Is there a correlation between the US crude oil import from Norway and the numbers of drivers killed in collision with a railway train? Or is there a correlation between the number of Math doctorates awarded and the amount of Uranium stored at US nuclear power plants? Nobody would say there is, but the opposite is actually true.

The website www.tylervigen.com shows spurious correlations; correlations that are there, but the two subjects have obviously nothing to do with each other. The website claims that it can show 30,000 of those spurious correlations. This can form a problem for Machine Learning.

Machine Learning is a specific part of Artificial Intelligence. It is defined as a field of computer science that gives computers the ability to learn without being explicitly programmed (Arthur Samuel, 1959). Brynjolfsson and McAfee define two types of machine learning: deep learning and reinforcement learning. With deep learning uses the computer large datasets of examples of the correct answer in particular problems. This gives the machine mapping from an input (x) and an output (y). For example: (x)=pictures of various animals and (y)= the name of this animal. The algorithms use big datasets to learn itself the correct answers. With reinforcement learning, the system specifies he current state of the system and the goal, lists allowable actions and describes the elements of the environment that constrain the outcomes for each of those actions. The system has to figure out how to get as close to the goal, given the allowable actions.

The big problem of Machine Learning is that it seeks statistical correlations between subjects in order to provide new information to people. As the example in the introduction shows, there are many spurious correlations that obviously have nothing to do with each other. Since the underlying structure is so complex, people can’t see it when the Machine Learning systems makes errors. This can cause spurious correlations that are less obvious. Because humans can’t recognize the spurious correlation, the Machine Learning system keeps making mistakes, as it bases its algorithms also on the wrong outcomes.

References:

Brynjolfsson, Erik and McAfee, Andrew ‘The business of artificial intelligence’ (2017)

Samuel, Arthur ‘Some studies in Machine Learning using the game of checkers’ (1959) IBM Journal of Research and Development

Since two weeks, KPN (the Dutch telecom company) is offering a nationwide network to link your devices to the Internet of Things. From this moment, the Internet of Things will greater it’s impact on the Dutch society and the economy. But what is the Internet of Things?

IoT refers to all devices which can be connected to the world-wide web. Obvious examples are smartphones, laptops and televisions, but it also possible to link your coffee machine, washing machine or a jet engine to the internet.

Analysts predict that in 2020 there will be between 26 billion devices connected with each other (forbes.com,2017). All these connected devices will lead to a new world of possibilities.

The connected devices will make our life much easier and more automatic: When your car has access to your agenda and automatically calculates the route to your next appointment and can notify the other party that you’re late when the traffic is heavy. Furthermore, your coffee machine can notify that your alarm is set at 06:30 a.m. and makes coffee for you at that time. These kinds of features increase safety (since you don’t have to text in the car that you’re late) and saves time. The coffee machine can present you a cup of coffee in the morning due to your alarm and is able to order new cups online when it knows that it’s running out of cups. Beside these ‘personal’ profit, IoT will also increase maintenance processes for companies since a connected jet engine can notify that parts break down and can notify the maintenance engineer. Cars can make maintenance appointments in the future at the car dealer. IoT combined with Big Data Analyses will show what the weak spots of a jet engine or a car are, so the manufacturer can improve these parts of the specific machine.

We are still at the beginning of an automated society and there will be much more innovations based on the Internet of Things. I’m really curious what the future will bring us!