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Data Skills in the energy transition Inequalities in the Internet of Things

by Alex van der Zeeuw

Installing a heat pump at home seems to become a popular solution to reduce unnecessary energy consumption, save costs, and create a greener environment. However, not every house works well with heat pump installations. Alternative options for the energy transition might be found in the gathering of accurate data generated from our homes and personalized to our homes. The internet of things, as a collection of everyday devices connected to the internet, can support people in making decisions based on the enormous amounts of personalized data collected. A common example of the IoT being used for improvement can be found with activity trackers to set personalized goals and aims based on user-generated data. Our research findings revealed that there is not much difference between the use of wearable health devices and home devices (such as smart light systems or smart thermostats) in how people relate to their devices in terms of data skills.

Data skills is an umbrella term used to describe the digital skills necessary to retrieve, read, present / visualize, and interpret data. As such, data skills are especially important in understanding how data is used by algorithms. This is very similar in how people are differently skilled in using search queries effectively for the algorithms of search engines such as Google. If you have a better idea which search terms are effective for your purpose, as a latent understanding in how search algorithms work, you do not have to think much about the relevancy the search results and just trust the algorithm. The same goes for the IoT. If you know how to set it up - what it does and how it can be applied effectively - you will have to think less about the results or the data. Instead, you can just trust the algorithm and let it do its work. In terms of data skills, what is similar between using Google, an activity tracker, or a smart thermostat, is that a better understanding of how it works, helps to think less about the outcomes. Its algorithms help to reduce cognitive strains in everyday life. In our research we find that this is how the IoT is commonly used. Whether it helps you to remember that you’ll have to take a few more steps this hour to improve your health, or it reminds you to turn the heating off to reduce energy consumption: The IoT is a tool that supports reducing cognitive strains.

By following different households over a period of 15 months, we found an interesting pattern from when people first start set up the IoT according to different levels of data skills, to how they change behavior when they start getting their personal data returned to them. What was first aimed at reducing cognitive strains, almost automatically turns into a tool for personalized improvement. Rather than forgetting about their IoT and its data, people start to actively live with their data; they become entrained by their data. People start using an activity tracker not only to get a certain number of daily steps but become actively involved in personalized improvements for their health. The same goes for IoT devices at home. A smart thermostat is not only used to have it turn off or on algorithmically, the second-by-second data returned to them, makes people become more aware of how or when to save energy. By living with data or using data as a lively ‘thing’, personal big data also exerts power with its requests or demands to work well. Think about the streaks you aim for with your daily steps, or the reminders to turn on you location for improved accuracy. The entrainment by personal big data, creates a hunger for more data.

The way we feed our behavior back into our IoT devices to create more data, is how data comes to matter. It changes our reality - our behavior and what matters in our behavior - according to the data we measure and use to achieve certain goals. Reality becomes mediated by the devices we own, the data we retrieve, more importantly the data we grow. However, the hunger for data to make it grow, to nurture it, or any other variation care to data, creates a gap between people in how well they are able to live with data. Here, data skills return as a vital skill to retrieve, read, and interpret, data and how people are able to live with data differently. Ones data hunger is fed with higher proficiencies in data skills. Consequently, in the energy transition between traditional heating, heat pump installations, or alternative options, some people are able to use very accurate, cared for data to inform their decisions, while others are not. This results in different levels of autonomy. One size fits all solutions might seem promising, personal big data generated with the IoT can certainly show otherwise.