Are You Wasting Your Personal Data?
21 Apr 2015

Are You Wasting Your Personal Data?

Original article published on Hub of All Things.

21 Apr 2015

Original article published on Hub of All Things.

Every day we interact with technology and (often without realizing it) generate enormous amounts of data about ourselves. Many of us even have distinct data habits, traces of which could be found in our smartphones or in social media. My day, for example, starts with an app which records my diet and exercise. Only a few years ago my sister (a professional volleyball player) used to nag me about my exercising regularly and would give me that disapproving look when I shirked and skipped the gym for a dinner with friends in my favourite French restaurant. Today, this job is done by the app which gives me warnings if I eat too much ice-cream (yes, it does happen!) and reminds me of scheduled runs or gym visits. Many of us use apps to shop for groceries, track our expenses, chat with friends and family, etc.

But do we actually know how much data we generate? And how often do we look back at the data we’ve generated to give these data a second thought and use them to change our behaviour? Personally, I do not know many people who do that. In fact, I think many of us do not realize or simply neglect self-generated data. In my social circle, the brightest example of this type of “data neglect” are my friends Rob and Alice, busy lawyers from New York City, who have an enormous amount of gadgets in their household tracing their energy consumption. Yet, leading very busy professional lives, they never review any of the figures collected by these gadgets and always keep all lights as well as two of their TVs switched on because they feel bad about leaving their German shepherd dog alone in the house all day. Clearly, my friends’ energy consumption data is wasted as it does not help them make optimal choices.

Before I joined the BIG group, I did not even realize that my personal choice data was collected by a myriad of different devices with which I interacted all day and that instead of using these data to make better decisions, I was wasting them completely. And there I was only a few months ago suddenly looking at my data from smartphone apps, shocked at how stupid some of my choices were! At one point I even thought that getting a PhD in Economics was a waste of time since it did not seem to teach me anything about making smarter decisions in my day-to-day life! Yet, if like me, you were neglecting your data, there is still hope. Do stop and look at what your technology tells you, pay attention to what you do and, who knows, maybe in just a few months you will decrease your bills, save for that fantastic vacation you’ve always dreamed of and even loose a few pounds! After all, if online companies are collecting and using your data, why should you neglect it? So, next time you see an annoying personalized advert from Facebook or Yahoo! for shoes that you would not consider buying even if someone held you at gunpoint, maybe this would be a good reminder that if you do not use your data, someone else will…

 


About the Author:

Ganna Pogrebna

3798791880957e5ffb98e1cb49a795caDr Ganna Pogrebna is a co-investigator in the HARRIET project. Ganna is Associate Professor of Decision Science and Service Systems at WMG. She is a decision theorist/behavioural economist and empirical econometrician with particular interest in decision making in a digital domain, IoT and behavioural aspects of platform choice. She also works on behavioural aspects of digitisation and business models in application to individual and household choice as well as smart cities where her areas of expertise include quantitative modelling, data analysis, and new business models. In 2011-2012 Ganna received a Leverhulme Early Career Fellowship in behavioural science. She has published in high quality peer-refereed economics and business journals. Within HARRIET, Ganna is particularly interested in the influence on the digital technology on individual decision making within the household and in the workplace. Her tasks include analysis of sensor data and derivation of HAT/HARRIET Algorithms for new products/services and business models.

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