Archive for the ‘Decision theory’ Category

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Social networking v1.0

Published by peter on 2008-10-25 in Culture, Decision theory, Globalization, History, Joint-Action Society and Team working. 0 Comments

Believers in the potential of Web 2.0, such as we at Vukutu, think it will change many things — our personal interactions, our way of being in the world, our social lives, our economic lives, even our sciences and technologies.   The basis of this belief is partly by comparison with what happened the first time social networking became fashionable in western society.   This occurred with the rise of the Coffee House in western Europe from the middle of the 17th century.
Coffee, first cultivated and drunk in the areas near the Red Sea, spread through the Ottoman empire during the 16th century.   In Western Europe, it became popular from the early 17th century, initially in Venice, becoming known to educated Europeans roughly simultaneously with marijuana and opium.  (An interesting question for marketers is why coffee became a popular consumer product in Europe and the others did not.)  Because of the presence there of scholars of the orient and scientists with an experimentalist ethos, coffee first arrived in the British Isles in Oxford, where it was consumed privately from at least 1637;  the first public coffee house in the British Isles opened in Oxford in 1650, called the Angel and operated by a Mr Jacob.  The first London coffeehouse was opened in 1652 by Pasqua Rosee; the same mid-century period saw the rise of public coffee houses in the cities of France and the Netherlands.  For non-marketers reading this, it is worth realizing that opening a coffee house meant first having access to a regular source of coffee beans, no mean feat when the only beans then grew in the Yemen and north-east Africa.

Facing competition, coffee houses soon segmented their market, and specialised in particular activities, types of conversation, or political positions (sound familiar,  bloggers?), and provided services such libraries, reading rooms, public lectures, scientific demonstrations and auctions. Educated people and businessmen would often visit several coffee houses each day on their rounds, to collect and trade information, to meet friends and colleagues, to commune with the like-minded, and to transact business.  The coffee houses were centres for learning and debate, just as blogs are today, as well as places of economic exchange.
What were the consequences of this new mode of human interaction?  Well, coffee houses enabled the launch of at least three new industries — insurance, fine-art auctions, and newspapers — and were the physical basis for modern stock exchanges.  For instance, English insurer Lloyds of London began in Edward Lloyd’s coffee house in 1688.  And these industries themselves enabled or facilitated others.  The development of an insurance industry, for example, both supported and grew alongside the trans-continental exploration undertaken by Dutch, English and Iberian merchant shipping fleets:  deciding whether to invest in  perilous oceanic voyages required some rigour in assessing likely costs and benefits if one wished to make a long-term living from it, and being able to partition, bundle, re-bundle and on-sell risks to others.
And coffee-houses even supported the development of a new science.  In the decade around 1665, the modern idea of mathematical probability arose, seemingly independently across western Europe, in what is now Britain, France, Italy, the Netherlands and Switzerland.   There is still some mystery as to why the mathematical representation of uncertainty became of interest to so many different people at around the same time, especially since their particular domains of application were diverse (shipping accidents, actuarial events, medical diagnosis, legal decisions, gambling games).  I wonder if sporadic outbreaks of the plague across Europe provoked a turn to randomness.  But there is no mystery as to where the topic of probability was discussed and how the ideas spread between different groups so quickly: coffee houses, and the inter-city and inter-national information networks they supported, were the medium.
What then will be the new industries and new sciences enabled by Web 2.0?
POSTSCRIPT: Several quotes from Cowan, for interest:

“No coffeehouse worth its name could refuse to supply its customers with a selection of newspapers.  . .  . The growing diversity of the press in the late seventeenth and early eighteenth centuries meant that there was great pressure for a coffeehouse to take in a number of journals.  Indeed, many felt the need to accept nearly anything Grub Street could put to press.  . . . Not all coffeehouses could afford to take in every paper published, of course, but many also supplied their customers with news published abroad.  Papers from Paris, Amsterdam, Leiden, Rotterdam, and Harlem were commonly delivered to many coffeehouses in early eighteenth-century London.  The Scotch Coffeehouse in Bartholomew Lane boasted regular updates from Flanders on the course of the war in the 1690s.   Along with newspapers, coffeehouses regularly purchased pamphlets and cheap prints for the use of their customers.” (pp. 173-174).

