An increasing number of businesses invest in advanced technologies that can help them forecast the future of their workforce and gain a competitive advantage. Many analysts and professional practitioners believe that, with enough data, algorithms embedded in People Analytics (PA) applications can predict all aspects of employee behavior: from productivity, to engagement, to interactions and emotional states.
Predictive analytics powered by algorithms are designed to help managers make decisions that favourably impact the bottom line. The global market for this technology is expected to grow from US$3.9 billion in 2016 to US$14.9 billion by 2023.
Despite the promise, predictive algorithms are as mythical as the crystal ball of ancient times.
[...] To manage effectively and develop their knowledge of current and likely organisational events, managers need to learn to build and trust their instinctual awareness of emerging processes rather than rely on algorithmic promises that cannot be realised. The key to effective decision-making is not algorithmic calculations but intuition.
What do you people think about predictive algorithms ? Mumbo jumbo or ??
(Score: 2) by Gaaark on Tuesday February 13 2018, @03:20AM
Mumbo AND Jumbo.
--- Please remind me if I haven't been civil to you: I'm channeling MDC. ---Gaaark 2.0 ---
(Score: 5, Informative) by Hartree on Tuesday February 13 2018, @03:28AM
You just tweak the weighting so that it gives the answer you wanted to sell to your marks... I mean customers/managers and then use the authoritative sound of data mining and predictive algorithms as evidence of your answer.
So they are quite useful just not for anything to do with reality.
(Score: 2) by takyon on Tuesday February 13 2018, @03:33AM (10 children)
https://www.iarpa.gov/challenges/gfchallenge.html [iarpa.gov]
[SIG] 10/28/2017: Soylent Upgrade v14 [soylentnews.org]
(Score: 4, Insightful) by c0lo on Tuesday February 13 2018, @03:51AM (9 children)
It would be funny if it wouldn't be so sad.
https://www.youtube.com/watch?v=aoFiw2jMy-0 https://soylentnews.org/~MichaelDavidCrawford
(Score: 3, Funny) by takyon on Tuesday February 13 2018, @03:58AM (2 children)
Let's make a team soylent and write a RNG IRC bot that predicts the future to get $200k.
[SIG] 10/28/2017: Soylent Upgrade v14 [soylentnews.org]
(Score: 2) by c0lo on Tuesday February 13 2018, @04:10AM
With the note that the problem is not set into the "earning money" territory, but in the "gambling" one.
I don't know, me thinks this may be relevant on the technical approach to the problem.
https://www.youtube.com/watch?v=aoFiw2jMy-0 https://soylentnews.org/~MichaelDavidCrawford
(Score: 2) by opinionated_science on Tuesday February 13 2018, @04:13AM
"interpolation, well understood. extrapolation, not so much".
Certainly something to bear in mind...
(Score: 1) by khallow on Tuesday February 13 2018, @05:27AM (5 children)
(Score: 2) by c0lo on Tuesday February 13 2018, @05:58AM (3 children)
Huh!... You reckon that the climatologists are doomed to fail but any other prediction capability is within reach of the current science/technology?
https://www.youtube.com/watch?v=aoFiw2jMy-0 https://soylentnews.org/~MichaelDavidCrawford
(Score: 1) by khallow on Tuesday February 13 2018, @06:25AM (2 children)
Note that the only attempts to evaluate such predictions rapidly devolved into apologism.
I think we're not only within reach, but we should have such now. It's just not in the interest of the people currently funding climate research to do so. Remember the basic problem: if climate change were to turn out to be no big deal, then the funding would go away, the finance industry wouldn't have their carbon markets revenue, and the rent seekers of the world would have to look for other, less gullible funding sources for their "green" projects.
My view on this is that the whole climate change thing should be thrown into a betting market, paying out in shares of some stock index fund. The crazy people who think the world is going to end in twenty years or that there is no global warming in the slightest would give their money via betting to the people with the more nuanced viewpoints. And the IPCC would have a tougher time when their predictions are countered by more accurate ones from the market. Is chocolate going to disappear by 2050? Well, state what an effect of that would be (say some stratospheric rise in the price of chocolate or a huge drop in production) with shares paying out to the "YES" side, if it happens, and the "NO" side, if it doesn't. You can even come up with various thresholds to get a more nuanced view of the problem.
