Wednesday, January 18, 2017 / Perth Australia / By Niekie Jooste
at WelderDestiny we spend a bit of time peering into the future, so it is important
to know our limitations in this regard. Often, we believe that we have a great
deal of control of the outcome of a sequence of actions, or can accurately
predict the outcome of a sequence of future events. Statistically speaking this
is not the case. This week we look at one of the reasons that predictions
about, and control of the future, is so difficult and elusive.
In this edition of "The WelderDestiny Compass":
“It ain’t what you don’t know that gets you in trouble. It’s what you know for sure that just ain’t so.” – (Attributed to Mark Twain, but real origin seems unknown)
As humans, we are good at deterministic thinking. In other words, we can normally come to a logical conclusion as to why a certain event leads to a specific outcome. When things are black and white, it is relatively simple to conclude that a specific action will lead to a specific outcome.
What we are not so good at, is when we are dealing with the grey areas of life. Unfortunately for us, most areas in life are grey. One action can potentially lead to many different outcomes, many of which may not have occurred to us, or may in fact be undesirable.
In other words, we live in a world where outcomes are more a matter of probabilities rather than certainties. Within this world, we can easily be tripped up when we believe that we know what the outcome of an action will be, when in fact there could be many different outcomes.
In this edition of The WelderDestiny Compass we will start to explore the reasons why we often get predictions wrong! We then explore how the internet of things could impact the world of the Welder.
If you would like to add your ideas to this week’s discussion, then please send me an e-mail with your ideas, (Send your e-mails to: email@example.com) or complete the comment form on the page below.
Now let's get stuck into this week’s topics...
I like to do a spot of stock market investing. I believe that it is a skill needed to survive into my retirement years, so I have started down this road. As with any of the other fields of interest that I have, I do a lot of reading, and follow a lot of different stock analysts and stock newsletters. Every stock market newsletter analyst has a different approach to how they pick stocks.
The newsletters that I really enjoy reading are those that do high level macro-economic analyses and then give stock tips based on their projections of how the macro-economic picture is going to play out. I do however seldom follow their recommendations for stock purchases, because my experience is that these analysts usually have the poorest records for stock market returns. From my experience, the analysts with the best results tend to be those with a more company specific selection methodology, or those with a more quantitative analysis methodology. Why would this be? Surely the big economic picture should give pretty good investment results?
Now, with investing there are many factors at play, but the one that is important within the discussion today is the “exacta-bet” factor. So, for those of us that are not gamblers, let me quickly explain what an exacta-bet is.
As applied to horse racing, the person placing the exacta-bet must not only predict the winner, but must also predict which horse will come second. To win this bet, the punter must correctly predict both the first and second placed horses in their correct sequence. Instinctively we know that this must be much more difficult than just predicting which horse comes first. To try and get our heads around what is going on, we can take a simple example.
Let us say that there are 10 horses in the horse race, then if we randomly guess the winner, then we have a 10% (1 in 10) probability of being right. If we got the first guess right, then we have a 11% (1 in 9) probability of randomly guessing the second horse. The probability of guessing both the first and second horses in the correct order is then 10% times 11%. Mathematically this is: 0.1 x 0.11 = 0.011 = 1.1%. We can see how quickly the probability of getting this right falls, when one prediction is based on the outcome of another prediction.
So, in the case of the stock tippers, let us
look at a topical example. Let’s say that an analyst looks at the American
presidential elections and then makes a stock tip based on his/her analysis.
This prediction is based on the following train of predictions:
In essence, the analyst needs to get 4 factors right, to give us a positive return on our investment. To get a feeling of how big an effect this has, let us consider a quick hypothetical example. Let us say that our financial analyst is really talented, and would normally be able to be 80% accurate in any of these predictions on their own. This would be a very talented analyst, so we are actually giving the analyst “the benefit of the doubt” regarding their ability level.
In our example, the probability of the analyst picking the right stock, based on his/her prediction of the election outcome is: 0.8 x 0.8 x 0.8 x 0.8 = 0.41 = 41%. Given that this is below 50%, we would have to conclude that a monkey throwing a dart to select stocks would be just as accurate as the really talented analyst. It is not that the analyst does not have ability, it is just that the odds are being stacked against the analyst by the methodology s/he uses.
So, what does this have to do with welding and The WelderDestiny Compass? Well, seeing as we are in the game of predicting and anticipating the future, we need to understand our limitations. The more detailed, and the “further down the line” we try to make the predictions, the less accurate they will be.
We are therefore not in the business of predicting exactly which technologies will become predominant. Rather, we are in the business of predicting which technologies could impact the world of the Welder, and how the Welder could position him/herself to take advantage of these technologies. Some of the technologies we focus on could be superseded by other technologies, or the way in which they are eventually implemented may be totally different from what we anticipate.
Within this context, please understand that this is a journey that we are on, and that there is no clear “finish line.” It is like navigating through a storm. Only once we get really close to any object will it become clear. While we are at a distance, the objects are little more than a blurry shadow.
Furthermore, it shows us that even those people and companies that are at the forefront of the newly emerging technologies, that will eventually form our world, cannot consistently steer their technology to the final finish line over a long timeframe. Even if they have an 80% success rate for each of their planned steps to “conquer the world”, after 4 planned steps they only have a 41% probability of success.
The companies that get their technology widely adopted will therefore be those that can adapt rapidly as conditions change, and that can think in terms of trends rather than specific roads of how to get from point A to point B.
Are you able to align your thinking to give you a statistical edge in anticipating the future, and taking advantage of the changes coming?
In future editions of The WelderDestiny Compass,
we will look at further factors that tend to reduce our control of future
outcomes and our ability to predict the future. By understanding these factors,
we start to see how to position ourselves and the need to be flexible in
meeting the challenges heading our way.
