If you were not already aware: I have a Kickstarter page for a project I’m calling Punk Mathematics. It’s a bit of bookfuturism (having various forms of interaction throughout the writing and rewriting process) on mathematics. It’s a set of stories of trying to understand real and imaginary things by thinking really hard about their structure. It’s a book about the subject I love most, written with maximal quirk factor.

There are three days left before the Kickstarter deadline. Check it out!

The answer to almost any question is available within seconds, courtesy of the invention that has altered how we discover knowledge – the search engine. Materializing answers from the air turns out to be the easy part – the part a machine can do. The real difficulty kicks in when you click down into your search results. At that point, it’s up to you to sort the accurate bits from the misinfo, disinfo, spam, scams, urban legends, and hoaxes. “Crap detection,” as Hemingway called it half a century ago, is more important than ever before, now that the automation of crapcasting has generated its own word: “spamming.”

Unless a great many people learn the basics of online crap detection and begin applying their critical faculties en masse and very soon, I fear for the future of the Internet as a useful source of credible news, medical advice, financial information, educational resources, scholarly and scientific research. Some critics argue that a tsunami of hogwash has already rendered the Web useless. I disagree. We are indeed inundated by online noise pollution, but the problem is soluble. The good stuff is out there if you know how to find and verify it. Basic information literacy, widely distributed, is the best protection for the knowledge commons: A sufficient portion of critical consumers among the online population can become a strong defense against the noise-death of the Internet.

The first thing we all need to know about information online is how to detect crap, a technical term I use for information tainted by ignorance, inept communication, or deliberate deception. Learning to be a critical consumer of Webinfo is not rocket science. It’s not even algebra. Becoming acquainted with the fundamentals of web credibility testing is easier than learning the multiplication tables. The hard part, as always, is the exercise of flabby think-for-yourself muscles.

Read more: http://www.sfgate.com/cgi-bin/blogs/rheingold/detail?entry_id=42805#ixzz0iTjBVWA7
(etiquette note: 3 paragraphs is fair reblog use, right?)

Funny he should mention algebra. I’ve been thinking a lot about the ways in which mathematics can contribute to crap detection. Examples of what I’m thinking of so far:

Hans Rosling, Let My Dataset Change Your Mindset, TED talk
I’ve tweeted this three times at least. You really must watch it. I had some dumb ideas about “the developing world” before Rosling corrects me with a whump upside the head of brilliantly narrated data. I’d love to interrogate http://gapminder.org but I don’t know the right questions. Anyone for some digital social science?

A few weeks back there was an interactive infographic that shows perceived sustainability graphed against actual sustainability (I’m afraid I’ve lost the link). Whole Foods in particular is perceived as being really green, without being substantially more sustainable than other grocery stores. Of course, have we detected crap re: Whole Foods, or have we detected crap re: the survey methods?

Benford’s Law
Naturally occurring data has a particular sort of probability distribution, no matter what kind of data. Seriously, the examples are bizarre. (Radiolab has a great story on this law, I believe in the ‘Numbers’ episode.) That gives it a potential use in detecting data which either 1. has interesting anomalies, or 2. is fraudulent. It seems we should be testing this law against all kinds of open data, if for no other reason than to ooh and aah over Benford’s law, but also with an eye for detecting surprising things.

Solitary play is just play. It’s fun, and self-absorbing, in a literal sense: your self is absorbed into the play, and we experience ego-less joy for a little while.

Play with playmates may be just play, but it often turns into games, and games have goals. It’s an arbitrary goal, accomplished via suboptimal means, but it’s a goal nonetheless. (If you want the ball in the hole so bad, why don’t you pick it up, walk it over, and drop it in? Because that’s not what golf is.)

I grew up reading “weird stuff”: The Invisibles, Planetary, weird science, industrial music magazines, RE/Search, and other things that were about people who were clearly much cooler than myself. Now that I’ve discovered atemporality as the spine of a design aesthetic, I want to do some solitary play with all of the culture I’ve absorbed over the past 33 years, and all the interesting new culture that is being, uh, cultured by the network.

What I’m trying to say is: If you are reading this blog for a new take on mathematics, economics, and game theory, you ought to check out Math for Primates, the blog/podcast/embryonic-community I’m developing with Nick. Math for Primates is a group project, and so it is relatively focused and goal-oriented despite the silliness and poo-flinging.

