Reaction to the Future, part infinity

Alvin Toffler, futurist and author of Future Shock and The Third Wave, died recently at the age of 87. Future Shock and The Third Wave [1] were favorite books of mine when I was in High School, and contains a lot of unexplored themes. The book's main argument was that rapid technological change is accompanied by a number of negative social effects, including reactionary political movements and collective psychocultural responses. As the rate and scope of technological change has increased [2], this shock to human society has become more acute [3]. The Thrid Wave was more directly related to cultural change, and assumed that major observed  transitions in cultural evolution [4] required profound shifts in sociology, economics, and psychology.

We can see this effect in our own society, particularly with respect to the economy of mind. As a cultural trend, more young people are pursuing a life of creative and/or mental productivity [5]. While some of this productivity is tangible (see the contemporary focus on applications of University research),  In particular, there is a strain of austerity thinking [6] that has arisen since 2008 which views intellectual expertise more generally and academic activity more specifically as a superfluous fraud. Since many of these pursuits require public (government) funding and/or provide no immediate tangible return, there is ideological bias at play as well. More generally, future shock can manifest itself as a revolt against modernity.

The blogger Drugmonkey, advancing the Mellon Doctrine (among other types of reactionary thinking) in the realm of biomedical science. 

Don't be a neo-reactionary! Hint: you don't need to appeal to religion to take this point of view.

The legacy of Toffler's ideas have gotten a bit muddled [7], and in exposed one of the problems with futurism: namely, it is hard to discern solid predictions from quasi-religious pronouncements. The unfortunate event of Toffler's death also coincides with the 50th Anniversary of the first episode of Star Trek (circa 1966). Star Trek's prime directive is an interesting detail of the Starfleet Academy rulebook consistent with Toffler's argument. The prime directive is more directly related to cultural evolution, and states that Starfleet cannot interfere in the normal trajectory of a given culture's development [8]. It is not clear how this works in practice, however, since mere cultural contact can change the trajectory of cultural evolution more than simple exposure to various foreign technologies [9]. On the other hand, if they are adopted, the introduction of single tools or cultural practices can have profound effects on a culture's trajectory.

This concept will take a long time to become culturally consistent. How long? Probably much longer than predicted by Gene Roddenbery (creator of Star Trek).

Some people who might argue that Toffler and Roddenbery are simply products of their era (the 20th century, a period of rapid technological change). Their views on the outcomes of change (technological advancement and modern cultural mores) are biased towards a historical positivism. In other words, progressive technological change is inevitable, even if we mediate this path to eventual enlightenment. Yet this view ignores the basic outlines of historical complexity -- that cultural and technological complexity does tend to increase, even if the process is painful, chaotic, and uneven [10].


NOTES:
[1] Toffler, A.   Future Shock. Random House, 1970 AND Toffler, A.   The Third Wave. Bantam Books, 1980.

[2] this is not necessarily equivalent to the rate of innovation, but rather has to do with the dynamics of technology adoption. For those of you who are familiar with early period (pre-2005) Wired magazine, ideological constructions around the term "neo-Luddite" characterizes the cultural aspect of this effect. For more, please see: Katz, J.   Return of the Luddites. Wired, June 1, 1995.

[3] this can be observational (such as noticing the preponderance of payphones in an several-decades old movie) or more profound (such as automation-related job losses).

[4] the major transitions of cultural evolution may or may not result from directional trends in cultural complexity.

[5] AKA The "yuccie" manifesto. For more, please see: Infante, D.   The hipster is dead, and you might not like who comes next. Mashable, June 09, 2015.

[6] Austerity thinking is associated with an obsession with debt which is underlain by a number of cultural and epistemic biases. There are a number of cultural antecedents that stress the connections between debt and morality, while most if not all cultural traditions are ill-equipped to deal with the logic and technical details of modern economics and finance. This latter point (an incompatibility between cultural traditions and advanced technology) was addressed in the book "Technopoly" by Neil Postman. A similar conceptual gap is also seen amongst popular responses to technologies such as genetic modification, which comes into conflict with many traditional cultural themes involving cleanliness and purity.

[7] There is a fascinating political subtext to how Toffler's ideas played out in society, namely his association with Newt Gingrich and anti-neo-luddite politics in the 1990s. Not particularly in line with Toffler's own views, but definitely a study in historical context. For more, please see: Murphy, T. Newt's New-Age Love Gurus. Mother Jones, January 30, 2012.

[8] For one interesting dissent on the optimality of the prime directive, please see: Clint, E.   The Prime Directive: Star Trek’s doctrine of moral laziness. Skeptic Ink blog, November 4, 2012.

[9] This statement is consistent with a process called "trans-cultural diffusion". For more, please see. Albrecht, K.   Trans-cultural diffusion. September 13, 2013.

[10] The essential lesson from the emerging field of cliodynamics. For more, please see: Turchin, P.   Arise 'cliodynamics'. Nature, 454, 34-35 (2008).