“Different coffeehouses also arose to cater to the socialization and business needs of various professional and economic groups in the metropolis. [London]  By the early decades of the eighteenth century, a number of separated coffeehouses around the Exchange had taken to catering to the business needs of merchants specializing in distinct trades, such as the New England, the Virginia, the Carolina, the Jamaica, and the East India coffeehouses.  Child’s Coffeehouse, located conveniently near the College of Physicians, was much favoured by physicians and clergymen.  Because such affiliations were well known, entry into one of these specialized coffeehouses offered an introduction into the professional society found therein.” (pp. 169-170).

“The numerous coffeehouses of the metropolis were greater than the sum of their parts; they formed an interactive system in which information was socialized and made sense of by the various constituencies of the city.   Although a rudimentary form of this sort of communication circuit existed in early modern England (and especially London) well before coffeehouses were introduced in places such as St. Paul’s walk or the booksellers’ shops of St. Paul’s churchyard, the new coffeehouses quickly established themselves at the heart of the metropolitan circuitry by merging news reading, text circulation, and oral communication all into one institution.  The coffeehouse was first and foremost the product of an increasingly complex urban and commercial society that required a means by which the flow of information might be properly channeled.” (p. 171)

 
References and Acknowledgments:
My thanks to Fernando E. Vega of the USDA for pointing me to the book by Cowan.
Brian Cowan [2005]:  The Social Life of Coffee:  The Emergence of the British Coffeehouse.  New Haven, CT, USA:  Yale University Press.
Ian Hacking [1975]:  The Emergence of Probability: a Philosophical Study of Early Ideas about Probability, Induction and Statistical Inference. London, UK: Cambridge University Press.
Fernando E. Vega [2008]: The rise of coffee.  American Scientist, 96 (2): 138-145, March-April 2008.

Perceptions and counter-perceptions

Published by peter on 2008-10-22 in Decision theory, Intelligence and Espionage and Prophecy. 0 Comments

The recent death of Yuri Nosenko allows me to continue an intelligence arc in these posts.  What is the connection to marketing, I hear you cry!  Well, marketing is about the organized creation and management of perceptions, which could also be a definition of secret intelligence activities.  In any case, the two disciplines have many overlaps, including some coincident goals and some similar methods, which I intend to explore on this blog.

