WHEN , IN THE late 1970s, desktop computers suddenly made it simple to solve non-linear equations, scientists in ﬁelds from ﬂuid dynamics to ecosystem studies began modelling their subjects with them. This was an earth-shaking development. Earlier, scientists could only model their subjects with relatively simpler, quicker-to-solve linear equations. With linear equations, ‘the sum of two equations is again a solution’. 1 A small cause will create a small effect, and a large cause, a large effect. They were the kinds of equations that Isaac Newton used to perfect his physics. Combined with René Descartes’ philosophy, Newton’s physics created a world view in which independent objects interacted according to a set of ‘Universal Laws of Nature’ in linear processes of cause-and-effect. Johannes Kepler had called the resulting world a ‘Clockwork Universe’. 2 However, as successful the resulting scientiﬁc paradigm proved to be, most of life is non-linear. After all, it took only a few small shifts in the genes of bacteria in Chinese fowl sometime around 1917 to cause the inﬂuenza epidemic that ravaged America and Europe at the end of World War I. Small causes can have enormous effects. But non-linear equations were much more time-consuming to solve. With the desktop computer revolution of the late 1970s, it was suddenly possible for scientists to model their topics with non-linear equations, with which small causes can have large effects. The scientists using them quickly made two discoveries. First, non-linear equations created a more accurate picture of how things in the world behaved.By Dmitri Bondarenko and Ken Baskin in History and Cultural History. Big History emerged as part of this non-linear way of understanding the world. What we discovered in working together is that the insights of complexity theory, which studies the
Abstract Despite the clear fitness conse?uences of animal decisions, the science of animal decision ma-ing in evolutionary iology is underdeveloped compared to decision science in human psychology. Specifically, the field lac-s a conceptual frameor- that defines and descries the relevant components of a decision, leading to imprecise language and concepts. The @Audgment and decision ma-ing (
Executive cognitive functions like working memory determine the success or failure of a wide variety of different cognitive tasks. Estimation of constructs like working memory load or memory capacity from neurophysiological or psychophysiological signals would enable adaptive systems to respond to cognitive states experienced by an operator and trigger responses designed to support task performance (e.g. by simplifying the exercises of a tutor system, or by shutting down distractions from the mobile phone). The determination of cognitive states like working memory load is also useful for automated testing/assessment, for usability evaluation and for tutoring applications. While there exists a huge body of research work on neural and physiological correlates of cognitive functions like working memory activity, fewer publications deal with the application of this research with respect to single-trial detection and real-time estimation of cognitive functions in complex, realistic scenarios. Single-trial classifiers based on brain activity measurements such as EEG, fNIRS or physiological signals such as EDA, ECG, BVP or Eyetracking have the potential to classify affective or cognitive states based upon short segments of data. For this purpose, signal processing and machine learning techniques need to be developed and transferred to real-world user interfaces.In this research topic, we are looking for: (1) studies in complex, realistic scenarios that specifically deal wit
Think of Halloween and scares probably are front of mind. Trick or treat. Ghouls and carved pumpkins. In share markets, it appears investor behaviour can also be skewed by scares that accompany dark nights and downbeat emotions associated with the end of summer in the Northern Hemisphere. The phrases “sell in May” (ideally, when prices are high) and “buy on Halloween” (if prices are in a dip) are well known. This “Halloween indicator” will not work every year but research suggests there is some evidence to back it up, on average. It is one of a range of calendar effects that some believe exist in financial markets.
