Over half of all tech industry workers view AI as overrated::undefined
I’ve found that relying on it is a mistake anyhow, the amount of incorrect information I’ve seen from chatgpt has been crazy. It’s not a bad thing to get started with it but it’s like reading a grade school kids homework, you need to proofread the heck out of it.
I recently used it to update my resume with great success. But I also didn’t just blindly trust it.
Gave it my resume and then asked it to edit my resume to more closely align with a guide I found on Harvards website. Gave it the guide as well and it spit out a version of mine that much more closely resembled the provided guide.
Spent roughly 5 minutes editing the new version to correct for any problems it had and boom. Half an hour of worked parsed down to sub 10
I then had it use my new resume (I gave it a copy of the edited version) and asked it to write me a cover letter for a job (I provided the job description)
Boom. Cover letter. I spent about 10 minutes editing that piece. And then that new resume and cover letter lead to an interview and subsequent job offer.
AI is a tool not an all in one solution.
I have found that it’s like having a junior programmer assistant. It’s great for “write me python code for opening an in file from a command line argument, reading the contents into a key/value dict array, then closing the file.” It’s terrible for “write me a python code for pulling data into a redis database.”
I find it’s wrong 50% of the time for certain command line switches, Linux file structure, and aws cli.
I find it’s terrible for advanced stuff like, “using aws cli and jq, take all volumes in a vpc, and display the volume id, volume size in gb, instance id it’s attached to, private IP address of the instance, whether is a gp3 or gp2, and the vpc id in a comma separated format, sorted by volume size.”
Even worse at, “take all my gp2 volumes and make them gp3.”
I feel like the AI in self-driving cars is the same way. They’re like driving with a 15 year old that just got their learners permit.
Turns out that getting a computer to do 80% of a good job isn’t so great. It’s that extra 20% that makes all the difference.
That 80% also doesn’t take that much effort. Automation can still be helpful depending on how much effort it is to repeatedly do it, but that 20% is really where we need to see progress for a massive innovation to happen.
What always strikes me as weird is how trusting people are of inherently unreliable sources. Like why the fuck does a robot get trust automatically? It’s a fuckin miracle it works in the first place. You double check that robot’s work for years and it’s right every time? Yeah okay maybe then start to trust it. Until then, what reason is there not to be skeptical of everything it says?
People who Google something and then accept whatever Google pulls out of webpages and puts at the top as fact… confuse me. Like all machines, there are failures. Why would we trust that the opposite is true?
My guess, wholly lacking any scientifc rigor, is that humans naturally trust each other. We don’t assume the info someone shares with us as wrong, unless there’s “a reason” to doubt. Chatting with any of these LLM bots feels like talking to a person (most of the time), so there’s usually “no reason” to doubt what it spews.
If human trust wasn’t so easy to get and abuse, many scams would be much harder to pull.
At least a Google search gets you a reference you can point at. It might be wrong, it might not. Maybe it points to other references that you can verify.
ChatGPT outright makes shit up and there’s no way to see how it came to a given conclusion.
Because the average person hears “AI” and thinks Cortana/Terminator, not a bunch of if statements.
People are dumb when it comes to things they don’t understand. I’m dumb when it comes to mechanical engineering of any kind, but I’m competent with software. It’s all about where people’s strengths lie, but some people aren’t aware enough to know they don’t know something
