In a forthcoming paper in the AAMAS proceedings, Craig Boutilier introduces the concept of a compensation rule, which augments typical scoring rule payments to form a net proper scoring rule. One proper compensation rule adds a payment equal to the expert’s loss in utility between the principal’s optimal decision and the expert’s preferred decision at that probability reported. This turns out to be more generous than necessary to guarantee expected expert utility is non-negative, but it is the only compensation rule that ensures expert prefer participation over the principal’s default policy. If experts are uncertain about the policy mapping reports to decisions, compensation can be reduced, but not eliminated.

Developing any proper compensation rule depends on the principal having full knowledge of the expert’s utility. Due to the strength of this assumption, the paper helpfully provides bounds on an expert’s incentive to misreport, the degree of misreporting, and the resulting expected utility loss of the decision-maker. With these bounds in hand, compensation rules can be developed to minimize the expected damage of misreporting without explicitly conditioning on the expert’s bias.

Unlike in other recent papers addressing decision markets, Boutilier assumes a single underlying random variable that can be observed regardless of the decision taken. This works well for events like the weather, where rain can be observed whether or not a wedding is held in the park or in a banquent hall. If instead, a company wanted to choose which state to open a new branch in based on expected sales, the sales in Maryland are never observed when the branch is opened in Massachusetts. This restriction in setting means the decision-maker can rely on a deterministic policy, mapping forecasts to decisions, without incentive issues. Being free from unobservable counterfactuals also simplifies the implementation of this scheme as a market scoring rule. I suspect these market scoring rules could be implemented as cost-function-based market makers without much difficulty, though Boutilier doesn’t address this.

Market scoring rules, and their equivalent formulation as cost-function-based market makers, debuted in “Logarithmic market scoring rules for modular combinatorial information aggregation” by Robin Hanson, first circulated as a working paper in 2002 and published somewhat perfunctorily in 2007. Mechanisms that solved similar problems, like David Pennock’s dynamic pari-mutuel markets, came out around the same time, but Hanson’s innovation has shaped up to be the seminal advance in prediction market design.

At first glance, a market scoring rule is an almost trivial extension of typical scoring rule: each participant receives the difference between the score of his report and the score of the previous participant. This doesn’t affect incentive-compatibility or willingness to participate, because in the worse case, a participant could match the report of the previous agent and have no net payment. As a result, the sum of all the payments to participants telescope, leaving the sponsor of the market liable only for the difference in the scores of the last participant and some initial report.

Although developed in the context of a sequentially applied scoring rule, this system turns out to be equivalent to an automated market maker that sells shares of contingent securities. This feels more like a prediction market, but with some striking advantages. First, the prices of securities always form a coherent probability distribution by construction, simplifying interpretation. Second, the market has infinite liquidity because all transactions are conducted through the market-maker. Third, prices for all securities are updated whenever a sale or purchase is made. Together, these advantages mean markets for conjunctive or conditional events can be feasibly priced. Even if no one else ever trades on a joint security that Obama wins the 2012 presidential election and it snows in Washington DC on inauguration day, this security can be bought and the information expressed in the purchase percolates out to all other combinations of events.

The modern prediction market literature largely revolves around market-makers inspired by Hanson. A decade later, the logarithmic market-maker now has a air of classic elegance to it, in contrast to the seemingly primeval prior literature and the complex refinements that have followed.

Alternatively, cash rewards could give a person a boost in adopting a habit. If the payment is removed, but the habit has been established, rates of engagement could be higher than the baseline. Given the public policy interest in making or breaking habits like regular exercise or smoking, respectively, knowing whether payments have a positive or negative effects is vital. I’m agnostic whether public policy should encourage better lifestyles, but at the very least it should do no harm.

Charness and Gneezy (working paper) address crowding-out vs habit-formation by paying undergrads at two universities for gym attendance. In addition to a control, one group was required to attend the gym once to receive payment, while another was required to attend eight times in a month. If a participant did not attend the gym regularly prior to the intervention and was in the eight-time treatment, they went to the gym about 0.75 times more per week than the control after the reward period. This group also showed some health improvements. For everyone else, regulars or one-time, the intervention had no or slightly negative effect. So, with a positive, lasting effect for some and no apparent downside, monetary incentives for exercise might be worth considering. This may be due to the subjects acquiring a habit rather than losing one, because incentive programs for quitting smoking for instance lose effect once the payments stop.

