Title 2 – TOK Essay May 2017 KQ 7: Are we moving towards “ End of Theory” with the Flood of Facts and Deluge of Data ?



Unlike in past, when Systematic data was scarce, Big Data is getting bigger and computing power is getting cheaper by the minute. In our present world massive amounts of data and applied mathematics are replacing every other tool and every other theory of human behavior, from linguistics to sociology. The hypothesize, model, test approach to science is becoming obsolete and is influencing the research practices of corporations, states, journalists and academics.

“The idea being that the data shadows and information trails of people, machines, commodities and even nature can reveal secrets to us that we now have the power and prowess to uncover.In other words, we no longer need to speculate and hypothesise; we simply need to let machines lead us to the patterns, trends, and relationships in social, economic, political, and environmental relationships.”

In physics Newtonian models were crude approximations of the truth and similarly in Biology the Mendelian process have turned out to be an even greater simplification of reality than Newton’s laws. The discovery of gene-protein interactions and other aspects of epigenetics has challenged the view of DNA as destiny and even introduced evidence that environment can influence inheritable traits, something once considered a genetic impossibility. The more we learn in any area of Knowing , in Evolutionary Biology for example, the further we find ourselves from a model that can explain it.

“Another example of this is the shotgun gene sequencing by J. Craig Venter. Enabled by high-speed sequencers and supercomputers that statistically analyze the data they produce, Venter went from sequencing individual organisms to sequencing entire ecosystems. In 2003, he started sequencing much of the ocean, retracing the voyage of Captain Cook. And in 2005 he started sequencing the air. In the process, he discovered thousands of previously unknown species of bacteria and other life-forms.”

“There’s no reason to cling to our old ways. It’s time to ask: What can science learn from Google?”

How so ever , the lure of Big Data to get all ideas from pattern mining can give us false patterns and interpretations that may be , forget wrong, very ridiculous. “No empirical observation is ever useful as a direct measure of a future observation,” Bar-Yam asserts. “It is only through generalization motivated by some form of model/theory that we can use past information to address future circumstances. Good science does not magically emerge from massive databases; it requires extracting the valuable information from the worthless and Big Data alone doesn’t discriminate between the two very well. “