you can serve others.
Stay curious enough to question your own assumptions, too.

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