Book cover of Everybody Lies. Source: Goodreads.
Stephen Davidovitz’s book, Everybody Lies, uncovers the power Big Data has to reveal patterns in human nature that cannot be captured by traditional methods. He demonstrates how digital traces can transform large, unfiltered information into meaningful data on people’s actions and thoughts while reducing biases such as social desirability (Eugene). Davidovitz investigates several subjects, including racial attitudes in the United States, patterns between body parts and horse racing and the hidden sexual preferences of men. With the aid of publicly available datasets and information from specialized websites, he introduces innovative techniques and uncovers unexpected correlations between diverse domains of data.
“Medical Data.” Image by Yamu_Jay via Pixabay.
One claim that I found personally illuminating is the use of doppelgänger data in the medical field. I found it intriguing that doctors could use treatment plans from similar patients to find the best possible way to diagnose and treat an individual. In a way, physicians already do this with symptoms and treatments, but not with this precision (Sassman). The only limitation of this method would be accessing other patients’ data since confidentiality laws prevent any disclosure of information without consent. However, if it were to be possible to obtain a large enough dataset, I believe this would be a significant step forward for the medical field.
“Surveys.” Image by Mohammed Hassan via Pixabay.
Dismissing alternative ways to analyze problems other than Big Data would be misleading. There are times in the book when he openly dismisses or mischaracterizes solutions presented by different people. For example, when his grandmother gives him dating advice, he labels her as a “data scientist”. As Colin Strong describes, “He is making a category error – thinking of her as a data scientist (and the generating rules from the data) misrepresents her ‘analysis’.” Immediately dismissing conventional wisdom is the wrong approach. Data analysis can be as flawed as “conventional wisdom” or survey data if fraudulent data or misrepresentative data is used. As Lisa Sussman points out with the data collected on suicide, “He writes on the commonality of suicidal ideation, as reflected by searches such as ‘suicidal’ and ‘how to suicide’ (p. 268). The number of such searches, however, does not correlate with the number of suicide attempts.” In addition, gaining information through other methods can be extremely helpful. For example, measurement tools such as surveys allow us to record data which may not be accessible, such as perceptions and opinions, which can be useful for drawing certain conclusions (Mouncey).
References:
This book explores how Big Data is used to reveal human behaviour. It covers a range of topics, from politics to race and sexual tendencies. The book is written by an expert in the field who is a former data scientist for Google. I will draw several examples from this book to support my arguments.
This source is a review and commentary on Stephen Davidovitz’s book, Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are. It goes through the key points of the book and offers some commentary on the use of Big Data as the primary way to draw conclusions on human behaviour.
This source is a review and commentary on Stephen Davidovitz’s book, Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are. It dives deeper into the primary questions asked within the book and raises concerns with some of Davidovitz’s arguments. I particularly used the source to support my argument about surveys still being important to modern research.
This source is an opinion piece on Stephen Davidovitz’s book, Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are. It brings up criticisms against several arguments within the book, such as the role of conventional wisdom and surveys. I used the source to support my opinion on the role surveys have in modern research.
This source is a review and commentary on Stephen Davidovitz’s book, Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are. I used it as a source since it dives deeper into the use of doppelgänger data within the medical field and the potential dangers of overly relying on Big Data.