Combine that with absolutely no restrictions on insider trading (aside from limiting the moral hazards of deliberately making a claim happen such as buying a ton of "YES" and then deliberately killing chocolate) and you have the makings of a fairly accurate prediction system.
(Score: 2) by c0lo on Tuesday February 13 2018, @07:11AM (1 child)
I'm noticing nothing of the kind, but if you feel better imagining such things who am I to deny your pleasure.
Matter of opinion.
Interesting, but betting will solve nothing. Except for those who can afford a huge spread bet, who won't see the problem solved but will profit from the outcome.
Oh, sorry, I take back the above, it's worse than a lottery, is one in which the powerful can make their prediction happen by manipulating the conditions for an outcome.
Thanks but no, thanks.
https://www.youtube.com/watch?v=aoFiw2jMy-0 https://soylentnews.org/~MichaelDavidCrawford
(Score: 1) by khallow on Wednesday February 14 2018, @06:42PM
Fortunately, that is something we can correct. Consider this example [carbonbrief.org]. At numerous points, the article speaks of the long term temperature sensitivity of a doubling of CO2 ("climate sensitivity").
Throughout the article there are all sorts of rationalizations for why the models are in error. This leads to the conclusion:
What is skillfully ignored here is that the actual heating has been significantly less than "climate sensitivity". For example, from 1970 to 2017, the various measures of global mean temperature went up about 0.65 C (as shown in that link, it has since gone up another 0.2C). Eyeballing figure [www.ipcc.ch], total anthropogenic contributions (in equivalent of CO2 emissions) has gone from 27 GtC to 49 GtC in 2010. Superficially, that would correspond to 0.75-1 C per doubling of CO2 equivalent (0.86 of a doubling roughly per 0.65 to 0.85 C increase in temperature). This is the great problem which has resulted in a quest for the "missing heat".
But of course one would need to include stratospheric global cooling gases and particles like sulfur dioxide and soot. That tends to get you somewhere near [www.ipcc.ch] the current estimate of radiative forcing from CO2, which I strongly suspect is why that parameter still is considered in a vacuum as in the above article.
If we take mean CO2 concentrations for 1970 and 2017 (325 ppm in 1970 and my estimate of 406 ppm for 2017), we get an effective doubling of 0.32 (that's 2.65 C for the high temperature in 2017). (Similar calculation yields 2.5 C in 2010). Sure looks nice, when you don't consider a third and growing portion of global warming.
What gets interesting here is when I look for independent confirmation of the global mean temperature graphs contained in the first article, I find that they tend to be fairly far off. For example, this link [cet.edu] which allegedly shows NASA GISS data, shows a bit under a 0.6 C climb in temperature between 1970 and 2010. I estimate that's almost 10% less than the apologist article shows for the same GISS data. That alone drops the temperature sensitivity through to 2010 by the same amount (to roughly 2.3 C per doubling, I estimate). Again, this is just with CO2 and ignoring the far greater rate at which non-CO2 sources are growing.
Another indication something is up comes from the accuracy of the models for time periods of the past. For the fourth IPCC assessment report and beyond, the models attempt to simulate small scale variation as well. For example, all the subsequent aggregations of models pick up the cooling that happened around 1992, during an El Nino [noaa.gov] year and then subsequently completely fail to model any such variation once one gets to the future.
One should see similar inaccuracies in the past because the physics and models didn't change. That's how it would work for weather models, for example. The same chaos that makes it so hard to model a few days into the future also makes it hard to model a few days into the past.
When all that mattered was that the models predicted extensive warming in the future, then they were significantly off in the near future. Notice that they suddenly became more accurate, starting in 2007, once criticism of past models surfaced, but the future predictions of extreme global warming remain unchanged. Climatology is one of those fields where one can be presented with contradictory evidence yet not bother to change the underlying models that led to the error beyond some superficial changes.
