In titling his new book, Nassim Nicholas Taleb has coined a new word: “antifragile.” I was not surprised that such a word did not previously exist, because, like most people, I had thought that the opposite of “fragile” was “robust.” But Taleb argues that something that is robust merely tolerates adverse or unexpected conditions, whereas something that is antifragile thrives—its performance actually improves. He uses the example of a mailed package labeled “Fragile, do not shake.” The opposite would say, “Antifragile, please shake.”
Taleb’s book mostly considers the notions of fragility and antifragility in biological, medical, economic, and political systems. Do we have any electronic systems that are antifragile?
Certainly, we engineers have done a superb job in designing robust systems that despite their burgeoning complexity have much longer life spans. The Internet is a leading example, having survived mostly intact for about three decades now (in the face of periodic predictions of its imminent collapse), with its robust flow control, alternative routing, and error control.
Evolution improves biological systems through survival of the fittest. Is there is a similar improvement in the performance of electronic systems? Perhaps. But I don’t think this is the same as the idea of designing a system that will actually work better when it experiences unexpected or random conditions.
There are, of course, power supplies that harvest energy from random vibrations, but perhaps that is too trivial an example. The closest examples I can find of antifragility in an engineered system involve multipath phenomena.
For the first half of the last century, multipath phenomena were harmful. In radio frequency transmission they caused signal fading as different paths became variously additive or destructive. In wire-line transmission there were similar effects due to the nonuniform delay of signal frequency components, resulting in intersymbol interference and degraded speeds.
These multipath impairments were eventually alleviated through diversity and adaptive signal processing. Still, I think of these adaptive systems as robust, rather than truly antifragile. Perhaps, though, we crossed the line to antifragile with the advent of multiple-input/multiple-output (MIMO) systems, in which we deliberately send multiple copies of the signal from different antennas, hoping there will be multipath phenomena that with processing can be used to enhance system performance. MIMO [PDF] is now commonly used in IEEE 802.11n (Wi-Fi), and elsewhere.
What I find fascinating now is the application of similar techniques in the new field of computational photography. In any scene, light arriving at our eyes or on a camera lens has come from multiple reflections, refractions, absorptions, and so forth. An ordinary camera captures an instantaneous superposition of all these arriving rays but loses any information about the directionality of rays, relative time delays, and individual amplitudes.
The first camera to record more of this information, the Lytro, is now a commercial product. Using a multifaceted lens and taking advantage of the ever-growing sensor capacity, the Lytro captures the directionality of light rays as they arrive. I am reminded of the early work in computer graphics that created lifelike representations using ray tracing, in which light rays—with all their reflections and refractions—are traced from a source to a viewer and computed to produce the image. With the Lytro we have the inverse problem: Given the rays, can we compute the scene? The Lytro software does exactly that and permits the user to choose a focus or move the perspective subsequent to image capture.
Recent experimental work at MIT carries this much further. Using a femtosecond laser to send extremely short pulses of light and repeating many times to gather enough signal strength, the system records times of arrival and relative amplitudes. The amazing claim is that it’s possible to see around corners with this technology. Some of the arriving light pulses will be reflected from surfaces that aren’t within the direct view of the detector. The more bounces, the better. Multipath is good; bring it on!
I invite the reader to think of other systems that might thrive under unexpected or adverse conditions. It’s a thought-provoking challenge.