Last week I almost sent an AI generated summary to a colleague without reading it. Something made me check it one more time. It turned out the summary had confidently changed the meaning of an important point.

The mistake wasn't dramatic, but it made me wonder how often this happens when people don't double check.

Most of us are focused on making AI more capable. We want it to work faster, solve harder problems, and save more time.

I think the bigger opportunity is making AI more accountable.

As AI becomes part of everyday work, mistakes stop being small inconveniences. They can affect business decisions, financial outcomes, and even people's lives. The more responsibility we give AI, the more important it becomes to know why we should trust its answers.

That shift feels bigger than simply building smarter models.

It's one reason I keep paying attention to @OpenGradient . The conversation isn't only about what AI can do. It's also about how confidence in AI can be earned instead of assumed.

Capability increases productivity.

Accountability determines where AI can safely be trusted.

I think that difference will matter much more over the next few years.

$OPG #opg
$OPG
Have you ever caught an AI mistake before using its output?