La generazione di una qualsiasi decisione, dall’acquisto di un prodotto a scelte più complesse, attiva una complessa rete neuronale per il processamento delle informazioni in parallelo e in serie, che è influenzabile da molte variabili esterne e interne. Oggi vogliamo approfondire il Nudge nel processo di decision making. Negli articoli precedenti abbiamo visto come le decisioni degli esseri umani sono fortemente influenzate dal pensare implicito e dall’effetto framing, come le informazioni sono presentate sia a livello macro dai contesti socio-culturali di riferimento sia dalla presentazione degli stimoli, e come le neuroscienze ne evidenziano la complessità del substrato dei percorsi cerebrali, cognitivi ed emotivi, impliciti e razionali. La ricerca scientifica ci permette di valutare come reagisce la mente umana di fronte a determinate condizioni e identificare i processi decisionali che attivano le scelte. Conoscendo i principi del funzionamento della mente, è possibile usare delle strategie per creare un contesto che favorisca la reazione di coinvolgimento psicologico di “engagement” oppure è possibile sollecitare a compiere determinati comportamenti con dei “ suggerimenti gentili”, sia nel contesto privato sia in quello pubblico.
A neuroscientist explains the cognitive effects of high-intensity workouts.
When I run, I think about everything. My mind wanders here and there and by the time I’m done, it often feels like I’ve found solutions for every problem I’ve ever had. There’s likely some truth to that feeling, too: Brain-imaging studies have shown that after about 30 minutes of aerobic exercise, activity in the brain’s “frontal executive network system” increases; this is the region of the brain associated with things like problem-solving, decision-making, and planning. It’s empirical evidence for something every runner already knows — that the activity can help you think through the things that are troubling you. It’s why I love it. It’s also why I hate it. Sometimes, I just want to shut my mind up and lock the world out, just for a little while. This year has been a long and weird one, and so I don’t think it’s a coincidence that I have somewhat recently embraced a rather specific new kind of workout: You could call it speedwork, or intervals, or the ridiculously named “fartlek” — in short, I am lately into running very, very fast. If long, slow runs provide the opportunity to think about everything, short, speedy runs give me, blessedly, a few brief moments to think about nothing. It’s like my body is working so hard that it requires the full attention of my mind, too. RELATED STORIES How Neuroscientists Explain the Mind-Clearing Magic of Running How Running and Meditation Change the Brains of the Depressed
Why You Should Bet Against Your Candidate When your favorite sports team is defeated, you’re disappointed, even dismayed. The same is true when your preferred political candidate doesn’t win. It hurts when your side loses. Fortunately, you can insure yourself against such unhappiness: just place a bet for your side to lose. This strategy, which…
Nobel laureate Daniel Kahneman and psychologist Gary Klein debate the power and perils of intuition for senior executives. For two scholars representing opposing schools of thought, Daniel Kahneman and Gary Klein find a surprising amount of common ground. Kahneman, a psychologist, won the Nobel Prize in economics in 2002 for prospect theory, which helps explain the sometimes counterintuitive choices people make under uncertainty. Klein, a senior scientist at MacroCognition, has focused on the power of intuition to support good decision making in high-pressure environments, such as firefighting and intensive-care units. In a September 2009 American Psychology article titled “Conditions for intuitive expertise: A failure to disagree,” Kahneman and Klein debated the circumstances in which intuition would yield good decision making. In this interview with Olivier Sibony, a director in McKinsey’s Brussels office, and Dan Lovallo, a professor at the University of Sydney and an adviser to McKinsey, Kahneman and Klein explore the power and perils of intuition for senior executives.
Can the general public learn to deal with risk and uncertainty, or do authorities need to steer people’s choices in the right direction? Libertarian paternalists argue that results from psychological research show that our reasoning is systematically flawed and that we are hardly educable because our cognitive biases resemble stable visual illusions. For that reason, they maintain, authorities who know what is best for us need to step in and steer our behavior with the help of “nudges.” Nudges are nothing new, but justifying them on the basis of a latent irrationality is. In this article, I analyze the scientific evidence presented for such a justification. It suffers from narrow logical norms, that is, a misunderstanding of the nature of rational thinking, and from a confirmation bias, that is, selective reporting of research. These two flaws focus the blame on individuals’ minds rather than on external causes, such as industries that spend billions to nudge people into unhealthy behavior. I conclude that the claim that we are hardly educable lacks evidence and forecloses the true alternative to nudging: teaching people to become risk savvy.
