This NRA seeks empirical economic research projects, historical analog research, concepts for
encouraging further economic activity in space, and unique stimulatory activities that promote
novel private/commercial uses of space, new private/commercial space opportunities, and
emerging private/commercial capabilities in suborbital, orbital or deep space environments that
enable discoveries, development and applications from these environments.
Specific topics of interest include:
Historical Economic Studies in the following areas:
Economic history of NASA programs;
Long term historical impact of the space program;
Economic and business histories of American private sector space enterprises (including companies, societies, and projects);
Economic histories of historical analog activities for space exploration (including detailed investigations into the financing of historical expeditions, settlements, and transportation infrastructure projects).
Current and Near-Term Trends, Analyses and Concepts for accelerating American space development, in the following areas:
Utilizing market mechanisms, private sector partnerships, and expanding markets to serve non-traditional commercial entities;
Promoting broader uses of space for public and/or economic benefit, including job creation and/or workforce development, and maintaining American leadership in the global space marketplace;
Encouraging engagement on space activities from citizen makers, crowd-funders, citizen explorers, and participation of innovators from non-traditional sectors that can have a transformative effect on future private/commercial space developments;
Identifying and evaluating economic applications of space systems design to earth-scale economic analysis, including integrated modeling of globalized economic systems and earth systems science;
Examining competitive stresses, potentials for public benefit, and issues affecting NASA or the nation in the commercial space arena;
Monitoring, investigating and reporting on opportunities enabled by the rapidly growing national and international entrepreneurial space communities;
Assessing the adequacy of economic assessment and evaluation tools and methods for space architectures;
Conducting case studies of space development projects that can be used to inform NASA on the opportunities and impediments to economic development in space.
Economics, Systems Analysis, and Projections, in orbital and deep space development; lunar development, asteroid development, and Mars development.
Upon testing, the system developed by Bartlett managed—in real time—to identify 20 of the 46 facial movements described in the FACS, according to a March report by Bartlett in Current Biology. And, even more impressive, the system not only identifies, but distinguishes authentic expressions from false expressions with an accuracy rate of 85 percent, at least in laboratory settings where the visual conditions are held constant. Humans weren’t nearly as skilled, logging an accuracy rate of about 55 percent.
Yes, Bartlett incorporated a lie detector into the facial recognition technology. This technology promises to catch in the act anyone who tries to fake a given emotion or feeling. Facial recognition is evolving into emotional recognition, but computers—not just people—are the ones deciding what’s real. ( If we add voice detection to face recognition, we end up with a complete lie detection package.)
…So we can begin to imagine a near future in which we’re equipped with glasses that not only recognize faces and voices, but also truths and lies—a scenario that would provoke a revolution in human interaction. It would also constitute a serious limitation on the individual’s autonomy.
Do you ever say “Rats!” after making a mistake? It now has a whole new meaning:
They [scientists] developed a task called Restaurant Row, in which rats decided how long they were willing to wait for different foods during a 60-minute run.
“It’s like waiting in line at the restaurant,” Prof Redish. “If the line is too long at the Chinese restaurant, then you give up and go to the Indian restaurant across the street.”
The rats waited longer for their preferred flavours, meaning the researchers could determine good and bad food options.
Occasionally the rats decided not to wait for a good option and moved on, only to find themselves facing a bad option – the scientists called this a regret-inducing situation.
In these cases the rats often paused and looked back at the reward they had passed over.
They also made changes in their subsequent decisions, being more likely to wait at the next zone and rushing to eat the reward that followed. The scientists say such behaviour is consistent with the expression of regret.
When experiments were carried out where the rats encountered bad options without making incorrect decisions, such behaviour was not present.
A programme that convinced humans that it was a 13-year-old boy has become the first computer ever to pass the Turing Test. The test — which requires that computers are indistinguishable from humans — is considered a landmark in the development of artificial intelligence, but academics have warned that the technology could be used for cybercrime.
…Eugene Goostman, a computer programme made by a team based in Russia, succeeded in a test conducted at the Royal Society in London. It convinced 33 per cent of the judges that it was human, said academics at the University of Reading, which organised the test.
It is thought to be the first computer to pass the iconic test. Though there have claims other programmes have successes, those included set topics or question in advance.
A version of the computer programme, which was created in 2001, is hosted online for anyone talk to. (“I feel about beating the turing test in quite convenient way. Nothing original,” said Goostman, when asked how he felt after his success.)
