No. of Recommendations: 8
Frankly, I'm surprised at that: that when you are specifically asking for Miami North Shore or West Miami (or whatever) you get City of Miami responses. My own experience is that, while not perfect, if you are asking specific questions with detail and go back and forth with prompts to elicit better answers with more specifics, you get a much better and accurate answer.
Nope - I'll get the Miami-Dade or Miami substantive responses, often misattributed to whatever City. The live links will also go to the big jurisdiction code provision. The AI box from google is the worst. I just googled "South Miami setbacks," and got this response:
South Miami setback rules dictate minimum distances for buildings from property lines (front, rear, sides) and vary by zoning (like RU-1, RU-2) and lot specifics (corner lots), generally requiring significant space (e.g., 15-25 ft front, 10% lot width for sides) but allowing some flexibility for sheds or pools; you need to check your specific zoning (Miami-Dade Code) for precise requirements, as they ensure light, air, and fire safety.
Very little of that is right. South Miami doesn't have zoning districts labeled RU-1 or RU-2 (those are county zoning designations), their front setbacks aren't 15-25 feet and they don't use a percentage of lot width for side setbacks, you shouldn't check the Miami-Dade Code for precise requirements (municipal zoning trumps the County requirements), and all of the links that are provided are to either the County or the City of Miami zoning regulations (the City of Miami is a separate city from South Miami).
I suspect it's an instance of what I think is a general principle of AI - namely, how it handles a subject is only as accurate as the degree people use the internet to talk about the thing. People don't write about the arcana of zoning rules the way that they do about Harry Potter. There isn't a massive repository of writing samples about zoning like there is Github for coding. Etc.
Because there's less material for the model to learn from, the mistakes are more egregious.
