My interest is in how problem-solving decisions are made, and what, if any skills could be taught to increase people's ability to make effective decisions? Effective, in this case, means that an external observer finds the decision a sufficient and satisfying solution to the problem given the thinker's current understanding of environment, context, and resources.

I understand the Information Principle of emotion takes the position that emotions are a "summary" of all that the unconscious notices about the current situation. (See this link for an excellent overview.) Given the breadth of its perception, and the faster processing time of its systems, emotion is tremendously powerful as an advisor. The reward system is triggered when a desired choice is contemplated, so is the role primary, rather than advisory? Is conscious thought -- what we come up with when we "think about our decision" -- always post hoc, used only for coming up with a way to explain what our feelings told us we wanted?

Regarding skills to increase effectiveness, I wonder at the value of learning to overcome our initial emotional response to allow the more deliberate conscious processes to make a real contribution. I have heard that trauma victims with absent emotions dither about the smallest decisions, so I'm not talking full suppression. Is anyone aware of research into the effect of trying to achieve some balance here?

  • $\begingroup$ I think that an important distinction is whether the decision being made is in line with what the person usually does, in which case emotion and rationalization would be strong forces propping it up, or if the decision is to do something new, which I think would require going against the guidance of emotion (summarized past experience) and any sort of rationalizing, to instead use actual rationality. $\endgroup$
    – user9634
    Commented Mar 23, 2015 at 19:29

3 Answers 3


This is a very broad topic. I'll attempt to quickly summarize the most relevant findings from a wide variety of research areas.


There is a fair bit of evidence that explanation follows decision-making, rather than the other way around. Here is a nice quote from Wikipedia attributed to Robert Zajonc: "decisions are made with little to no cognitive process ... we make judgements first, and then seek to justify those judgements by rationalization." My favourite example of rationalization is Choice Blindess experiments, where subjects are "tricked" into believing that they made decisions that they did not actually make, but they nonetheless explain them as if they did.

Dual Process Theory:

Part of the implication of this phenomenon is that the human mind is divided into (at least) 2 seemingly independent processes - an unconscious process that makes the decision, and a conscious process that seeks to justify it after the fact. Emotion plays an important role in some of these theories, though not all. Emotion certainly affects decision-making, and may help decision-making under some circumstances.


The tendency to make decisions unconsciously - biased by emotion and many other cognitive biases - can be overcome in a straightforward manner. In several experiments, this is done simply by ... asking. For example, Timothy Wilson induced different (rational) decisions from subjects by simply asking them to provide reasons for their decisions before making them. Similarly, Ap Dijksterhuis induced rational decisions from subjects by asking them to think about their decisions before making them.

Bounded Rationality:

Unfortunately, the results of the above experiments demonstrate that decision-making is not always improved by conscious deliberation before making a decision. This is because sometimes decisions need to take emotions into account to be successful (as in Timothy Wilson's experiments where subjects are asked to predict their preferences), and other times human deliberation is limited by bounded rationality - we have a very limited capacity for logical thought. Perhaps the best way to overcome some of our cognitive limitations is to use computers to make rational decisions, but at the moment, humans are still better at making decisions than computers in many areas where rule-based decision-making is not practical to use.


An interesting perspective to clarify the interplay between rational and emotional can be found in the 'risk as feelings' approach. Here is the paper and here the abstract:

Virtually all current theories of choice under risk or uncertainty are cognitive and consequentialist. They assume that people assess the desirability and likelihood of possible outcomes of choice alternatives and integrate this information through some type of expectation-based calculus to arrive at a decision. The authors propose an alternative theoretical perspective, the risk-as-feelings hypothesis, that highlights the role of affect experienced at the moment of decision making. Drawing on research from clinical, physiological, and other subfields of psychology, they show that emotional reactions to risky situations often diverge from cognitive assessments of those risks. When such divergence occurs, emotional reactions often drive behavior. The risk-as-feelings hypothesis is shown to explain a wide range of phenomena that have resisted interpretation in cognitive–consequentialist terms.

Loewenstein, G.F., Weber, E. U., et al (2001) Risk as feelings. Psychological Bulletin, 127(2):267-286.

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    $\begingroup$ can you expand your answer give a more specific summary of the paper and how it addresses this question than just the abstract? $\endgroup$ Commented Apr 29, 2012 at 4:42

The human brain is subject to many faults and biases (Kahneman, 2011).

Human beings usually use heuristics, screening, ranking, and other rules of thumb to limit the complexity of a decision.

Kahneman has described the two cognitive systems that drive our judgement and decision making (Kahneman, 2011). System 1 refers to our intuitive system, which is typically fast, automatic, emotional, implicit, and effortless. Despite its long-standing effectiveness in specific decision situations, particularly when quick decisions are of great value (Gladwell, 2007), it can also be the cause of several cognitive biases that hinder our judgements and decisions. On the contrary, system 2 refers to reasoning, which is obviously lazier and effortful than system 1, but more conscious, deliberative, and logical.

For complex high-stakes decisions, it is worthwhile to follow a formal, rational, systematic procedure. This is the aim of decision analysis, helping DMs overcome system 1’s errors and biases towards system 2’s more careful and conscious deliberation (Clemen, 2008). Indeed, considerable research suggests that people will maximize their chances of making the best decision if they use a sound decision analysis method (Russo and Schoemaker, 1989).

If a decision-maker wants to guide his decision making process satisfying a set of simple and transparent axioms, which most people would regard as rational (Goodwin and Wright, 2004), and some logical theorems that follow from them, then the unique standard for correctness is decision analysis (Keeney, 1982; Howard, 2007).

Kahneman D (2011) Thinking, Fast and Slow. Farrar, Straus and Giroux

Gladwell M (2007) Blink: The Power of Thinking Without Thinking. Back Bay Books

Clemen RT (2008) Improving and measuring the effectiveness of decision analysis: Linking decision analysis and behavioral decision research. In T Kugler, JC Smith, T Connolly, Y-J. Son (eds.) Decision Modeling and Behavior in Complex and Uncertain Environments, Springer, New York: 3-31

Russo JE, Schoemaker PJH (1989) Decision Traps: The Ten Barriers to Brilliant Decision-Making and How to Overcome Them. Doubleday, New York

Goodwin P, Wright G (2004) Decision Analysis for Management Judgment. Wiley and Sons, New York

Keeney RL (1982) Decision Analysis: An Overview. Operations Research, 30(5): 803-838

Howard RA (2007) The Foundations of Decision Analysis Revisited. In W Edwards, RF Miles Jr, D von Winterfeldt (eds.) Advances in Decision Analysis: From Foundations to Applications, Cambridge University Press, Cambridge: 32-56


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