Piketty Reviews: the year in review

Thomas Piketty's book "Capital in the Twenty-first Century" became quite the phenomenon this year. Originally published in French, it was translated into English in 2014 and has since elicited a large amount of feedback. I have collected a series of book reviews over the course of this year that provide a bit of perspective on the book. This could either prove to be prophetic, or another "End of History and the Last Man". The diversity of responses presented here suggests that the relationship between inequality and economic growth will become a defining social issue in years to come.

Even at 696 pages and a large number of graphs, it is quite a captivating read. Piketty synthesizes data from multiple sources and arrives at a fundamental set of relationships between concentrations of capital (e.g. inherited wealth) and economic growth (e.g. the diffusion of capital into the broader economy). Based on this intellectual synthesis, Piketty's presents two laws of inequality [1, 2]. These laws are drawn from the cross-national and historical data analyses. In particular, the second law serves as shorthand for the book's main thesis. While people might debate how exactly to define "wealth" and "growth" or how well this framework describes the macroeconomic present, Piketty's book gives us the conceptual tools to discuss these issues more clearly.

Piketty's insight is quite simple: there is a proportional and often unbalanced relationship between wealth and growth that transcends both nation and historical era. When the returns on inherited wealth exceeds income growth generated by resource exploitation, entrepreneurship, or innovation, high degrees of social and economic inequality result (W > G -- see Figure 1). This often occurs when growth is slow or nonexistant, and the rate of return on inherited capital exceeds growth by default. In terms of social relations, the W > G scenario allows for inherited wealth to triumph over social mobility and new wealth creation. By limiting social mobility, a host of related factors act to reinforce income inequality [3]. Yet this relationship does not always hold. For example, historical periods during which opportunities for economic expansion and social mobility exceed the power of inherited wealth (such as the latter half of the 20th century) tend to be characterized by high rates of conventional growth (e.g. increases in GDP). While the power of inherited wealth is curbed by growth, it might also be curbed by taxation policy. In any case, the second half of the 20th century scenario can be formulated as G > W, or growth exceeding wealth.

Figure 1. Extreme inequality, shown in both artistic and symbolic logical form.

Piketty arrives at this conclusion by using historical data. These data suggest that the slow growth and high levels of inequality which characteerize the early 21st century will recapitulate a pattern typical of the 19th century or even the European middle ages. The predominance of rentier behavior amongst the 21st century elite is indeed reminiscent of the medivel era, where the primary source of wealth generation came from rents paid to a landed gentry [4]. While the mode of wealth generating is variable from century to century, the basic tension between inherited versus newly-generated wealth is predicted to govern economic dynamics. And in this context, inequality can inflence a host of societal characteristics, from social stratification to technological innovation [5].

Perhaps these consequences of inequality are simply a consequence of an over-domineering financial industry, which provides massive returns to investment income relative to labor productivity. In this sense, history is more contextual than cyclical. But history can also parallel broadly-stated theoretical predictions. This state of affairs can be compared with the prediction made by Karl Marx with respect to the end of capitalism itself [6]. As capitalism matures (so-called "late stage" capitalism), we can expect most forms of labor to become devalued. While this is not something that Piketty predicts for the future, this devaluation is due to both various resource consolidations promulgated by the owners of capital and a by-product of technological innnovation (particularly automation -- see [7]). Piketty's solution to countering this type of structural inequality is wealth redistribution, which is something America pioneered [8], but is needed on a global scale to avoid the predicted negative consequences of economic growth stagnation [9].

Here is my collection of Piketty reviews

Introducing Piketty:

Galbraith, J.K.   Kapital for the Twenty-first Century? Institute for New Economic Thinking blog, March 31 (2014).

Frankel, J.   Piketty's Fence. Jeffrey Frankel's blog, September 22 (2014).

Yglesias, M.   The Short Guide to Capital in the 21rst Century. Vox blog, April 8 (2014).

Dorman, P.   Piketty for Dummies. EconoSpeak blog, April 26 (2014).

Wolf, M.   "Capital in the Twenty-first Century", by Thomas Piketty. FinancialTimes.com, April 15 (2014).

R.A.   Thomas Piketty's "Capital", summarized in four paragraphs. Economist, May 4 (2014).

Cowen, T. and de Rugy, V.   Why Piketty's Book Is a Bigger Deal in America Than in France. NYTimes The Upshot, April 29 (2014).

Eakin, E.   Capital Man. Chronicle of Higher Education, April 17 (2014).

Broader Economic Implications:
An Interview with Adair Turner: "Which Capitalism for the 21rst Century?". Institute for New Economic Thinking blog, November 12 (2013).

Hutton, W.   Capitalism simply isn't working and here are the reason why. The Guardian, April 12 (2014).

Boucoyannis, D.   Adam Smith is not the antidote to Thomas Piketty. WaPo Monkey Cage blog, April 22 (2014).

Cassidy, J.   Forces of Divergence: is surging inequality endemic to capitalism? The New Yorker, March 31 (2014).

Krugman, P.   Why we're in a New Gilded Age. New York Review of Books, April 10 (2014).

