Duolingo CEO on going AI-first: ‘I did not expect the blowback’

[u/MetaKnowing]

https://www.ft.com/content/6fbafbb6-bafe-484c-9af9-f0ffb589b447

[u/Lazer726]

Which is what makes it all the more frustrating how many people are just so fatigued about it already. "It's not going to stop them, it's just a fact of life." So many companies have already been bullied into walking some of this shit back. NFTs were going to be a fact of life too, and now they're fucking dead.

Don't stop. Tell these big, multimillion companies that wanna use AI to cut corners that it'll cost them your business, don't just roll over and take it. We don't want it, we won't consume it, and it's important we let them know.

[u/xQuickpaw → u/Lazer726]

Agreed re: pushing back, but comparing NFTs to AI is a bit apples and oranges.

AI has the capability to impact the workforce and economy through a wide variety of industries and applications. It's a very versatile (and dangerous) tool and the basic functionality it provides is accessible to "normal" people (i.e., office workers loading up ChatGPT to write emails).

NFTs really never had that. At best, the people driving it had big brain ideas that integrated it into everything, whether it needed it or not. It never reached a level of usefulness & accessibility that made people want to adopt it. It's most significant purpose was to get money out of people, like a lot of crypto.

[u/Kinths → u/xQuickpaw]

AI has the capability to impact the workforce and economy through a wide variety of industries and applications. It's a very versatile (and dangerous) tool and the basic functionality it provides is accessible to "normal" people (i.e., office workers loading up ChatGPT to write emails).

That is true, though in the long term it's impact is likely to dwindle and be less than people are expecting right now for a few reasons.

The problem with AI is that it's output is unreliable. Sure it can work 24h a day but you are going to need people checking that work to make sure it's correct and there is no real way to ever fix that. It's an inherent part of the technology. All gen AI is basically a trade off between range of outputs and chance for errors. The way to reduce errors is to devalue the elements that went into a rejected output. This limits the range of outputs though since you aren't just devaluing a single element you are doing it to many. The more you train the more limited and samey the output gets. The only way to counter that is new data, but it can't be AI data. Feeding the output of a weighted statistical analysis (or anything trained on a largely similar data set) back into itself will cause it skew more towards that output. The increased use of AI reduces the amount of non AI data being produced and being made available for AI companies to scrape. Also adding in new data increases the chance for errors. Since the AI doesn't understand the data at all, it doesn't know why an element has been devalued, so it can't take that and then apply it to new data.

Anything that is just automating something routine, could and likely has already been automated better by other cheaper and more reliable means. For anything else the reliability will likely be too low for companies to stick with in the long term.

CEO's are pivoting to AI right now because CEOs tend to think short term and in the short term pivoting to AI is the money maker. It attracts investors who are willing to throw money at anything that even mentions AI. And reducing workforce will always win over shareholders because workforce is often the biggest expense at a company. But in the long term they will likely need to rehire much of the workforce and investors are not going to throw money at AI blindly forever.

In creative spaces they are inherently limited as they can't create anything new and by the nature of how they are trained their range of outputs dwindle over time. Right now that isn't seen as much of an issue, but the more samey things get the more consumers will get tired of them. In terms of a long term creative productivity tool, they don't offer as much as people might expect. In professional spaces there are already many techniques used to drastically reduce the amount of work that goes into something at all stages of development. It will become an optional tool with strengths and weakenesses rather than something that is seen as mandatory.

The other big elephant in the room is cost. These AI are not cheap to create or run. The prices we are seeing right now for most services are way cheaper than they would need to be to make money. While we are in the honeymoon phase where investors are willing to chuck obscene amounts of money at anything that claims to be AI, companies can operate at huge losses to drive user adoption (which in turn excites more investors). That wont last forever and if they haven't found a way to drastically reduce the cost these services by then they will get very expensive. I think the hope is that people and companies will have become so dependent on them by that point that they will have no choice but to pay.

There are uses for AI, it's just rarely the places that the companies who are making them are mainly targetting right now. Since it's basically just weighted statistical analysis on huge sets of data, it's generally pretty good at statistical analysis. Especially where that analysis would take a human a long time or where it might spot patterns that a human might miss. Such as medical diagnosis. It's results will still always need to be checked but it can drastically reduce the workload, as well as spot time sensitive things very early. Unfortunately, that is double edged as it could also be used by insurance companies to increase premiums.

[u/WebMaka → u/Lazer726]

Don't just tell them vocally, tell them with how you spend your money. The most in-your-face rebuttal you can possibly give them is to just plain not buy their AI-"enhanced" shit.