Review:
How Data Happened: A History from the Age of Reason to the Age of Algorithms is one of those books I am happy the authors thought to write, because it asks a basic question that many of us are too busy or thoughtless to ask. How did we get here? As the title makes clear, the book tries to trace the roots of our current data-obsessed global society back several centuries to find out what people, ideas, and concepts helped make the modern 21st century world of surveillance capitalism possible. The story told in the book is sometimes amusing, like how Guinness wanted to use data to make better beer more reliably. At other times however, the story is much more sinister and helps highlight the dangers of how data can be gathered and used to reinforce prejudice, like when eugenicists set out to use data to prove the inferiority of certain races.
Overall, How Data Happened is an illuminating book that helps explain how we came to live in a world that is monitoring us constantly, to gather data on us so that companies and politicians can sell us their products or opinions. I highly recommend this book to everyone. Every once in a while it is beneficial for us to take a step back from our busy lives and ask ourselves how we got here. Just as importantly and what I will be discussing in a moment is another question that we should all ask ourselves. Does it have to be this way?
Discussion:
To continue the discussion first I want to quote two of my favorite passages in the book, one quite long and the second only part of a sentence. (In the second quote my own emphasis is added).
“Powerful forces often are reticent to investigate the historical genesis that made them possible–or even dominant. Complex histories unsettle the obviousness, the legitimacy, of their power. In looking at the far from obvious ways technologies come to prominence, history unsettles the idea that the growth of certain technologies themselves drives history, a view called “technological determinism.” It has been very lucrative for many interested actors, for example, to claim that older views of privacy are outdated in the age of the internet, even that the internet itself causes the decline of privacy. Neither claim is true. But such stories offer a potent version of history, ubiquitous in debates around the internet, that legitimates the current order of things as necessarily so.”
“Date is made, not found…”
The passage I just quoted above was probably my favorite in How Date Happened. Partly because it relates to ideas and concepts that I talked about in my own book. Obviously the quoted passage is referring to government and corporate surveillance and the erosion of privacy in the 21st century. Wiggins and Jones are making the point that the current model of the internet built on data gathering for targeted ads is not inevitable, and that studying the history of data and technology shows us that it’s not a straight road to the present. Rather, there were an infinite number of forks and divergent paths along the history of data, and we could have gone down any number of those divergent paths at different points in time.
I firmly believe this idea that nothing is inevitable applies to all human events and decisions, not just to the history of data. This is a point that I will harp on until I am blue in the face. Nothing being inevitable and everything being contingent is both a good and a bad thing. It means that had people acted differently in the past, things might have turned out worse, but it also means things could have gone better as well. If everything that happened in the past is contingent, that means that it can be changed for the future. This doesn’t mean we should blindly hope for a better tomorrow, but it does mean that we have a chance of creating a better tomorrow if we work to achieve it.
Take for example, the subject of How Data Happened. Just because we live in a world of surveillance capitalism doesn’t mean we are doomed to always live in one. If everything in the past was contingent, that means the present is as well.So maybe with enough effort, we can live in a future with a renewed emphasis on our right to privacy, our right to our own data, and the right to know who is gathering data on us and why.
“Date is made, not found.” I’m sure the authors would agree with me when I say that if you only remember one thing from How Data Happened, it should be this statement. Because these five words capture the essential problem with how many people perceive data. There is often a mistaken assumption that conducting a study or a survey automatically produces some universal truth that we are forced to recognize. Even more importantly, many people assume that data contains no bias; and by extension, the institutions, algorithms, and AIs that use this data contain no bias.
The complete opposite is true. Data is created, collated, interpreted, and presented by people. Data can absolutely reflect and reinforce the bias of the people creating it. Wiggins and Jones demonstrate in their book that many of the early and enthusiastic creators of data in the 19th and 20th centuries were eugenicists. If a bunch of eugenicists published data that purported to “prove” the biological inferiority of different races, should we accept that data as unassailable truth? Or is it more likely that these eugenicists gathered their data and then interpreted and presented that data in a way that reinforces their preconceptions?
Taking eugenics and phrenology seriously in the 21st century might sound silly. However, it was treated as a science by some people up until the relatively recent past (and still is taken seriously by some up to this day). Furthermore, this racist pseudoscience led to some truly horrifying policies being enacted such as forced sterilization in the United States (which was done until the 1970s by the way). In the US we are still living with some of the structural and institutional discriminatory practices that can trace their direct lineage to eugenics.
The point of this, and the point made in How Data Happened, is to remember that data is not inherently unbiased. Data in fact has the potential to reinforce and legitimize bias and discrimination. With this in mind we need to be extremely careful what data is being fed into algorithms and AIs to ensure that discrimination is being eliminated rather than supported.
Conclusion:
How Data Happened is an excellent resource for anyone wondering what confluence of factors led us to the digital environment that we are mired in today. As it said in the passage I quoted above, unraveling the history of a topic can help dispel the illusion that things have to be this way, and that we don’t have the power to change in the present. As usual if you are interested in the book I will have links for it just below.
Links to How Data Happened:
https://www.barnesandnoble.com/w/how-data-happened-chris-wiggins/1141651636?ean=9781324006732