Shenk, T.   Thomas Piketty and Millenial Marxists on the Scourge of Inequality. The Nation, April 14 (2014).

Faux, J.   Thomas Piketty Undermines the Hallowed Tenets of the Capitalist Catechism. The Nation, April 18 (2014).

Rosenberg, P.   Thomas Piketty terrifies Paul Ryan: Behind the right’s desperate, laughable need to destroy an economist. Salon, April 30 (2014).

Ritholtz, B.   Piketty vs John Stuart Mill’s Marketplace of Ideas. The Big Picture blog, May 1 (2014).

Kaminska, I.   Inequality and Hyperinflation. Dizzynomics blog, April 25 (2014).


Criticisms: In May, there was a post on the Financial Times' Money Supply blog that claimed to find flaws in Piketty's data analyses and basic aproach to studying inequality. The following articles are a rebuttal to these claims.

Piketty, T.   Appendix to Chapter 10. Inequality of capital ownership. Addendum: response to FT. May 28 (2014).

Buchanan, M.   Economists, Show your Assumptions. Bloomberg View, May 6 (2014).

Irwin, N.   Everything You Need to Know About Thomas Piketty vs. The Financial Times. NY Times The Upshot, May 30 (2014).

Winship, S.   Financial Times vs. Piketty on US. Smoke, No Fire. Forbes, June 2 (2014).

Return to an Ancien Regime?

So is growth truly over? Or are we transitioning to a new mode of production? Perhaps it is not the nature of growth that guides thinking about this but the existential need for a powerful ruling class. Such a desire for oligarchy mirrors many popular interpretations of Piketty's main thesis, but in a more fatalistic manner. This hidden cultural theme might explain the recent (and disturbing) trend towards neo-reactionary thought amongst certain segments of Western society [10, 11]. So-called neo-reactionary thinking involves a combination of radical libertarianism with dictatorship. In and of itself, this would be a fairly predictable reaction to a period of great social and economic change. Yet this movement even has legions in the technology industry, a social milieu that a) represents the "new" economy and a prime source of future economic growth, and b) represents an industry that could help us overcome the limitations of traditional growth. This might reflect an inability to think innovatively about social and cultural change, or perhaps it shows how inerred we truly are to old ideas.


NOTES:
[1] Galbraith, J.K.   Unpacking the First Fundamental Law. Economist's View blog, May 25 (2014). AND Krussell, P. and Smith, T.   Is Piketty's "Second Law of Capitalism" Fundamental? Vox blog, June 1 (2014).

[2] von Schaik, T.   Piketty's laws with investment replacement and depreciation. Vox blog, July 6 (2014).

[3] Krugman, P.   Piketty Day Notes. Conscience of a Liberal blog, April 16 (2014).

[4] Kaminska, I.   The Tyrrany of Land. Dizzynomics blog, February 5 (2014).

[5] Hanlon, M.   Why has human progress ground to a halt? Aeon Magazine, December 3 (2014).

[6] Jeffries, S.   Karl Marx's guide to the end of capitalism: a primer. The Guardian, October 20 (2008).

[7] Gordon, R.J.   Is U.S. Economic Growth Over? Faltering Innovation Confronts the Six Headwinds. NBER Working Paper No. 18315 (2012).

[8] Geier, K.   Taking Aim at Inequality. Blog of the Century, March 12 (2014) AND Yglesias, M.   If growth is dead, we need radical redistribution. Moneybox blog, October 7 (2013).

[9] Cowen, T.   "Unified Growth Theory" by Oded Galor. Marginal Revolution blog, June 9 (2011) AND Kuznets Curve. Wikipedia. December 30 (2013).

[10] Pein, C.   Mouthbreathing Machiavellians Dream of a Silicon Reich. The Baffler, May 19 (2014).

[11] Brin, D.   "Neo-Reactionaries" drop all pretense: End democracy and bring back lords! Contrary Brin blog, November 26 (2013).

Introducing the Evolution of Inequality Project

The study of income and resource inequality has been the academic topic du jour this year, highlighted by Thomas Piketty's economic history opus [1] and a special issue of Science [2]. There was even a paper on the 1% vs. the 99% of academic publishing [3] which argues that in terms of citations, the rich tend to get richer. But how do these patterns emerge and evolve? Is it a merely a statistical artifact, or a reflection of how complex, hierarchical societies tend to evolve? For example, we might assume that extreme inequality is maladaptive. But upon simulating a range of artificial societies of different population sizes, initial degrees of stratification, and behavioral features, we might find that extreme inequality tends to occur under specific conditions.

This is the motivating factor for my interest in the topic. Unlike many of the more well-versed approaches to the topic, an alternative view of inequality is a cross between statistical distributions, nuanced views of human sociobiology, and the aftermath of social change. While most economists have taken a materialist view of inequality, I feel that evolutionary perspectives would be helpful in teasing out questions of inequality's origins. This might involve data as diverse as historical data, ethnographic data, evolutionary modeling, and behavioral/neurophysiological data. In the end, we will be able to provide a conceptual alternative to the usual discussion at the intersection of behavior, biology, and social change. An inclusive, multidisciplinary approach is a core component of this project.