If, on the other hand, you believe that when the going gets weird, the weird turn pro, you should stick around. I’m collecting a bunch of shiny new toys and I’m looking forward to playing with them. This is going to be solo play, so I’m giving myself free license to be self-absorbed and meandering*, until/unless a solo game with a point emerges, at which point all bets are off.

notes for my Brain (links to come):

atemporality (@bruces, @justinpickard)
serious play: Evoke and SuperBetter (@evokenet, @avantgame)
soft development / networked development (@hexayurt, @leashless)
evolutionary health (@johndurant)
learning experience design: networked learning, learning as game, games in learning
consciousness health: luck-training, mind-training

* – Look, I’ll just admit it: I got into atemporality because it gives me wardrobe ideas. I don’t think you understand how much psychic censoring takes place to get me to not discuss my clothing and hair in our ostensibly mathematical podcast. It’s like there’s a fight for influence inside my head waged between the homunculi of John Horton Conway and Dennis Miller.

Although I do not want to over-stress the parallels between open source software and open source appropriate technology, the fundamental conditions that support these technologies are very similar. There is a rapidly growing network – just over half the human race has cell phones now, and the rest will be online within 10 years. The network and hardware platform make information exchange about solutions possible. Training and education materials are developed internationally, providing low-cost solutions for all. The difference between hacking on a Linux kernel and figuring out a rope pump implementation question – if you have access to a network and people with expertise to support your work – is really not all that large. The commodity hardware – whether it is a cheap computer, or some bits of car tire and washers and a wheel and a rope – is used to solve the problem at hand using knowledge from the network. And there is no shortage of people to research and extend global knowledge in these areas: there are five times as many incredibly smart people in the poor parts of the world as in the rich ones, simply because there are five times as many people. As they begin to come online in the next few years, the collective intelligence of the human race is going to increase by a factor of five. Nobody knows what this means yet, but I’m very hopeful that it is going to enable us to think our collective way out of all kinds of problems that currently look insurmountable.

I call this whole approach to development the “soft development path”. It is ICT and open source heavy, and capital and infrastructure light. I think it is reasonably clear that all of the technologies exist to allow people to enjoy essentially first-world standards of public health and education using relatively limited material resources. It is the only approach I know of to international development – or the future of the human race – which allows everybody to live a good life without destroying the planet in the process. By decoupling personal welfare with economic growth, we become able to provide for everybody. The example of Kerala in India proves that under the right conditions it can be done even without broad-based use of advanced appropriate technology options. The additional leverage of internet-supported appropriate technology roll-out opens up the real possibility of a world in which all people can enjoy a good standard of living, with long life, abundant food and good health, without requiring us to solve many of the apparently intractable political problems which have plagued the global economy and particularly international development over the years.

from http://agit8.org.uk/?p=268 , worth reading slowly

We try to describe intuitively what is meant by a linear system…

[If we know or assume that a system is linear, then:] If we know the outputs for a collection of different inuts, we know the outputs for all inputs that can be obtained by combining these inputs in various ways.

…

So many of the problems that we encounter are assumed to be linear problems and so many of the mathematical techniques developed are inherently linear… Potential theory, the theory of heat, and the theory of small vibrations of mechanical systems are examples of linear theories.

In our latest episode, we talk about the sex lives of lizards, how to be maximally unbeatable at rock-paper-scissors, and while I think we did okay at explaining Quantum Game Theory, we fail to save the Enterprise.

I will freely admit that I’ve done my share of sneering at social innovation entrepreneurs. They can be chipper and self-congratulatory, and they waste valuable characters using your given name in their alarmingly earnest DMs. However, we are moving out of the cheap talk phase of social networks. Within about 7 hours of the Haitian earthquake, I read on Twitter of a number allowing you to text $10 to the Red Cross. As I did so, I realized I was doing it, partly because it was right, but mostly because it was easy. I would use the same device to send the donation as I had used to read it, so there was no context switching; there was no need to fact-check because the information was from someone I’ve learned to trust. Our tools are getting better at convincing us to do the right thing, and making it easier to do it.

Watch for Evoke. It’s going to be the real deal. In the meantime, send 10 bucks to the Red Cross by texting “haiti” to 90999.

Paying attention to the last ten years means we need to realize that nonproprietary, distributed production is not the poor relation of traditional proprietary, hierarchically organized production. This is no hippy lovefest. It is the business method on which IBM has staked billions of dollars; the method of cultural production that generates much of the information each of us uses every day. It is just as deserving of respect and the solicitude of policy makers as the more familiar methods pursued by the film studios and proprietary software companies. Losses due to sharing that failed because of artificially erected legal barriers are every bit as real as losses that come about because of illicit copying. Yet our attention goes entirely to the latter.

