Anderson: The End of Theory

In recent years, the scientific community and the broader society has been inundated with data. Data from social media reveals insights about individuals and groups, satellite data can reveal migration patterns and deforestation trends, and weather stations or unmanned sensing sites can reveal new information about the climate, organisms, or even the path dust travels across the world. Given this influx of data, it is time for scientists to change their approach to science. Traditionally, in the absence of comprehensive data, models are used to explain natural and physical phenomena. Models are created using small data set and used to fill in gaps of knowledge and extrapolate likely outcomes. They have been very useful, but the new era of big data will usher in change. Take for instance Charles Darwin’s model for evolution; it is a widely celebrated model and has proven useful for hundreds of years, which I fully recognize. However, there are drawbacks, inconsistencies, and room for improvement. Employing big data could render such a model obsolete, changing the Theory of Evolution to the Correlation of Evolution. By collecting and inputting millions of data points about morphology, genes, extinct creature, and present organisms and using advanced, high-power statistical tests biologists could produce an algorithm that becomes the unequivocal solution to evolution. Biologists will no longer have to rely on a model, with enough data it will practically be fact. This is because in the new world of big data, as Anderson put it “correlation is enough”. With the size of current data sets, correlation is now empirical, rendering all forms of deductive reasoning obsolete.

Kitchen: Theory Will Remain

The world has been inundated with data over the past decade. There are people who argue this influx will lead to the extinction of theory, as they believe models based on a few data points will no longer be necessary when the whole data set becomes available, especially compounded with new statistical methods. Nevertheless, data cannot be the only aspect of science. To illustrate, questions and hypotheses represent scientists’ approach to making new discoveries. Without such a process, scientists would be sifting through data (as in computers would be synthesizing the data) either hoping to find a correlation at least vaguely associated with their area of interest within their field. Rather, scientists need a focus in order to refine their approach, and from questions and hypotheses come theories. Granted, these theories will be largely supported by data, but a human will be the instigator of the data collection, instead of a computer on the prowl for any correlation. Furthermore, everything in life has some level of ambiguity. No matter how much data one has about a subject, it is an oversight to approach a human problem with a computer alone. For instance, imagine a scientist is using demographic data to analyze the race, socioeconomic status, and neighborhood of residence in a certain area. Their computer has discovered a correlation that black residents on average make less money than white people and they live in segregated neighborhoods. Based on this correlation alone, the scientist may perhaps assume that black people are predisposed to make less money. Although the data supports this claim, looking at this from a broader perspective one can reasonably assume that the true reason for socioeconomic disparities is long-standing, systemic racism. This example is somewhat extreme and assumes great ignorance on the part of the scientist, nevertheless, a less obvious nuance could easily confound results and not be found. In short, forgoing theory and focusing on data alone presents two major downfalls. First, it would create a lack of focus and specificity in many fields of science, as the data would dicate research rather than the scientist. Additionally, it is important to consider social and cultural context, instead of relying fully on data, as the former two inform many patterns found throughout the world.