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"At the cosmic dinner party, intelligence is the loudest thing in the room."




Through the study of animal communication, my colleagues and I have developed a new kind of detector, a “communication intelligence” filter, to determine whether a signal from space is from a technologically advanced civilization or not. Most previous SETI (Search for Extraterrestrial Intelligence) efforts have looked for radio transmissions with a narrow band of frequencies or for optical signals that blink very rapidly. From what we know about astrophysics, such transmissions would be clearly artificial, and their discovery would indicate technology capable of transmitting a signal over interstellar distances. SETI efforts generally throw away wideband radio signals and slower optical pulses, whose provenance is less obvious. Although those signals might well be from intelligent beings, they might also originate in natural sources of radio waves, such as interstellar gas clouds, and we have lacked a good way to tell the difference.


One aspect of human linguistics that emerged from early statistical studies of letters, words, and phonemes is known as Zipf’s Law, after the Harvard University linguist George Zipf. In English text, there are more e’s than t’s, more t’s than a’s, and so on, down to the least frequent letter, “q.” If one lists the letters from “e” to “q” in descending order of frequency and plots their frequencies on a log-log graph, one can fit the values with a 45-degree line—that is, with a line with a slope of –1. If one does the same thing with text made up of Chinese characters, one also gets a –1 slope. And the same is true with the letters, words, or phonemes of a conversation in Japanese, German, Hindi, and dozens of other languages. Baby babbling does not obey Zipf’s Law. Its slope is less than –1 because the sounds spill out nearly at random. But as children learn their language, the slope gradually tilts up and reaches –1 by about the age of 24 months.


Most linguists used to suppose that Zipf’s Law was a characteristic of human languages only. So we were quite excited to find that, upon plotting the frequency of occurrence of adult bottlenose-dolphin whistles, that they, too, obeyed Zipf’s Law! Later, when two baby bottlenose dolphins were born at Marine World in California, we recorded their infant whistles and discovered that they had the same Zipf’s Law slope as baby human babbling. Thus baby dolphins babble their whistles and have to learn their communication system in a way not dissimilar from the way baby humans learn their languages. By the time the dolphins reached the age of 12 months, the frequency of occurrence distribution of their whistles had reached a –1 slope, as well.


As a test of our approach’s ability to separate astrophysics from an intelligent signal, we turned to an example from radio astronomy. When stellar pulsars were discovered by astronomers Jocelyn Bell Burnell and Antony Hewish in 1967, they were dubbed “LGMs” for “little green men.” Since these radio sources pulsed so regularly, some scientists initially speculated that they could be the beacons of very advanced extraterrestrials. So we re-analyzed the pulses from the Vela Pulsar with the help of Simon Johnston of the Australia Telescope National Facility and obtained a Zipf slope for the pulsar signals of about –0.3. This is inconsistent with any language as we know it. In addition, we found little or no conditional probabilistic structure within the pulsar signals. And indeed pulsars are now known to be natural remnants of stellar supernovae. Information theory could thus easily distinguish between a putative intelligent signal and a natural source.



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