My research organization (Orthogonal Research) is trying to initiate work on a project called "The Evolution of Value and Inequality". This project is an attempt to understand the emergence of these social inequalities as a set of evolutionary and biobehavioral phenomena. While the argument can be made that an evolutionary perspective might be helpful in understanding unequal allocations of resources, it is sorely lacking in the general discussion. The broadness of the initiative is necessary to make the connection between the pure inferential approach of evolutionary science coherent public policy outcomes. An initial grant application to the Washington Center for Equitable Growth (submitted January 2014) did not get funded, one reason being that the idea needed more conceptual and empirical fleshing out.

So upon doing some more conceptual refinement, I just finished submitting a second version of this proposal to the Institute for New Economic Thinking (INET). While I will not get into the technical details here, the basic idea is to construct adaptive computational models that mimic a social hierarchy (so-called hierarchical network models). Each node of these directed graphs are informed in their behavior by neuroimaging and other physiological sources of data on human behavior.

The project is focused around evolutionary models of social change (social and cultural change), the underlying assumptions of which can be verified by the collection of biobehavioral data (e.g. neuroimaging experiments). The empirical component is meant to test assumptions of individual and social behavior, and serves as an alternative to the rational expectations assumption that dominates much of conventional economics. However, it also refines many of the model-free findings that
characterize behavioral economics [4].

The evolutionary aspects of this work are also quite interesting. Because we are bridging the short-term (behavioral) and the longer-term (social evolution), there are at least three forms of adaptation: a social learning mechanism, a cultural evolutionary form of selection, and a neurophysiological imperative that satisfies various material, social, and existential needs of an individual. This gives us a fitness and selection criterion that is tangentially related to reproductive success. Subsequent evolutionary algorithms and simulations may bear out the evolutionary dynamics of value construction and social stratification.

Another contribution of this project is to link the statistical aspects of inequality with an evolutionary and demographic framework. The oft-referenced phrase the "1%" or the "0.01%" has its roots in an exponential (non-normal) statistical distribution called the power law. Power laws of various size tend to describe observed income distributions in many different types of society. As inequality increases sharply in a single society, or as different degrees of inequality are observed in different contexts, the power law and in conjunction with various stable states can be used as selection criteria.

Schematic of expected results. Both the C and L parameters refer to operations on intra- and bi-level hierarchical networks dynamics, respectively.

As proposed in the first part of this post, the resulting evolutionary algorithms and experimental inquiries provide us with a possibility space for given outcomes. Given a set of initial conditions, we can observe the tendencies of inequality of resource allocation. If there are common outcomes relative to a number of different initial conditions, this could tell us something cross-cultural and fundamental about the nature of inequality. Ultimately, the outcomes of this project could help to identify and predict opportunities to head off crises and as an architecture for achieving sustainable economic growth.

NOTES:
[1] Piketty, T.   Capital in the 21rst Century. Harvard University Press (2014).

[2] Citation for the special issue: Science, 344, May 23 (2014). One article with particular relevance to social evolution is: Pringle, H.    The Ancient Roots of the 1%. Science, 344, 822-825 (2014).

[3] Ioannidis JPA, Boyack KW, Klavans R.   Estimates of the Continuously Publishing Core in the Scientific Workforce. PLoS One, 9(7), e101698. doi:10.1371/journal.pone.0101698 (2014).

[4] Camerer, C.F. and Loewenstein, G.   Behavioral Economics: past, present, future. In "Advances in Behavioral Economics". C.F. Camerer, G. Loewenstein, and M. Rabin eds. Chapter 1. Russell Sage Foundation (2004).

Behavioral Economics Reading List. Russell Sage Foundation blog, March 23 (2012).

Ancien Regimes, Google Grokking, and Starstuff

This post is in two parts, and is cross-posted in part to Tumbld Thoughts. In Part I, I will review a number of papers, blog posts, and articles from my reading queue [1]. This time, I focus more on short threads than scientific papers. In Part II, I will provide supplementary reading to the third episode of the Cosmos reboot.

I. Reading Queue (recent papers, blog posts, and news stories).

1) How Academia and publishing are destroying scientific innovation. King's Review, February 24 (2014).

An interesting interview with Sydney Brenner on the resistance to innovation in academic science. Driven by the nature of publishing and promotion.  Is academic science tailor-made for the most average mind? Kary Mullis and J. Craig Venter might agree with the sentiment. On the other hand, the open-access revolution is predicated on the idea that academic publication (and indeed all of proprietary and pre-internet scientific information dissemination) is a broken system. Whatever that means these days, since everyone in education and academia seems to be a revolutionary.

The "lack of innovation in academia" straw man argument, in graphical form. COURTESY: Macintosh Ad, 1984.

2) Bot and Dolly and the rise of creative robots. Bloomberg Businessweek, March 20 (2014) AND More news is being written by robots than you think. SingularityHub, March 25 (2014).