First, let us focus on Nosenko.   He presented himself in Geneva in 1961 to CIA as an agent of KGB willing to spy for the Americans, and then defected to the USA in 1964.  Among other information, he came bearing a firm denial that the USSR had had anything to do with the assassination of John F. Kennedy in November 1963.   JFK’s alleged assassin, Lee Harvey Oswald, was, after all, one of the very few (perhaps under 1000) people who had defected from the USA to the USSR between 1945 and 1963, and one of the even fewer (perhaps under 50) people who had defected back again.  Nosenko claimed to have read Oswald’s KGB file.
From the start, lots of doubts arose regarding Nosenko’s testimony.   He did not seem to know his way around KGB headquarters, his testimony contradicted other information which CIA knew, there were  internal inconsistencies in his story, and he cast serious aspersions on an earlier defector from KGB to CIA, claiming him to be a KGB plant.   Was Nosenko, then, a KGB plant or was he the genuine defector?   Within CIA the battle waged throughout the 1960s, with first the sceptics of Nosenko and then subsequently the believers in his bona fides holding sway.  Chief among the sceptics was James J. Angleton, who came to see conspiracies everywhere, and who was eventually fired from CIA for his paranoia.   (Robert De Niro’s film “The Good Shepherd”  is based on the life of Angleton, with Matt Damon taking this part, and features a character based on Nosenko.)  Finally, CIA decided officially to believe Nosenko, and he was placed in a protection programme.  He was even asked to give lectures to new CIA recruits on the practices of KGB, such was his apparent acceptance by the organization.
This final position so angered one of the protagonists, Tennent Bagley, that, 40 years later, he has written a book arguing the case for Nosenko being a KGB plant who duped CIA.   The book is very compelling, and I find myself very much inclined to the sceptic case.   However, one last mirror is missing from Bagley’s hall.   What if the top-most levels of CIA really did doubt that Nosenko was genuine?    Would it not be better for CIA to not let KGB know this?  In other words, if your enemy tries to dupe you, and you realise that this is what they are trying to do, is it not generally better to let them think they have succeeded, if you can?    Certainly, more information (about their methods and plans, about their agents, about their knowledge) may potentially be gained from them if you manage to convince them that they have indeed duped you.  All you lose is – perhaps – some pride.  Pretending to be duped by Soviet intelligence is perhaps what Britain’s MI6 did regarding Kim Philby, Donald Maclean and Guy Burgess:  it is possible that MI6 knew many years before their defections that these men were working for the Soviets, and used them in that period as conduits for messages to Moscow.
In the case of Nosenko the dupe arrived bearing a message about the JFK assassination.   For many and various reasons (not all of them necessarily conspiratorial), CIA may have been keen to accept the proposition that KGB were not involved in JFK’s assassination.   How do you convince KGB that you believe this particular message if you don’t believe the messenger is genuine?   So, also for pragmatic reasons, the top levels of CIA may have decided to act in a way which would lead (they hoped) to KGB thinking that the KGB’s ruse had worked.
How then to convince KGB that their plant, Nosenko, was believed by CIA to be for real?  Simply accepting him as such would be too obvious – even KGB would know that his story had holes and would not believe that a quick acceptance by CIA was genuine.   Better, rather, for CIA to argue internally, at length and in detail, back-and-forth-and-forth-and-back, about the question, and then, finally, in great pain and after much disruption, decide to believe in the defector.   Bagley either does not understand this last mirror (something I sincerely doubt, since his book evidences a fine mind and very keen understanding of perception management), or else perhaps his book is itself part of a plan to convince KGB that Nosenko was fully believed by CIA.
 
References:
Tennent H. Bagley [2007]: Spy Wars: Moles, Mysteries, and Deadly Games.  New Haven, CT: Yale University Press.
Robert De Niro, Director [2006]:  The Good Shepherd. Universal Pictures.
Tim Weiner [ 2007]:  Legacy of Ashes: The History of the CIA.  Doubleday.

Putting the "Tea" in IT

Published by peter on 2008-07-16 in Computer technology, Decision theory, Lead users and Marketing strategy. 0 Comments

One of the key ideas in the marketing of high-tech products is due to Eric von Hippel of the MIT Sloan School, the idea that lead users often anticipate applications of new technologies before the market as a whole, and even before inventors and suppliers. This is because [tag]lead users[/tag] have pressing or important problems for which they seek solutions, and turn to whatever technologies they can find to respond to their problems.
A good example is shown by the history of Information Technology. The company which pioneered business applications of the new computer technology in the early 1950s was not a computer hardware manufacturer nor even an electronic engineering firm, but a lead user, Lyons Tea Shops, a nationwide British chain of tea-and-cake shops. [tag]Lyons[/tag] specified, designed, built, deployed and operated their own computers, under the name of Leo (Lyons Electronic Office). Lyons, through [tag]Leo[/tag], was also the first to conceive and deploy many of the business applications which we now take for granted, such as automated payroll systems and logistics management systems. One of the leaders in that effort, David Caminer, has recently died at the age of 92. LEO was later part of ICL, itself later purchased by Fujitsu.
This post is intended to honour David Caminer, as a pioneer of [tag]automated business decision-making[/tag].

