Vad teknikföretag vet om dina barn

We are fascinated by the possibility of "intelligent machines," machines that can surpass human nature, machines that can solve our problems, and eliminate our weaknesses. Yet this is often only a dream. In this fantastic book, Meredith Broussard demonstrates that our understanding of artificial intelligence is in fact based more on myths, dreams and expectations rather than reality. This is a must read for anyone who is interested in understanding the impacts of AI in our data-driven world, and how much could go wrong if we believe in the accuracy and power of AI technologies.

Today algorithms are used everywhere to profile and judge us, and to make data-driven decisions about our lives. Yet algorithms are not objective nor neutral, but they are human made, and hence always biased and inaccurate. This book is of key importance for anyone who is interested in the fallacy of algorithms and in the social inequalities and real-life harms that they can cause.

Governments use algorithms and data driven systems to decide all sorts of things from access to welfare to health. Eubanks' book on automating inequality is particularly important because it shows that there is something profoundly unequal and unjust about the different ways in which automation impacts high-income families on the one hand, and low-income families on the other. Data technologies and automated systems are not equal or fair, and the experience of data harms depends on one’s position in society. This is a scary but crucial reading, if you are interested in understanding how automated systems are actually amplifying social inequalities.

We hear a lot of talk about the importance of data privacy and data regulation, but there is very little understanding of what data privacy actually means. In her ground-breaking book, Nissenbaum argues that when people are concerned about privacy they are not really concerned about sharing personal data in public. What they are concerned about is having control over their personal data flows so that they can determine, which personal data is shared in which context. In our new data environments, it is becoming increasingly impossible to control our data flows: our employers have access to all sorts of personal information and companies and governing bodies can profile us on the basis of data collected from a plurality of contexts. Nissenbaum’s book is thus a key reading for anyone who is interested in data privacy and data regulation, and is really willing to understand why data privacy matters.