First article is a profile on the business of "smart" mechatronics for movies. I was really hoping for more, given the title. Like robots that write the news and the rise of so-called creative algorithms (second article). Bot and Dolly were behind the challenging special effects in the movie "Gravity" and the IRIS motion control system. 

IRIS on the set. Or writing a very large-print news article.

3) Why car and energy companies have a hard time experimenting like Google does. Gigaom, January 15 (2014).

This article argues that the profit margins of a given industry determines how likely companies in that sector are to innovate. In other words Google (in the information/internet sector -- high profit margin) is a paragon of innovation, while General Motors or Delta Airlines (in the much less profitable automotive and airline industries, respectively) are not well-known for innovation. So, clearly, being ancien regime vs. being a Google Grokker has nothing to do with it, right?

The whole profit margins argument suffers from what I call a suppression of the perpendicular axis. Perhaps a better alternative hypothesis exists, but is tangential (or perpendicular) to the one being explored and is suppressed by the author's narrative. While the "profit margin by sector/rate of innovation" relationship seems to exist, it is superficial and does not account for variation within industries or even the way profits are acquired (e.g. pharmaceutical companies must innovate to have new sources of profit).

The Everett Rogers view of "getting with the program".

4) Strength of weak signals. McKinsey Quarterly, February (2014).

A play on the "strength of weak ties" idea, this article heeds our attention to weak signals (e.g. valuable information) inherent in the massive amount of data available via internet and through social media. The authors play up the idea that often these cryptic signals are embedded in noise -- and offer multiple ways to marshal this information. This goes beyond the typical filtering app for Facebook.

5) Collective attention in the age of misinformation. arXiv:1403.3344 [cs.SI]. AND The curious nature of sharing cascades. arXiv:1403.4608 [cs.SI].

The first paper looks at the emergence of alternative theories on Facebook. Theories that run counter to the established wisdom of the ancien regime, but are not reasonable by any means. This ranges from fringe theories to full-blown conspiracy theories. As an example, the authors looks at Facebook interactions during a recent Italian election. Unfortunately, unsubstantiated information (including conspiracy theories) spread much like factual information. That is, until someone knocks down the post with reason and facts, which is why we need skeptics to speak up.

A related paper (also using Facebook as a source of data) looks at the nature of resharing cascades (how far-reaching a post or story becomes). Not all information is shared equally, as some posts/stories get far more exposure than others. The nature of resharing is the essential to its longevity. However, the initial degree of exposure (e.g. being shared by people with lots of followers) is key to initiating what will become a long chain of resharing (e.g. cascade). Essentially, mass initial broadcasts have the best change of become long resharing chains -- but this is likely a quasi-stochastic process [2].

A revolutionary HMD? VR according to the Oculus Rift.

6) Jeffries, A.   Will Facebook ruin Oculus? Kickstarter backers voice concerns. The Verge.

Answer: depends on what you mean by "ruin". Such titles are always meant to be provocative, from the question mark to the verb. From the perspecitve of the ancien regime (Barry Ritholtz, Bloomberg News), if there is no return of equity to the initial Kickstarter investors, then it is a scam. However, it is like saying that because someone once gave me a research grant, then they are entitled to a future Nobel Prize or Distinguished Scholar award. Perhaps I shouldn't plant the seed of that idea, or am I too late? And would such an innovation (investing in potential) simply be new wine in old bottles?

Rather, let's suppose that the Google Grokkers who made initial investments in Oculus had a different goal in mind -- essentially "don't be evil" over "Wall Street". A different kind of social contract that focuses on building great things instead of tangible/immediate return on investment, perhaps. But is Facebook's offer of $2 billion a realistic investment in a company that resembles Fakespace (a non-hyped VR company)? If there's one thing that defines Oculus in my mind, it is hype. In fact, if there's one thing that defines Facebook and Kickstarter in my mind, it is also hype. But then there's this from the Prosthetic Knowledge tumblr. Nevertheless, perhaps the "scam" deepens, as Facebook's acquisition of Oculus has become a visual meme.

Perhaps the whole ancien regime vs. Google Grokker distinction is being falsely applied here. Or perhaps some people just want to see this particular ship go down.

7) Comparing miRNA and viroids: highly conserved molecular mechanisms for the transmission of genetic information. Frontiers in Cellular Neuroscience, February 20 (2014).

Sometimes, when the part of the title says "transmission of genetic information", the Lamarkian imagination goes wild [3]. But really, they are talking about RNA and miRNA serving as messengers in complex signaling systems. Their discussion of miRNA is interesting -- while there is amazing diversity in miRNA types and families, their basic structure and function tends to be highly-conserved. This conservation (found in viroids as well as miRNA) is a consequence of an "information transfer mechanism" that emerged in some Eukaryote common ancestor. 

8) How tech became the enemy. SFGate, March 24 (2014).

9) The brutal ageism of tech. New Republic, March 23 (2014).

Who's the good guy and who's the bad guy? In the context of the tech industry, the answer might better suited to a discussion on video game development or the Winklevoss twins. But both the organizational man and counterculture ethos are well-represented in the tech world. This is cross-cut by the more recent phenomenon of the internet billionaire and their supposed lack of social responsibility [4]. And tech leaders who believe odd things about the way societies should be run [5]. I'm not sure if tech populism stems from the counterculture, but it looks like Henry Ford's obsession with social engineering all over again.

