Bounded Rationality and Beyond
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Thinking, Fast and Slow: A New Way to Think About Thinking

Thinking, Fast and Slow: A New Way to Think About Thinking | Bounded Rationality and Beyond | Scoop.it
Legendary Israeli-American psychologist Daniel Kahneman is one of the most influential thinkers of our time. A Nobel laureate and founding father of modern behavioral economics, his work has shaped how we think about human error, risk, judgement, decision-making, happiness, and more. For the past half-century, he has profoundly impacted the academy and the C-suite, but it wasn’t until this month’s highly anticipated release of his “intellectual memoir,” Thinking, Fast and Slow, that Kahneman’s extraordinary contribution to humanity’s cerebral growth reached the mainstream — in the best way possible.
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Bounded Rationality and Beyond
News on the effects of bounded rationality in economics and business, relationships and politics
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Easy money or a golden pension? Integrating economics and psychology

The American economist Richard H. Thaler is a pioneer in behavioural economics, a research field in which insights from psychological research are applied to economic decision-making. A behavioural perspective incorporates more realistic analysis of how people think and behave when making economic decisions, providing new opportunities for designing measures and institutions that increase societal benefit. Economics involves understanding human behaviour in economic decision-making situations and in markets. People are complicated beings, and we must make simplifying assumptions if we are to build useful models. Traditional economic theory assumes that people have good access to information and can process it perfectly. It also assumes that we can always execute our plans and that we only care about personal gain. This simplified model of human behaviour has helped economists to formulate theories that have provided solutions to important and complicated economic problems. However, the discrepancies between theory and reality are sometimes both systematic and significant. Richard Thaler has contributed to expanding and refining economic analysis by considering three psychological traits that systematically influence economic decisions – limited rationality, perceptions about fairness, and lack of self-control. Limited rationality
https://www.nobelprize.org/nobel_prizes/economic-sciences/laureates/2017/popular-economicsciences2017.pdf
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Evolution and Devolution of Social Complexity: Why Do We Care?

Evolution and Devolution of Social Complexity: Why Do We Care? | Bounded Rationality and Beyond | Scoop.it

Over the past 10,000 years human societies evolved from “simple” – small egalitarian groups, integrated by face-to-face interactions – to “complex” – huge anonymous societies of millions, characterized by great differentials in wealth and power, extensive division of labor, elaborate governance structures, and sophisticated information systems. What were the evolutionary processes that brought about such an enormous increase in social scale and complexity? We also need to understand why social forces that hold huge human societies together sometimes fail to do so. Complex societies collapsed on numerous occasions in the past, and may be at risk today. There are clear signs that even industrialized, wealthy, and democratic Western societies, that seemed to be immune to collapse until recently, are becoming less stable. Research on social complexity will bring understanding that is of direct value to our societies and human well-being.

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Gigerenzer’s simple rules

Gigerenzer’s simple rules | Bounded Rationality and Beyond | Scoop.it

Why simple rules of thumb often outperform complex models

This is the age of big data. We are constantly in quest of more numbers and more complex algorithms to crunch them. We seem to believe that this will solve most of the world’s problems - in economy, society and even our personal lives. As a corollary, rules of thumb and gut instincts are getting a short shrift. We think they often violate the principles of logic and lead us into making bad decisions. We might have had to depend on heuristics and our gut feelings in agricultural and manufacturing era. But this is digital age. We can optimise everything. Can we? Gerd Gigerenzer, a sixty nine year German psychologist who has been studying how humans make decisions for most of his career, doesn't think so. In the real world, rules of thumb not only work well, they also perform better than complex models, he says. We shouldn’t turn our noses up on heuristics, we should embrace them.

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Design Thinking: the New DNA of the Financial Sector

Design Thinking: the New DNA of the Financial Sector | Bounded Rationality and Beyond | Scoop.it

Fending off Fintech with Design Thinking

The banking industry has become increasingly concerned over the challenge that emerging fintech startups pose to banks’ traditional ways of doing business and the threat that they present to revenue streams. In response, many banks have created internal innovation labs to counter these risks. “Design thinking” has become an important tool in the effort and is being used to explore how banks can boost their growth by applying the approach in a rapidly changing environment and an era of de-banking.

