Let's do a little #AIhype analysis, shall we? Shotspotter claims to be able to detect gunshots from audio, and its use case is to alert the cops so they can respond.
Q1: Is it plausible that a system could give the purported output (time & location of gunshot) given the inputs (audio recordings from surveillance microphones deployed in a neighborhood)?
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A1: At a guess, such a system could detect loud noises that include gunshots (but lots of other things) and might be able to provide some location information (which mics picked it up?) but keep in mind that cityscapes provide lots of opportunities for echos...
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Q2: How was the system evaluated?
A2: We don't actually know, but the company says their "ground truth" data come from cops.
.@MayorofSeattle@SeattleCouncil we should under no circumstances be deploying systems that have not been evaluated for accuracy by neutral third parties.
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@MayorofSeattle@SeattleCouncil Also relevant here: The company seems to be saying "Just because there's no evidence that we were right doesn't mean there wasn't gunfire." THIS IS NOT THE ATTITUDE OF CAREFUL ENGINEERS!
A3: The citizens & residents of Seattle whose neighborhoods are repeatedly accosted by police coming in on high alert with the belief that a gun was just fired. What a recipe for disaster.
A4: Same, frankly. It is not at all clear that the people who live where these surveillance systems are set up benefit from police barging in on high alert. Who asked for this, @MayorofSeattle ? Does it meet their needs?
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@MayorofSeattle@SeattleCouncil Q5: What problem is the system meant to solve and how does the framing of the automated system narrow the type of solutions that are underconsideration?
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@MayorofSeattle@SeattleCouncil A5: Looks like the problem is gun violence. But framing the solution as starting from detecting the sound of gunshots is fundamentally reactive, and meets violence (and false reports of violence) with surveillance at best and state violence at worst.
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@MayorofSeattle@SeattleCouncil A5 cont: This framing leaves out of view all proactive approaches to reducing gun violence, starting with, ahem, FEWER GUNS but also programs that address root causes.
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In summary, hell no @MayorofSeattle and @SeattleCouncil. A tech city like Seattle should know better than to fall for #AISnakeOil and a city with Seattle's policing history must do better than to head down paths like these.
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As OpenAI and Meta introduce LLM-driven searchbots, I'd like to once again remind people that neither LLMs nor chatbots are good technology for information access.
Why are LLMs bad for search? Because LLMs are nothing more than statistical models of the distribution of word forms in text, set up to output plausible-sounding sequences of words.
Either it's a version of ChatGPT OR it's a search system where people can find the actual sources of the information. Both of those things can't be true at the same time. /2
Also: the output of "generative AI", synthetic text, is NOT information. So, UK friends, if your government is actually using it to respond to freedom of information requests, they are presumably violating their own laws about freedom of information requests. /3
It is depressing how often Bender & Koller 2020 is cited incorrectly. My best guess is that ppl writing abt whether or not LLMs 'understand' or 'are agents' have such strongly held beliefs abt what they want to be true that this impedes their ability to understand what we wrote.
Or maybe they aren't actually reading the paper --- just summarizing based on what other people (with similar beliefs) have mistakenly said about the paper.
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Today's case in point is a new arXiv posting, "Are Language Models More Like Libraries or Like Librarians? Bibliotechnism, the Novel Reference Problem, and the Attitudes of LLMs" by Lederman & Mahowald, posted Jan 10, 2024.
A quick thread on #AIhype and other issues in yesterday's Gemini release: 1/
#1 -- What an utter lack of transparency. Researchers form multiple groups, including @mmitchell_ai and @timnitgebru when they were at Google, have been calling for clear and thorough documentation of training data & trained models since 2017. 2/
In Bender & Friedman 2018, we put it like this: /3
With the OpenAI clownshow, there's been renewed media attention on the xrisk/"AI safety" nonsense. Personally, I've had a fresh wave of reporters asking me naive questions (+ some contacts from old hands who know how to handle ultra-rich man-children with god complexes). 🧵1/
As a quick reminder: AI doomerism is also #AIhype. The idea that synthetic text extruding machines are harbingers of AGI that is on the verge of combusting into consciousness and then turning on humanity is unscientific nonsense. 2/
t the same time, it serves to suggest that the software is powerful, even magically so: if the "AI" could take over the world, it must be something amazing. 3/
"[False arrests w/face rec tech] should be at the heart of one of the most urgent contemporary debates: that of artificial intelligence and the dangers it poses. That it is not, and that so few recognise it as significant, shows how warped has become the discussion of AI,"
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"We have stumbled into a digital panopticon almost without realising it. Yet to suggest we live in a world shaped by AI is to misplace the problem. There is no machine without a human, and nor is there likely to be."