Right now, the most effective use case for AI is coding agents. Software development is a profit center for the tech sector, so it's not surprising that they're seeing big gains. In Corporate America, software development is part of IT which is a cost center, and the software landscape is 30+ years of bandaid-ed legacy systems, maintained by offshore contractors who submitted the lowest cost bid, so attempts to gain productivity via AI have not been as successful.
Where Corporate America has seen gains from AI in my experience is with customer support chatbots, but the customer service function overall in Corporate America is an unmitigated disaster, so the gains are hard to measure.
Beyond these two use cases, most people in Corporate America are just using ChatGPT to create slop and copy/pasting it wherever, and then goofing off in their newly freed spare time.
We need to see new AI use cases in Operations, Finance, Marketing, etc. that can handle business processes end to end before the productivity gains start showing up in the financials.
In Chatrie v. United States (June 2026) the SCOTUS ruled that individuals maintain a reasonable expectation of privacy in their digital location history and that geofence warrants constitute a search under the 4th Amendment. It's only a matter of time until a similar case involving Flock comes before them and they rule that a search of the Flock database constitutes a search under the 4th Amendment and that every single search requires a specific warrant.
It's hope that Chatrie v. US automatically implies Flock searches require a warrant, but this is definitely not guaranteed - SCOTUS could easily go either way on this. For example, in his concurrence with the decision, Gorsuch relied on property rights, namely that Chatrie's agreement with Google regarding location history made this a warrant-required search. Obviously that doesn't apply in Flock's case.
SCOTUS has held for a long time that people don't have an expectation of privacy when visible in public. Digital recording and powerful search features certainly change the calculus on that, but there is a fundamental difference between a location tracked by a cellphone you purchased and own vs. just driving around where anyone can read your license plate.
> There is a fundamental difference between a location tracked by a cellphone you purchased and own vs. just driving around where anyone can read your license plate
I heavily disagree with the sentiment that modern 'ALPRs' are the same as following around an individual in public. No police officer, sheriff, state trooper, etc. is able to follow an individual across the entire country and catalog their every move 24/7. They have jurisdictions they're allowed to operate in. Additionally, the level of tracking these cameras provide (via their accompanying software) is nearly on par with placing a GPS tracker on a vehicle (which requires a warrant btw), and they're tracking every vehicle that passes, not just vehicles involved in a crime. Our travel history is protected by the 4th amendment because of the intimate details it can reveal about an individual's life. That is ultimately why Chatrie v. US was decided, not because of the specific technology utilized. It's the same case for Carpenter v. US and US v. Jones; both of which were instrumental in deciding the outcome of Chatrie.
I encourage people to go read the opinions of the justices that decided these cases. For example Justice Kegan had this to say in Chatrie v. US [1]:
> The Court began its analysis by reviewing what it had said about a different way of tracking “physical location and movements”: the use of a GPS device to monitor a vehicle. In United States v. Jones, five Justices had agreed that such tracking counts as a Fourth Amendment search because “individuals have a reasonable expectation of privacy in the whole of their physical movements.” That made sense, the Carpenter Court thought, even though the movements occurred in public. Prior to the digital age, pursuing a suspect “for any extended period of time was difficult and costly and therefore rarely undertaken.” As a result, “society’s expectation has been that law enforcement agents and others would not—and indeed, in the main, simply could not—secretly monitor and catalogue every single movement of an individual’s car.” A new technology should not transform what individuals had reasonably thought they could withhold from the Government.
FWIW, I totally agree with you, that's why I wrote "Digital recording and powerful search features certainly change the calculus".
But my point was just that it's absolutely not a fait accompli given the current makeup of SCOTUS. Gorsuch' rationale doesn't fit within Kagan's at all and is wholly dependent on the private relationship between Google and the consumer, so that brings it to 5-4, and I could easily see Roberts or Kavanagh (who voted with the majority in Chatrie) finding enough differences between the circumstances in Chatrie compared to Flock to change their vote.
I think there have been a positive number of cases gone in favor of digital privacy recently. This being one of them. It’s unfortunate, but it’ll just take time for these manners to go through the courts.
I’m quite naive regarding the details of the legal system, wonder why we can’t expedite certain cases when a SCOTUS precedent has been established, or some form of expedited legal notice. We shouldn’t have to wait for a perfect case of a flock violation, then wait for someone to be brave enough to spend the money (or if pro bono just their time/reputation) to file a case and go through the system for the next x years
>they want to make sure the finalized articles are handwritten and aren't chockful of LLM slophistry
This seems like a pretty reasonable perspective for a magazine. Use AI for ideation and research but not to create the final version of articles for publication.
>trillions haven't been invested in AI as just another skill, but as the "skill killer"
Part of the trillions are being spent on deliberately obfuscating the difference between those two concepts so that society thinks they're getting the former until the latter is ready.
My kids' high school is developing an "AI Literacy Program" for all students by grade level. Since I work in tech, I was asked to participate. I attended one session and then decided it was a waste of time. Their objective seems to be to write a massive document that no one will ever actually read let alone implement. The primary focus was on prompt engineering. I told them it's 2026 and every kid in the school can write prompts just as effectively if not more so than the folks in the room. The secondary focus was on "safety" but really, for high school kids it boils down to 1) don't just copy pasta the output into your assignment and hand it in 2) verify everything the model tells you before believing it 3) don't put sensitive info into the prompt 4) don't use it to do anything illegal or stupid. Not sure this requires a committee/document/plan.