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What’s the future of modern commerce? Or, why did Amazon buy Whole Foods?

What’s the future of modern commerce? Or, why did Amazon buy Whole Foods? | Bounded Rationality and Beyond | Scoop.it
Today's retail environment demands a shift in mindset and an unprecedented level of consumer understanding. Contributor Brian Solis lays out the path he believes retailers must take to be successful.
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Adaptive Capacity as Emergent Capacity

Center for Collective Dynamics of Complex Systems (CoCo) Seminar Series September 20, 2017 Pamela Mischen (Public Administration, Binghamton University) "Adaptive…
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Empatia e Neuroeconomia (prof. Guido Baggio)

Come si comporta il cervello nelle decisioni di tipo economico? La neuroeconomia, recente e affascinante frutto del dialogo tra economia, psicologia e neuroscienze, ha dimostrato che accanto al lato razionale hanno un ruolo fondamentale le emozioni nei processi decisionali e comportamentali di carattere economico. Il presupposto da cui parte l'analisi neuroeconomica è che, a differenza di quanto affermato dall'economia classica dell’homo oeconomicus, l'uomo non è un animale razionale, bensì agisce sotto l'impulso di processi neuronali automatici e molto spesso inconsci, quindi indipendenti dalla propria volontà. Ciò fa sì che il comportamento economico umano sia frutto di un conflitto neuronale tra razionalità ed emotività, automatismo e consapevolezza. A partire da queste premesse, l'obiettivo della neuroeconomia è quello di offrire un modello sufficientemente unitario della condotta umana che riesca a rendere conto dell’origine biologico-sociale tanto dei comportamenti economici centrati sull’interesse individuale quanto dei comportamenti economici cosiddetti altruisti, cioè capaci di tenere in considerazione l’appartenenza degli individui ad una comunità sociale.

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Here's what 180 years of prices in Sweden tell us about globalization

Here's what 180 years of prices in Sweden tell us about globalization | Bounded Rationality and Beyond | Scoop.it

New research looking at prices in Sweden, suggests intranational price convergence may be a 'precursor to globalization'.When you think globalisation began depends on how you define it. Ancient civilizations and medieval cities of course exchanged tools, plants, diseases, and ideas. But most recent discussions of the start of globalisation define it as integration of a market across regions or countries, as measured by the convergence of commodity prices. For example, The Economist (2013) argues there was a world silver market after about 1500. O’Rourke and Williamson (2002) argue that commodity price convergence is indeed the best way to measure the integration of markets that defines globalisation. They note the international trade in luxury goods – such as spices, silk, furs, and gold – from 1500 to 1800. But they suggest that falling transport costs led to a globalisation big bang in the 1820s marked by the integration of markets for necessities like grains and textiles. For the first time, this international integration began to affect how capital and labour were used within domestic economies, and thus also began to be the subject of political debates.

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What Economics Models Really Say - Evonomics

Why is there such an enormous gulf between what economists know and what they say in public?

The blurb on the jacket of Economics Rules says, “In this sharp, masterful book, Dani Rodrik, a leading critic from within, takes a close look at economics to examine when it falls short and when it works, to give a surprisingly upbeat account of the discipline.” I heartily agree with nearly all of this, with the exception of the “upbeat” part. As I will explain toward the end of this review, my view of economics, and, especially, of the role that economists play in public policy, is much more critical. A central theme in the book is the role of mathematical models in economics. Formal models in economics and other social sciences are often disparaged. According to the critics (who include some economists, many other social scientists, and the overwhelming majority of historians), models oversimplify complex reality, employ unrealistic assumptions, and deny “agency” to human beings.