As I make the transition from economics student to economics researcher, questions like these are at the front of my mind. What exactly are economists trying to accomplish? My current opinion is that, contra Friedman, economic theory is not about prediction. Instead economics models are frameworks for ex ante understanding and evaluation of counterfactuals. I see strong ties between economics and evolutionary biology. If anything, economic tools like game theory are better suited to evolution than their original domain.

(ht: MR)

“I didn’t set out to make cheese graters,” Mr. Grace, an engineer by education, said recently… “I thought I was making serious woodworking tools,” he continued. “To see them used in the kitchen, that was frankly a personal disappointment.”

“We laughed when people told us they were using our products in their kitchens,” recalled Microplane’s Web site and woodworking-products manager, Maria Grace, one of Richard Grace’s daughters. “But we didn’t turn down their orders.”

(hat tip: Kottke)

Flash videos: http://academicearth.org/courses/psychology-of-families-and-couples
RealPlayer videos and mp3s: http://www.oid.ucla.edu/webcasts/courses/2008-2009/2009spring/psychm176-1
Additional accompanying videos at: http://www.sscnet.ucla.edu/ssc/lederman/bradbury/bradbury.html (Based on the first few, these videos are not that interesting and don’t add much. Despite being less than ten minutes each, my attention wandered quickly.)

*   *   *

Lecture 1: Course Introduction

In this lecture, Karney defines intimate relationships, points out how important they are in our lives, and identifies the big mystery in the field. To him, the really interesting question about love is why it changes over time,  possibly despite our desires for it to stay the same.

04:00 — Interdependence as a measure of whether a relationship exists; the degree to which the actions of one entity affects the outcomes of another determines the degree the two are related.
06:30 — Dimensions of interdependence: frequency of contact, duration of contact, diversity of types of interactions, direction of influence (uni- vs. bi-directional), and strength of influence
13:30 — Hence, a close relationship is one of strong, frequent, and diverse interdependence that lasts over a considerable period of time.
14:30 — Close relationships include family, friends, and intimate relationships, but this course only focuses on intimate ones, so what is intimacy?
16:30 — Sexual potential is a necessary, but not sufficient, component.
18:30 — Fidelity: you don’t care as much if your friends have other friends, but intimate partners are treated as special and unique, with a possessive element.
23:00 — Intimate relations are really, really powerful. Constitute our highest highs and lowest lows, to the point of affecting our health and longevity.
27:30 — Lying and deception: white lies are told to strangers, but the big lies are saved for close partners. If a wife is murdered, the first place to look is the husband.
31:00 — Holding a partner’s hand reduced the threat of an electric shock delivered in a brain scanner, and the stronger the relationship, the greater the effect.
33:00 — Couples that are nicer to each other tend to live longer.
35:00 — Why do some relationships last and some don’t?
36:30 — Over 50% of first marriages dissolve through divorce or legal separation.
37:40 — Divorce rate is highest in the second year, and declines steadily from there.
39:00 — Younger age of marriage correlates with higher rates of divorce, as well as remarriages.
41:00 — Rather than ask what prevents divorce, maybe we should care about what makes a relationship satisfying.
43:00 — However, we have a good sense of what makes a marriage satisfying: trust, humor, good sex, chemistry. The huge mystery is why things change.

*   *   *

Lecture 2: Methods of Studying Families and Couples

To objectively study an abstract topic like love, researchers must identify a concrete representation to measure. Methods of study include self-reports and direct observation, each with their own benefits and drawbacks. Because relationships are so important, research must be conducted carefully to remain ethical, but the potential benefits of understanding are enormous.

09:30 — Relationship science measures constructs, i.e. abstract ideas like love, commitment, or satisfaction. These can’t be studied directly, so a construct is operationalizalized by translating it into concrete terms.
14:30 — Health is a construct, but number of visits to a doctors is an operationalization.
15:00 — Self-reports are one possible measure of love. Only way to discover some things.
17:30 — Zick Rubin constructed one of the first love scales, a list of 13 questions for the respondent to rate agreement on a scale from 1 to 9.
23:00 — Self-reports are easy to conduct, cheap, and quick, but people are apt to lie or simply not be aware of the truth.
26:00 — Couples were asked to check a list of activities they did together over the last 24 hours, and agreement only occurred 50% of the time.
29:00 — Another strategy is systematic observation of verbal communication, emotional expressions, length of eye gaze, or biological responses.
47:00 — Observation can be very relevant (if you choose the metric well), has lots of detail, and requires concrete definitions.
48:45 — On the other hand, it’s very expensive, must be done with the subject aware they are being observed, and we don’t always know what a behavior means to the people involved.
54:30 — Cross-sectional research helps with description of what traits are associated with others. Longitudinal research helps with prediction.
57:00 — Type of research can lead to contradictory results.
59:00 — Cross-sectional data showed marital happiness increased steadily from 20 years on, but longitudinal data showed satisfaction declining through married life.
61:00 — Who are we studying?
65:00 — How ethical is the research?
68:00 — A study involving one group being repeatedly questioned and another only at the beginning and the end, and intense study magnified existing feelings. Good relationships became better and bad ones became worse.

