We will always have to find things to do for the less gifted in order to provide them with some dignity. Even if they are not strictly needed for reasons of productivity or profitability. Anything else would be inhumane.
We already have plenty of those in the most profitable industries today.
This has not been my experience. People need something to do but not many people know that about themselves. It leads to a lot of... 'wasteful' behaviors, rather than enriching ones. I think it's going to be something that has to be taught to people, a skill like any other. Albiet a little more abstract than some.
You'd be surprised how many people would just drink themselves to metaphorical or literal death.
I think you’re hinting at some very hurtful, dangerous ideas.
The obvious rebuttal to the idea that AI will eat software engineering is "we'll always need 'software engineers' and the nature of what they do will just change", which is probably true for the foreseeable future, but ignores the fact that sufficiently advanced AI will be like a water line rapidly rising up and (economically) drowning those that fall below it and those below that line will be a very significant percentage of the population, including even most of the "smart" ones.
However this ends up shaking out, though, I think its pretty clear we're politically and economically so far from ready for the practical impact of what might happen with this stuff over the next 10-20 years that its terrifying.
"60-80% of you aren't really needed anymore" looks great on a quarterly earning statement until the literal guillotines start being erected. And even if we never quite reach that point there's still the inverse Henry Ford problem of who is your customer when most people are under the value floor relative to AI that is replacing them.
I'm not trying to suggest there aren't ways to solve the economic and political problems that the possible transition into an AI-heavy future might bring but I really just don't see a reasonable path from where we are now to where we'd need to be to even begin to solve those problems in time before massive societal upheaval.
If we can't completely automate accounting, then there is no hope for any other field.
Seems like an easy job for AI. Take all scraps of paper out of box, record a video of all scraps, AI make sense of the handwriting and other things. Eventually make a robo that allows you to dumb the scraps into an accounting box that does all of this automatically - fish out receipts, scan, OCR, understand meaning, do arithmetic, done.
Honestly, who would miss this kind of work?
Also, accountants don't just track the numbers, they also validate them. Some of that validation can be done automatically, but it's not always cheeper to hire a programmer to automate that validate than to just pay a bookkeeper to do it. But even if you do automated it, you still need someone to correct it. The company I used to work had billing specialists who spent hours every week pouring over invoices before we sent them to clients checking for errors that were only evident if you understood the business very well, and then working with sales and members of the engineering teams to figure out what went wrong so they could correct the data issues.
In short, a typical accounting department is an example of data-scrubbing at scale. The entire company is constantly generating financial information and you need a team of people to check everything to ensure that that information is corrects. In order to do that, you need an understanding, not just of basic accounting principles, but also of the how the specific company does busines and how the accounting principles apply to that company.
Who benefits from these bespoke solutions? Can you give a example of how one company would do its books vs another and why it would be beneficial?
>> accountants don't just track the numbers, they also validate them
What information do they use to validate numbers? Why is it not possible for today's AI to do it?
For a more concrete example, I'll tell you about something I have some experience with, commission systems. Commissions seems like it would be something that was straightforward to calculate but it's tied to business strategy and that's different for every company. Most companies for example will want to compute commissions on posted invoices, which makes the process much simpler because posted invoices are immutable, but I once built a commission calculator for a company years ago that often had a long gap (months) between a booking and when they could invoice the client, so they wanted to calculate commissions from bookings but only pay them when invoiced. Because bookings were mutable, and there were legitimate reasons to change a booking before you invoiced it, that, combined with a lot of fiddly rules about which products were compensated at which rates and when, meant that there was a lot of "churn" in the compensation numbers for sales reps from day to day; they're actual payment might differ from what they thought they earned. That was a problem that the company dealt with, the tradeoff being that they could show earnings numbers to the sales reps much more quickly and incentivize them to follow up with the clients on projects so that they could eventually be paid.
I remember another commissions situation where there was a company that sold a lot projects with labor involved. They were able to track the amount of labor done per project, but they compensated the sales reps by line item in the invoices, and the projects didn't necessarily map to the line items. This meant that even though the commissions were supposed be computed from the GP, there wasn't necessarily a way to calculate the labor cost in a way that usable for commissions so the company had to resort to a flat estimate. This was a problem because the actual profitability of a project didn't necessarily factor into the reps' compensation. Different companies that had a different business model, different strategy, or just different overall approach would not have had this problem, but they might have had other problems to deal with created by their different strategies. This company could have solved this problem, but they would have had to renegotiate comp plans with their sales reps.
There are off the shelf tools available for automatically calculating commissions, but even the most opinionated of them are essentially glorified scripting platforms that let you specify a formula to calculate a commission, and they don't all have the flexibility that manager might want if they wanted to changed their compensation strategy. And this is only one tiny corner of accounting practice.
Basically, when it comes to arithmetic very few accountants are out there manually summing up credits and debits. In large companies, the arithmetic has been automated since the 70s; that's largely what those old mainframes are still doing. But every company has a different compensation plan, different org structure, different product, different supply chain, different legal status, different reporting requirements, etc, etc, and that requires things to be done differently.
> What information do they use to validate numbers? Why is it not possible for today's AI to do it?
For an example, they would need to cross check with a sales rep and an engineer to makes sure that the engineer had not turned on a service for the customer that the sales rep had not sold. If that happened, they would have to figure out how to account for the cost. Given that the SOPs were written in plain English, I suppose it's possible that an AI might be trained to notice the discrepancy, but if you could do that, you could just as easily replace the engineer. And that didn't account for situations where the engineer might have had an excuse or good reason for deviating from the SOP that would only come to light by actually talking to them.
But some percentage of people don't really benefit that much from education as other people. And I wouldn't won't those people feel useless because it's more economical to replace them with bots instead of giving them something to do regardless.
Why not… not have jobs? In your opinion, is a job necessary for one to have “purpose”?
Edit: also side note but telling people they’re “triggered” because they disagree with you comes off as condescending IMO
The smart money is retiring early and stockpiling wealth so as not to fall into the UBI class.
I meant the ability to acquire a competency through education that's hard to replace with AI.
So we can't just increase education and hope people's abilities will stay above that of future AIs. We need to create other ways of giving people a purpose that don't even need more or better education, even if I'm all for it.
I'm not exempting myself by the way.