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Social Preferences and Political Attitudes: An Online Experiment on a Large Heterogeneous Sample

Abstract This paper investigates – in a large heterogeneous sample – the relationship between social preferences on the one hand, and socioeconomic factors and political preferences on the other hand. Socioeconomic factors correlate with social preferences, and social preferences robustly shape political attitudes and voting behavior in a particular way: Selfish subjects are the extremists on one side of the political spectrum – they are more likely to vote for a rightwing party, they are less inclined to favor redistribution and they are more likely to self-assess themselves as right-wing than all the other types. Inequality-averse subjects, altruists and maxi-min sit at the opposite end of the political spectrum, while all the other types behave less systematically and in a less extreme fashion. Overall, our evidence indicates that elicited social preferences are externally valid as a predictor for political attitudes, and that social preferences are fairly stable across contexts and over longer periods of time.
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It Takes a Theory to Beat a Theory: The Adaptive Markets Hypothesis - Evonomics

We need a new narrative for how markets work. We now have enough pieces of the puzzle to start putting it all together.

After 2008, the wisdom of financial advisers and academics alike seemed naive and inadequate. So many millions of people had faithfully invested in the efficient, rational market: what happened to it? And nowhere did the financial crisis wound one’s professional pride more deeply than within academia. The crisis hardened a split among professional economists. On one side of the divide were the free market economists, who believe that we are all economically rational adults, governed by the law of supply and demand. On the other side were the behavioral economists, who believe that we are all irrational animals, driven by fear and greed like so many other species of mammals. Some debates are merely academic. This one isn’t. If you believe that people are rational and markets are efficient, this will largely determine your views on gun control (unnecessary), consumer protection laws (caveat emptor), welfare programs (too many unintended consequences), derivatives regulation (let a thousand flowers bloom), whether you should invest in passive index funds or hyperactive hedge funds (index funds only), the causes of financial crises (too much government intervention in housing and mortgage markets), and how the government should or shouldn’t respond to them (the primary financial role for government should be producing and verifying information so that it can be incorporated into market prices).

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The Most Intolerant Wins: The Dictatorship of the Small Minority

The Most Intolerant Wins: The Dictatorship of the Small Minority | Bounded Rationality and Beyond | Scoop.it
How Europe will eat Halal — Why you don’t have to smoke in the smoking section — Your food choices on the fall of the Saudi king –How to prevent a friend from working too hard –Omar Sharif ‘s…
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Big Picture of Big Data - Top 10 Big Data Trends in 2017 - DataFlair

Big Picture of Big Data - Top 10 Big Data Trends in 2017 - DataFlair | Bounded Rationality and Beyond | Scoop.it
Big data trends for 2017-top trends of big data analytics to understand big data predictions in 2017 for data scientists, data analysts and data engineers.
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Mobility can promote the evolution of cooperation via emergent self-assortment dynamics

Mobility can promote the evolution of cooperation via emergent self-assortment dynamics | Bounded Rationality and Beyond | Scoop.it

Cooperation among animals is ubiquitous. In a cooperative interaction, the cooperator confers a benefit to its partner at a personal cost. How does natural selection favour such a costly behaviour? Classical theories argue that cooperative interactions among genetic relatives, reciprocal cooperators, or among individuals within groups in viscous population structures are necessary to maintain cooperation. However, many organisms are mobile, and live in dynamic (fission-fusion) groups that constantly merge and split. In such populations, the above mechanisms may be inadequate to explain cooperation. Here, we develop a minimal model that explicitly accounts for mobility and cohesion among organisms. We find that mobility can support cooperation via emergent dynamic groups, even in the absence of previously known mechanisms. Our results may offer insights into the evolution of cooperation in animals that live in fission fusion groups, such as birds, fish or mammals, or microbes living in turbulent media, such as in oceans or in the bloodstreams of animal hosts.

 

Joshi J, Couzin ID, Levin SA, Guttal V (2017) Mobility can promote the evolution of cooperation via emergent self-assortment dynamics. PLoS Comput Biol13(9): e1005732. https://doi.org/10.1371/journal.pcbi.1005732


Via Complexity Digest
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Arjen ten Have's curator insight, Today, 10:26 AM
Cooperation is always explained by Hamilton's rule (Benefit > Relationship*Cost) but that does not hold when mobility is taken into account. Here a model is presented that deals with mobility. Although modeled for animals, this obviously goes for Human society as well.
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The Future of Economics: From Complexity to Commons

The Future of Economics: From Complexity to Commons | Bounded Rationality and Beyond | Scoop.it
Complexity science shows us not only what to do, but also how to do it: build shared infrastructure, improve information flow, enable rapid innovation, encourage participation, support diversity and citizen empowerment.