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Lecture 3: Theories of Intimate Relationships, Part I

Theories are like maps: they are better to the extent they correspond with reality, but also leave out details. They provide direction for further research by organizing existing knowledge. Two prominent theories are based on evolutionary history and childhood attachment. Evolutionary psychology looks to selection pressures in our ancestral environment that are carried over into the modern world. Attachment theory says that the mental models we build in childhood of how loved ones treat us are also applied in adulthood to romantic partners.

Note: A UC San Diego class was mentioned where the students did exercises designed to make them fall in love with paired partner. The class was taught by Robert Epstein, who was profiled in this article. Epstein wrote an article in Scientific American Mind on how we fall in love, along with descriptions of the exercises. Some include embracing and synchronizing breathing, gazing into each others’ eyes for two minutes, mimicking each others’ actions, sharing secrets, standing four feet apart and moving slightly closer every ten seconds until almost touching, and placing palms close, but not touching, and trying to sense the other person. Each is inspired by research, and said to increase closeness even with complete strangers.

02:00 — We develop personal theories about love to navigate our own relationships.
03:30 — “Science is built up of facts, as a house is built of stones; but an accumulation of facts is no more a science than a heap of stones is a house.” — Henri Poincaré
07:00 — What does a good theory do? Organizes existing knowledge, explains in a parsimonious way, makes specific predictions, and guides measurement decisions.
12:30 — A good theory of relationships should encompass the full range of predictors, specify mechanisms of change, and account for variability between between couples and within couples over time.
17:00 — Theories can be organized by how far they look back into human history.
17:30 — Evolutionary psychology looks for motives when seeking and dealing with a partner in ancestral environments. “Human seek specific mates to solve specific adaptive problems that their ancestors confronted during the source of human evolution.” — David Buss.
24:30 — Psychological mechanisms are the tendency to think and respond to a certain situation in a certain way, and are passed down just like physical traits.
30:00 — Our psychological mechanisms is adapted to living on the African savannah, not modern society.
33:00 — Theory of Parental Investment posits that the particular facts of human reproduction — women bearing a small number of children that require a high investment from the mother, but not necessarily the father — exerts the most influence on sexual preferences.
37:00 — Women should prefer men capable of protecting them and men should prefer women who are more fertile because of the differential costs.
40:40 — David Buss showed women find emotional infidelity worse than sexual infidelity, and vice versa for men.
45:00 — This result held internationally, across cultures and levels of development.
49:00 — The evolutionarily instilled psychological mechanisms are not necessarily conscious.
54:40 — Does the theory only pick out obvious predictions? A striking result: Ovulating women should be more sensitive to cues of reproductive fitness. To test this, college men were tested for physical symmetry, a known marker of genetic health. They were given clean t-shirts to wear while sleeping. Women who were ovulating preferred the scent of more symmetric men, even though other women couldn’t discern the difference.
61:00 — However, evolutionary theory doesn’t account well for differences within genders or how relationships change once they are formed.
62:00 — Attachment theory looks into our personal past, to the relationships we formed as children with our parents.
66:00 — From those early relationships, we develop mental models about whether others will be available to care for us, which are also applied to relationships.
67:00 — Mary Ainsworth showed babies tend to have three styles of attachment: secure, avoidant, and anxious/ambivalent. These ways of coping continue into adulthood.
69:00 — Same system might have evolved to deal with parent-child and lover relationships.
72:00 — Attachment theory can explain where our standards and expectations for intimacy come from and why we end up in the same types of relationships.

*   *   *

Lecture 4: Theories of Intimate Relationships, Part II

Other theories of love include Social Exchange Theory, Social Learning Theory, and Social Ecological Theory. The first says partners evaluate relationships based on their net rewards and costs. The second focuses on how partners respond to each others’ actions, with behavior being conditioned by repeated interaction. The last looks to external influences like culture or major events to explain how relationships differ and why they change.

