Are you using AI to make better rideshare decisions?

I’ve started using AI to research unfamiliar pickup and drop off areas before deciding whether certain rides are worth taking.

I’ll ask about the neighborhood’s general income level, housing costs, density, safety, nearby businesses, and whether I’m likely to get another ride after the drop-off. Obviously, these are estimates, not guarantees, and I’m not making decisions based on race or any other protected characteristic.

One pattern I’ve noticed is that middle and upper middle class areas seem to tip the most consistently. Extremely wealthy passengers are hit or miss, and lower income passengers understandably may not have much room to tip.

It’s not the only factor. The upfront fare still has to make sense without a tip. But AI gives me more context than a random address or two cross streets, especially when I’m outside the parts of the city I know well.

It’s also been really useful late at night. If I get a ride going into an unfamiliar area, I’ll ask for things like poverty rates, general safety indicators, and nearby economic conditions. If I see something like “a significant portion of nearby residents are below the poverty line,” and it’s after 9 PM, I’ll usually pass on it. It just helps me avoid ending up in situations I’m not comfortable with in the middle of the night.

Anybody else doing this? What information are you asking for, and has it actually improved your decisions?