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re: We've become slaves to big data
Posted on 4/25/20 at 7:48 pm to OleWarSkuleAlum
Posted on 4/25/20 at 7:48 pm to OleWarSkuleAlum
quote:
Is more information with which to make decisions a bad thing?
Absolutely not when it is legit and accurate. I think the problem with COVID related big data is that most of it is cooked and pretty much all of it is inaccurate.
Posted on 4/25/20 at 7:55 pm to TigerCruise
quote:
Do you only make decisions based off of the data?
Yes I’d rather a objective decision than a subjective one.
Big data is awesome and it is a huge benefactor to businesses making the correct informed decisions
Posted on 4/25/20 at 8:49 pm to TigerCruise
The multi-variable data sets compound even minor errors into huge inaccuracies, especially data sets that include predict human behavior.
The problem starts in defining data sets, which is incredibly difficult for any non-binary variable. The problems compound in the collection of the data. The errors compound exponentially in applying the data.
The problem is finally capitalized by human bias in applying the results.
Here is a tiny real-world example which will show what I’m talking about:
A local U.S. Probation office wanted to track efforts to get probationers employed. They looked at the existing data which was collected in a binary fashion; employed or unemployed.
The officers were the people collecting the data. They used the data to keep track of who they needed to focus their efforts on.
In the real world, many probationers had some employment, but it was inconsistent, or over-stated by the probationer, or unverified, or seasonal, etc. For example, one guy might be self-employed as a “concert promoter/D.J.” Some months he made good money, but mostly he was “working” by doing unpaid stuff. In that case, an officer might be prompted to mark the guy as unemployed, maybe as a way to remind himself to check in the probationers sketchy and unreliable employment.
Now, in this example, if the probation office decided to do work evaluations of their officers by looking at the “data” on the percentage of probationers on there case load who were unemployed.
After that change was made, in one month’s time, the employment percentage for that office went from 35% to 80%. The administrators for that office didn’t question this astounding “data”, and reported this “data” to Congress, which promptly awarded those administrators for such a remarkable turnaround.
Except for simply, binary data sets, this type of result is all too common.
We simply and consistently over-estimate our ability to collect and analyze and vastly under-estimate the major errors that occur with only minor input variability.
The problem starts in defining data sets, which is incredibly difficult for any non-binary variable. The problems compound in the collection of the data. The errors compound exponentially in applying the data.
The problem is finally capitalized by human bias in applying the results.
Here is a tiny real-world example which will show what I’m talking about:
A local U.S. Probation office wanted to track efforts to get probationers employed. They looked at the existing data which was collected in a binary fashion; employed or unemployed.
The officers were the people collecting the data. They used the data to keep track of who they needed to focus their efforts on.
In the real world, many probationers had some employment, but it was inconsistent, or over-stated by the probationer, or unverified, or seasonal, etc. For example, one guy might be self-employed as a “concert promoter/D.J.” Some months he made good money, but mostly he was “working” by doing unpaid stuff. In that case, an officer might be prompted to mark the guy as unemployed, maybe as a way to remind himself to check in the probationers sketchy and unreliable employment.
Now, in this example, if the probation office decided to do work evaluations of their officers by looking at the “data” on the percentage of probationers on there case load who were unemployed.
After that change was made, in one month’s time, the employment percentage for that office went from 35% to 80%. The administrators for that office didn’t question this astounding “data”, and reported this “data” to Congress, which promptly awarded those administrators for such a remarkable turnaround.
Except for simply, binary data sets, this type of result is all too common.
We simply and consistently over-estimate our ability to collect and analyze and vastly under-estimate the major errors that occur with only minor input variability.
Posted on 4/25/20 at 8:58 pm to OleWarSkuleAlum
quote:
Is more information with which to make decisions a bad thing?
Treating the purveyors of it like medieval priests who are relaying the word of God is.
If you are going to publish the results of a model used to drive trillions of dollars of spending you should be willing to publish every single bit of data input into it and every single assumption made in the model so it can be peer reviewed.
Posted on 4/25/20 at 9:05 pm to TigerCruise
The problem is there are people stupid enough to believe we can build shite like an Iron Man Space suit. The world's richest company can't build a fricking phone that is impervious to spontaneous reboots. We still can't predict the weather or even fight a fricken virus. Sure technology is great but we rely WAY TOO heavily on it. There are billions of people on this earth that are putting sole reliance on data and dismiss common sense.
So, is it best to have science on your side? Of course, but you need to have a back up plan. If there were an EMP attack we would be completely screwed because the population is so high that manual farming operations couldn't keep up with the demand. For those of us that have the country boy will survive attitude. Wild life like deer and catfish would be blown through in a matter of a year. Your best bet is to own enough property that gardening and chickens can feed the family. If things get to the point where stores are out of food, then what?
So, is it best to have science on your side? Of course, but you need to have a back up plan. If there were an EMP attack we would be completely screwed because the population is so high that manual farming operations couldn't keep up with the demand. For those of us that have the country boy will survive attitude. Wild life like deer and catfish would be blown through in a matter of a year. Your best bet is to own enough property that gardening and chickens can feed the family. If things get to the point where stores are out of food, then what?
Posted on 4/25/20 at 9:17 pm to Purple Spoon
Exactly. I am a data analyst and I have worked for companies where I would get the data requested, build some reports etc. give to mgmt and I have seen mgmt manipulate the data provided to fit their agenda. I got called on it at one company to which I pulled all data provided and showed how it was manipulated by my end user. The VP who did the manipulation was fired shortly after.
Also shite in= shite out.
Also shite in= shite out.
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