One of the use cases I thought was reasonable to expect from ChatGPT and Friends (LLMs) was summarising. It turns out I was wrong. What ChatGPT isn’t summarising at all, it only looks like it…
At a consulting job I did recently they got an AI for a specific task to have an 25% rejection rate. Which I thought was pretty good and the team working on it said there was no way they could do better, this is the absolute best.
So they went and asked the customers if they would be interested in this feature and how much they would be willing to pay. The response was nobody was willing to pay at all for the feature and a 25% rejection rate was too high.
The reason customers gave was this meant they still need a human to check the results, so the human is still in the loop. And because the human basically has to do most of if not all of the work to check the result, it didn’t really save that much time. And knowing their people, they will probably slack on the checks, since most are correct. Which then leads to incorrect data going forward. This was simply not something customers wanted, they want to replace the humans and have it do better, not worse.
And paying for it is out of the question, because so many companies are offering AI for free or close to free. Plus they see it as a cost saving measure and paying for it means it has to save even more time for it to be worth.
So they put the project on ice for now, hoping the technology improves. The next customer poll they did, AI was the most requested feature. This caused some grumbles.
I think the best way to use “AI” for work, is together with a human to improve output of that human, because the human learned the skill on how to use “AI” to work more efficiently. This is happening at my workplace right now. More and more coworkers are learning when it is the right moment to start writing a prompt.
I see a future (or maybe I hope), where a brilliant mind finds an efficient way to train “AI” by just working with it and get so efficient that we can have more time for us…
At a consulting job I did recently they got an AI for a specific task to have an 25% rejection rate. Which I thought was pretty good and the team working on it said there was no way they could do better, this is the absolute best.
So they went and asked the customers if they would be interested in this feature and how much they would be willing to pay. The response was nobody was willing to pay at all for the feature and a 25% rejection rate was too high.
The reason customers gave was this meant they still need a human to check the results, so the human is still in the loop. And because the human basically has to do most of if not all of the work to check the result, it didn’t really save that much time. And knowing their people, they will probably slack on the checks, since most are correct. Which then leads to incorrect data going forward. This was simply not something customers wanted, they want to replace the humans and have it do better, not worse.
And paying for it is out of the question, because so many companies are offering AI for free or close to free. Plus they see it as a cost saving measure and paying for it means it has to save even more time for it to be worth.
So they put the project on ice for now, hoping the technology improves. The next customer poll they did, AI was the most requested feature. This caused some grumbles.
I think the best way to use “AI” for work, is together with a human to improve output of that human, because the human learned the skill on how to use “AI” to work more efficiently. This is happening at my workplace right now. More and more coworkers are learning when it is the right moment to start writing a prompt.
I see a future (or maybe I hope), where a brilliant mind finds an efficient way to train “AI” by just working with it and get so efficient that we can have more time for us…
We gotta fight for that, I think
I think a lot of people will have to learn the hard way that AI isn’t what it’s cracked up to be.
Saving this comment for posterior
Posterity?
https://www.merriam-webster.com/dictionary/posterity
Why would I save something for posterity when I could save it for posterior?
Butt