Wealth does not bring goodness, and all that...
The researchers created an imaginary world, filled with 1,000 individuals with varying levels of talent in random positions who were exposed to random lucky and unlucky events. After a simulation of 40 years, meant to represent a person’s career, the distribution of wealth looked an awful like it does in the real world, with a small percentage of people obtaining the most capital.
“Were the most successful people also the most talented ones? That’s what we would expect… But we discovered that this is not the case. Instead, very often, the most successful people are moderately talented but very lucky."
“We discovered a strict correlation between luck and success. Encountering a series of lucky events was responsible for incredible success even if their individual talent was lower than super talented people. This is what we usually see around us in the real world. There are plenty of instances of people who we don’t consider particularly smart but in some way they reach a high level of wealth and success.”
Sort-of tempted to read the original paper to see if there's any statistical evidence for this. It wouldn't be surprising, but on the other hand rich idiots tend to be far more noticeable than the talented people who have the good sense to keep quiet. My guess would be that wealth and power both attract the corrupt and corrupt the innocent, but I wouldn't like to hazard where the balance lies. And there could be a large fraction of rich people who are wonderful philanthropists and not corrupted at all, for all I know. Then there's the even more complex issue of basic social justice that people earning 1,000x more probably aren't 1,000x more capable or hardworking than those at the bottom.
The team found several alternatives that could change the way we currently reward people who are already successful. For instance, instead of handing out bonuses for already high-performing sales people, one strategy could be giving a small amount of money to everyone, which was more effective than the meritocratic system in the computer simulation. Even giving money to 25% of people at random (regardless of their past performance) led to a higher percentage of the most talented people in the computer model who achieved success than rewarding the most successful people, since as we know, success was largely a proxy for luck.
But past performance is no guarantee of future performance, warns Biondo. “If you value merit exclusively by means of past results, once you realise your past results can be generated not only by talent, but also because of fortunate events, then you are rewarding luck, not merit.”
And one can imagine positive feedback effects at work here : reward the lucky people and people assume the reward was given fairly, giving them greater credibility and allowing them to exploit more opportunities for success in the future.
http://www.bbc.com/capital/story/20180309-your-hard-work-doesnt-actually-pay-off
Do read the original paper. I'm going to use it as the end of my "Data Science Concepts" class (i.e., data science without the math or programming) next week. Your quote here parallels one of the things in the paper--that funding scientists follows that same model. Due to the serendipity of discovery, you're most likely to find a breakthrough by giving all scientists a little rather than super-funding the science rock stars. I can dig up the link if you want.
ReplyDeleteMany years ago, when the 486 chipset was considered a mighty powerhouse of desktop computing, I picked up a strange gig.
ReplyDeleteHow does anyone make money trading commodities futures? "Buy low, sell high" of course, and the futures markets allow you to sell before buying, etc.
The first software I ever wrote for money was analysis of this sort of market. But this gig was different. My client was telling his clientele he could help them make more money by learning from where they'd succeeded and failed before. We had an enormous historical dataset of market price data going back, some of those markets, to the beginning of the Chicago Mercantile Exchange in 1898.
I was exceedingly well compensated for this work. Essentially, we put their trade book on some fancy charts and predicted the past. Then we let the suckers clients pore over the charts, and do some "technical trading analysis" so they could look for more such opportunities as they arose. We'd then construct rule-based models to "alert" the clients, should the precursors to such conditions arise again. Or, we could sell them models. The money just rained down, like a cow pissing on a flat rock.
You will, of course, recognise this as a con job. Really, under the covers, we always injected risk and profit stops on these models to impose some discipline on their trading. We'd farm these models, weeding out losers, models for long-trending markets. models for highly stochastic markets, little miracles of post hoc fallacy.
Eventually I quit in disgust, not wanting to be part and parcel of such a scam. And the client really was a jerk.
Success is not merely luck, thought that's a large part of it. Success is putting yourself in the right place, time after time, day after day, patiently working towards a goal. Smart people are not always ambitious people. I have yet to see anyone succeed, over the course of a long and meaningful career, who did not first crave success. If the need is there, there also is someone who will work hard to succeed.
Michael J. Coffey Yes, please find the link. It is possibly the strongest case for a universal basic income.
ReplyDeleteBenjamin Gustafsson -- It's at arxiv.org - arxiv.org/pdf/1802.07068v2.pdf And I had that same thought, though they look at education rather than UBI as a way of "raising all boats" as it were.
ReplyDeleteThe link to the paper is actually in the original article. Looks like a good read from the abstract.
ReplyDeleteDan Weese Your comment reminds me of the difference between malevolence and intelligence. It would be interesting to see someone model the effects of that (I seem to recall that this has been done, but I'm not going to look that up right now).
Rhys Taylor A sociopath just doesn't limit his options.
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