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Why is AI so useless for business?

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Re: Why is AI so useless for business?

#101

Post by [deleted] »

csours wrote: post #76
BlackFly wrote: post #23

Earlier quoted context omitted.

If school grades are indicative, even a 90% accuracy is commendable for human driven tasks. The big difference is that when a human double checks their own work, they may not make the same mistake twice. Or even better, when a second person checks the work. Mistakes are tolerable, but you need to be able to recover from them somehow, and recovery from an AI mistake seems to be something that people like to pretend is…

If I get 90% of my math correct on a test, that's great! If I get 90% of my math correct while engineering a rocket, that's terrible!

[deleted]

Re: Why is AI so useless for business?

#102

Post by kgin »

ethanbond wrote: post #18

I’ve been working in the “real world business processes that companies are trying to AI-ify” realm for quite a while now. Pharma, cyber security, oil and gas production, etc. This article doesn’t mention a really, really straightforward factor for why AI hasn’t invaded these domains despite billions of dollars being dumped into them. An automated process only has to be wrong once to compel human operators to double o…

The blame issue is huge.

When humans are wrong, the business’ “ego” can be saved by blaming the employee who made the call, sometimes firing them. But the process goes on with the same error rate.

But when software makes the wrong call, it feels like the business itself has done the wrong thing. With no way to externalize the blame for the decision, the blame gets placed on the decision to use ml in the first place.

Re: Why is AI so useless for business?

#103

Post by Mvandenbergh »

tragomaskhalos wrote: post #16

Our immediate goal should be to set our sights lower; forget ML, instead improve and expand technologies like RPA ( https://en.wikipedia.org/wiki/Robotic_process_automation ), which is only "AI" in the narrowest sense. Example: my wife is an admin in a school office, and a ludicrous amount of her and her colleagues' time is spent on replicating data entry between a multiplicity of different incompatible systems. The…

Agreed. Taking large amounts of admin workers from low productivity to moderate productivity (and RPA can easily boost the productivity of these kinds of tasks, if not the whole job by 200%) has a much bigger effect than hyperoptimising workflows that were already highly optimised.

Re: Why is AI so useless for business?

#104

Post by pwdisswordfish2 »

NalNezumi wrote: post #68

I'm going to go against the flow of most comment here and say that it's not always business misunderstanding AI. Bad labeled data and unclear goals/expectations sure, but the latter one should be identifiable by a good ML/Data scientist, if you have any insight to what you can actually deliver. But most ML/Data Science people have no proper understanding of AI/ML, and when just traditional "coding" can solve the prob…

Can you get your money and time back when it does not perform as promised?

Re: Why is AI so useless for business?

#105

Post by SkyBelow »

ethanbond wrote: post #18

I’ve been working in the “real world business processes that companies are trying to AI-ify” realm for quite a while now. Pharma, cyber security, oil and gas production, etc. This article doesn’t mention a really, really straightforward factor for why AI hasn’t invaded these domains despite billions of dollars being dumped into them. An automated process only has to be wrong once to compel human operators to double o…

>An automated process only has to be wrong once to compel human operators to double or triple check every other result it gives. This immediately destroys the upside as now you’re 1) doing the process manually anyway and 2) fighting the automated system in order to do so.

I think this is the core of the problem. 99% isn't good enough. Even 99.9% isn't good enough when we are talking acceptable accepted error margins. Even if humans make more mistakes than the AI, telling our customer it was a human error is much easier for our customers to accept than telling them it was a program error without our threshold tolerance.

We see this with self driving cars. People's reactions to the machines is that the machines have to be far better than humans before humans will be okay with the risks involved. This also holds for financial aspects. Imagine your grocery store telling you that there is a X% chance of being double charged for an item and that is within acceptable error tolerance. Even if X is lower than the rate that human grocers accidentally double charge will people be okay with that as the planned error rate or will they demand perfection?

Re: Why is AI so useless for business?

#106

Post by tyingq »

afarviral wrote: post #61
tyingq wrote: post #42

Earlier quoted context omitted.

RPA can be a dangerous band aid. It often uses screen scraping or similar brittle interfaces that are known to change. Or, it doesn't know about certain error conditions, etc. Also, if it's been running for months before it breaks, the humans that used to do the work are gone, or have forgotten how to do it.

