The Power of Data
A Lebanese bank ad, IBL, that is usually played around the time of the evening news promises to see our dreams before our numbers. However, the director synchronized the ad wrong and showed the numbers floating around the people before showing their dreams. The ad goes on to say that don’t let numbers get in your way, even though they do float around you. But, lets disregard the bad choreography of the ad, they do have a point.
In his book Metric Power, David Beer describes Metric power as the ability to quantify any data of our liking, and the power it has on people. Basically the power of numbers. The standard of measurement to anything really has been blown out of proportions in recent times. With a simple google search of “can thoughts be measured” you can see a confirmation of that on MIT engineering school’s page telling you indeed they can “by watching one neuron at a time, or by looking at how millions of them are talking to each other” yet that is only possible during neurosurgery (Massachusetts Institute of Technology, 2011). Beer emphasizes that even though measurement is important it should not be set in stone. In an article he wrote for the guardian he concluded with “Metrics don’t need our trust in order to be a powerful presence in our lives; they just need our attention.”. (Beer, 2016) The central themes of Beers book are ‘Measurement’, ‘Circulation’ and ‘Possibility’. To begin with measurement, which is the tool we use to “measure” a population or “social entities quantitatively” (Williams, 2016), so everyone is a number. For example, registry numbers for Lebanese citizens who are from Beirut. The second theme is circulation which moves more towards how this data is used by a society. As an example, if you have the data of all LGBT in Lebanon, socially, you cannot publish it for fear of backlash, so the ethical and technical aspect of data is more alive here. Lastly, possibility whelms into categorizing data and using it unjustly for stereotyping or generalizing. When we combine all of Beer’s themes they all deal with the realm of how data interacts with its humans. Indeed, they play a huge role of our daily lives from registering your child in a country all the way to stereotyping Latin Americans and categorizing them as drug lords based on numbers, but it is also much simpler, like using the number given to us by our pedometer to say “ wow I really should have went up the stairs today”. Or in the opposite spectrum, the lack of data in restaurants, by not giving us the calorie count of each meal maybe could have stopped us from buying a certain dish or not going to the restaurant all together.
A historical example of metric power is Cesare Lombroso, aka the father of criminal anthropology. Lombroso believed that he found a pattern between criminals, “you didn’t learn to become a criminal, you were born to become one. (Atlas Obscura , n.d.)Also called “biological determinism,” He studied skulls and noted that physical features such as large jaws, forward projection of jaw, low sloping foreheads, flattened hard shifty eyes, scanty beard or baldness among many others were characteristics of natural born criminals. (Simon, 2014)He also included the black race and tattoos into the mix. (Simon, 2014)To compare this with modern days, not much has changed. With the introduction of predictive policing which uses data to stop crime before it happens. An example of this machine is Predopol. “PredPol takes a feed from each department’s Records Management System (RMS) to collect crime type, location and date/time. This data is collected at least daily and feeds our prediction engine, which is run once a day to create predictions for each beat, shift and mission type.” (PredPol , n.d.) To relate this with Beer’s exemplification of metric power “metrics are based upon models of the world, these models, such as those used in algorithm design, have the potential to become realities in their own right and to fulfil their own prophecies, to perpetuate disparity and so on.” (Beer, Conclusion: The Intersections and Imbrications of Metric Power , 2016) But what happens when the algorithm is wrong? Does it also use “if you liked this criminal here are also similar criminals you can arrest”? To go on, predictive policing and natural born criminals is a rigid form of metric power. To go back to Beer who said “This is a form of control through limit, a form of power that operates by shaping edges to what can be known and by channeling activity in certain directions through its presentation of pre-set constraints that shut down options, choices, and movements.” (Beer, Conclusion: The Intersections and Imbrications of Metric Power , 2016)The data used by both predictive policing and natural born criminals cannot be changed, as data in both cases actually existed once, but does not mean it will happen again. Also, Lombroso and predictive policing use a form of categorization. “Metrics have the capacity to order and to divide, to group or to individualize, to make-us-up and to sort-us-out” (Beer, Conclusion: The Intersections and Imbrications of Metric Power , 2016)Lombroso categorized his data by physical features and ethnicity making anyone who biologically looked like that a criminal. The same applies with predictive policing who use statistics to differentiate between ethnicity. For example, people born in Baghdad are more likely to be criminals than those born in New York, or a black man is twice more likely to commit a crime than a white. All this contribute to bias, unnecessary stereotyping and false predictions.
References:
Atlas Obscura . (n.d.). Cesare Lombroso's Museum of Criminal Anthropology. Retrieved from Atlas Obscura : http://www.atlasobscura.com/places/cesare-lombrosos-museum-of-criminal-anthropology
Beer, D. (2016). Conclusion: The Intersections and Imbrications of Metric Power . In D. Beer, Metric Power (pp. 173-176).
Beer, D. (2016, August). Numbers don’t need to be trusted to shape our lives: they just need our attention . Retrieved from TheGuardian : https://www.theguardian.com/science/political-science/2016/aug/11/numbers-dont-need-to-be-trusted-to-shape-our-lives-they-just-need-our-attention-bbc
Massachusetts Institute of Technology. (2011, May ). How are thoughts measured? Retrieved from MIT School of Engineering : http://engineering.mit.edu/ask/how-are-thoughts-measured
PredPol . (n.d.). How PredPol Works. Retrieved from PredPol : https://www.predpol.com/how-predpol-works/
Simon, M. (2014, November). Fantastically Wrong: The Scientist Who Seriously Believed Criminals Were Part Ape. Retrieved from WIRED: https://www.wired.com/2014/11/fantastically-wrong-criminal-anthropology/
Williams, T. C. (2016, October ). The London School of Economics and Political Science . Retrieved from The London School of Economics and Political Science Review of Books: http://blogs.lse.ac.uk/lsereviewofbooks/2016/10/27/book-review-metric-power-by-david-beer/