Putting the "Tea" in IT

Published by peter on 2008-07-16 in Computer technology, Decision theory, Lead users, Marketing strategy and Matherati. 0 Comments

One of the key ideas in the marketing of high-tech products is due to Eric von Hippel of the MIT Sloan School, the idea that lead users often anticipate applications of new technologies before the market as a whole, and even before inventors and suppliers. This is because lead users have pressing or important problems for which they seek solutions, and turn to whatever technologies they can find to respond to their problems.
A good example is shown by the history of Information Technology. The company which pioneered business applications of the new computer technology in the early 1950s was not a computer hardware manufacturer nor even an electronic engineering firm, but a lead user, Lyons Tea Shops, a nationwide British chain of tea-and-cake shops.  Lyons specified, designed, built, deployed and operated their own computers, under the name of Leo (Lyons Electronic Office). Lyons, through Leo, was also the first to conceive and deploy many of the business applications which we now take for granted, such as automated payroll systems and logistics management systems. One of the leaders in that effort, David Caminer, has recently died at the age of 92. LEO was later part of ICL, itself later purchased by Fujitsu.
This post is intended to honour David Caminer, as a pioneer of automated business decision-making.

Banking on Linda

Published by peter on 2008-06-28 in Decision theory, Probability theory and Uncertainty. 0 Comments

Over at “This Blog Sits”, Grant McCracken has a nice post about a paradigm example often used in mainstream economics to chastise everyday human reasoners. A nice discussion has developed. I thought to re-post one of my comments, which I do here:

“The first point — which should be obvious to anyone who deals professionally with probability, but often seems not — is that the answer to a problem involving uncertainty depends very crucially on its mathematical formulation. We are given a situation expressed in ordinary English words and asked to use it to make a judgment. The probability theorists have arrived at a way of translating such situations from natural human language into a formal mathematical language, and using this formalism, to arrive at an answer to the situation which they deem correct. However, natural language may be imprecise (as in the example, as gek notes). Imprecision of natural language is a key reason for attempting a translation into a formal language, since doing so can clarify what is vague or ambiguous. But imprecision also means that there may be more than one reasonable translation of the same problem situation, even if we all agreed on what formal language to use and on how to do the translation. There may in fact be more than one correct answer.
There is much of background relevance here that may not be known to everyone, First, note that it took about 250 years from the first mathematical formulations of uncertainty using probability (in the 1660s) to reach a sort-of consensus on a set of mathematical axioms for probability theory (the standard axioms, due to Andrei Kolmogorov, in the 1920s).   By contrast, the differential calculus, invented about the same time as Probability in the 17th century, was already rigorously formalized (using epsilon-delta arguments)  by the mid-19th century.   Dealing formally with uncertainty is hard, and intuitions differ greatly, even for the mathematically adept.
Second, even now, the Kolmogorov axioms are not uncontested. Although it often comes as a surprise to statisticians and mathematicians, there is a whole community of intelligent, mathematically-adept people in Artificial Intelligence who prefer to use alternative formalisms to probability theory, at least for some problem domains. These alternatives (such as Dempster-Shafer theory and possibility theory) are preferred to probability theory because they are more expressive (more situations can be adequately represented) and because they are easier to manipulate for some types of problems than probability theory. Let no one believe, then, that probability theory is accepted by every mathematically-adept expert who works with uncertainty.
Historical aside: In fact, ever since the 1660s, there has been a consistent minority of people dissenting from the standard view of probability theory, a minority which has mostly been erased from the textbooks. Typically, these dissidents have tried unsuccessfully to apply probability theory to real-world problems, such as those encountered by judges and juries (eg, Leibniz in the 17th century), doctors (eg, von Kries in the 19th), business investors (eg, Shackle in the 20th), and now intelligent computer systems (since the 1970s). One can have an entire university education in mathematical statistics, as I did, and never hear mention of this dissenting stream. A science that was confident of its own foundations would surely not need to suppress alternative views.
Third, intelligent, expert, mathematically-adept people who work with uncertainty do not even yet agree on what the notion of “probability” means, or to what it may validly apply. Donald Gillies, a professor of philosophy at the University of London, wrote a nice book, Philosophical Theories of Probability, which outlines the main alternative interpretations. A key difference of opinion concerns the scope of probability expressions (eg, over which types of natural language statements may one validly apply the translation mechanism). Note that Gillies wrote his book 70-some years after Kolmogorov’s axioms. In addition, there are other social or cultural factors, usually ignored by mathematically-adept experts, which may inform one’s interpretations of uncertainty and probability. A view that the universe is deterministic, or that one’s spiritual fate is pre-determined before birth, may be inconsistent with any of these interpretations of uncertainty, for instance. I have yet to see a Taoist theory of uncertainty, but I am sure it would differ from anything developed so far.
I write this comment to give some context to our discussion. Mainstream economists and statisticians are fond of castigating ordinary people for being confused or for acting irrationally when faced with situations involving uncertainty, merely because the judgements of ordinary people do not always conform to the Kolmogorov axioms and the deductive consequences of these axioms. It is surely unreasonable to cast such aspersions when experts themselves disagree on what probability is, to what statements probabilities may be validly applied, and on how uncertainty should be formally represented.
Reference:
Donald Gillies [2000]: Philosophical Theories of Probability. (London, UK: Routledge)

