The Stochastic Lens

Why your AI is basically just guessing

Your DAM’s AI doesn't actually see a photo of a tree. It looks at a bunch of pixels, runs some math, and decides there's a 90% chance it's looking at a "tree." It’s not finding facts; it’s just making a very educated guess.

If you want your library to actually work, you need to understand how this math works. Here’s the deal:

1. You have to decide how "strict" to be

AI doesn't just give you one tag. It generates hundreds of guesses in the background. You have to tell the system where to draw the line. If you set the "confidence threshold" to 60%, you’ll get loads of tags, but half of them will be wrong. Set it to 95% and your data will be clean, but the AI might ignore a perfectly good photo because it was only 94% sure. It’s a bit like a nervous intern - do you want them to shout out every thought, or only speak when they’re certain?

2. Watch out for "hallucinations"

Sometimes the math just fails. The AI sees a blurry yellow fire hydrant and decides it’s definitely a Minion. If your team trusts every tag blindly, your search results will turn into a mess. You’ve got to remind people that the AI is just playing a numbers game, so they know when to step in and tidy up the nonsense.

3. AI has no memory

An AI is great at spotting a mountain or a dog, but it has no idea who took the photo or why it matters. It can tell you it's a "Tree", It can identify the genus (what it is) but it doesn't know that specific tree was planted by the CEO's grandfather in 1954. The AI handles the boring "grunt work" like identifying shapes, while humans handle the important stuff like usage rights, project names, and expiration dates.

The bottom line

AI gives you the raw ingredients, but you’re the chef. It can tell you what a file looks like, but it’ll never understand what that file is for. Never mistake a 99% confidence score for the absolute truth.