History of Decision Making and Application to Dispute Resolution

Decision-making is an integral part of conflict resolution. Any decisions taken at any level during the resolution process must consider all the conflicting needs of the individuals who are in conflict.

To understand how decision-science can be applied to mediation, we must understand the history of formal decision-making. 

Many historians attribute early thinking about decision-making to ancient Greeks; however, early Greek philosophers did not develop rational decision-making theory.   Greek philosophers were not familiar with the mathematical concepts of probability therefore, they only identified rational choice as an area that needed diligent study. Some philosophers like Herodotus, however, did explore concepts of “right” to mean rational and “contrary to good counsel” to mean irrational.   Other philosophers like Aristotle, for example, in Book III of his “Topics” did propose early logic on rational preference.  

“If A be without qualification better than B, then also the best of the members of A is better than the best of the members of B”

It wasn’t until the 1600s that thinkers like Blaise Pascal and Pierre de Fermat began to discuss concepts of probability. This was followed by the work of Arnauld and Nicole in 1662 referred to as Port-Royal Logic and was published under the title of “La Logique, ou l’art de Penser.”   In the 1700s, Bernoulli introduced the concept of moral value as an improvement over Port-Royals Logic of good and evil. For Bernoulli the moral value of an outcome was a technical term that referred to how good or bad an outcome was from the decision maker’s perspective. Modern decision theory on the other hand is dominated by attempts to create axiomatic principles of rational decision making. In the early 20th century, the English philosopher, Frank Ramsey, in his paper with Bertrand Russell on probability, proposed eight axioms for how decision-makers should choose among uncertain prospects. These axioms (which will not be discussed in this short article) were compatible with the principle of maximizing expected value, by assigning numerical probabilities and values to potential outcomes. 

 While there have been many contributors to modern decision-making theory over the years, the history of decision-making strategies is not one of unalloyed progress toward perfect rationalism. In fact, over the years, we have steadily been coming to terms with contextual and psychological constraints on our ability to make optimal choices. Complex circumstances, limited time, and inadequate mental computational power reduce decision makers to a state of “bounded rationality,” argues Herbert Simon. While Simon suggests that people would make economically rational decisions if only they could gather enough information, Daniel Kahneman and Amos Tversky identify factors that cause people to decide against their economic interests even when they know better.

Decision-theory, as a term, is broadly used in several contexts that span theoretical inquiries into the nature of decision-making, including game theory and social choice theory, as well as individual decisions that do not consider the behavior of others.   There are four well-defined areas of decision theory:

  • Normative Decision Theory
  • Rational and Right Decisions
  • Risk, Ignorance, and Uncertainty
  • Social Choice Theory

Normative Decision Theory

Normative decision theory, as opposed to Descriptive decision theory, attempts to yield prescriptions about what participants in a decision are rationally required or should do. Normative decision theory, which encompasses analytical modeling of decisions and calculation of expected value or decision utility, provides important reminders that any decision about uncertain risks or benefits requires assessing as precisely as possible the likelihood and severity of all relevant possible outcomes. In addition, methodologies such as Analytical Hierarchical Process, Multi-attribute Utility Theory, etc. aid decision makers in prioritizing objectives. Informed decision-making standards identify the critical information that stakeholders must know before making their decisions.

Rational and Right Decisions

It is important to realize that a decision can be rational without being right, and right without being rational.   In general, we say that a decision is right if and only if the outcome is at a minimum, at least as good as that of every other possible outcome. On the other hand, a decision is rational if and only if individuals rely on rational calculations to make rational choices that result in outcomes aligned with their own best interests.   Adam Smith was one of the first economists to develop the underlying principles of the rational choice theory. 

Risk, Ignorance, and Uncertainty

In decision theory, everyday terms such as risk, ignorance and uncertainty are used as technical terms with well-defined meaning:

Decision under risk means that the decision maker knows the probability of all the possible outcomes.

Decision under uncertainty means that we do not have a complete picture of all the possible outcomes or how to assign probabilities to them.

Decision under ignorance the probabilities and possible outcomes, are unknown or nonexistent.

Social Choice Theory

Decisions that are made collectively, or in a group, fit into the category of social choice theory. Social choice theory seeks to establish principles for how decisions involving more than one decision maker (e.g. in mediation) ought to be made. The basic problem is defined as how do we aggregate the divergent beliefs and goals of a heterogeneous set of individuals into a fair and collective decision? 

A social choice problem is any decision problem faced by two or more people (group) in which each individual can state ordinal preferences over outcomes.     

Conclusion

Over the past 2 decades, the neuroscience community has significantly evolved its understanding of human decision making over and our predispositions to cognitive biases, such as:

Optimism bias. The tendency to believe that we’re less likely to experience a negative event outcome (e.g. litigation) compared to others.

Confirmation bias. Why humans seek, understand, favor, and remember things in a way that confirms our preexisting beliefs.

Availability heuristic. A mental shortcut our brains use which relies on immediate examples that come to mind when evaluating a specific concept or problem

These are examples of factors that we know drive intuition-based or emotional decision making.  There is also a growing body of behavioral research that shows how lawyers and clients – indeed all of us – process and filter information, weeding out unwanted input in favor of self-serving affirmations. In other words, we hear what we want to hear and largely disregard the rest. Call it egocentric or emotional bias. It is these biases that drive our decision making and act as barriers to dispute resolution.   

Decision science, which is a combination of business, math, technology, design thinking and behavioral sciences, is designed to address these issues of bias in decision making and produce more rational decisions.  

NextLevel™ Mediation’s system’s use of decision science methodologies, addresses these issues and helps produce more rational mediation results . 

author

Robert Bergman

Robert Bergman with Next Level Mediation provides full mediation services - including proprietary and confidential Decision Science (DS) analysis that assists each party in understanding their true litigation priorities as aligned with their business objectives. Each party receives a one-time user license to access our exclusive DS Application Cloud. We… MORE

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