---
title: Use AI, But Don't Hand It the Future
description: Discover the importance of informed skepticism and proactive engagement in shaping the future of AI, as we navigate the rapidly evolving landscape with a focus on understanding, learning, and supporting developers who share our values. 6 tips for embracing the AI revolution.
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date: 2026-08-27T15:12:23Z
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AI has been part of my thinking and writing for more than a decade, long before the current wave of tools. I use it every day. It lets me do work I could not previously do alone — especially in image and video generation — and it removes a great deal of friction from repetitive tasks. After years of operating as a one-person operation, the right tools can begin to feel like an orchestra.

I do none of this without skepticism.

### The Model Is a Mirror

As of early 2024, these systems are not independent minds. They are reflections of the data they were trained on, further shaped by the objectives, constraints, and values of the people and organizations that built them. That is not a conspiracy claim. It is a description of how the technology actually works.

A model trained primarily on one culture’s texts, one industry’s priorities, or one political climate’s assumptions will carry those patterns forward. It will not invent a neutral view of the world. It will reproduce, amplify, and sometimes quietly rearrange whatever was present in its training mixture and whatever its creators chose to emphasize or suppress.

The future of these systems will therefore be shaped less by abstract capability than by the concrete values of the people currently building and deploying them. That is the part worth paying attention to.

### What Informed Engagement Looks Like

If you are uneasy about that concentration of influence, the useful response is neither panic nor denial. It is deliberate participation. The practical steps are straightforward:

1. Accept that the technology is not going away. Waiting for comprehensive regulation to solve the problem is not a strategy.
2. Learn how the systems actually behave, not only how they are marketed.
3. Support the developers and companies whose stated values and demonstrated practices you can live with.
4. Withdraw support from those whose practices you cannot.
5. Become competent enough with the tools that you can produce the outcomes you intend rather than the ones the default settings prefer.
6. Treat every interaction as a small training signal. Correct the model when it is wrong, incomplete, or leaning on unexamined assumptions. The quality of the engagement shapes what the system becomes more likely to produce next.
 
None of these steps require technical expertise. They require attention and consistency.

### Information Has Always Been Power

AI does not invent the problem of biased or weaponized information. It accelerates and scales it. Every output — text, image, code, summary — is a curated reconstruction drawn from prior human material and filtered through the priorities of its makers. Not every actor in that chain is primarily interested in giving you the most accurate or complete picture.

The only reliable defense is still the old one: go in with eyes open, keep your own judgment online, and refuse to outsource the final evaluation of what is true or useful.

### The Stance Worth Keeping

I use these tools because they expand what one person can make. I remain skeptical because the systems are not neutral and the people building them are not interchangeable. Both facts can be true at the same time. The work is to stay inside that tension rather than resolving it into either uncritical enthusiasm or reflexive rejection.

That posture — engaged, informed, and unwilling to hand over the terms of the future — is the one I have found most sustainable.