Before doing so, executives should ask themselves two sets of questions. Good managers—even great ones—can make spectacularly bad choices. Some of them result from bad luck or poor timing, but a large body of research suggests that many are caused by cognitive and behavioral biases. While techniques to “debias” decision making do exist, it’s often difficult for executives, whose own biases may be part of the problem, to know when they are worth applying. In this article, we propose a simple, checklist-based approach that can help flag times when the decision-making process may have gone awry and interventions are necessary. Our early research, which we explain later, suggests that is the case roughly 75 percent of the time. Biases in action In our experience, two particular types of bias weigh heavily on the decisions of large corporations—confirmation bias and overconfidence bias. The former describes our unconscious tendency to attach more weight than we should to information that is consistent with our beliefs, hypotheses, and recent experiences and to discount information that contradicts them. Overconfidence bias frequently makes executives misjudge their own abilities, as well as the competencies of the business. It leads them to take risks they should not take, in the mistaken belief that they will be able to control outcomes. The combination of misreading the environment and overestimating skill and control can lead to dire consequences. Consider, for instance, a decision made by Blockbuster, the video-rental giant, in the spring of 2000. A promising start-up approached Blockbuster’s management with an offer to sell itself for $50 million and join forces to create a “click-and-mortar” video-rental model. Its name? Netflix. As a former Netflix executive recalled, Blockbuster “just about laughed [us] out of their office.”1 Netflix is now worth over $25 billion. Blockbuster filed for bankruptcy in 2010 and has since been liquidated.
In cognitive science, the rational analysis framework allowsmodelling of how physical and social environments imposeinformation-processing demands onto cognitive systems. Inhumans, for example, past social contact among individualspredicts their future contact with linear and power functions.These features of the human environment constrain theoptimal way to remember information and probably shapehow memory records are retained and retrieved. We offera primer on how biologists can apply rational analysis tostudy animal behaviour. Using chimpanzees ( Pan troglodytes )as a case study, we modelled 19 years of observationaldata on their social contact patterns. Much like humans,the frequency of past encounters in chimpanzees linearlypredictedfutureencounters,andtherecencyofpastencounterspredicted future encounters with a power function. Consistentwith the rational analyses carried out for human memory,these ﬁndings suggest that chimpanzee memory performanceshould reﬂect those environmental regularities. In re-analysingexisting chimpanzee memory data, we found that chimpanzeememory patterns mirrored their social contact patterns. Ourﬁndings hint that human and chimpanzee memory systemsmay have evolved to solve similar information-processingproblems. Overall, rational analysis offers novel theoreticaland methodological avenues for the comparative studyof cognition
What do predictive analytics and behavioral economics have in common? Quite a bit, as it turns out.
Two overdue sciences Near the end of Thinking, Fast and Slow, Daniel Kahneman wrote, “Whatever else it produces, an organization is a factory that produces judgments and decisions.”2 Judgments and decisions are at the core of two of the most significant intellectual trends of our time, and the one-word titles of their most successful popularizations have become their taglines. “Moneyball” is shorthand for applying data analytics to make more economically efficient decisions in business, health care, the public sector, and beyond. “Nudge” connotes the application of findings from psychology and behavioral economics to prompt people to make decisions that are consistent with their long-term goals. Other than the connection with decisions, the two domains might seem to have little in common. After all, analytics is typically discussed in terms of computer technology, machine learning algorithms, and (of course) big data. Behavioral nudges, on the other hand, concern human psychology. What do they have in common? When the ultimate goal is behavior change, predictive analytics and the science of behavioral nudges can serve as two parts of a greater, more effective whole.