(Score: 0) by Anonymous Coward on Tuesday February 13 2018, @04:47PM
dude this is just a new version of a totem, you can just go to the church instead
(Score: 5, Insightful) by legont on Tuesday February 13 2018, @03:33AM
See, the managers, once invested into this, will expect employees to conform or else. Happens all the time. Just recall all the greatest software development mumbo jumbos of the last decades. Not to mention the infamous cubical wall hight effect.
So, yes, the algorithms will work. Workers will find a way to fit into them.
"Wealth is the relentless enemy of understanding" - John Kenneth Galbraith.
(Score: 5, Insightful) by NotSanguine on Tuesday February 13 2018, @03:48AM (4 children)
This sort of thing (predictive analytics algorithms) has been done for decades by consulting firms.
They gather the "relevant" (that's the important part and all of it comes from the client) data and organize it. They then pass that data through a proprietary algorithm and it spits out predictions.
That some folks have taken algorithms and turned them into code isn't so surprising. Nor is it likely to be anywhere near as effective as humans doing the same thing.
Why? because humans, while gathering the data, can see details about the corporate culture, interpersonal relationships and other things that are difficult (at best) to quantify. A good consultant will pick up on those things and include them in their analysis.
Even with additional data that computing systems can't quantify, these types of predictions are notoriously inaccurate except in the simplest cases.
But, PT Barnum (or whoever it was who said, "There's a sucker born every minute.") was right. And the people this will annoy the most are the old-school soothsayers -- the "management" consultants. As that will directly cut into their bottom lines.
No, no, you're not thinking; you're just being logical. --Niels Bohr
(Score: 2) by takyon on Tuesday February 13 2018, @03:56AM (3 children)
It's about time to integrate machine learning into the secret sauce to keep the illusion going for a few more years.
Proprietary cloud AI predictive analytics platform utilizing open source intelligence and machine learning.
[SIG] 10/28/2017: Soylent Upgrade v14 [soylentnews.org]
(Score: 2) by NotSanguine on Tuesday February 13 2018, @04:10AM (1 child)
Oh Takyon! You know how hot I get hearing buzzwords and jargon! Don't stop! Oh yeah!
No, no, you're not thinking; you're just being logical. --Niels Bohr
(Score: 4, Funny) by c0lo on Tuesday February 13 2018, @04:14AM
Stop already! Think of those polar bears.
https://www.youtube.com/watch?v=aoFiw2jMy-0 https://soylentnews.org/~MichaelDavidCrawford
(Score: 2) by c0lo on Tuesday February 13 2018, @04:13AM
If it doesn't include blockchain technology, it's worthless.
(or did the blockchain bubble already burst already?)
https://www.youtube.com/watch?v=aoFiw2jMy-0 https://soylentnews.org/~MichaelDavidCrawford
(Score: 5, Insightful) by Anonymous Coward on Tuesday February 13 2018, @04:06AM (2 children)
The Deification of the Algorithm.
We've done this type of thing to all sorts of things throughout history, and it's always been for the same purpose: keep a group of people in check... (conveniently, always a group 'we' don't belong to, it's always the other ones that need to be kept in check)
(Score: 0) by Anonymous Coward on Tuesday February 13 2018, @06:07AM (1 child)
Used to be "computer", and now it's "algorithm".
(Score: 2) by MostCynical on Tuesday February 13 2018, @06:25AM
Don't forget "...in the Cloud"
"I guess once you start doubting, there's no end to it." -Batou, Ghost in the Shell: Stand Alone Complex
(Score: 0) by Anonymous Coward on Tuesday February 13 2018, @07:08AM (1 child)
i predict my prediction is wrong
(Score: 0) by Anonymous Coward on Tuesday February 13 2018, @10:52PM
*implodes*
unless you ran it on a q-comp
(Score: 4, Insightful) by looorg on Tuesday February 13 2018, @07:54AM
All of the above really? It's not a surprise tho since companies have told other companies that all their data is like gold and they can gain knowledge if just the right method is applied to them, or it's put into the cloud or into the lake or into the mist or into the (whatever is the new buzzy trendy word is) or the new AI or PA or ML technique is used. In truth almost all their data is, unstructured, shit and borderline worthless and can only predict shit and no matter how much you polish it and turn it about it is still going to be shit that can only predict shit. That said it is not that data can't be used to predict things, sadly they are not going to be revolutionary things we never thought of before or could have thought of before so it doesn't really add anything new or something unheard off. So yes it's borderline mumbo and jumbo and a few other things that is no better (or much better) then crystal balls, tea leaves or tarot cards or just plain old guessing combined with telling the customer what they want to hear (aka lying your ass off).
