[tonymet]

so are means. Mean reported crime dropping in urban areas does not mean that things are adequately safe. having x% lower chance of getting mugged in the hood doesn’t mean that your kids can ride the bus alone.

Urban areas in the 90s , in projects and ghettos were basically war zones in terms of murder rates. They pushed the average murder & violent crime rates off the charts. Those have come down, but that doesn’t mean that the cities are now safe for 5 year olds to walk around alone.

Compare moderately sketchy parts of LA to Tokyo or Helsinki and tell me which one feels safe and which doesn’t . You can tell yourself “LA is so much better than the 90s” but you still won’t feel safe in the same way.

[ineedasername]

Precisely this! Too many confounding variables to look at such a surface level, a few high-level population wide stats. Nothing is that simple, nothing is clean in this sort of thing. Messy, interrelated factors, and you can chip away at the question bit by bit to reveal things but that is what it takes, not this do-it-with-vibes approach that's been around long before agents started taking prompts to code.

My hope is that agentic analysis that does this tedious methodical chipping away, comparative cross referencing of seemingly disparate datasets, will help shift society the tiniest bit away from law & policy making via hot takes that make even the well intentioned fall on their face with poor reasoning and the more cynical wield ambiguity a cudgel of control by any emotion they can incite, usually not the good ones.

[tonymet]

Let’s see how it goes. I don’t think safety is properly being measured. Much like you can’t measure a beautiful property or a delicious dish. It has to be experienced.

Moreover, AI guardrails will interfere with you identifying any meaningful anthropological conclusions.

[ineedasername]

>AI guardrails will interfere with you identifying any meaningful anthropological conclusions.

In this respect it depends on how AI is used. In this case, I didn't envision it doing this in the "deep research" sense or otherwise making its own conclusions from data, I meant more in the vein of a well scaffolded agent loop iterating through, for example, census tract-level data, cross referencing that with other data sources to find the relevant, granular-but-requires-intelligent-judgment details to piece together countless small datasets to assemble a large pictured. Grunt work that is repetitive but just variable enough you can't do something like download/scrape and assemble at scale because each block or tract or zip code needs one small bit of human judgement.

None of that is my work though, just where I think things might usefully go. For my part I'm trying to jump industries into AI more directly, it aligns well with my background, but that fact combined with zero industry connections (save Claude Code's recommendation & endorsement, that I had to tell it not to email on my behalf to Anthropic) hasn't broken down that wall yet, and in the meantime I try to build useful things that might help in that direction. So I'm aware of AI's blind spots on some things, and its significant capabilities still need significant shepherding.