It might sound strange, but unusual cues that actually distract you can make top reminders for that to-do list. When trying to save more money or pay off a debt, a carefully thought-out plan can really improve personal finances. But it all takes time – and it can be so easy to forget the detail, or otherwise not follow through with a strategy. There’s no foolproof way to remember everything, even when it’s to do with money; memories fade and present bias keeps the focus on the here and now. However, research by Todd Rogers at Harvard and Katherine Milkman of the University of Pennsylvania reveals that certain types of reminder work better than others – sometimes improving the ability to remember tasks on schedule by as much as 32%. Matching the right cues Rogers and Milkman found that making up unrelated, striking cues and matching them up with tasks we need to be reminded about can help. In a first small experiment, the team aimed to get people to remember a promise to donate to charity.
Human choices are remarkably susceptible to the manner in which options are presented. This so-called “framing effect” represents a striking violation of standard economic accounts of human rationality, although its underlying neurobiology is not understood. We found that the framing effect was specifically associated with amygdala activity, suggesting a key role for an emotional system in mediating decision biases. Moreover, across individuals, orbital and medial prefrontal cortex activity predicted a reduced susceptibility to the framing effect. This finding highlights the importance of incorporating emotional processes within models of human choice and suggests how the brain may modulate the effect of these biasing influences to approximate rationality.
L’attenzione è quel processo mentale che permette di elaborare una parte limitata d’informazioni del nostro mondo, selezionandola dall’enorme quantità di stimoli che ci circondano. Le risorse cognitive di un individuo sono limitate e riuscire ad elaborare solo le informazioni rilevanti è un meccanismo che abbiamo ereditato dai nostri antenati. Evoluzionisticamente parlando, permette di aumentare le probabilità di sopravvivenza. Nel mondo animale, identificare un predatore (o una preda) in tempi ridotti consente la messa in atto del comportamento più efficiente (attacco o fuga). Siamo sottoposti a una quantità enorme di stimoli, e il nostro cervello seleziona automaticamente le informazioni da filtrare. Scopri come.
Alessia Alò Scritto da Alessia Alò Nella vita di tutti i giorni, molto più spesso di quel che crediamo, siamo soliti utilizzare delle scorciatoie per prendere decisioni, dare giudizi, risolvere problemi e in definitiva rapportarci col mondo. Queste scorciatoie sono per la maggior parte corrette e ci consentono di interpretare la realtà in maniera rapida ed efficiente. Tuttavia, all’interno di questo processo, possiamo incappare in quelli che vengono chiamati unconscious bias e perciò giungere a delle conclusioni errate sul mondo che ci circonda. Soprattutto quando dobbiamo prendere decisioni in condizioni di incertezza è probabile che la razionalità umana venga ostacolata proprio da queste distorsioni del giudizio. Rimuovere ed evitare del tutto i nostri bias è impossibile, è molto importante invece prenderne consapevolezza al fine di ridurli e saperli gestire nel modo più adeguato. Per capire meglio di cosa si tratta e rapportare i bias alla nostra esperienza vorrei di seguito esplorarne due, molto frequenti e a volte correlati tra loro:
A third of the UK population spent at least one year in relative income poverty between 2011 and 2014. Traditionally policymakers and anti-poverty organisations such as the Joseph Rowntree Foundation (JRF) have focused on boosting people’s economic capital (e.g., income) and human capital (e.g., educational attainment) to reduce poverty. While investments in these areas have led to important gains in opportunity for many Britons, emerging research from behavioural science shows that other less tangible resources, which derive from psychological, social and cultural processes, significantly influence people’s ability to overcome disadvantage. BIT was commissioned by JRF to examine the role of individual decisions in shaping people’s experiences of poverty in the UK and to identify the drivers of these decisions. This reflects JRF’s interest in looking beyond traditional, structural drivers of poverty. Our findings, based on a review of the published literature, are presented in a new report, launched today. Building on the concepts of economic and human capital, our report proposes a more expansive capital-based model of poverty and decision-making, encompassing environmental, social, character and cognitive capital (Figure 1). For example, an individual may use their social capital (e.g., trusted social connections) to identify labour market opportunities; but being low in environmental capital (e.g., overcrowded housing) may reduce opportunities for parents to talk with their child in ways that build their human capital (e.g., speech development).