(Score: 2, Interesting) by anubi on Tuesday February 13 2018, @08:12AM (5 children)
I read a nice book James Gleick wrote [amazon.com] years ago... its on Chaos theory.
My take on it is he has the right idea... you may define the boundaries with statistical analyses, and probabilities, but exact predictions are damn near impossible. Prime examples being the weather or the stock market.
I've noted during the past that the people that projected high levels of knowledge of the stock market were likely the wrongest when TSHTF. But then, they were presenters, not knowers. And Presentation is 100% of the game when it comes to coaxing people to invest.
This faith-based stuff drives me nuts. I want something that follows LAW, not hopes and whims. That's why I went into engineering. I feel much more comfortable knowing how my stuff works, instead of just hoping it won't break.
"Prove all things; hold fast that which is good." [KJV: I Thessalonians 5:21]
(Score: 0) by Anonymous Coward on Tuesday February 13 2018, @10:19AM (3 children)
I predict, that Dow Jones index will hit 100,000 by 2030.
Yes, will happen. Doesn't mean exactly when.
(Score: 1) by anubi on Tuesday February 13 2018, @10:45AM (2 children)
Providing the world still values a USDollar.
I believe our financial system - so encumbered by debt - is quite unstable and apt to topple.
I also believe the only reason the USD is still viable, is the banking elite are counting on the United States Military to enforce any claims they may wish to enforce around the world, as holding title does not do much good unless you have the ability to inflict pain to enforce your claim to rents due. Otherwise, your debtor will take your stuff and just laugh at you if you are not backed up by the power to hurt.
If you don't have the power to hold onto it, you can not own *anything*. You either have to have the local power to enforce your claim, or have some agent working in your behalf to enforce your claim for you. AKA "Civilization".
The whole world in in debt to the bankers - thanks to usury and fractional reserve banking. And yes, the USA *is* the "world police", enforcing the claims of the Bankers. That is the only reason I can see that the USA is so "fortunate". WWII. We won. We have the bomb and the means to deliver.
Although we have a concept of "Eminent Domain", that's only used against the little people who don't have the resources to fight back.
And besides, who is to say that Elon Musk is doing good stuff with his resources - and should be left alone - or even given more, while George Soros is nothing but a leech and should have his assets confiscated?
"Prove all things; hold fast that which is good." [KJV: I Thessalonians 5:21]
(Score: 3, Interesting) by PiMuNu on Tuesday February 13 2018, @01:56PM
> Providing the world still values a USDollar.
Just for reference, this is how Britain operated during 19th Century, based on debts of foreign powers to UK built up during 18th century and Napoleonic wars. With the added requirement that world trade *had* to operate out of UK ports, enforced by superior military tech (gunboats) and a surprisingly small standing army.
(Score: 2) by FatPhil on Tuesday February 13 2018, @09:43PM
If the dollar were to plunge in value, and the worthless make-nothing-useful companies were to pop like balloons, what would you imagine would happen to the DJIA? The core fundamental businesses that make America work would still be valued, but the dollar would be less, so their share price might rocket. And therefore so would the DJIA, being a weighted mean of share prices - *measured in now worthless dollars*.
Part of the recent SP500/DJIA growth in the last year is because Trump's tanked the dollar by 20% http://www.x-rates.com/graph/?from=EUR&to=USD&amount=1 . Check GOLD and SILVER too - magically increasing in value in USD whilst slowly fading in GBP, EUR, JPY, CHF, ...
