Models of Affective Decision Making

Charpentier, Caroline J.; Neve, Jan‐Emmanuel De; Li, Xinyi; Roiser, Jonathan P.; Sharot, Tali

doi:10.1177/0956797616634654

Cited by 83 publications

(37 citation statements)

References 38 publications

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“…Further, these results show that the type of affective processing previously found in decisions from experience (affective learning tasks such as the Iowa Gambling Task) seems to extend to a descriptive choice context. Our findings also corroborate results from studies in psychology that investigated the affective basis of risky choice more generally (e.g., Charpentier, Neve, Li, Roiser, & Sharot, 2016;Loewenstein et al, 2001;Mellers & McGraw, 2001;Mellers, Schwartz, Ho, & Ritov, 1997;Rutledge, Skandali, Dayan, & Dolan, 2014). For example, Charpentier et al (2016) found that feelings associated with losses were more important than feelings associated with gains for predicting choices in mixedgamble trials, despite the fact that the feelings across both domains were similar in terms of magnitude.…”

Section: Hypothesissupporting

confidence: 89%

Affective response predicts risky choice for fast, but not slow, decisions.

Persson¹,

Asutay²,

Hagman³

et al. 2018

Journal of Neuroscience, Psychology, and Economics

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We use skin conductance to measure emotional arousal in subjects who make risky choices under time pressure or time delay. Our results show a strong correlation between subjects' skin conductance responses and their risky choices under time pressure but not under time delay. Subjects were more risk taking for higher levels of measured electrodermal activity (skin conductance). In line with descriptive theories of risky choice, the effect was most pronounced for choices involving losses rather than gains. Taken together, our findings indicate that participants under time pressure rely on affect at the point of decision-making. This provides support for behavioral models that recognize the role of emotional brain systems in decision making under risk.

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Section: Hypothesissupporting

confidence: 89%

Affective response predicts risky choice for fast, but not slow, decisions.

Persson¹,

Asutay²,

Hagman³

et al. 2018

Journal of Neuroscience, Psychology, and Economics

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show abstract

“…Participants completed an additional gambling task at the end of the experiment, which would enable us to estimate and account for risk attitudes when estimating the control premium in the gain and loss domain (task adapted from Charpentier et al 2016 ). This is helpful, because the probability of the agent selecting the correct stimuli in relation to the participant doing so is different, and alters on each trial.…”

Section: Methodsmentioning

confidence: 99%

“…On half the trials, the sure option yielded a gain (range £1 to £12), and the gamble option included another gain (range £6 to £34) and £0. These trials allowed estimation of risk aversion (see Charpentier et al 2016 ).…”

Section: Methodsmentioning

confidence: 99%

The intrinsic value of choice: The propensity to under-delegate in the face of potential gains and losses

2017

Self Cite

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Human beings are often faced with a pervasive problem: whether to make their own decision or to delegate the decision task to someone else. Here, we test whether people are inclined to forgo monetary rewards in order to retain agency when faced with choices that could lead to losses and gains. In a simple choice task, we show that participants choose to pay in order to control their own payoff more than they should if they were to maximize monetary rewards and minimize monetary losses. This tendency cannot be explained by participants' overconfidence in their own ability, as their perceived ability was elicited and accounted for. Nor can the results be explained by lack of information. Rather, the results seem to reflect an intrinsic value for choice, which emerges in the domain of both gains and of losses. Moreover, our data indicate that participants are aware that they are making suboptimal choices in the normative sense, but do so anyway, presumably for psychological gains.

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“…Our modeling approach provides novel insight into how explicit feelings relate to choice. (Charpentier, Neve, Li, Roiser, & Sharot, 2016) .Such understanding is of theoretical importance and also has practical implications for policymakers, economists, and clinicians who often measure explicit feelings to predict choice (Benjamin, Heffetz, Kimball, & Rees-Jones, 2012, 2014. Action in the 8-fold path, emphasize the importance and universal responsibility, truth, and accuracy of the information you 'tell 'and how important that information for your EI as well.…”

Section: Educational Psychology and Eimentioning

confidence: 99%

The Nature of Human Intelligence

Sternberg¹

2018

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Humankind faces many problems such as like terrorism, crime, the collapse of the family unit, drug abuse, war, theft, etc., the multidisciplinary research was done to find whether that there are basic and common psychological reasons are or not. So, I have found some fundamental factors that are significantly limited or revers of the human intelligence by some decisions making and those limitations might be due to activating of delusional thoughts and decisions which are declined of intelligence, mainly cause by psychological mind viruses[ MV] in them, as I hypothesis, here. Those issues are been impact on optimal living, psychological, physical and social well-being. So, better practical solutions and preventive methods are needed. The leading psychological limiting factors for intelligence development are known as MV and its' remedies are healthy mind viruses [HMV]. The intelligent learning, training (meditation) and intelligent decisions might evolve the nature of the brain, nurture and x-micro particle genome [X-MPG], all these six factors seem to be interdepended. The X-MPG might bond with the xunique micro-particle [X-UMP]. However, the X-UMP might never evolve or change and it might maintain the uniqueness of the conscious state of a person. But, the X-MPG helps to evolve the latent potential level of well-being and optimal living gradually, of the related 4 person. Here, I show the unearthed-core of early Buddhist teachings, training (meditation) and decisions inclusive of the 8-fold path may be an efficient methodology for Intelligence evolution. The evolution of nature, nurture, X-MPG, psychological well-being, and intelligence might be represented in a theoretical 3D graph. If life after death occurs, when clinical death of a person's finally evolved level and micro quantum key of the X-MPG[ +X-UMP] might be crucial to natural transmission to bond with a matching and vacant zygote/early embryo of its micro quantum particles and its new conscious state, might depend on the lastly evolved genome of the X-MPG. However there are many more mysterious issues to be solved in future researches, so this might not a theory of everything on the main theme.

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Models of Affective Decision Making

Cited by 83 publications

References 38 publications

Affective response predicts risky choice for fast, but not slow, decisions.

Affective response predicts risky choice for fast, but not slow, decisions.

The intrinsic value of choice: The propensity to under-delegate in the face of potential gains and losses

The Nature of Human Intelligence

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