Fordlandia, not Silicon Valley. But still, it might all be the same.....

But if you haven't made your fortune by age 35, you should probably give up, at least according to reading #9. At least that's the gist of the ageism in tech argument. Apparently, eternal innovation is only a property of the young, and experience plays no role in the development of cutting-edge tech. People who remember the ancien regime should not try to work with Google Grokkers, as their ideas will simply get in the way [6].

10) The future of brain implants. Wall Street Journal. 

The article by Christof Koch and Gary Marcus in the WSJ (!) surveys the state-of-the-art technology in the area of brain-machine interfaces and implants to mitigate brain disorders and damage. Informative and not too technical, but with a nauseating dash of techno-optimism and Reagan-worship. Is this really the hallmark of a good tech story, or a way to placate the ancien regime?

11) Nonhuman Gamblers: lessons from rodents, primates, and robots. Frontiers in Behavioral Neuroscience, 8, 33 (2014).

A comprehensive, cross-species review of the neural substrate and mechanisms involved in pathological gambling. Also includes computational examples (robot models). The authors also favor methodological integration, which is always a good thing. Definitely a trait of the most astute Google Grokkers.

Rat casinos. For purposes of studying the Neuroscience of addiction.

12) Stable Isotope Analysis of Precipitation Samples Obtained via Crowdsourcing Reveals the Spatiotemporal Evolution of Superstorm Sandy. PLoS One, 9(3), e91117 (2014).

Using stable isotope analysis, the authors were able to better understand the hydrologic and thermodynamic processes behind extra-tropical hurricanes. Notoriously hard to predict, a sufficient understanding can only be gained from a large-scale spatiotemporal analysis. But wait....this analysis (685 samples) was done by the crowd! Google Grokkers at work! An excellent emerging method applied to a very hard-to-predict storm. This might also be useful in gauging the true effect size of anthropogenic climate change.

COURTESY: Figure 1 from Article #12.

[1] To do this, I use the theme of the ancien regime and Google Grokking. The former refers to the landed gentry (e.g. old guard) during the French Revolution, while the latter refers to upstart information technology companies such as Google and Grok (Jeff Hawkins' analytics start-up). Grok is also a science fiction reference, courtesy of Robert Heinlein, and American tech-oriented slang for "passionately liking something".

[2] This principle works for Twitter posts as well: Anderson, M.   Forecasting when hashtags will go viral. IEEE Spectrum, March 27 (2014).

[3] This Technology Review article discusses an older set of studies, but every time a paper involving an "epigenetic" phenomenon of significant consequence (e.g. life-history effects, cognitive effects) comes out, the media speculation is predictable.

[4] On the whole, the tech world has some notable exceptions to this. A recent story about Tim Cook vs. climate change deniers at Apple's annual shareholder meeting is one such example.

[5] For examples, see exhibits A and B. Just so you know that I'm not making this up. But sometimes it is ridiculousness in the name of free publicity.

[6] this section is deeply infused with sarcasm. Is this simply a lack of perspective on the part of young techies and investors, or the consequences of a major generation gap? 

II. Supplemental Readings for Cosmos, episode III.

Here are the supplemental readings for the Cosmos reboot, episode III: "When Knowledge Conquered Fear". Topics are take-off points from the show's segments and are in no particular order.

History of Science, or, fishes vs. first principles:
Sample, I.   How a book about fish nearly sank Isaac Newton's Principia. April 18 (2012).

False Pattern Recognition:
Shermer, M.   Patternicity: finding meaningful patterns in meaningless noise. Scientific American, December (2008).

Hubscher, S.   Apophenia: definition and analysis. WebCite, Article 117. November 4 (2007).

Transition from Astrology to Astronomy:
Harmonices Mundi, Wikipedia.

Lyman, D.   Kepler's The Harmonies of the World - A Transition from Astrology to Astronomy. Yahoo! voices, October 29 (2009).

The Orbit Simulator. Laboratory for Atmospheric and Space Physics, University of Colorado.

Astrology and Astronomy in Other Cultures:
Placing, K.   Archaeoastronomy and Ethnoastronomy: a web-based activity exploring how different cultures have interpreted constellations. University of Sydney Uniserve Science.

Earliest Ancient Observatory in the Americas. COURTESY: RedOrbit.com.

Berger, K.   Ingenious: Edwin C. Krupp. Nautil.us, March 27 (2014).

Predictive Demography:
Alho, J. and Spencer, B.   Statistical Demography and Forecasting. Springer, Berlin (2006).

Mueller, L.D., Nusbaum, T.J., and Rose, M.R.   The Gompertz equation as a predictive tool in demography. Experimental Gerontology, 30(6), 553-569 (1995).

