This simulation from Jean Lievens.
A survey of swarming, a sub-topic of complexity. No mention of stigmergy though.
Here are some excerpts from Janet’s fascinating paper.
In late 2007 in Kenya, US educated Kenyan journalist Ory Okolloh had become one of the main sources of information about the election and the violence that broke out soon after. Because of the government‟s ban on live reporting and censorship of the mainstream media, Okolloh solicited information about incidents of violence from ordinary people in the form of comments posted on her personal blog. The mainstream media was not reporting on the violence because of the government ban, and Okolloh was quickly overwhelmed by the numbers of emails and messages that she received. In order to focus on the “immediate need to get the information out”, in early January Okolloh posted a request on her blog for help to develop a website where people could post anonymously online or via mobile phone text messages, the most accessible type of communications technology in Kenya. Within a day the Ushahidi („testimony‟ in Swahili) domain was registered and the website went live within less than a week. Built by 15-20 mainly Kenyan volunteers using open source software, the project was funded entirely by donations. Immediately, over 250 people began using the site to share information, even including radio stations. The process of report verification was simple. If the reporter could be identified, they were contacted for verification; if anonymous, a certain volume of similar reports was considered verification. Within weeks hundreds of incidents of violence had been documented in detail that would have otherwise gone unreported, and the website received hundred of thousands of site visits from around the world, sparking increased global media attention.
Following the events in Kenya, Humanity United, a non-profit organization dedicated to ending modern slavery and mass atrocities, offered to fund redevelopment of Ushahidi as a broadly available platform for collecting and visualizing information. In late 2008 the alpha version was released and tested in the Democratic Republic of Congo, among other places. The beta version, utilizing FrontlineSMS, free software that turns a laptop and a mobile phone or modem into a central communications hub, was released in 2009. The Frontline SMS software can be used on a single laptop computer without the need for the internet, allowing users to send and receive text messages with large groups of people through mobile phones. Since its original release in 2005, it has been widely adopted in the grassroots non-profit community and nominated for several awards [Banks]. Today, Ushahidi defines itself as “a non-profit tech company that develops free and open source software for information collection, visualization and interactive mapping” [http://ushahidi.com], and the development of Ushahidi has continued. Presently, there are three free downloads available: the Ushahidi platform, the Crowdmap application, and the SwiftRiver application. In 2008, Ory Okollah said, “We anticipate that the platform will revolutionize how many organizations handle their data and also democratize how information is collected and shared in crisis situations” and characterized the Ushahidi development strategy as: “pushing the boundaries of Rapid Prototype Model, Crowdsourcing, Visualization, Mapping, and Mobile Phone Platforms.”
A study of the evolution of the Ushahidi software presents strong evidence of cognitive stigmergy at two levels. The first level is the development of the Ushahidi platform, both initially and through the creation of the enhancements. The development of the software using a Rapid Prototype model and crowdsourcing on widely available mobile phone platforms follows examples of some FLOSS development teams that have been shown to use cognitive stigmergy as a tool to organize and coordinate work. The utilization of the software by end users as volunteers and contributors also demonstrates the role of cognitive stigmergy at the level of group action. The occurrences of crowdsourcing demonstrate cognitive stigmergy. The reasons for the great success of Ushahidi lie precisely in its raison d‟etre: it was conceived as a way for people to give testimony to the world about a great crisis that was occurring. Ushahidi was meant to empower, to give voice, and was specifically designed to do so for all. Heylighen points out that the inexpensive cost of information via the internet is a major force for the increase in all forms of information, easy access to it and voluntary creation and sharing of forms of it. The combination of easy access, low cost, and a compelling social concern lead to powerful motivations for many to participate. The use of the Rapid Prototype Model meant that the functionality could be delivered while there was still an urgent need for it, before the crisis could pass and life returned to normal and that urgency was forgotten. The use of Visualization and Mapping was crucial. Human cognitive stigmergy is based on people perceiving changes in their environment and responding to them. Visual images and information are more meaningful even when the place is not known, even more powerful when it is. Testimony has more power when it is visualized. The dependence on Crowdsourcing as a resource for development, support and the generation of information is an obvious example of stigmergic self-organization. As a way to maximize participation and crowdsourcing, the use of Mobile Phone Platforms via FrontlineSMS is a clear success: “In Africa, cellphone penetration – the number of phones as a percentage of the population – is still the lowest in the world, but it is growing quickly. In 2010, an estimated 41 per cent of the population on the continent had cellphones, compared with 76 per cent globally. That’s double what it was in 2005”. Worldwide, it is estimated that there are five billion mobile phones in use as of 2010, and for many users, these are the only access they have to computing or telecommunications capability.
