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How to recognize AI snake oil [pdf]

cs.princeton.edu

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Re: How to recognize AI snake oil [pdf]

#81

Post by cosmojg »

jacquesm wrote: post #41

Lots of AI is actually large numbers of humans working on small bits of problems that are beyond our ability to automate. Not infrequently these are passed off on the outside as 'ai' startups. There are some good examples too where the companies that use machine learning properly and to good effect. Interestingly they don't blab about it because it is their edge over the competition and often just knowing that someth…

> if it requires advertising it is probably fake, if it is very quiet and successful it is likely genuine.

This is true of almost any product being offered for sale. Good advice.

Re: How to recognize AI snake oil [pdf]

#82

Post by buboard »

eloff wrote: post #54
buboard wrote: post #14

Earlier quoted context omitted.

You should emphasize that this is Organic AI. It's low carbon and overall greener.

You mean high carbon, low silicon? Because humans usually have a higher carbon footprint than computers, it takes a lot of computers to match one human. Plus we're made of carbon.

i m not sure, if you factor in the CO2 footprint of computer manufacture, and the fact that AI needs powerful computers & networking to be delivered. Our body carbon is almost 100% recycleable.

Re: How to recognize AI snake oil [pdf]

#83

Post by segfaultbuserr »

This presentation categorized AI-related tech with social outcomes as fundamentally dubious, such as predicting criminal recidivism, predicting terrorist risk, or predictive policing. The rationals are that

(1) technically, the technology is far from perfect.

(2) Social outcomes like fairness are fundamentally difficult to state.

(3) Its inherent problem is amplified with the ethical/moral problems.

Of course many find it's unacceptable due to the ethical problems in a typical Western liberal democracy. But what if I'm an authoritarian who wants to find the tools of suppression, and I don't care the false positives or the ethical problems? Is it going to help my regime, or is it going to have the opposite effect?

I highly suspect that the answer is the former one. Fortunately, the technical limitations of "AI" means it's still more or less ineffective today, but it can only get better.

Therefore, I don't think AI with social outcomes are fundamentally dubious, but rather, fundamentally dangerous.

Re: How to recognize AI snake oil [pdf]

#84

Post by MiroF »

sanchezdev wrote: post #78
MiroF wrote: post #47

Earlier quoted context omitted.

I work in the industry on NLP tasks. Unsupervised learning has been behind the largest developments in the last decade in the field.

I don't disagree with your point, but the unsupervised aspect of NLP typically isn't useful on its own. Usually it's a form of pre-training to help supervised models perform better with less data. From Google in 2018: "One of the biggest challenges in natural language processing (NLP) is the shortage of training data. Because NLP is a diversified field with many distinct tasks, most task-specific datasets contain onl…

As I said, I'm an NLP researcher and practitioner, so you don't need to quote this at me.

The unsupervised aspect is the engine driving all modern NLP advancements. Your comment suggests that it is incidental, which is far from the case. Yes, it is often ultimately then used for a downstream supervised task, but it wouldn't work at all without unsupervised training.

Indeed, one of the biggest applications of deep NLP in recent times, machine translation, is (somewhat arguably) entirely unsupervised.

Re: How to recognize AI snake oil [pdf]

#85

Post by bulldoa »

reggieband wrote: post #58

I don't have time to read the entire paper but I would like to share an anecdote. I worked at a company with a well staffed/funded machine learning team. They were in charge of recommendation systems - think along the lines of youtube up next videos. My team wanted better recommendations (really, less editorial intensive) so the ML team spent weeks crafting 12 or more variants of their recommendation system for our c…

Isn't sparse recommendation for videos kind of solved in netflix prize, where the winner uses SVD to extract signature characteristic and recommend videos base on that?

Re: How to recognize AI snake oil [pdf]

#86

Post by nerdponx »

reggieband wrote: post #58

I don't have time to read the entire paper but I would like to share an anecdote. I worked at a company with a well staffed/funded machine learning team. They were in charge of recommendation systems - think along the lines of youtube up next videos. My team wanted better recommendations (really, less editorial intensive) so the ML team spent weeks crafting 12 or more variants of their recommendation system for our c…

That's surprising to hear. Comparing model performance to a randomized baseline model is a "must-have" on my team before we feel comfortable presenting to management.

Re: How to recognize AI snake oil [pdf]

#87

Post by sgt101 »

I read "Why are HR departments apparently so gullible?" and as someone who has worked in a corporate for 20 years I spotted my underwear.

The identification of facial recognition as problematic because of accuracy doesn't match my thinking. I believe that the key issue is that given a set of targets facial recognition systems will find near misses from the wider population of all faces offered as candidates, that they then flag as potential matches. This leads to real world problems (like innocent folks being arrested).

Automated essay grading and content recommendation are both very problematic because they do not account for originality and novelty. A lecturer grading an essay that is written my a strong mind from a different culture might be able to recognise and credit a new voice, a learned classifier never will. Similarly content recommenders have us trapped in the same old same old bubble, nothing strikingly new can get through.

Re: How to recognize AI snake oil [pdf]

#88

Post by tlb »

The economic point of AI decision systems is that they can make an automated decision for $0.0001 of computer time, instead of $10 for a few minutes of an expert's time. For something like spam filtering, you obviously need the cheap solution. But you don't need that for the social interventions where you're making a decision about parole or something. You can spend $10 (or $1000) of people's time to make those decisions, because both their volume and impact is at human scale.

Re: How to recognize AI snake oil [pdf]

#89

Post by outworlder »

itronitron wrote: post #67
deusofnull wrote: post #61

Earlier quoted context omitted.

I worked for a company that had a "big data machine learning" product. Yeah, it was mostly elasticsearch aggregations.

well, aggregations are just leveraging how the data fields are analyzed and labeled, so if those were based on ML/NLP techniques then it could be legit

> so if those were based on ML/NLP techniques then it could be legit

Occam's Razor is whispering that it probably wasn't legit.

Re: How to recognize AI snake oil [pdf]

#90

Post by the8472 »

dghughes wrote: post #72
mumblemumble wrote: post #18

Earlier quoted context omitted.

Or keep calling it AI, and concede that AI stands for "actual intelligence" if someone asks you directly.

AI now is like Cyber was in the 1990s it's seems to be nothing but a buzzword for many organizations to throw around. The term AI is used as if humanity now has figured out general AI or artificial general intelligence (AGI). It's quite obvious organizations and people use the term AI to fool the less tech inclined into thinking it's AGI - a real thinking machine.

Cyber is still happens to be a buzzword, it just shifted meaning to the defense sector.
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