Macro-economic models

Published by peter on 2008-05-13 in Decision theory, Economics and Forecasting. 0 Comments

The New Zealand-born economist, Bill Phillips, is best known for identifying an empirical relationship between a country’s inflation rate and its unemployment, the so-called Phillips curve.  However, before becoming an economist, Phillips had been an engineer, and in 1949 he built one of the first models of a national economy, the MONIAC.  MONIAC used flows of coloured water to represent money flows through an economy, and perhaps explains (or is a reflection of) traditional economics’ obsession with distinguishing stocks from flows.
In the 1970s, the Australian cartoonist Bruce Petty also built a physical model of a national economy, but this time with seats for several human operators, representing variously The Government, The Unions, Big Business, etc.   Instead of the hydraulic flows used by Phillips, Petty’s model used mechanical levers and pulleys, which impacted in convoluted ways on the machine and on the other operators.   This model looked something built by Heath Robinson or Rube Goldberg, and was immense fun to watch it at work.   I’ve not yet been able to find a video of Petty’s model at work.

Sexapedalianism

Published by peter on 2008-04-13 in Culture, Decision theory, Economics and Forecasting. 0 Comments

Statistician Dennis Lindley wrote a book called “Making Decisions” which included the stunningly-arrogant sentence: “The main conclusion [of this book] is that there is essentially only one way to reach a decision sensibly.” He justifies this outrageous claim, contrary to all human experience and a moment’s reflection, by saying that, “any deviation from the precepts is liable to lead the decision-maker into procedures which are demonstrably absurd — or as we shall say, incoherent.” (page vii, second edition, 1985). There follows an account of maximum-expected utility decision theory, which is justified in the standard way using Dutch Book arguments (considerations of certain infinite gambles).

I have never trusted these Dutch Book arguments, first because we all live in a finite world, and so games in which one party is guaranteed to win after an infinitely-large time strike me as games selling pie-in-the-sky. Everyone is rich eventually when investing in a Ponzi scheme, also. And second, gambling is such a socially- and culturally-embedded practice that I cannot possibly conceive how it could be used to justify decision-making procedures claiming universal validity. (For a start, to gamble you need to believe that events in the universe are not pre-determined, something which perhaps half of humanity does not currently believe.) The statistician Cosma Shalizi over at Three-Toed Sloth has a nice parody of the advice of decision-theory ideologues here.

