I’m not the first one to recognize this and won’t be the last but those who work with computer formulas and those who work will business models know it and there’s a lot of good information out on the web about this with documentation of you want to look for it. Someone told me the other day that after reading some of my articles here, they came to the realization that “computers can be wrong now” unlike what we knew for years. In the early days the use of “boring” lineal data was about all we had out there. I say boring because it’s flat out math, accounting, budgets, all the “real” numbers out there that help businesses run. It’s not like that anymore.



We read the news everyday and everyone of us whether you are conscious of it or not makes a determination of “is that real” or not. This is what we are experiencing when we have the real world clashing with the world of making money using non linear information and speculating. There’s a big drive behind this of course and that is money. You can listen to any good mathematician and and they opening discuss the margins of errors in any of out intelligence we create today, and yes as the title suggests here some of this is “not real”. Today the clash between both worlds is bigger than it’s ever been and all of us consumers not being into math for the most part are somewhat lost.



In the finance world the goal is to show less risk to make or receive money. Turn this around a little and when you enter the world of health insurance and I guess this could apply this for any insurance for that matter, you have the opposite, accelerate the “risk factors” to keep money and not have to spend it. In a very simple way one side hides the risk to create a “rosy” world to make money and the other side accelerates it to keep money in their pockets. This is really nothing new and has gone on for years but today we have a world where both sides have accelerate the processes and it’s all about money.



I keep using this video as an example “The Quants of Wall Street Documentary” and do so because that is where a lot of begins, with companies, banks, you name it. They design the business models and there’s nobody around auditing these models. The truth is they are so complex at times, where do you find someone to do that? It might well and beyond what another quant could do. CEOs just have to listen to their quants and there’s extreme pressure on the quants as well. In the video you can hear this. The one computer programmer says it “you can’t be wrong” “you have to be right” and that’s because there’s a lot of money based on the work they do and it drives big sectors of the economy. Yes, that’s a lot of pressure to do that job and as you hear in the video they tell you it’s fantasy numbers and formulas.



I think it is interesting how the one quant here says “I apologize to the planet” as he knows and is telling you. The end result is that we are working with a very complex world of fiction being mixed with the real world and even in a humorous way he states “the real world is dirty” when compared to the “wonderful” world of math which is exciting and where you can create what ever you want. Three years ago I made a post when the Madoff case arose and asked if we needed a Department of Algorithms or something along that line to catch some of this that was sliding through. Madoff was not a dummy in knowing how to play the system and it was reported that his IT folks were the brains of it to constitute hiding the “real” side of all of this.



Again some of the comments made in the video are pretty interesting and I think right on the money. Sure, quants have a bit of an ego and so do computer programmers too as they create this. The quant builds the model and the programmers do the work to create infrastructure that makes it run. When you watch the video, the one technologist says “I can do it in my sleep” and talks about his world of being in a cubicle for the most part, cranking out code and how he forgets about having fun at times as this is pretty absorbing too and requires a lot of focused time.



If you listen more to some of the comments some have a flair of humor to them too “CEOs are "CEOs are actually fantastic instruments when they slice and dice” and when you look back here he also says there’s way too much math in finance today and we have seen this with the likes of Jamie Dimon when asked about their model in saying “I don’t know” and that comes right back around to complexities again. He’s not the only one but we happen to have him on video for proof, but you can go further and read more about the likes of Mr. Corzine for one example trying to find out what the algorithms did with his money. Same stuff everywhere you turn when you can’t find the money and we come back to models and algorithms. They rely on the quants to not only create the models but also be right there to tell everyone else what to do next and this is a very powerful position when you think of it. In the video the one former programmer is spending $60k to take a class to become a quant as he wants some of that power too.



Now when it comes down to us as consumers there has never been a time to when risk comes down to the levels we have today, there’s no slack at all in anything and we are dealing with a world of data that is growing with flaws every day. We’re not quants out here but how much of the risk factors that we are judged upon are fiction? The reality of this is starting to show as the desire for money is pushing all of this and the field of predictive analytics is an area subject to “huge” abuse. There’s the real stuff out there too but when it doesn’t make enough money we can venture back over the fictional world and create numbers and formulas that do that.



It’s an interesting world indeed that is ending up to be the undoing of what we have developed as our culture over the years, one side hiding risk and other parts exploiting it. Is there any balance here when you bring in the error factors that are always there and fictional models? Of course not and it is making everybody crazy and this give a lot people a big area of control and moves a lot of money to the direction of very few in the US so the land of opportunity tends to shrink a bit. You have to deal with and try to make sense of the fiction that’s mixed in out here.





That’s why I started by series on the Attack of the Killer Algorithms to try and use everyday examples to help and maybe show the cause and effect of some of this so maybe it might be recognized when trying to make sense on how to live in the world of minimizing risk and accelerating risk clash. When someone is going to spend some money on you, the key is to accelerate that risk and when the other party is going to make money off you, then the game is to lower that risk perception. It’s all done with numbers, formulas and computer code. When practiced in this manner and when you question some of this how often have you heard “it was a business decision” and ethics and accuracy questions may not get the proper attention as that’s a big cover all. In the old days before computers did this work, there was a human who made some of these decision and thus so there was a human element built in, but not today.









We have great science out there today too and their work needs to progress forward of course as they find cures, treatments, etc. but even in their world they have to run interference with some of the fiction that appears there too and we have all read that in the news about those who have faked their research for the sake of money and guess what the same old risk factors and the clash of the real world and the one of fiction are right back in there again. When this occurs in the world of science it really hurts everyone as other scientific information is built on top of what they produce and when it’s all fiction, a lot of time and money is wasted. This is almost tongue and cheek to a degree but I found a study in PLOS One that says the fear of math makes us feel physical pain and what was funny is that I had a few programmer tell me that “yes they feel pain with some of the complexities they work with”…so not just a consumer perception at all.





