Has scientific method become obsolete?

An article in Wired by Chris Anderson argues that it is:

The scientific method is built around testable hypotheses. These models, for the most part, are systems visualized in the minds of scientists. The models are then tested, and experiments confirm or falsify theoretical models of how the world works. This is the way science has worked for hundreds of years.

Scientists are trained to recognize that correlation is not causation, that no conclusions should be drawn simply on the basis of correlation between X and Y (it could just be a coincidence). Instead, you must understand the underlying mechanisms that connect the two. Once you have a model, you can connect the data sets with confidence. Data without a model is just noise.

But faced with massive data, this approach to science — hypothesize, model, test — is becoming obsolete.

There is now a better way. Petabytes allow us to say: “Correlation is enough.” We can stop looking for models. We can analyze the data without hypotheses about what it might show. We can throw the numbers into the biggest computing clusters the world has ever seen and let statistical algorithms find patterns where science cannot.

Learning to use a “computer” of this scale may be challenging. But the opportunity is great: The new availability of huge amounts of data, along with the statistical tools to crunch these numbers, offers a whole new way of understanding the world. Correlation supersedes causation, and science can advance even without coherent models, unified theories, or really any mechanistic explanation at all.

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

There are several other articles too in the same issue about areas where petabytes of data are the norm — crop predictions, monitoring epidemics, visualization of big data and so on.

However, I still do not see this kind of “science without models” succeeding in all areas of science; from the examples that are discussed, I see that this type of methodology might be very useful in cases where there are far too many parameters, and most of them are not controllable.

At a more fundamental level, in spite of what Chris Anderson has to say, science is about explanations, coherent models and understanding.  In my opinion, all of what Anderson shows is that, if you have enough data, you can develop technologies without having a clear handle on the underlying science; however, it is wrong to call these technologies science, and argue that you can do science without coherent models or mechanistic explanations.



One Response to “Has scientific method become obsolete?”

  1. Update on scientific methodology obsoleteness « Entertaining Research Says:

    […] is becoming obsolete with the availability of large chunks of data? In that post, I conceded that it might be possible to develop some technologies without recourse to the underlying science: At a more fundamental level, in spite of what Chris Anderson has to say, science is about […]

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