A: Hey, you over there, the one walking! You’re doing it wrong.
B: Excuse me?
A: You’re only using two feet! You should keep at least three of your six in contact with the ground at all times.
B: …
A: Look, it’s easily proved that’s the optimal way to walk. Otherwise you’d be unstable, and if you were walking past a Dutchman he could kick one of your legs with his clogs and knock you over and then lecture you on how to make pancakes.
B: What? Why a Dutchman?
A: You can’t trust the Dutch, they’re everywhere! Besides, every time you walk it’s really just like running the gauntlet at Schiphol.
B: It is?
A: Don’t change the subject! Walking like that you’re actually sessile!
B: I don’t seem to be rooted in place…
A: It’s a technical term. Look, it’s very simple, these are all implications of the axioms of the theory of optimal walking and you’re breaking them all. I can’t get over how immobile you are, walking like that.
B: “Immobile”?
A: Well, you’re not walking properly, are you?
B: Your theory seems to assume I have six legs.
A: Yes, exactly!
B: I only have two legs. It doesn’t describe what I do at all.
A: It’s a normative theory.
B: For something with six legs.
A: Yes.
B: I have two legs. Does your theory have any advice about how to walk on two legs?
A: Could you try crawling on your hands and knees?

The network is the consumer

Published by peter on 2008-03-24 in Advertising, Consumer Behaviour, Culture, Decision theory, Economics, Game theory, Joint-Action Society, Market planning and Marketing strategy. 0 Comments

Economists use the term network good to refer to a product or service where one user’s utility depends, at least partly, on the utility received by other users. A fax machine is an example, since being the sole owner of fax is of little value to anyone; only when others in your business network also own fax machines does owning one provide value to you. Thus, a rational consumer would determine his or her preferences for such a good only AFTER learning the preferences of others.   This runs counter to the standard model of decisions in economic decision theory, where consumers come to a purchase decision with their preferences pre-installed; for network goods, the preferences of rational consumers are formed instead in the course of the decision process itself, not determined beforehand.   Preferences are emergent phenomena, in the jargon of complex systems.

What I find interesting as a marketer is that ALL products and services have a network-good component. Even so-called commodities, such as natural resources or telecommunications bandwidth, can be subject to fashion and peer-group pressure in their demand.  You can’t get fired for buying IBM, was the old saying.   Sellers of so-called commodities such as coal or bauxite know that the buyers make their decisions, at least in part, on the basis of what other large buyers are deciding.  Lest any mainstream economist reading this disparage such consumer behaviour, note that in an environment of great uncertainty or instability, it can be perfectly rational to follow the crowd when making purchase decisions, since a group may have access to information that any one buyer does not know.  If you are buying coal from Australia for your steel plant in Japan, and you learn that your competitors are switching to buying coal from Brazil, then there could be good reasons for this; as they are your competitors, it may be difficult for you to discover what these good reasons are, and so imitation may be your most rational strategic response.

For any product and service with a network component, even the humblest, there are deep implications for marketing strategies and tactics.  For example, advertising may not merely provide information to potential consumers about the product and its features.  It can also assist potential consumers to infer the likely preferences of other consumers, and so to determine their own preferences. If an advertisement appeals to people like me, or people to whom I aspire to be like, then I can infer from this that those other people are likely to prefer the product being advertized, and thus I can determine my own preferences for it. Similarly, if the advertisement appeals to people I don’t aspire to be like, then I can infer from this that I won’t be subject to peer pressure or fashion trends, and can determine my preferences accordingly.

For several decades, the prevailing social paradigm to describe modern, western society has been that of The Information Society, and so, for example, advertising has been seen by many people primarily as a form of information transmission.  But, in my opinion, we in the west are entering an era where a different prevailing paradigm is appropriate, perhaps best called The Joint-Action Society;  advertising then is also assisting consumers to co-ordinate their preferences and their decisions.    I’ll talk more about the Joint-Action Society in a future post.