Still on Hayek. Having just received my copy, I thought I’d give it another plug. My chapter Mindscapes and Landscapes: Hayek and Simon on Cognitive Extension is in this collection. The full line-up as follows:
Foreword; V. Smith
Introduction; R. Frantz & R. Leeson
Friedrich Hayek’s Behavioural Economics in Historical Context; R. Frantz
A Hayekian/Kirznerian Economic History of the Modern World; D. McCloskey
Was Hayek an Austrian Economist? Yes and No. Was Hayek a Praxeologist? No.; W. Block
Error is Obvious, Coordination is the Puzzle; P. Boettke, W. Caceres & A. Martin
Hayek’s Contribution to a Reconstruction of Economic Theory; H. Gintis
On the Relationships Between Friedrich Hayek and Jean Piaget; C. Chelini & S. Riva
Cognitive Autonomy and Epistemology of Action in Hayek’s and Merleau-Ponty’s Thought; F. Di Iorio
Hayek’s Sensory Order, Gestalt Neuroeconomics, and Quantum Psychophysics; T. Takahashi & S. Egashira
Mindscapes and Landscapes: Hayek and Simon on Cognitive Extension; L. Marsh
Hayek’s Complexity Assumption, Ecological and Bounded Rationality, and Behavioural Economics; M. Altman
Subjectivism and Explanations of the Principle; S. Fiori
Satisficing and Cognition; Complementarities between Simon and Hayek; P. Earl
The Oversight of Behavioural Economics on Hayek’s Insight; S. Rizzello & A. Spada
Complexity and Degeneracy in Socio-Economic Systems; G. Steel & H. Hosseini
Some extracts from Thierry’s paper:
Contemporary analysis usually divides games of chance into three dimensions. In Machina and Schmeidler’s (1992) terms, this division can be viewed based on the example of an urn containing 90 balls of different colors, out of which an agent pulls a ball, of which he must ex ante guess its color to achieve a predetermined gain. If the agent knows that the number of red, white, and black balls is the same (30), he finds himself in a situation of risk: He knows the possible consequences and the probability distributions, that is, he has one in three chances of getting a ball of any particular color. However, if he knows that these balls are red, white, and black, but in indefinite proportions, he is confronted with situations qualified as uncertainty: The consequences are known, but the probability distributions are not. Yet again, if the agent knows there are 90 balls of different colors in the urn but does not know how many of these colors there are, he is in a state of incomplete information: The agent is unable to define the list of possible outcomes (situation of ambiguity) and can expect some surprises identifiable ex ante, as states of nature are identifiable.
An extra dimension may be added to this distinction: If the agent has himself placed 30 red balls in the box, but he does not know what other elements of indefinite character and number there are in the box, nor the structure of gains or losses associated with various results, then we can consider that the agent is in a position of ignorance. Not only is he unable to define the list of consequences of the game, but he also does not know the distribution of events. The agent is able to define what he knows, but unlike the three previous cases, he cannot determine the scope and nature of what he ignores. The surprise is necessarily unexpected in the sense that the agent is unable to identify ex ante the possible states of nature.
It is in this latter perspective that Kirzner (1973, 1979, 1982) argues that market actors face a phenomenon of ‘‘genuine ignorance,’’ reflecting their inability to know all the opportunities for exchange or profit available in an economy. At any point in time, each individual perceives only fragmentary aspects of social reality in which he participates, and not its other facets. Each exchange is made in ignorance of other exchanges performed at the same time; thus, there is no common knowledge of prices and no actor can perceive the whole. In a monetary economy, the consequences of these independent exchanges are mutually dependent. The implications of this genuine ignorance on the coordination of activities are thus considerable. Using the example of Schmeidler and Machina’s urn (1992) from the time when the consequences of a draw for each individual depend on the (unknown) number of elements (of unknown character) deposited in the ballot box by an (unknown) number of (unknown) people, the ability of such a game to produce a balance is at least questionable.