Other Notes:
Interestingly, the LaRouche PAC hosts a site devoted to the Harmonices Mundi. The LaRouche movement seems quite pseudo-scientific to me, even though they advocate a more scientific approach to governance and policy. This paradox might be similar to Isaac Newton's fascination with pseudo-science (e.g. search for a Bible code), which was mentioned in Episode 3. Sometimes, the more things look enlightened, the more they stay the same.

Edison and Darwin Day(s) Items of Interest

February 11 is Edison Day and February 12 is Darwin Day. In honor of both (tech innovator and naturalist), I will cross-post some materials from Tumbld Thoughts, in addition to some interesting Darwin-Day related items courtesy of the Center for Scientific Inquiry (CFI).

February 11: Happy Edison Day!

Taken in part from a Chicago Ideas Week poster.

In honor of Edison Day (his posthumous 167th birthday), here are a few readings from IEEE Spectrum on the D-Wave quantum computer. Or pseudo-Quantum computer, depending on how you interpret the evidence.

The D-wave uses a 512-qubit architecture [1] to perform quantum annealing (a form of combinatorial optimization). This should allow for quantum computing-like capabilities upon scale-up (e.g. faster computation, exceeding Moore's Law) [2].

However, its current form is actually slower than conventional (e.g. classical digital) computers, and may not provide the theoretically-predicted advances in computational power [3, 4]. In fact, it may not be a quantum computer at all, a seemingly straightforward fact nobody can seem to verify [5].

NOTES:

[1] Hsu, J.   Scientists confirm D-wave's computer chips compute quantum mechanics. IEEE Spectrum, July 3 (2013).

According to this article, the company has kept the details of how the D-Wave functions shrouded in mystery. They have taken a "show but don't tell" (e.g. celebrate the black box) approach, which was a tactic employed by Edison in one infamous instance.

[2] Hsu, J.   D-wave's Year of Computing Dangerously. IEEE Spectrum, November 26 (2013).

[3] Hsu, J.   D-wave's quantum computing claim disputed again. IEEE Spectrum, February 10 (2014).

[4] Guizzo, E.   Loser: D-wave Does Not Quantum Compute. IEEE Spectrum, December 31 (2009).

[5] Mirani, L. and Lichfield, G.   Why nobody can tell whether the world's biggest quantum computer is a quantum computer. Quartz, April 15 (2014).

The Next Day: Darwin's Legagy, one year older, one year better!

In honor of this year's Darwin Day, I bring you the "Art of Darwin" [*] along with a diversity of evolutionary-oriented readings (on 10 distinct topics) from my reading queue. These should highlight the manner in which Evolutionary Science has grown since Darwin's lifetime.

1) Human Genetics: Loh, P-R., Lipson, M., Patterson, N., Moorjani, P., Pickrell, J.K., Reich, D., and Berger, B.   Inferring Admixture Histories of Human Populations Using Linkage Disequilibrium. Genetics, 193, 1233-1254 (2013).

2) Evolution of Sociality: Waters, J.S., Holbrook, C.T., Fewell, J.H., and Harrison, J.F.   Allometric Scaling of Metabolism, Growth, and Activity in Whole Colonies of the Seed-Harvester Ant Pogonomyrmex californicus. American Naturalist, 176(4), 501-510 (2010).

3) Evo-Devo (animals): Keller, R.A., Peeters, C., and Beldade, P. Evolution of thorax architecture in ant castes highlights trade-off between flight and ground behaviors. eLife, 3, e01539 (2014).

4) Experience-dependent Plasticity (plants): Gagliano, M., Renton, M., Depczynski, M., and Mancuso, S.   Experience teaches plants to learn faster and forget slower in environments where it matters. Oecologia, doi:10.1007/s00442-013-2873-7.

5) Evolution of Phenotypes: Tobias, J.A., Cornwallis, C.K., Derryberry, E.P., Claramunt, S., Brumfield, R.T., and Seddon, N.   Species coexistence and the dynamics of phenotypic evolution in adaptive radiation. Nature, doi:10.1038/nature 12874 (2013).

6) Evolution of Genomes: Wu, X. and Sharp, P.A.   Divergent Transcription: A Driving Force for New Gene Origination? Cell, 155, 990-996 (2013).

7) Genetic Regulation: Stergachis, A.B. et.al   Exonic Transcription factor binding directs codon choice and affects protein evolution. Science, 342, 1367 (2013).

8) Artificial Life (Robustness and Evolvability): Payne, J.L., Moore, J.H., and Wagner, A.   Robustness, Evolvability, and the Logic of Genetic Regulation. Artificial Life, 20(1), 111-126 (2014).

9) Evolutionary Biomechanics: Witton, M.P. and Habib, M.B.   On the Size and Flight Diversity of Giant Pterosaurs, the Use of Birds as Pterosaur Analogues and Comments on Pterosaur Flightlessness. PLoS One, 5(11), e13982 (2010).

10) A dissenter (sort of): Ruse, M.B.   Why I'm not celebrating Darwin Day. Chronicle of Higher Education Brainstorm blog, February 9 (2014).

 

[*] representations of Darwin and his legacy from around the web. Sources in order (from top to bottom): A, B, C, D, E, F.