At my work we are leaning heavily on RPA to automate away drudgery and ultimately reduce expendature. However it has been immensely frustrating, prone to errors and garnered endless suspicion. The experience has been that bots written by the service desk staff doing the job function better and are much more under our teams governance, which the official "automation" teams within our org are painful to deal with due t…

I've experienced the same. Centralized RPA teams tend to, for example, do web scraping when they could easily use an existing REST API. Because they either don't know it exists, or don't have that skill set.

Similarly, seen things like using a email as a trigger, when the source application has configurable web hooks.

Feels like there's an RPA culture of sorts to assume the things being automated only have human based interfaces.

Re: Why is AI so useless for business?

#107

Post by toss1 »

laichzeit0 wrote: post #7

> why can't it read a PDF document and transform it into a machine-readable format? > why can't I get a computer to translate my colleague's financial spreadsheet into the format my SAP software wants? Because you probably expect it to be 100% or maybe 99.999% accurate, and we can't do that. Imagine "AI" translating someones financial spreadsheet into a different format and dropping a zero somewhere. Oops.. but your…

The requirement for 100% accuracy is close, but not quite correct.

Even in many highly critical human endeavors, there are many errors.

The key to success is not absolute error-free perfection, it is no critical errors in components that are severe enough to kill the project.

Every rocket launch has some issues, but the successful ones have issues where it doesn't explode or land in the wrong orbit.

In the spreadsheet example, dropping a critical zero will cause damage akin to the rocket explosion. But dropping an "O" in a label field is utterly trivial.

Humans understand the distinction, constantly make such judgements and focus on the critical areas in their moment-to-moment work and embed it in their work processes. These constant criticality judgements are not just binary, but refined scaled, and serve to apply resources where needed.

The AI systems do not have such a judgement layer, and apply the same degree of inaccuracy to every part of their domain. So, absolute 100% accuracy is required, as errors are no less likely in the critical components.

Re: Why is AI so useless for business?

#108

Post by vsareto »

SkyBelow wrote: post #105
ethanbond wrote: post #18

I’ve been working in the “real world business processes that companies are trying to AI-ify” realm for quite a while now. Pharma, cyber security, oil and gas production, etc. This article doesn’t mention a really, really straightforward factor for why AI hasn’t invaded these domains despite billions of dollars being dumped into them. An automated process only has to be wrong once to compel human operators to double o…

>An automated process only has to be wrong once to compel human operators to double or triple check every other result it gives. This immediately destroys the upside as now you’re 1) doing the process manually anyway and 2) fighting the automated system in order to do so. I think this is the core of the problem. 99% isn't good enough. Even 99.9% isn't good enough when we are talking acceptable accepted error margins.…

Even if you balance the double charging with a chance to get an item for free (or negative price, acting as a credit), humans will still complain when they get double charged and stay silent when they get the bonus. But of course there's rich people who don't even care they were double charged for something like groceries.

Most of these issues aren't about how many 9's of reliability there are, but whether or not some person is accountable. AI is not itself accountable, only the person in charge of it.

Many companies already give gift cards or whatever when a human mistake happens as a form of customer service, and there's not enough compensation around AI error rates to make them palatable.

Re: Why is AI so useless for business?

#109

Post by synthc »

Machine learning requires a large high-quality dataset, which a lot of companies simply don't have. Building one takes a lot of time and money. The gains don't outweigh the costs in many cases.

Another problem is that machine learning models are never a 100% correct and not easily interpretable, so they cannot be used for some critical processes. Good luck with explaining a customer why his account blocked due to a false positive made be the AI.

I think there is still a lot of potential for boring symbolic AI, in a lot of domains you can get results quickly, reliably and if the AI is wrong it's easy to debug.

Re: Why is AI so useless for business?

#110

Post by mark_l_watson »

I have been an AI practitioner since the 1980s, sort of a fan! That said, I like this article on several levels most particularly for calling out possible AI products for business.

I lived through the first AI winter. As effective as deep learning can be, problems like model drift, lack of explainability, and getting government regulators to sign off on financial, medical, etc. models are very real problems.

Two years ago I was at the US Go Open and during a social break I was talking to a lawyer for the Justice Department and he was telling me how concerned they were about the legal problems of black box models.

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