Via june holley, Bernard Ryefield
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Neuroeconomia. Quando tra il tuo cervello e quello di un cocainomane non passa alcuna differenza

Neuroeconomia. Quando tra il tuo cervello e quello di un cocainomane non passa alcuna differenza | Bounded Rationality and Beyond | Scoop.it

“La Neuroeconomia è un neonato settore della ricerca neuroscientifica di spiccato carattere interdisciplinare, volto a costruire un modello biologico dei processi decisionali. Essa si situa al crocevia tra discipline alquanto differenti per scopi, metodi, prospettive d’indagine, tra le quali, in particolare, l’economia cognitiva e sperimentale, le neuroscienze, la microeconomia, la psicologia, l’epistemologia e la filosofia della mente filosofia, ciascuna delle quali fornisce uno specifico contributo allo studio della decisione umana. Se gli economisti si chiedono quale sia la decisione ottimale (massimizzante) tra più alternative possibili in condizioni di incertezza, i filosofi si interrogano sulla nozione di razionalità economica e delle sue violazioni, gli psicologi studiano quali processi sono messi in atto dalla mente umana durante la scelta e come le emozioni possano influire positivamente o negativamente su di essi, i neuroscienziati indagano il funzionamento del sistema nervoso, chi si occupa di neuroeconomia tenta di far convergere i contributi da tutte queste discipline per capire come il cervello ci consente di prendere decisioni. Integrando contributi e metodi da tutte queste discipline, è oggi possibile “osservare” l’attività neurale in tempo reale, “guardando dentro il cervello”, per esaminare quali regioni cerebrali sono maggiormente coinvolte nella presa di decisione, e come il loro funzionamento è influenzato dalle opzioni disponibili, dal contesto nel quale esse sono presentate, dai fattori emotivi, dalle interazioni con altri individui.

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How Artificial Intelligence Is Disrupting Finance

How Artificial Intelligence Is Disrupting Finance | Bounded Rationality and Beyond | Scoop.it
The applications for artificial intelligence in finance include everything from automated risk management and trading to underwriting and claims.
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Tapping into how the brain perceives values can influence choices

Tapping into how the brain perceives values can influence choices | Bounded Rationality and Beyond | Scoop.it
Researchers have been able to tap into the decision-making processes in the brain to play with our sense of value.
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When our brain decides for us… And without our permission

When our brain decides for us… And without our permission | Bounded Rationality and Beyond | Scoop.it
(Originally published in Slovak at mindworx.net) Most of us probably believe that we are in control of our own decisions. We have our opinions, beliefs and principles, we know what we like and dislike and we always decide in accordance with our preferences. However, this is not entirely true. Our brain reacts to all kinds…
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An anatomy of murder – The Economist

An anatomy of murder – The Economist | Bounded Rationality and Beyond | Scoop.it
In the “fake news” era, few things are more important to a 174-year-old newspaper than hard facts. At The Economist this is perhaps best demonstrated in the kind of painstaking work done by our data…
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The emergence of altruism as a social norm

The emergence of altruism as a social norm | Bounded Rationality and Beyond | Scoop.it

Expectations, exerting influence through social norms, are a very strong candidate to explain how complex societies function. In the Dictator game (DG), people expect generous behavior from others even if they cannot enforce any sharing of the pie. Here we assume that people donate following their expectations, and that they update their expectations after playing a DG by reinforcement learning to construct a model that explains the main experimental results in the DG. Full agreement with the experimental results is reached when some degree of mismatch between expectations and donations is added into the model. These results are robust against the presence of envious agents, but affected if we introduce selfish agents that do not update their expectations. Our results point to social norms being on the basis of the generous behavior observed in the DG and also to the wide applicability of reinforcement learning to explain many strategic interactions.

