Archivio per maggio 2015

30
Mag
15

Why Good People Do Bad Things AND How To Stop Them – PsyBlog

See on Scoop.itBounded Rationality and Beyond

How to stop people carrying out unethical behaviours. 

People who anticipate temptation are less likely to do bad things, a new study finds. The research also found that when people thought unethical behaviour reflected poorly on them, they also resisted. Dr Oliver Sheldon, one of the study’s authors, said:

“People often think that bad people do bad things and good people do good things, and that unethical behavior just comes down to character.

But most people behave dishonestly sometimes, and frequently, this may have more to do with the situation and how people view their own unethical behavior than character, per se.”

See on spring.org.uk

30
Mag
15

Chances of going to college based on parent’s income – Decision Science News

See on Scoop.itBounded Rationality and Beyond

What is the chance of a kid going to college based on parent’s income?

The amazing team at the New York Times have a “You Draw It” feature in The Upshot in which readers try their hands at drawing a graph. The graph should show the probability of a child going to college based on their parents’ percentile in the income distribution.

As a cool added feature, after people took their guesses, they could see, in shades of red, the other guesses people had taken and compare it to the actual graph.

SPOILER ALERT: You can see the true answer at the bottom of this post. If you want to try your hand at guessing, click through to the NY Times and guess before proceeding.

One way to interpret this relationship is that for every percentile increase in parental income, the probability of college enrollment increases by a constant amount, which might seem somewhat surprising. Even the NY Times editors were surprised by this linear relationship, and the data they collected showed that other people were, too.

Jake Hofman and I wondered “what if people didn’t take the X-axis literally, what if they thought about it as something like log income or income (instead of percentile in the income distribution)?” Percentiles are tricky. They’re buckets with equal numbers of people, but those people can have very different incomes. What would the graph look like if the X-axis were income? Would this relationship be more intuitive to readers?

See on decisionsciencenews.com

30
Mag
15

Analytical Computation of the Epidemic Threshold on Temporal Networks

See on Scoop.itBounded Rationality and Beyond

The time variation of contacts in a networked system may fundamentally alter the properties of spreading processes and affect the condition for large-scale propagation, as encoded in the epidemic threshold. Despite the great interest in the problem for the physics, applied mathematics, computer science, and epidemiology communities, a full theoretical understanding is still missing and currently limited to the cases where the time-scale separation holds between spreading and network dynamics or to specific temporal network models. We consider a Markov chain description of the susceptible-infectious-susceptible process on an arbitrary temporal network. By adopting a multilayer perspective, we develop a general analytical derivation of the epidemic threshold in terms of the spectral radius of a matrix that encodes both network structure and disease dynamics. The accuracy of the approach is confirmed on a set of temporal models and empirical networks and against numerical results. In addition, we explore how the threshold changes when varying the overall time of observation of the temporal network, so as to provide insights on the optimal time window for data collection of empirical temporal networked systems. Our framework is of both fundamental and practical interest, as it offers novel understanding of the interplay between temporal networks and spreading dynamics.

Analytical Computation of the Epidemic Threshold on Temporal Networks
Eugenio Valdano, Luca Ferreri, Chiara Poletto, and Vittoria Colizza
Phys. Rev. X 5, 021005 (2015)

http://dx.doi.org/10.1103/PhysRevX.5.021005

See on journals.aps.org

30
Mag
15

Google a step closer to developing machines with human-like intelligence

See on Scoop.itGlobal Brain

An algorithm developed by Google is designed to encode thought, which could lead to computers with ‘common sense’ within a decade, says leading AI scientist

See on theguardian.com

30
Mag
15

The Behavioral Economics Diet: The Science of Killing a Bad Habit – Nir and Far

See on Scoop.itBounded Rationality and Beyond

The science of how taking a simple bet can increase your odds of changing a bad habit. 

Diets don’t work. Studies showthat temporary fixes to old habits actually make people gain weight. Essentially, the dieter’s brain is trained to gorge when off the diet and inevitably the weight returns.

In my previous essay, I shared the story of my father’s struggle with bad eating habits. He had put on weight over the last few decades and despite several attempts, he had trouble taking it off. In his late 60s he faces pre-diabetes and a daily ritual of taking a handful of pills.

But over the last five months, something has changed. He’s found a new way to resist the temptation of the food he’s been trying to stop eating for years.

See on snip.ly

29
Mag
15

Behavioural economics: How to ‘nudge’ customers and influence people

See on Scoop.itBounded Rationality and Beyond

Behavioural economics posits that all behaviour, including in business, is shaped by irrational and unconscious influences such as bias, social pressure and cognitive inertia. The notion of psychology as a driver of economic action is not new: As an academic discipline behavioural economics dates back to the 1970s, and the foundational principle back at least to Adam Smith’s The Theory of Moral Sentiments.Behavioural economics has, however, only in recent years found widespread currency within the business world, spurred by a plethora of bestsellers, includingThinking Fast and Slow (2011) by Daniel Kahneman and Predictably Irrational (2oo8) by Dan Ariely. Increased interest from the business community is due to the insights gleaned from the discipline, which have been used to successfully “nudge” customer behaviour in a variety of sectors, such as wealth management, insurance, customer products and retail. Specifically, behavioural economics has been used by product managers to guide consumers toward certain product choices (i.e., “choice design”), by marketers to develop brochures and Web sites that more persuasively communicate marketing messages and by service managers to design better support experiences.

The field can provide hundreds of potential “triggers” to augment behaviour, depending on the business objective, situation and context. Psychologists Robert Cialdini, Noah Goldstein and Steve Martin identify 50 different possible applications in The Small Big: Small Changes That Spark Big Influence (2014).

See on business.financialpost.com

29
Mag
15

How Economists Work and Think: Review of The World in the Model by Mary S. Morgan, Cambridge, Cambridge University Press, 2012

See on Scoop.itBounded Rationality and Beyond

How Economists Work and Think: Review of The World in the Model by Mary S. Morgan, Cambridge, Cambridge University Press, 2012

The World in the Model: How Economists Work and Think  is a timely and important book. Fordecades now, but especially in the years following the financial crisis, economistsÕ modelingpractices have been the target of a sustained critique. Under slogans such as Òeconomics isabout people, not curves,Ó critics have attacked the use of formal and abstract models ineconomics in favor of the careful historical study of observable social phenomena. If the battlelines look familiar, it may be because they largely mirror those drawn during theMethod enstreit  a century ago. The critique has succeeded in inspiring a series of movements among economics students in Spain, the UK, and elsewhere, but in spite of its venerable history appears to have been largely ineffective in changing the minds of practicing economists. To them, it does not reflect more than a superficial understanding of what they aretrying to accomplish by means of their modeling practices; nor does it propose what seems tothem a workable alternative approach.Meanwhile, philosophical literature on models and modeling in economics often fallsshort. For one thing, many contributions to this literature fail at the outset to adequatelydelineate the extension of the word model, thereby leaving it open to what sort of thing, precisely, the analysis is supposed to apply. Moreover, much of this literature depends to agreat extent on metaphors that are immediately appealing, but whose exact implicationsremain unspecified. For both these reasons, philosophical accounts of models and modelingare often hard to assess. And, more importantly in the present context, they don’t shed as much light as they should on contemporary economic modeling practices, their strengths and weaknesses.
See on academia.edu




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