Extra Goodies, courtesy of CFI

Here are some extra Darwin Day goodies, courtesy of the CFI. The first is a poster. While similar to their Carl Sagan poster series, they only have one style (although they also have a customized Facebook page cover shown below). The second is a link to the audiobook version of "Origin of the Species" (courtesy Librivox).

Speculating (and modeling speculation) about Biology, Culture, and Peer-review

Here are the latest features cross-posted to Tumbld Thoughts. A cornucopia of themes, from a model of pure speculation (I), to a new paper and reflections on the diversity of life-history strategies to aging across 46 species (II), and the human actions and reactionary tendencies that result from massive cultural change (III). Also featured is an update on biases inherent in the peer-review process (IV). So let's get started.

I. Pure (or Applied) Speculation

Here is an interesting model of predicting the future, courtesy of Anthony Dunne and Stuart Candy. In the book "Speculative Everything", Dunne and co-author present a design-centered vision for predicting the future [1].

Dunne's talk at the Resonante conference features a model of future prediction proposed by Stuart Candy of the Sceptical Futurist blog and LongNow foundation. Candy's model treats the future as a prismatic spectrum of future outcomes.

Using the prismatic spectrum metaphor (my coinage), the future is understood as an extension of the present, with progressively more and less likely outcomes. The "preferred futures" fall between the most likely and the most promising potentials.

II. What happens when you combine phylogeny, demography, meta-analysis, and life-history?

Apparently, yes it does.....

The top picture is from a new paper [2] that combines a phylogenetic perspective with demography (quasi-phylodemography) to look at variation in aging across the life-history of 46 species. A summary and set of insights from Phenomenon blog can be found in [3]. 

By compiling data from multiple sources and conducting a meta-analysis, the authors of [2] found that life history trends for fertility, mortality, and survivorship vary widely both cross-culturally (in humans) and across the tree of life. 

To make sense of this diversity, the authors of [2] propose a fast-slow continuum of senescence: from populations with a short-lived, early reproductive period to populations with a long-lived, extended reproductive period. These results can be compared with the review in [4], which presents the standard view of why we age, circa 2000.

III. The Action and Reaction of Cultural Change

Here is a rather long, detailed FAQ (some might say manifesto) from the Slate Star Codex on how to be an anti-reactionary. The detail is in the nature of Reactionism (or Neo-reactionism), which is the tendency to embrace the past (or zombie ideas) as if modernization will only bring degradation and "ruin everything" [5].

This notion of progress and reaction are largely based on human value systems, as Scott Alexander points out. While the reactionary would argue that turning away from traditional cultural value systems leads to economic ruin and rampant crime, the data show the opposite.

To get right to the point of this argument (so to speak), go to Section 3.3 (then where does progress come from). There you will find data from the World Values Survey, where the so-called "vanguard" countries (in terms of growth and safety) possess high levels of both secular-rational and self-expression values [6]. 

IV. Herding in peer-review

With significant apologies to Gary Larson and the scientific community. Please read on....

In the last Synthetic Daisies post, I featured a new paper of mine posted to the arXiv called "A Semi-supervised Peer Review System", which was itself based on a previous Synthetic Daisies post. In this paper, I introduced a model of automated objective manuscript evaluation focused on fraud detection. 

Now there is a new paper in Nature [7] that discusses the phenomenon of herding in peer-review and evaluation. Here, the authors use a Bayesian (as opposed to a signal detection) statistical model to describe what happens when reviewers converge upon a misclassification (e.g. rejecting a paper with solid conclusions and methods). They call for the inclusion of subjectivity in the decision-making criterion: subjective decisions are those that include assessing both the strength of a reviewer's agreement with the conclusions and more conventional features of the manuscript (e.g. strength of the premises and methods employed).

In the graphs above, two scenarios are compared: M1 (which is the subjective strategy) and M2 (which is a purely objective strategy). The authors claim that the M1 strategy prevents so-called herding and promotes a more unbiased outcome.

NOTES:

[1] the inability of people to envision novel and coherent futures is a prominent theme in "The Secret War between Downloading and Uploading" by Peter Lunenfeld. 

[2] Jones, O.R. et.al   Diversity of aging across the tree of life. Nature, doi:10.1038/nature12789 (2013).

[3] Hughes, V.   Why do we age: a 46-species comparison. Phenomena blog, December 8 (2013).

[4] Kirkwood, T.B.L. and Austad, S.N.   Why do we age? Nature 408, 233-238 (2000). Source of the bottom image.

[5] what that everything constitutes is not always clear. However, it could be the shock and uncertainty of the culture change process itself.

[6] similar to the argument Steven Pinker makes in "The Better Angels of our Nature", and for similar reasons.

[7] Park, I-U., Peacey, M.W., and Munafo, M.R.   Modelling the effects of subjective and objective decision-making in scientific peer review. Nature, doi:10.1038/nature12786 (2013) AND Dapper, A.   Should Scientists be more subjective? Nothing in Biology Makes Sense! blog, December 11 (2013).