Great minds discuss ideas; average minds discuss events; small minds discuss people; the smallest discuss themselves
(Score: 2) by TheRaven on Tuesday February 13 2018, @10:24AM
Weather is a nice example. You can predict the weather with around 60% accuracy by saying today will be the same as yesterday. You can also predict it with around 60% accuracy by saying that it will be the same as precisely one year ago. Combining these two techniques doesn't get you more than about 65% accuracy. Doubling the amount of compute that you throw at the models gives you less than a linear increase in complexity.
You see this kind of diminishing returns in a lot of things. You can get around 90% accuracy from a trivial 4-state branch predictor and around 95% accuracy from the kind that we make students implement as an exercise. With a modern pipeline, you need to predict about 25 branches into the future to keep the pipeline full, so a 95% accurate predictor gives you only a 35% probability of keeping the pipeline full. Going from 90% to 95% was quite easy, going from 95% to 97% is really hard and still gives you only around a 50% chance of keeping the pipeline full.
sudo mod me up
(Score: 2) by acid andy on Tuesday February 13 2018, @11:35AM (3 children)
I've seen the sort of attitudes that foster processes like this even in a very small company. Management that completely saturate themselves in business bullshit for human resource development and take every process in the book there as a drop in fix for any problem with their staff. The staff are unhappy and argumentative. Right, just send them to a team-building event. Productivity is down and staff are stressed. No problem, let's just put up some motivational posters. (I love despair.com )
Now I'm not saying that the above techniques can't work for some employees, sometimes, but cynics like me just see them as a patronizing insult. The really, really idiotic part of isn't just that they take these business processes as some kind of divine truth, it's that almost always the real causes of the employee dissatisfaction are starting them right in the fucking face! Especially in a small company where they can, you know, actually talk to their employees. And I don't mean talk down to them in some detached, holier-than-thou, wanky business lingo. I mean actually frankly talk to them as human beings about what is wrong! More often than not in fact there will be employees that are already telling them exactly what the problem is. But the business bullshit bible tells them that those employees are not team players and are a poor fit in their organization. They don't share the same vision. Probably best they seek opportunities else where.
Basically, these people have a massive fucking common sense bypass. I suppose part of it is it's not convenient, or profitable for them to admit the truth to themselves. Much better to bolt on some bullshit platitudes so the company can claim to care about their stuff yet still get all the benefits of not giving a fuck.
If a cat has kittens, does a rat have rittens, a bat bittens and a mat mittens?
(Score: 2) by acid andy on Tuesday February 13 2018, @12:34PM
My rant was typo-ridden - I know. Just to put it in context, my post was illustrating that most of the problems involving human beings often can't be solved with lazy, simplistic algorithms or flow charts. It's pseudo-science trying to find shortcuts to solve problems when typically there will already be a real, optimal solution staring somebody in the face. The trouble for the management overlords is they can't tell who to ask or who to believe for that optimal solution. It will be one of their subordinates. And the information they need probably won't appear on some crappy feedback form. I can't see how a prediction algorithm can approach anything like that optimal solution without actually acquiring the data that involves it. For example, say employees are stressed an less productive due to unrealistic deadlines. If the magic employee behavior prediction algorithm isn't fed data about deadlines being perceived as unrealistic, how can it possibly come out with the right result?
It's total bullshit for unscientific idiots.
If a cat has kittens, does a rat have rittens, a bat bittens and a mat mittens?
(Score: 2) by PiMuNu on Tuesday February 13 2018, @01:45PM (1 child)
I agree with your comments for small organisations. What about for big ones where the management are several layers away from the people actually doing the work. In an outfit with more than ~ few 100 staff, it isn't possible for senior management to just chat to people. What happens if "joe middle management" is an arse, how do you then manage joe to make sure that the people under him don't suffer too much?
(Score: 3, Insightful) by acid andy on Tuesday February 13 2018, @08:48PM
Yeah in the big organizations it's down to the middle managers to cut the bullshit and talk frankly to those under them and escalate any needed changes or even better find a way to deal with it without involving their higher ups. As for the asshole managers, those that have a high employee turnover or lots of employees requesting transfers are probably the ones the higher ups need to bypass, move or get rid of.
If a cat has kittens, does a rat have rittens, a bat bittens and a mat mittens?
