Is There Intelligent Life Out There?

Source: Quanta Magazine, Feb 2016

As future telescopes widen the survey of Earth-like worlds, it’s only a matter of time before a potential biosignature gas is detected in a faraway sky. It will look like the discovery of all time: evidence that we are not alone. But how will we know for sure?

At a 2013 symposium, Seager presented a revised version of the Drake equation, Frank Drake’s famous 1961 formula for gauging the odds that SETI would succeed. Whereas the Drake equation multiplied a string of mostly unknown factors to estimate the number of radio-broadcasting civilizations in the galaxy, Seager’s equation estimates the number of planets with detectable biosignature gases. With the modern capacity to look for any life regardless of whether it’s intellectually capable of beaming messages into space, the calculation of our chances of success no longer depends on uncertainties like the rareness of intelligence as an evolutionary outcome or the galactic popularity of radio technology.

Scheduled to speak last at the symposium, Seager set a light-hearted tone for the after party. “I put it all in our favor,” she said, positing that life has a 100 percent chance of arising on Earth-like planets, and that half of these biospheres will produce detectable biosignature gases — another uncertainty in her equation. Crunching these wildly optimistic numbers yielded the prediction that two signs of alien life would be found in the next decade.

A Flowchart on Attending Tae-kwon-do classes :)

From my daughter, Feb 2016

Domain-Specific Creativity

Source: Creativity Post, Feb 2016

One of the big questions in creativity research and theory is the degree to which the skills that underlie creativity vary by domains.

Is there something analogous to the g of intelligence — call it c — that is predictive of creative performance across most domains? Can many of the creative-thinking skills that might help someone design a creative advertising campaign also be employed in helping that person write a creative sonnet, find a creative resolution to a scheduling conflict, develop a creative new approach to an engineering problem, choreograph a creative dance routine, and devise a creative scientific theory?

Or, conversely, are the skills that underlie creative performance in different domains largely distinct and applicable only in their respective domains?

The question of domain generality or specificity is ultimately one of transfer. Whenever something previously learned in one context is applied successfully in a different context, transfer has occurred.

The difference in the contexts may be relatively large or relatively small, with transfer much more likely the more similar the situations (Woolfolk, 2010). Distinctions have been made between “low-road trans- fer” (“the spontaneous, automatic transfer of highly practiced skills, with little need for reflective thinking”; Salomon & Perkins, 1989, p. 118) and the much more difficult “high-road transfer” (which involves consciously applying knowledge or skill learned in a different context).

most transfer occurs within contexts that are quite similar. Research has suggested that transfer across domains is both difficult to achieve and relatively rare (Willingham, 2002, 2007).

The theory that creativity is domain-general therefore predicts positive correlations among the levels of creativity exhibited by individuals in different domains. Domain specificity predicts the opposite.

Baer (1996) showed that when creativity training is targeted at improving divergent thinking skills in a particular domain (or even a particular sub-domain), it is creativity in that area alone that shows an increase in subsequent testing. Creativity ratings on tasks in other domains or subdomains were not affected by domain-specific creativity training.

The goal of most creativity trainers and teachers is to boost creative thinking skills in many areas, not just in a single domain.

If creativity is domain-specific, as I have argued, then creativity assessment must also be domain-specific. If no domain-general creativity-relevant skills or other attri- butes exist, then there are no domain-general creativity-relevant skills or other attri- butes to measure. One could assess domain-specific skills that might contribute to creative performance in one (or some) domain(s), but any measure of creativity would need to state for what domains it claims to be a valid measure.

Creativity assessment has often assumed domain generality. By far, the most common tests of creativity have been divergent thinking tests, and the most widely used divergent thinking tests are the torrance tests of creative thinking (TTCT), which come in two forms, figural and verbal, although both are used as general measures of creativity (Kaufman, Plucker et al., 2008b; Torrance & Presbury, 1984).

… Torrance himself offered showing that figural and verbal divergent thinking scores are not correlated, and are therefore measuring two essentially unrelated sets of skills.