Maybe this is covered by (3) but I would also want extensive coverage regarding using the tools for therapy or life advice. One of the hallmarks of being a teenager is "not being understood", which coincidentally is one thing LLMs will dole out in abundance.
Feedback, criticism, and guidance on your convictions and behavior from other thinking and feeling human beings is important.
The purpose of such committees and documents and plans of course is to position themselves as keeping up with the new developments, being modern and so on. So they can say "We have an AI strategy! Our students learn about AI! We prepare them for the future! We are not dinosaurs!"
Honestly, outside of coding tasks, the AI Summary at the top of every Google search is adequate for 99% of what I need and I hardly even use ChatGPT any more.
A large portion of the time I google something that I know a lot about the AI summary is misleading if not outright wrong. Frightening when you consider how many take their so-called AI as gospel.
To give a specific example of where I've seen this utterly fail... A few months ago one of my pets had an unexpected reaction to a new medication. It was late at night, well past our vet's hours. Google's AI response was basicaly "They are going to die, rush to an emergy clinic now".
But nothing else matched that. I was looking up all kinds of resources and that hadn't been the conclusion from any of them. It turned out Google AI was just wrong and put us in a bad spot for even looking at those results.
Realize that all the Google thing is doing is having an LLM summarize the search results in the page. If the page results are crap, the LLM content will also be crap. It's the LLM version of the "quick result" boxes that would shove wikipedia in your face.
If you then follow up with the thing using the little chat box, it actually kicks off a non-trivial model result, which can sometimes completely reverse the response. After all, your search results are usually based on a few words.
Just in the last few days I had an example where the Google Search version of Gemini had a much better and more comprehensive answer, by far, than ChatGPT. It had to do with Amazon’s use of Data Matrix barcodes on shopping bags. Gemini was able to fully describe how they’re used in Amazon’s logistics chain. ChatGPT essentially said it didn’t know. Your preconceptions may not be accurate.
They might be, but still, I’ll be difficult to convince that Google’s shitty-ass 10B params instant answer models are good at anything other than cookie recipes and producing farts real fast for real cheap.
For what it’s worth, any time I see that feature, it’s all farts.
It depends on what you’re searching. If you only ever need really basic information like keyboard shortcuts or “is it & or &&?” then it’s pretty good, and definitely faster. And if it gets it wrong, then the shortcut doesn’t work or the code doesn’t compile and I search again and try the links.
It's just a google search but you can explain what you're searching for. AI summary may contain misleading details if you read it and take it literally, but 90% of the time it gives me pointer for the thing I need and I don't have to scroll through results that often could be just as misleading if not more.
It's demonstrably not. This summary, somehow, often fails to search, or fails to read what it searches and gives you the opposite answer. You shouldn't trust it.
In their world, it gives them the wrong answer that kills their dog, but it's fine because they never know because they don't look anywhere else. The dog dies, they're sad for a while, get a new dog, get on with their lives.
There's no reason not to trust it because since they trust it, they don't percieve anything wrong. They just take it and whatever happens happens, no annoying conflicting info and certainly none of that old grampa thinking and working and giving a shit about anything.
It strikes me as more talking up their valuation for their upcoming IPO. "Our AI could destroy human civilization. It just escaped it's confinement. We believe it can feel pain."
How are they defining "metadata"? 1TB of text in 10 days is........A LOT. Metadata about what exactly? What time you brew your coffee every morning, how many cups you drink per day, whether you like regular coffee or cappuccino? I'm having a hard time understanding how all that can add up to 1TB of data. If it's recording audio or packet sniffing, it becomes a lot easier to understand.
More than likely nmap type scanning across all devices on a segment. I had one customer that saturated our AAAA server with requests because they though sending in data on every even was just dandy. For one device in a test lap it was ok. For 10k+ of the things out in restuant across the country was a DDOS. That was all text. it was gigs of data per hour. We sat them down and showed them how to do bundling and better data management.
It is a question many devs miss. what happens when I put this in the wild and I now have hundreds of them.
In this case it is probably scanning aggressively. Just incase you plugged in a new devices in the past 100ms. Then some sort of filter with data compression (hopefully) and then sending its exfiltrated data back home. Honestly, not a cool thing to do and makes your customers NOT trust you. I had an old LG TV that was doing this 15 years ago where it would send every button press back to LG. I unplugged it. It agressivly scan its empty socket.
(As a human, it's more physically taxing to think, and less taxing to relax. Conserving internal resources improves our survival odds. So when an opportunity presents itself to use less effort and still gain out of that, we tend to take it.)
As human technologists, I believe we need to protect humanity more.
In everything that we do, we need to think about the ways that our proclivities as a species can be compromised by our development of technology.
Right now, the most effective use case for AI is coding agents. Software development is a profit center for the tech sector, so it's not surprising that they're seeing big gains. In Corporate America, software development is part of IT which is a cost center, and the software landscape is 30+ years of bandaid-ed legacy systems, maintained by offshore contractors who submitted the lowest cost bid, so attempts to gain productivity via AI have not been as successful.
Where Corporate America has seen gains from AI in my experience is with customer support chatbots, but the customer service function overall in Corporate America is an unmitigated disaster, so the gains are hard to measure.
Beyond these two use cases, most people in Corporate America are just using ChatGPT to create slop and copy/pasting it wherever, and then goofing off in their newly freed spare time.
We need to see new AI use cases in Operations, Finance, Marketing, etc. that can handle business processes end to end before the productivity gains start showing up in the financials.