But even if you’re not into advanced mathematical brain fry, the underlying point of the talk is very important. According to Weinstein, there is an obviously incorrect economic assumption about human behavior, expressed in this quote:

“…tastes neither change capriciously nor differ importantly between people. On this interpretation one does not argue over tastes for the same reason that one does not argue over the Rocky Mountains—both are there, will be there next year, too, and are the same to all men.”
—Gary Becker and George Stigler, 1977, De Gustibus Non Est Disputandum

…and that wrong assumption has affected the discipline of economics as described in this quote:

“That the problems [of changes of taste] have remained central and largely unresolved for twenty-five hndred years no doubt makes some economists think it wise to define them out of the discipline, at whatever cost in realism and relevance.”
M.S. McPherson, ‘Changes in tastes’, entry in The New Palgrave: A dictionary of Economics, 1987, pp 401-403.

In short, economics uses, as a fundamental axiom, the obviously wrong idea that we all prefer the same things to the same degree for our entire lives.

Srsly!

However, I sort of can’t blame any economist who would hope like hell this assumption, while obviously incorrect, would be unimportant. I can’t blame them because, when you assume the obviously wrong idea is in fact wrong, the mathematics behind fundamentally important and useful economic concepts become, to use a technical phrase, really fucking hard. I have compassion for anyone who doesn’t want to go anywhere near an infinite-dimensional function space bundle!

But, still. A crazily wrong axiom has to go. Suddenly, there’s all kinds of low-hanging theorems just waiting to be picked up by mathematicians and physicists and anyone else who is willing to touch a fiber bundle. So, who’s with me?

[ETA: There's a whole interesting undercurrent of the extension of that idea of 'the unreasonable effectiveness of mathematics', and I think that's really interesting from a calculus education standpoint, too. I got too excited about the economics part to mention it!]

Part I.
I intend to work in Computational Analysis of Social and Organizational Systems (CASOS), with Professor Kathleen Carley, Professor Cleotilde González, or Professor James Herbsleb as possible advisors.

I became interested in this area when I discovered the work of Dr. Jane McGonigal, Director of Game Research and Development at the Institute for the Future (IFTF). Dr. McGonigal creates games designed to “create large-scale collaborative communities, to improve players’ real quality of life, and to solve real-world problems, by overlaying game systems and game content on top of everyday reality.” (from her website: http://avantgame.com/bio.htm#GAMES).

I want to explore the area between these game design principles and the mathematical theory of games. Mathematically, a game is defined by a set of players, a set of strategies, and a set of payoffs. To a massively multiplayer game designer, a game seems instead to consist of a community of sometimes cooperating, sometimes competing players, a set of subgames (i.e., not every player in the community always appears to be playing the same game), and a set of rewards (which may be monetary, virtually monetary in a game with a virtual economy, pseudo-monetary as in a points or grading system, a public list of achievements describing the prowess of a player, or the positive psychological rewards of accomplishment, amusement, excitement, opportunity to display skill, etc.). Where the game theorist is most concerned about how a player might maximize his or her utility, the game designer is concerned with creating an immersive and engaging experience to people at play. In exploring the region in between these two conceptions of what a game is (through theory, simulation, and playable experiments), I aim to develop an understanding of the various ways one can motivate and engage people through play.

Part II.
I am applying to Carnegie-Mellon because I have found no other program exploring the space between the theoretical-computational results of game theory and social network analysis, and the social-cultural aspects of how people socialize, share information, and play in and around the modern world’s rapidly evolving information ecology. My end goal is to apply what I learn in my doctoral research to design new forms of massively collaborative projects, be they educational, civic, scientific, economic, environmental, or humanitarian. The social problems of the 21st century demand collaboration on a massive scale, of a kind that 20th century institutions are not always directly suited for, and the cognitive investment the world spends in immersive games is an untapped resource that might be channeled into solutions.

Part III.
In my education at Portland State University, I took one year each of game theory and quantum game theory. The latter is still early in its development, but has been used by Hanauske, Kunz, Bernius, and König (http://arxiv.org/abs/0904.2113) to analyze the 2008 economic crash, using the metaphor of quantum entanglement to account for the influence of socio-economic context factors, leading me to believe it may have utility in understanding the behaviors of communities at play. I also took one year each of elementary graph theory and algebraic graph theory; I am interested in learning to apply graph-theoretical concepts to the dynamics of socially networked gamers.

In the realm of large-scale collaborative games, I was one of the roughly 7,000 people who played Superstruct, the IFTF’s massively multiplayer future forecasting game. The IFTF chose me as one of the SEHI ‘19, the 20 Superstruct players who “turned the superstruct community [into] a true, working engine of ideas”. I also received the Pandora Award (Bronze) from Chris DiBona, Open Source Program Manager for Google, for my in-game efforts to harness the power of disaffected and angry hackers for good.

Part IV.
Since completing my master’s degree this summer, I have been self-educating myself in Unix, shell-scripting, and data visualization (using Processing). Primed by my experience in Superstruct, I have been monitoring trends in open development, attention management and information filtering, and the legal complexities engendered by the internet’s role as world-spanning copy machine.