To kind of elaborate a bit more on PLOS One, we now have this, an abstract on how to head off some of the fiction some methodologies on how to head off the some of the fiction or as it’s called “fiddling” with P Values. Why would somebody write this abstract and offer this type of information if they didn’t think they were helping solve a problem?









So one day your have little or no risk and look great and the next day risk is accelerated and you are the bottom of the barrel, again depending on what type of assessment and analytics are use and for what purpose. I am seeing others in the IT world beginning to reflect back to in their blog comments and so forth as well with the same type of thoughts here….what really matters is what’s in the real world…not the world of fiction”. So sometimes the question might come up when our numbers are run through all types of analytics “Am I going to be a good risk today or a bad risk” and some of this might come down to who wants to make a buck today. It’s starting to show a bit with more getting unsettled with the way formulas and math are used. There was a good panel discussion on this with value in data and the gal from T-Mobile was spot on here with stating some of what we were doing was “silly” in other words they were not capturing data with value with some of the methodologies they were using and this is important as we move forward into big data. That video is what inspired me to elaborate a little bit more on how data out of context combined with fictional models and code will end up exploiting consumers as all of this data may get sold and combined with a new source of data. Sometimes with the billion dollar data selling business we have out there don’t care how the data they sold gets used either, they made their money with a sale, that’s sales 101. They just made a sale and are not responsible for the next group down the line and what queries they write. And so it goes, the write some queries and bingo we have more data for sale and is there value and are these analytics hiding or accelerating risk? Data is re-rolled and builds upon itself. I can once more again suggest that we should licensing and taxing these folks as there’ need to be some regulation here of some sort to demand some accuracy and value. I would think the folks in science would like this as the money derived could keep their funding going being the NIH is looking at budget cuts.







Again in the video, one comment too about all of this is the quant asking when it comes to science “who’s splitting atoms today” few as they want to live in the fantasy world of the quants to where power and math rule and offer a lot control and with that comes a lot of money. The same quant is also pretty critical on economists saying “they think they are scientists and they have no laws” and this is not picking per se on economists but rather stating what they have out there today to work with is also challenging because we come back to the same issue, have their numbers been skewed too? They have the same thing chewing at them as well and it makes it hard. In the past before the ups and downs of risks accelerated, they could be better predictors but they are in the same boat as the rest of us. The quant continues and states that “models can be used to hide risk” so there you have it from the horse’s mouth. He should know as that’s part of what they get hired to do and he apologizes to the planet. It’s pretty interesting too when he goes through his book of pledges and promises that is kind of the hypocritical pledge that quants should take. In other words he reads what he deems pledges of value and cites that nobody might be minding this shop.



There are thousands of intelligent people in the tech world that can write queries and relate data, I can do it and have done it jillions of times as when used properly and in context, gives us intelligence and value. When we go off into the non linear world though it gets a little strange out there. Let me use a real stupid example here. What if I had a data base of people who own hummingbird feeders and then I had a data base of those same people who have chronic health conditions. Well if I found that more than 5% of those with chronic conditions owned hummingbird feeders do I put that out that owning a hummingbird feeder is a good indication that those people will or do have chronic health conditions? I used this example to be very stupid so make a point. We see stuff like this in the news all the time. Does it have value, of course not, but something like this has the potential to get added into some risk assessment, no matter how ridiculous it is. Here’s a good book to read that says a lot more than I can that came out back in September of 2010.









Welcome to the world of obscure analytics as a lot of the time we see the results but the data used to create this is unknown or maybe even misstated. If you want to see one of these in this same relative area, in real life, read about what FICO does and how they sell their analytics service using credit score and other data which they do not tell us the origins of the data used outside of your credit report to score you on being medication compliant. Their market is to sell this to pharma and insurance companies. Since I am on the topic of credit here when it comes to risk, we have companies like this selling risk assessments that operate outside where the government can regulate that sell all kinds of information about us and as a consumer we can’t even get to it, perhaps due to the way the business model is constructed?





It’s a tangled web out there of credible and non credible data at work and with such a strong driving force of money we have today is there any way to correct any of this? I read an article at Zero Hedge the other day and the title was “All I want for Christmas is the Truth”..I think we can all relate to that but the chances of that happening are slim and none as Santa, who is the big symbol of Christmas is fat and obese and the symbol of everything the analytics tell us is wrong with us relative to weight and he’s not business professional either so the poor guy doesn’t stand a chance. On the other hand though is that us, as humans, we still love him anyway and accept for what he is and the joy he brings to all. But again, let’s not fall into the caverns of fiction that can only see that he is obese as he too could be destroyed by exploiting his risk but never mind the sack of presents he carries:) If we didn’t have this issue in healthcare, I don’t this this institute at the link below would have been created and I’m glad they are around too. In summary, there’s a lot more room for some humanism today.





Earlier this year I posted a video with Dr. Hamburg, head of the FDA giving her address at the Albert Einstein College of Medicine and she has a very tough and sometimes thankless job, but what she says here is good and she gets it and thank goodness we don’t have a “business executive type” running the FDA!





In the left hand side of this blog you can find the 4 videos that I chose that I think really make some phenomenal and accurate assessments of where we are today. These are people much smarter than me but I hope by grouping all of them together for viewing that it might give some food for thought out there as to the title of this post.. Just scroll down a little and they are always here and if I run across others, I’ll add them. To risk or not to risk, …a huge issue today with digging to find truth and reality and separate it from the fiction we have been fed for the pursuit of money. The economy and all of us depend on it.





Video collection here with related material…

