The Complexity Paradox of ChatGPT, AI and UX

How do you teach people to use something that goes through step-change improvements every 6 months?

Put it like this; there's a clue that ChatGPT isn't as intuitive as a traditional search engine.

It's that companies are hiring for a skill known as "prompt engineering".

It's harder to build predictable and transparent experiences when even literal computer scientists can't predict the outcome of a prompt, or explain it to someone on the train.

This is a case study about ChatGPT. 

But more so, it's about core principles of design that are being stretched and tested by AI.

And I think it explains the strategy for Apple Intelligence.

Imagine searching on Google to find out when the Oasis tour starts.

I know you're probably skim reading this. But for 30 seconds, slow down and try to recognise some of the subconscious behaviour going on.

You've seen this results page:

Subtle pieces of information, combined with your own context, help you build an answer that you're somewhat confident in.

Confidence and predictability create comfort.

For example:

• I've heard of The Guardian, that's likely accurate
• But it looks like there's an inconsistency
• Ticketmaster is a very reliable source, because they actually sell the tickets

Still with me? Okay.

In other words, it'll attempt to complete that for you.

There's a faulty assumption that when people use the internet, the only relevant piece of information is the result.

But let's give this example to ChatGPT.

They'll draw from Wikipedia and a celebrity blog that I've never heard of.

Even if the answer was the same, and despite showing their sources, you wouldn't feel as confident about it.

i.e., a big area of resistance for fully autonomous driving.

Now consider that with these newer models, the "chain of thought" is intentionally masked.

A second layer of abstraction.

Using the Oasis example, o1 Preview will "confirm the tour status", and then get the answer wrong.

This isn't just a short term accuracy problem, it's at the core of how we use products.

As we outsource this "thinking", we lose the subconscious processes that make experiences feel comfortable.

And that might be a big problem for these wrappers that utilise OpenAI's API.

This is why Apple embedding AI into very specific features, makes a lot of sense.

And over time, having a single generic chat interface that completes your maths homework, books you an Uber and writes poetry for your spouse, probably doesn't.

P.S., If you want to dive more into the UX of chatbots, I've got you covered 🤖.