Both the verbal and the figural tests are commonly used, both by researchers and by school systems, as general measures of creative potential. But they are almost completely orthogonal measures—they can’t both be measuring the same thing if they yield totally different and uncorrelated scores—so they cannot be measures of domain- general creativity. They can, at most, be measures of creativity in their respective domains. 

Domain specificity suggests that we will need many theories of creativity, not a single grand unifying theory.

The kinds and degrees of expertise likely to promote creativity in a domain will vary greatly across domains. The same is true of all of the general ideas commonly proposed for skills or other attributes important to creativity.

They vary by domain (The theory that creativity is domain-specific is itself a kind of meta-theory. It can help guide the search for specific theories in different domains—mostly by showing the need for such separate theories rather than a grand, domain-general theory—but by itself it does not provide a theory of how creativity works in any given domain. 

Domain-specific theories of creativity limit the range of creations and creative processes that are presumed to have some underlying unity. 

On Marvin Minsky’s Remarkable Imagination

Source: Medium, Jan 2016

There was a great contradiction about Marvin Minsky. As one of the creators of artificial intelligence (with John McCarthy), he believed as early as the 1950s that computers would have human-like cognition. But Marvin himself was an example of an intelligence so bountiful, unpredictable and sublime that not even a million Singularities could conceivably produce a machine with a mind to match his. At the least, it is beyond my imagination to conceive of that happening.

He questioned everything, and his observations were quirky, innovative, and made such perfect sense that you wonder why no one else had thought of them. After a couple of hours with him, your own vision of the world was altered.

Only years later did I realize that his everyday Minsky-ness imparted a basic lesson:

if you saw the world the way everybody else did, how smart could you really be?

But maybe Marvin could imagine it. His imagination respected no borders.

Marvin Minsky: Farewell from Stephen Wolfram

Source: Stephen Wolfram blog, Jan 2016

The Marvin that I knew was a wonderful mixture of serious and quirky. About almost any subject he’d have something to say, most often quite unusual. Sometimes it’d be really interesting; sometimes it’d just be unusual. I’m reminded of a time in the early 1980s when I was visiting Boston and subletting an apartment from Marvin’s daughter Margaret (who was in Japan at the time). Margaret had a large and elaborate collection of plants, and one day I noticed that some of them had developed nasty-looking spots on their leaves.

Being no expert on such things (and without the web to look anything up!), I called Marvin to ask what to do. What ensued was a long discussion about the possibility of developing microrobots that could chase mealybugs away. Fascinating though it was, at the end of it I still had to ask, “But what should I actually do about Margaret’s plants?” Marvin replied, “Oh, I guess you’d better talk to my wife.”

For many decades, Marvin was perhaps the world’s greatest energy source for artificial intelligence research. He was a fount of ideas, which he fed to his long sequence of students at MIT. And though the details changed, he always kept true to his goal of figuring out how thinking works, and how to make machines do it.

Once someone told me that Marvin could give a talk about almost anything, but if one wanted it to be good, one should ask him an interesting question just before he started, and then that’d be what he would talk about. I realized this was how to handle conversations with Marvin too: bring up a topic and then he could be counted on to say something unusal and often interesting about it.

…  always a certain warmth to Marvin. He liked and supported people; he connected with all sorts of interesting people; he enjoyed telling nice stories about people. His house always seemed to buzz with activity, even as, over the years, it piled up with stuff to the point where the only free space was a tiny part of a kitchen table.

Marvin also had a great love of ideas. Ones that seemed important. Ones that were strange and unusual. But I think in the end Marvin’s greatest pleasure was in connecting ideas with people. He was a hacker of ideas, but I think the ideas became meaningful to him when he used them as a way to connect with people.

Magic Lantern Festival (London) for Chinese New Year 2016

Source: Mashable, Feb 2016
<see source for more pictures>

 

 

 

Magic Lantern Festival for Chinese New Year ’16 (London)

Source: Buzzfeed, Feb 2016
<see source for more pictures-slider for before/during night-time perspectives>