The computer programme claims to be a 13-year-old boy from Odessa in Ukraine.
[When] computers acquire the necessary capabilities…speeded-up data processing and interpretation will be necessary if professional services are to be rendered with any adequacy. Once the computers are in operation, the need for additional professional people may be only moderate…
There will be a small, almost separate, society of people in rapport with the advanced computers. These cyberneticians will have established a relationship with their machines that cannot be shared with the average man any more than the average man today can understand the problems of molecular biology, nuclear physics, or neuropsychiatry. Indeed, many scholars will not have the capacity to share their knowledge or feeling about this new man-machine relationship. Those with the talent for the work probably will have to develop it from childhood and will be trained as intensively as the classical ballerina.
Michael then discusses what will happen to those people who cannot work productively with the machines. Some will still work in person-to-person interactions, but the others will end up in government-designed public tasks and work short hours and subsist on the public dole. He also considers the possibility of sending some of these individuals to poorer countries where automation is not so far advanced.
Economics assumes that people are rational, self-interested, lightning fast calculators. Obviously a bad assumption as we are constantly told. Chimps, on the other hand, are rational, self-interested, lightning fast calculators. That is the surprising conclusion to a great paper by Colin Camerer and co-authors. Camerer had chimps play versions of the matching pennies game also called the cat and mouse game. In the cat and mouse game each player can go left or go right. The cat wins when cat and mouse choose the same strategy. The mouse wins when they choose different strategies. In the simple version the best strategy is 50:50, toss a coin. When the payoffs change, however, the optimal strategies still involve randomization but they change in surprising and nonobvious ways.
Chimps play the cat and mouse game very well. First, the chimps converge on the Nash Equilibrium strategies. In one set of games the Nash equilibrium strategies had randomization frequencies of .5, .75 and .8 and the chimps played .5, .73 and .79. Second, when payoffs change the chimps adapt their strategies very quickly simply by observation of outcomes.
Camerer et al. also tested humans in similar games and they found that humans often deviate from NE play and they adjust their strategies more slowly when payoffs change, i.e. they learn more slowly! The only thing that Camerer didn’t do was to play humans against chimps in the same game. That would have been awesome!
If you want to understand how chimps are able to play these games so well check out this video. When you see what this chimp is doing you will be amazed!
A Hong Kong VC fund has just appointed an algorithm to its board.
Deep Knowledge Ventures, a firm that focuses on age-related disease drugs and regenerative medicine projects, says the program, called VITAL, can make investment recommendations about life sciences firms by poring over large amounts of data.
Just like other members of the board, the algorithm gets to vote on whether the firm makes an investment in a specific company or not. The program will be the sixth member of DKV’s board.
Cap and trade is going nowhere at the federal level but the California program is large and expanding and the CA program allows for properly monitored and regulated offsets to be purchased from anywhere in the United States. As a result, a price on carbon is being established nationally. As the NYTimes indicates in a very good article, once a market and a price have been established, contentious politics turns into mutually beneficial economics.
Experts who support cap and trade contend that a market mechanism can reach more deeply into the economy than any other approach, changing the behavior even of people and companies that might not necessarily care about global warming.
The Wisconsin dairymen perhaps serve as an example of that.
Even as the methane-powered generator roared on his property, John T. Pagel said he was not convinced that the climatic changes happening in the United States were a result of human emissions. He suspects they might be part of a natural cycle. But with Californians dangling cash in exchange for his willingness to cut emissions, he jumped at the chance to build his digester.
“We are doing exactly what they asked us to do to get paid to reduce carbon,” Mr. Pagel said. “If somebody else believes in it enough to put up the money, that’s all I need to know.”
In both games and movies the production of visuals is very expensive, and the people responsible for creating those visuals hold sway in proportion to their share of the budget.
I hope I won’t come off as unduly cynical if I say that such people (or, barring that, their paymasters) are looking for the biggest possible bang for the buck. And it is much easier and cheaper to take the existing visual environment and degrade it than it is to create a new vision of the future from whole cloth. That’s why New York keeps getting destroyed in movies: it’s relatively easy to take an iconic structure like the Empire State Building or the Statue of Liberty and knock it over than it is to design a future environment from scratch. A few weeks ago I think I actually groaned out loud when I was watching OBLIVION and saw the wrecked Statue of Liberty sticking out of the ground. The same movie makes repeated use of a degraded version of the Empire State Building’s observation deck. If you view that in strictly economic terms–which is how studio executives think–this is an example of leveraging a set of expensive and carefully thought-out design decisions that were made in 1930 by the ESB’s architects and using them to create a compelling visual environment, for minimal budget, of a future world.