(Score: 2) by fadrian on Tuesday February 13 2018, @01:39PM
Predictive algorithms work fine when they do work. Of course, this does not stop them from being overhyped and misused. And anyone who currently tries to apply them to the work domain is either a genius with a breakthrough or a total tool (in the case of this article, I'm leaning towards the tool side). Just sayin' that you shouldn't be throwing out babies with bathwater - there are some fine techniques and outcomes when predictive algorithms are applied appropriately.
That is all.
(Score: 4, Interesting) by Thexalon on Tuesday February 13 2018, @03:17PM (4 children)
Algorithms aren't going to give you anything substantially better than educated guesses. Therefor, instead of using algorithms, we should use human educated guesses. Which are no better than the algorithmic guesses. Brilliant.
As far as trying to use algorithms to manage your employees: If you don't have a good idea of which of your people should be rewarded when you can do so, which should be punished, and which should be fired at first opportunity, then you are an incompetent manager. And if you're a good middle manager at a company that treats you like you're an incompetent manager and doesn't trust you to manage your people effectively, then that's an incompetent upper management at a poorly run company, and you'll need to decide whether you want to continue to put up with that. This idea of trying to turn people into a set of numbers and metrics is fundamentally stupid, and has absolutely no basis in either psychology or the behavior of great managers.
The only thing that stops a bad guy with a compiler is a good guy with a compiler.
(Score: 2) by FatPhil on Tuesday February 13 2018, @09:55PM (3 children)
True even for the largest of companies, even the Fed...
"Alan Greenspan, the former Federal Reserve chairman who some blame for policies that helped enable the financial crisis, believes people can be irrational after all. [...]" https://www.huffingtonpost.com/2012/06/21/alan-greenspan-animal-spirits_n_1615160.html
Helocopter Ben was just as bad, Yellen was utterly useless but fortunately for her managed to get (kicked) out before the inevitable bust occurs. God only knows what Dotard Drumpf has plonked into that role. He can't be as bad as almost everyone else who's got himself promoted into that role in living memory, can he?
Great minds discuss ideas; average minds discuss events; small minds discuss people; the smallest discuss themselves
(Score: 2) by Thexalon on Tuesday February 13 2018, @11:48PM (2 children)
Fed chairs are given 2 jobs:
1. Keep inflation from going too high.
2. Keep unemployment from going too high.
I'm going to have a hard time criticizing Ben Bernanke, and a very very very hard time criticizing Janet Yellen, because by all available measures they did those jobs very well under very difficult circumstances. As bad as the 2008 crash was, it could have been much worse than it actually was in the US, and if you need proof of how much worse it could have gotten you can look at Spain or Greece. For example, unemployment peaked at around 10% in October 2009 (before Yellen was even involved, I might add) and has since then steadily declined down to the current 4.1%. Meanwhile, inflation has if anything been unusually low for most of that time.
And if you're going to argue that the numbers I just cited were fictitious due to the US government faking the numbers, I should point out that the source that people making this claim usually cite, ShadowStats [shadowstats.com], shows nothing that would indicate that Yellen or Bernanke did a worse job than Greenspan, and indeed shows a slight decrease in unemployment under Yellen.
The only thing that stops a bad guy with a compiler is a good guy with a compiler.
(Score: 2) by FatPhil on Wednesday February 14 2018, @09:00AM (1 child)
Great minds discuss ideas; average minds discuss events; small minds discuss people; the smallest discuss themselves
(Score: 2) by Thexalon on Friday February 16 2018, @02:49AM
1. The entire concept of money is artificial. We made it up. It's a useful social construction, but it's not a law of nature.
2. Manipulating the money flow and interest rates are exactly how you keep inflation under control.
3. None of that has to do with the competence of Ben Bernanke or Janet Yellen, who were given 2 jobs to do, and did those jobs using the powers at their disposal.
I get that you don't like the concept of the Fed even existing, but that's different from whether or not the people involved in running it are competent bosses. If you have a problem with what the Fed is allowed to do, that's a matter for Congress, not the Fed governors.
The only thing that stops a bad guy with a compiler is a good guy with a compiler.