The internet of things (IoT) is a term that is often used today. In essence it refers to devices being connected to the internet, rather than just computers. Now having said this, we need to understand that any device that is able to send and receive data over the internet, does contain a computer of some or other description. In essence then, the IoT is really how computers are being embedded into everyday devices and objects, which are then connected to the internet to send and receive useful data.
The typical IoT device we think of is the fridge that has a built-in touch screen through which you can easily submit shopping requests, or that can even place certain shopping items (like milk) onto your shopping list, which would then be available on your smart phone when you go to the store.
Other typically expected IoT devices would be any home appliance that has its own diagnostic system that could alert the manufacturer when something is wrong, or through which the manufacturer could remotely access the device to try to diagnose any problems you may be experiencing. Think clothes washing machine or dish washing machine as examples.
Once we start to think about it, we realise that just about anything could end up being part of the IoT. The only real requirements would be that there are sensors to collect useful information, and that the device has a computer and interface to the internet.
Within this context, we can see how wearable technology like smart watches could provide data to our own future artificial intelligence computers, and also to companies that are collecting data for analysis and “resale” purposes.
Imagine what information you could get from “smart shoes” that analyse what your gait is like, and can anticipate future foot problems and provide you with suggestions to modify your gait, or to use specific shoes aimed at minimising any problems. Imagine what the medical fraternity could do with that information when collected across thousands of people.
Another issue with the IoT is the sheer volume of data collected, that would need to be stored for analysis. It would be huge. Already data storage companies are positioning themselves to take advantage of this market. These cloud storage companies are already big, just based on the current internet activities, but they will need to grow exponentially to be ready for the IoT data avalanche.
So, the main attractions of the IoT are:
Based on these two broad categories of how the data from the devices can be used, we can see that numerous business models are possible for companies that move into the IoT data space.
No conversation about the IoT would be complete without the obvious down sides to this trend. The obvious down sides are the potential loss of personal privacy and associated constant surveillance, and also the potential for hacking and theft of our devices and data. Around these areas there are also large industries being established.
Can you think of how the internet of things can impact your job? How can it be useful, and how could it be a threat to your job?
Many automated welding machines are already connected to a computer in some way or another. Most modern welding power sources have computer based control systems. Many of these power sources can be interfaced with a network. Many power sources are in fact networked and could be accessed at any time from a computer anywhere in the world. In this regard, the IoT has already arrived in the world of automated and robotic welding.
This has happened, because these types of equipment already have the necessary sensors attached to measure a wide array of welding parameters, and they tend to be “fixed in place”, so the interface complications associated with mobility are minimised.
In the case of the field Welder, the IoT has pretty much been non-existent. The first obvious application would be in diagnostics and calibration of the equipment itself, as the equipment could be interfaced with a network on a routine basis to perform those functions. This application will however not have much of an impact on the job of the field Welder in a direct way.
Future IoT application to the field Welder will in all probability arise mainly as part of an artificial intelligence platform, as the artificial intelligence platform would be highly advantageous in performing control and monitoring functions even while the equipment is not connected to the internet. For continuous IoT functionality, continuous internet access would obviously be required.
For the immediate future, a plan for cheap global wireless internet coverage is not in place. There have certainly been proposals on how to achieve cheap global wireless coverage, and eventually this will happen, but I believe that that is still a few decades away. I could obviously be wrong about this timing, but it is much more likely that artificial intelligence networked on a localised wireless network to other devices around it, will be realised before cheap global wireless internet coverage.
This model of locally networked artificial intelligence with “smart devices” around it will give similar functionality to continuously internet connected devices, because the “real time” IoT functionality could be provided by the artificial intelligence. As soon as the artificial intelligence is within reach of an internet connection, the stored data could be uploaded and analysed as needed for the wider “big data” IoT functionality.
At any rate, the artificial intelligence would make it much more effective to add all kinds of sensors to the Welder to record the necessary parameters and inputs. This would be the case whether the device is constantly connected to the internet or not. So, what kind of sensors are we talking about?
In the last edition of The WelderDestiny Compass we looked at machine learning vision systems. Such systems would be able to potentially perform measurements such as welding travel speed, which is necessary for real time calculation of welding heat input, when combined with voltage and current inputs from the welding power source.
Another very useful sensor would be an infrared enabled vision system. While measuring welding heat inputs are widely used currently, they are not perfect measurements. In future newsletters, or the WelderDestiny website, we will deal with why this is the case. Suffice to say that the actual information that we want when measuring the heat input is the cooling rate of the weld and the heat affected zone (HAZ) of the base metal. With an infrared enabled vision system, the cooling rate calculation could be made directly, rather than relying on the imperfect heat input proxy that we currently rely on.
With a continuous record of the weld cooling rate, we could have an almost fool-proof measure that Hydrogen Assisted Cold Cracking (HACC) has not occurred. (Click here for more information on HACC.) This will mean that the need for time delays following welding, followed by ultrasonic testing, could be reduced or in many cases eliminated.
In cases where high heat inputs are problematic, such as with the welding of stainless steels, this record could serve as assurance that the microstructures are not degraded, allowing the material’s full corrosion resistance to be realised.
Are you ready for a welding future where the
networking of devices is necessary? Are you ready for a future in which it will
be assumed that the Welder understands why and how weld cooling rates are
measured? (and other metallurgical knowledge)
Yours in welding
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What are your thoughts on the exacta-bet principle. Do you see examples of where people are making this mistake without even realising it? / Can you see applications where the internet of things (IoT) can have a significant impact? / Please share your stories, insights and even fears or wishes regarding today's topics.
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