05:30 — Best prediction of poverty is recent divorce.
09:30 — Social Exchange Theory posits partners evaluate the rewards and costs ssociated with being in the relationship, along with the alternatives. Recognizes that satisfaction with a relationship is not the only net outcome of the relationship.
14:00 — Rewards include material gains, status, comfort …
15:00 — Costs include pain, lost opportunities …
16:30 — Satisfaction is the difference between the outcome and expectations. Dependency is the difference between the outcome and the alternatives. The two are correlated, but could be very different.
23:00 — The theory predicts break-ups and divorce. Between 20-40% of people who file for divorce never follow through, possibly because the costs become more salient.
26:30 — Explains why some distress relationships continue, but still doesn’t address change well.
32:30 — Social Learning Theory says our behavior is molded and shaped within relationships. Rewarding and punishing interactions affect later behavior and judgments.
37:00 — Behaviors accumulate. Negative behaviors might be met with rewards in the short-term, but bring long-term costs. Nagging might bring desired actions right now, but in the future, communication might jump to resistance and yelling.
43:00 — Capability to spontaneously generate positive emotion can sustain a relationship.
45:00 — Reactions to behaviors mediated by cognitive models; same action might be interpreted differently at different times or by different people.
48:00 — Social Learning suggests researchers should observe actual interactions.
51:00 — Good couples have conflict, but can prevent negative feedback loops that make the conflict grow and continue.
53:00 — The theory suggests interventions can successfully improve relationships.
55:30 — Explains how relationships change through accumulated negativity, but leaves out where negative behavior originally comes from and how spontaneous improvement improves.
58:00 — Last theory is Social Ecological Theory, which looks to the stresses, supports, and constraints in the surrounding environment.
66:30 — Suggests culture and SES should be taken seriously.

Three five-word summaries:
Sam feels lot of guilt.
Poor writer envies rich publishers.
Johnson equal to forty Frenchmen.

While this book is exemplary as a biography, I lost interest half way through. Johnson’s character and relationships are what shine through, rather than the actual course of his life, so while this was a worthwhile read, diminishing returns set in very quickly. Feel free to skip around rather than stick to the chronological ordering.

New York : Basic Books, 2008. xiv+528 pp.

* * *

Excerpts:
p. 22 — “He devoured books with deadly seriousness, in the same way that he devoured food. He’d often keep a book on his lap while dining, a habit that Boswell cheekily compared to a dog holding a bone in its paws while chewing on scraps.”
p. 24 — “Johnson believed, like that other uneasy wanderer D.H. Lawrence, ‘When in doubt, move.’ ”
p. 29 — “In Johnson’s time, when the average height of an Englishman was five feet, five inches, only three men in a thousand reached his impressive height of five feet, eleven.”
p. 40 — “Aware that he’d wasted time during his first year, he promised in his diary of October 1729, the beginning of his second, to ‘bid farewell to Sloth, being resolved henceforth not to listen to her syren strains.’ But he cast this resolution in mythological rather than personal terms and, like many a vow made throughout his life, was unable to keep it.”
p.  46 — “In a famous pronouncement in Rasselas, he declared, ‘of the uncertainties of our present state, the most dreadful and alarming is the uncertain continuance of reason.’ Johnson — renowned, ironically, for his uncommon sense, sound judgment and rational thought — was terrified that his rational faculty would weaken and he would lapse into permanent darkness.
p. 48 — “The direst danger was solitude, which made his mind stagnant and morbid. His great aim in life was to escape from himself, and he tried to prevent mental disease by constant company.”

• Are communicators: In particular, they tend to write for non-specialists. A selection effect is at work here; as a young grad student, I read specialist-oriented authors, but I haven’t become intimately familiar with many yet. Even so, writing for an intelligent popular audience forces clarity. My icons’ writing communicates. That may seem tautological, but too many authors send messages off into the void without being received. If the audience fails to understand, no communication has taken place. I don’t necessarily aspire to being widely read, but when I write or speak, I want my point to get across.
• Have a sense of humor: They are clever and willing to look on the lighter side of life. Confidence in their work is a contributing factor. None are so worried about being taken seriously that their work is dry, dour, and formal. They are unafraid to let their personality come out. There is also a hint of optimism. While DFW had an occasional melancholy tone, the sarcasm endemic in modern humor is missing from all of them.
• Have high standards: The important counterpoint to this aspect is a willingness to continue producing until their standard is met. I tend to shut projects down that set off my crap-meter. This blog is first and foremost a means for me to produce, but I still plan to attend to the good example set by these nine regarding quality.
• Are analytical: Left-brained and often technical, they share the distinctive style of thinking associated with math, science, and philosophy.
• Have diverse interests: They are known not just for writing on a variety of subjects, but weaving them together in defiance of subject and genre. While specialization is still a key to success, they do so by creating their own niche, rather than burrowing into an old subject.  The best way to be a specialist is to be sui generis.
• Are foxy: In Berlin’s sense and since revived by Tetlock, foxes are likely to see complexity and nuance in the world, in contrast to hedgehogs who subscribe to overarching theories. My icons’ multiple influences and broad interests give them an appreciation of the competing explanations of the world. They tend to be more cautious and more willing to change their mind. They advance policies, ideas, and methodologies while remaining non-ideological.