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NeuroEconomia: Come il Cervello prende le Decisioni - Video Corso

NeuroEconomia: Come il Cervello prende le Decisioni - Video Corso | Bounded Rationality and Beyond | Scoop.it

Economia, Psicologia e Neuroscienze stanno oggi convergendo in una nuova disciplina chiamata Neuroeconomia, con l'obiettivo di fornire una unica teoria generale dei processi decisionali umani. La Neuroeconomia offre a economisti, psicologi e scienziati sociali una più profonda comprensione di come l'uomo prendere le decisioni, partendo dal presupposto che, a differenza di quanto affermato dall’economia tradizionale, l’uomo non è un animale razionale, ma agisce sotto l’impulso di processi neuronali automatici e molto spesso inconsci, quindi indipendenti dalla propria volontà. Il cervello é programmato per prendere rischi o per evitarli ? Come è valutata dal cervello una "decisione giusta" ? E possibile prevedere le intenzioni di acquisto di un consumatore ? Possiamo modulare il comportamento del cervello riguardo gli aspetti economici ? Per rispondere a queste domande e conoscere meglio le basi della Neuroeconomia a partire dal prossimo 23 Giugno la prestigiosa Higher School of Economics di Mosca, presenta un nuovo interessante video corso di 9 settimane totalmente gratuito, intitolato Introduction to Neuroeconomics: how the brain makes decisions che tratterà molti argomenti partendo dai fondamenti della neuroeconomia e neuroanatomia del cervello trattati in quattro moduli successivi, guarda la video-presentazione del corso :

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LE DISTORSIONI COGNITIVE. L'essere umano è davvero razionale?

Prima di parlare di bias cognitivi, è bene introdurre il concetto di euristiche: escamotage mentali che portano a conclusioni veloci con il minimo sforzo cognitivo, o meglio scorciatoie comode e rapide estrapolate dalla realtà. (2002 Kahneman e Frederick). I bias cognitivi, invece, sono euristiche inefficaci, pregiudizi astratti che non si generano su dati di realtà, ma si acquisiscono a priori senza critica o giudizio, fondati, su percezioni errate o deformate, su pregiudizi e ideologie. Di seguito alcuni dei BIAS più comuni.Secondo Daniel Kahneman occorre impegnarsi a costruire una "società critica", nella quale ci siano "osservatori critici". 

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Artificial Intelligence, Deep Learning and Big Data: a New Start?

When I was a university student I was terribly naïve about the power of Artificial Neural Networks. While I was trying to replicate portions of human cognition by practicing with neural networks and non-linear dynamics, I stumbled into a crazy idea: the time series of the winning results of a multimillion lottery are apparently chaotic; what if - say because of the mechanical constraints of the devices that pick up the numbers or for any other reason in the universe- there was a hidden statistical pattern behind that apparent chaos? If that was the case, then anyone endowed with the ability to deal with the chaotic nature of that huge amount of data could probably get an insight into that hidden mechanism. As it is well known, recurrent neural networks are non-linear dynamical systems able to learn time series. That was sufficient for me to start encode thousands of winning series of a popular lottery into vectors to feed into my latest Recurrent Multi-layer Neural Network experiment to make it learn to predict, at least at a degree, the next winning one. I was trying to hack the lottery. Wow! You may say: are you crazy? Probably, I was. And I was even crazier because of having implemented the whole stuff in Java and expected it to run on my Intel 486 Windows PC! I know you want to know how it ended. Let it suffice to say that I did not become a millionaire. Jokes aside, the very high dimensionality of data and the computational resources needed to carry out the training of the network largely exceeded my computer's capability that finally, after two days of computation, got stuck. That was the very first time I had a joint meeting with what we currently call "Deep Learning" and "Big Data".
https://www.linkedin.com/pulse/artificial-intelligence-deep-learning-big-data-new-start-terenzi
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Managing deep uncertainty: Exploratory modeling, adaptive plans and joint sense making

Community member post by Jan Kwakkel How can decision making on complex systems come to grips with irreducible, or deep, uncertainty? Such uncertainty has three sources: Intrinsic limits to predictability in complex systems. A variety of stakeholders with different perspectives on what the system is and what problem needs to be solved. Complex systems are…
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