Valerie Ehrlich, PhD

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I’ve been thinking a lot lately about the difference between 'efficiency' and 'efficacy' when it comes to integrating AI into our daily workflows.

Last week, I was talking with a client who was feeling overwhelmed by the sheer volume of tools available. They felt like they were running faster and faster, but not necessarily getting anywhere meaningful.

It’s a feeling I know well. (And, if I’m being honest, one I still struggle with some days!)

What we realized together was that the missing piece wasn't a better prompt or a faster model. It was the intentional space for human sense-making. We tend to think of AI as a way to skip the 'boring' parts, but sometimes those boring parts—the sorting, the reading, the reflecting—are exactly where the real insights live.

In my own practice, I’ve started enforcing a '15-minute buffer' after I use an LLM to synthesize notes. I don't look at the output right away. Instead, I write down:

what I remember most vividly from the original text

the 'gut feeling' I had during the initial read

the one question I still haven't answered

how I want the final result to feel

This simple act of slowing down ensures that I remain the 'instrument' of the work, and the AI remains the 'assistant.'

But what I’m taking away from this even more is that 'responsible AI' isn't just about policy. It’s about the small, daily practices that keep us human-centered in a world that is constantly asking us to move faster.

How are you building in space for reflection this week? I’d love to hear your 'slow-down' rituals! ❤️🌀

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