The last trait explains why Robin Hanson didn’t quite make the cut. His public persona¹ is highly centered around a couple big ideas like signaling and near/far modes of thinking. Because big ideas are, by their nature, widely applicable, I frequently find myself asking what Hanson would think of a behavior or phenomenon. So, while I try to emulate foxes, one of the best ways to do so is collecting a large collection of hedgehog shoulder-daemons ready to give their explanation.

* * *

1: In a recent interview by Colin Marshall, Hanson explains he is much more of a generalist in everyday life, but thinks promoting a small core of ideas publicly will have the highest impact.

In order, from left to right and top to bottom,

• David Foster Wallace: Novelist and essayist. Though I came across his work in the post-death coverage, I did not realize DFW had died until after devouring A Supposedly Fun Thing I’ll Never Do Again and  Consider the Lobster. His humor, descriptive power, and mathematical background left me grasping for any work of his I could get my hands on.
• Colin Marshall: Broadcaster and blogger. I have a feeling Marshall would object to being placed on anyone’s icon list. Nevertheless, I admire his ambition, high personal standards, will to produce, dedication to his aesthetic, and desire to improve himself. He might not have much name recognition now, but I expect his personal brand will rise sharply in value over time.
• Eliezer Yudkowsky: AI theorist and blogger. While still at Overcoming Bias, Yudkowsky wrote daily essays for over two years, explaining everything from rationality and consciousness to quantum mechanics and ethics. Besides the high volume, his posts maintained a surprisingly high signal-to-noise ratio. His knack for coining phrases and illustrative stories makes the concepts stick, ready to be deployed in everyday thought.
• Ben Casnocha: Entrepreneur and blogger. In addition to the obvious admiration he deserves for venturing into business so young, Casnocha strikes me as thoughtful, caring, and optimistic to an uncommon degree. His initiative and demeanor are both worth emulating.
• Tyler Cowen: Economist and blogger. This man deserves the central position. He exemplifies Berlin’s fox, drawing insight from a vast array of sources and unwilling to hew to a single explanation. Economics, cuisine, history, literature, psychology, philosophy, and travel all play side by side in his works. Of anyone I hope to one day be compared to, it is Tyler Cowen.
• Douglas Hofstadter: Cognitive scientist and author. Gödel, Escher, Bach is his best known work, but Le Ton beau de Marot is even more stunning. Hofstadter’s attention to quality, down to the page breaks in his books, is awesome. His ideas are deep and shook many of my previous beliefs about language and thought to the core. He introduced me to Lisp, a language that is still special to me. His works show the possiblities when you are truly committed to a project. I’m still amazed at the number of spine-tingling moments per page his writing produces.
• Umberto Eco: Novelist and essayist. Eco’s novels have a depth to them that astounds me. Additionally, he is a public intellectual who remains surprisingly free from the fuzzy-headed thinking usually associated with that status.
• Donald Knuth: Computer scientist, programmer, and typographer. Despite its name, Knuth’s famed Art of Computer Programming is a favorite math book of mine. I admire his tenacity in pursuing that project. Begun in 1968, the work continues into the present. Talk about long-term vision. In an effort to ensure it was done right, he invented TeX along the way, which I am grateful for. I’ve been known to put math books down solely because they weren’t typeset in TeX.
• Paul Graham: Programmer, essayist, and venture capitalist. Graham gains bonus points for promoting Lisp, but his essays are the main target of my admiration. His writing is a paragon of relevance and clarity. He also works to foster the next generation of entrepreneurs through his venture capital firm Y Combinator.

Other close runners-up include Robin Hanson, Terry Pratchett, Seth Roberts, Edward Tufte, John Conway, and Dan Dennett.