Computing Community Consortium Blog

The goal of the Computing Community Consortium (CCC) is to catalyze the computing research community to debate longer range, more audacious research challenges; to build consensus around research visions; to evolve the most promising visions toward clearly defined initiatives; and to work with the funding organizations to move challenges and visions toward funding initiatives. The purpose of this blog is to provide a more immediate, online mechanism for dissemination of visioning concepts and community discussion/debate about them.

Computational Biology and “Dusting Off the Turing Test”

April 15th, 2012 / in big science, research horizons, Research News / by Erwin Gianchandani

A series of spheres with two-dimensional patterns generated by computer simulation shows that Turing's reaction-diffusion model may be the basis for skin patterning in animals. A modulation of one parameter value in a reaction-diffusion-based model causes the pattern to change gradually from spots to labyrinths, with the range encompassing the diversity of patterns seen on animal skin [image courtesy Seita Miyazawa, Osaka University, via Science/AAAS].This week’s Science magazine features a special section on computational biology:

Today, the availability of vast quantities of new data, together with striking advances in computing power, is promising to give us new insights into the mechanisms of life. This special section … highlights recent advances and outstanding challenges.

Such a section would be interesting by itself. But there’s one particular perspective — “Dusting Off the Turing Test” (subscription required) — that stands out.

In the introduction to the special section, the editors of Science reference Turing:

A discussion of computational biology has to start with a pioneer of the field, Alan Turing, especially in this centennial year of his birth. He introduced us to the digital computer and proposed that much biology could be described by mathematical equations — the number of spirals in a sunflower is a Fibonacci number and pattern formation in animal skins can be described by a reaction diffusion model. Turing lacked the data and the computing power to substantiate his models.

But as Robert French writes in the perspective, “two revolutionary advances in information technology” — the ready availability of vast amounts of data and the advent of sophisticated techniques for collecting, organizing, and processing this rich collection of data — “may bring the Turing test out of retirement” (following the link):

…Two deep questions for AI arise from this new technology. The first is whether this wealth of data, appropriately processed, could be used by a machine to pass an unrestricted Turing test. The second question, first asked by Turing, is whether a machine that had passed the Turing test using this technology would necessarily be intelligent.


Suppose, for a moment, that all the words you have ever spoken, heard, written, or read, as well as all the visual scenes and all the sounds you have ever experienced, were recorded and accessible, along with similar data for hundreds of thousands, even millions, of other people. Ultimately, tactile, and olfactory sensors could also be added to complete this record of sensory experience over time. Researchers at the cutting edge of today’s computer industry think that this kind of life-experience recording will become commonplace in the not-too-distant future…


Assume also that the software exists to catalog, analyze, correlate, and cross-link everything in this sea of data. These data and the capacity to analyze them appropriately could allow a machine to answer heretofore computer-unanswerable questions that tap into facts derived from our embodiment or from our subcognitive associative networks, like the finger experiment that began this article or like asking native English speakers whether the neologism “Flugblogs” would be a better name for a start-up computer company or for air-filled bags that you tie on your feet for walking across swamps… By extension, if a complete record of the sensory input that produced your own subcognitive network over your lifetime were available to a machine, is it so far-fetched to think that the machine might be able to use that data to construct a cognitive and subcognitive network similar to your own? Similar enough, that is, to pass the Turing test…


From Dusting Off the Turing Test, by Robert M. French, Science 13 April 2012: 336 (6078), 164-165. [DOI:10.1126/science.1218350]. Reprinted with permission from AAAS.

To learn more, check out the special issue on computational biology, as well as French’s perspective (subscription required) — and share your thoughts below.

(Contributed by Erwin Gianchandani, CCC Director)

Computational Biology and “Dusting Off the Turing Test”

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