The stakes of this phenomenon of ignorance compel us to identify its sources. These are not found in any complexity of information, neither in the cost of its acquisition nor in its treatment (deliberation) from a perspective of bounded rationality. They come from a more fundamental phenomenon of dynamic subjectivism. According to authors such as Kinder (1973, 1979, 1997) and Lachmann (1977, 1986), agents’ preferences, endowments, knowledge, and strategies should be defined as personal, unique. Therefore, each individual is a priori ignorant of how others evaluate goods and services. Economic analysis is not therefore based on a perfect, or even sufficient knowledge of actors to coordinate their activities. The diversity of actors’ preferences, interpretations, and expectations would certainly not be a problem if they were constants. A process of trial and error would lead to new learning, opening onto a price structure that would allow coordination. But this is in fact not the case because the individual performances would change continuously, according to an endogenous process, ultimately explained by ignorance or internal self-ignorance (Aimar, 2008a). As Hayek (1951a, 1951b) explained, the actor can only partially perceive the existing opportunities for satisfaction, for reasons related to the organization of the human brain and the tacit characteristic of knowledge. His conscious choices being ignorant of a portion of his subjectivity, he makes mistakes, expressed by disappointment with satisfaction. He undergoes a de facto internal discoordination, forcing him to change his representations to make his beliefs conform to the reality of his interior environment. But changing choices results in transforming his internal environment and de facto creates new unknown areas. The mind, constantly evading the consciousness’s desire to fully absorb it, makes the process of self-discovery never-ending. Thus, market discoordination, the result of genuine ignorance, is finally but an internal discoordination, consequence of a phenomenon of self-ignorance.
It was around this phenomenon of genuine ignorance and its perverse effects on coordination between individuals that Kirzner introduced the theme of entrepreneurship. The entrepreneurial function, driven by the incentive of profit, is to discover unperceived opportunities. Mobilizing qualities of alertness, reflected in cognitive openness, it reveals previously hidden information. Through his discoveries being translated into new money transactions, the entrepreneur socializes his knowledge and contributes to pulling market activities toward coordination. He goes beyond reducing ignorance; he transforms ignorance into uncertainty. But according to Kirzner, a parallel mission of the entrepreneur is to organize already discovered opportunities in the form of firms’ production plans, in order to protect them from risk of obsolescence resulting from the volatility of data.
In a dynamic world, discovery and exploitation of opportunity are then the two faces of entrepreneurship. The author argues that these two dimensions may be contradictory in the entrepreneurial mind. As much as discovery implies a cognitive opening to the outside, all exploitation of discovered opportunities is accompanied by elements of mental rigidity. These take the form of cognitive closure, thus opposing the entrepreneur’s perception of new opportunities. The aim of this contribution is to illuminate by the structure of this contradiction by economic analysis, to provide the means to verify it through experimental economics and to consider its extensions in terms of neuroeconomics.
Our plan is this: After explaining the basics of the theory of entrepreneurship and the elements that determine its duality, we will define the bases for an experimental protocol likely to support our thesis of an opposition in the cognitive field between the relative strengths of discovery and the exploitation of opportunities in the entrepreneurial mind. The last section forms the conclusion.
In the context of organizational economics, the relationships between cognition and complexity have been studied for many years through the lens of bounded rationality. However, this is outside Austrian theories, which do not define the act of knowing as the result of a deliberated choice between gain and cost but as the result of a spontaneous process. Unfortunately, the internal forces of this process remain ill-defined. Yet, much Austrian work has shown the relationships between the institutional environment and entrepreneurship. However, in spite of Kirzner’s (1985, p. 25) appeal for a psychological study of entrepreneurial qualities, the mental determinants of entrepreneurship have still not been studied. Therefore, our goal here is to use Austrian tools to define the relationship between organizational complexity and entrepreneurial discovery from a mental angle. Using the example of a protocol, we intend to establish the bases on which to experiment with the various theoretical propositions in this matter. This should allow a finer judgment of the determinants of entrepreneurial discovery and a better understanding of the effects of competition.