As a counter-example, you might look at AVATAR, in which they actually did go to the trouble of creating a new planet from whole cloth. This was far more creative and visually interesting than putting dirt on the Empire State Building, but it was also quite expensive, and it was a project that very few people are capable of attempting.
…That [dystopian] environment also works well with movie stars, who make a fine impression in those surroundings and the inevitable plot complications that arise from them. Again, the AVATAR counter-example is instructive. The world was so fascinating and vivid that it tended to draw attention away from the stars.
Thanks for posting the Joseph Stiglitz dissertation. It’s always great to see the dissertations of Nobel winners.
For a future post, I thought a good topic might be “best dissertations ever” across fields. Obviously, you’ll know most about economics (assume Nash and Arrow are contenders here?), but I wonder about physics, biology, chemistry, history, etc. Not sure what an English dissertation looks like except in writing (a novel? collection of short stories?), but them, too. Would make for an interesting comments section.
And thanks for the never ending stream of great posts across the years,
In economics Michael Spence on job market signaling comes to mind, as does Frank Knight’s Risk, Uncertainty, and Profit. (Paul Samuelson’s renowned dissertation was mostly a wrong turn for mathematical economics, even though it got the ball rolling.) In English there is Harold Bloom’s doctoral dissertation on Shelley and surely much more. Elsewhere, Marie Curie did something on “radio-active substances” and Jane Goodall covered the chimpanzee. There is Claude Shannon on information, Max Weber on the Protestant Ethic, and Wittgenstein’s Tractatus. How about Gauss and Turing? Might de Broglie come in first overall?
I’ll say no to Marx’s “The Difference Between the Democritean and Epicurean Philosophy of Nature.” But how about some of those Russian mathematicians in the mid to late 20th century? They came up with their key contributions quite early in life and I suspect some of those were in their doctoral dissertations.
At RAND in 1954, Armen A. Alchian conducted the world’s first event study to infer the fissile fuel material used in the manufacturing of the newly-developed hydrogen bomb. Successfully identifying lithium as the fissile fuel using only publicly available financial data, the paper was seen as a threat to national security and was immediately confiscated and destroyed. The bomb’s construction being secret at the time but having since been partially declassified, the nuclear tests of the early 1950s provide an opportunity to observe market efficiency through the dissemination of private information as it becomes public. I replicate Alchian’s event study of capital market reactions to the Operation Castle series of nuclear detonations in the Marshall Islands, beginning with the Bravo shot on March 1, 1954 at Bikini Atoll which remains the largest nuclear detonation in US history, confirming Alchian’s results. The Operation Castle tests pioneered the use of lithium deuteride dry fuel which paved the way for the development of high yield nuclear weapons deliverable by aircraft. I find significant upward movement in the price of Lithium Corp. relative to the other corporations and to DJIA in March 1954; within three weeks of Castle Bravo the stock was up 48% before settling down to a monthly return of 28% despite secrecy, scientific uncertainty, and public confusion surrounding the test; the company saw a return of 461% for the year.
That is the subtitle of a new paper (pdf) by and George J. Borjas and Kirk B. Doran, the abstract is this:
Knowledge generation is key to economic growth, and scientific prizes are designed to encourage it. But how does winning a prestigious prize affect future output? We compare the productivity of Fields medalists (winners of the top mathematics prize) to that of similarly brilliant contenders. The two groups have similar publication rates until the award year, after which the winners’ productivity declines. The medalists begin to “play the field,” studying unfamiliar topics at the expense of writing papers. It appears that tournaments can have large post-prize effects on the effort allocation of knowledge producers.
On the other hand, his findings argue against the need to create strong incentives to succeed. If some people are genetically oriented toward success, then they do not need lower tax rates to spur them on. Such people would be expected to succeed regardless. The ideal society implicit in Clark’s view is one in which the role of government is to ameliorate, rather than attempt to fix, the unequal distribution of incomes. As Clark puts it,
“If social position is largely a product of the blind inheritance of talent, combined with a dose of pure chance, why would we want to multiply the rewards to the lottery winners? Nordic societies seem to offer a good model of how to minimize the disparities in life outcomes stemming from inherited social position without major economic costs. (page 15)”