The present study used positron emission tomography (PET) to examine the cerebral activity pattern associated with auditory imagery for familiar tunes. Subjects either imagined the continuation of nonverbal tunes cued by their first few notes, listened to a short sequence of notes as a control task, or listened and then reimagined that short sequence. Subtraction of the activation in the control task from that in the real-tune imagery task revealed primarily right-sided activation in frontal and superior temporal regions, plus supplementary motor area (SMA). Isolating retrieval of the real tunes by subtracting activation in the reimagine task from that in the real-tune imagery task revealed activation primarily in right frontal areas and right superior temporal gyrus. Subtraction of activation in the control condition from that in the reimagine condition, intended to capture imagery of unfamiliar sequences, revealed activation in SMA, plus some left frontal regions. We conclude that areas of right auditory association cortex, together with right and left frontal cortices, are implicated in imagery for familiar tunes, in accord with previous behavioral, lesion and PET data. Retrieval from musical semantic memory is mediated by structures in the right frontal lobe, in contrast to results from previous studies implicating left frontal areas for all semantic retrieval. The SMA seems to be involved specifically in image generation, implicating a motor code in this process.
White House releases report on applying behavioral science to government policy The White House’s Social and Behavioral Sciences Team (SBST), a subgroup of the Office of Science and Technology Policy that has been working to make government more effective, recently released its second report. This might seem like quiet, behind-the-scenes-work, but it can make a…
THE SOCIAL AND NATURAL SCIENCES DIFFER IN THIS REGARD We have talked in the past about how economics does not cite other fields much (see Pieters and Baumgartner, 2002). Are authors rewarded for writing papers this way? In social science, the answer seems to be yes. A recent article in Plos One “The Impact of …
By guiding the design of customer interactions, the principles of behavioral science offer a simple, low-cost route to improved customer satisfaction. Service operations seem a natural setting for the ideas of behavioral science. Every year, companies have thousands, even millions, of interactions with human beings—also known as customers. Their perceptions of an interaction, behavioral scientists tell us, are influenced powerfully by considerations such as its sequence of painful and pleasurable experiences. Companies care deeply about the quality of those interactions and invest heavily in effective Web sites and in responsive, simplified call centers. Yet the application of behavioral science to service operations seems spotty at best. Its principles have been implemented by relatively few companies, such as the telecommunications business, which found that giving customers some control over their service interactions by allowing them to schedule field service visits at specific times could make them more satisfied, even when they had to wait a week or longer. Many more companies ignore what makes people tick. Banks, for example, often disturb the customer experience by altering the menus on ATMs or the interactive-voice-response (IVR) systems in call centers. They fail to recognize the psychological discomfort customers experience when faced with unexpected changes.
Which is smarter—your head or your gut? It’s a familiar refrain: you’re getting too emotional. Try and think rationally. But is it always good advice? In this surprising book, Eyal Winter asks a simple question: why do we have emotions? If they lead to such bad decisions, why hasn’t evolution long since made emotions irrelevant? The answer is that, even though they may not behave in a purely logical manner, our emotions frequently lead us to better, safer, more optimal outcomes. In fact, as Winter discovers, there is often logic in emotion, and emotion in logic. For instance, many mutually beneficial commitments—such as marriage, or being a member of a team—are only possible when underscored by emotion rather than deliberate thought. The difference between pleasurable music and bad noise is mathematically precise; yet it is also something we feel at an instinctive level. And even though people are usually overconfident—how can we all be above average?—we often benefit from our arrogance. Feeling Smart brings together game theory, evolution, and behavioral science to produce a surprising and very persuasive defense of how we think, even when we don’t.
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