Copyright (c) 2013 John L. Jerz

Judgment and Decision Making (Connolly, Arkes, Hammond, 2000)

Home
A Proposed Heuristic for a Computer Chess Program (John L. Jerz)
Problem Solving and the Gathering of Diagnostic Information (John L. Jerz)
A Concept of Strategy (John L. Jerz)
Books/Articles I am Reading
Quotes from References of Interest
Satire/ Play
Viva La Vida
Quotes on Thinking
Quotes on Planning
Quotes on Strategy
Quotes Concerning Problem Solving
Computer Chess
Chess Analysis
Early Computers/ New Computers
Problem Solving/ Creativity
Game Theory
Favorite Links
About Me
Additional Notes
The Case for Using Probabilistic Knowledge in a Computer Chess Program (John L. Jerz)
Resilience in Man and Machine

ConnollyArkesHammond.gif

"The three papers in this section are excellent...In this highly readable paper, Dawes draws on examples from a number of disparate fields to discuss the well known, though surprising, finding that simple weighted means of predictor variables produce more accurate forecasts than experts who are basing their judgment on the same variables." International Journal of Forcasting

Book Description
Researchers in a growing number of fields--public policy, law, business, medicine, psychology, engineering, and others--are working to understand and improve human judgment and decision making. This book, which presupposes no formal training, brings together a selection of key articles in the area, with careful organization, introduction and commentaries. Issues involving medical diagnosis, weather forecasting, labor negotiations, risk, public policy, business strategy, eyewitnesses, and jury decisions are treated in this largely expanded volume. This is a revision of Arkes and Hammond's 1986 collection on judgment and decision making. Updated and extended, the focus of this volume is interdisciplinary and applied.

p.4 A decision maker needs only four types of information to construct a decision tree:
1. What are my possible courses of action? (Alternatives)
2. What are the events that might follow from these actions? (Outcomes)
3. What is the likelihood of each event?
4. What is the value of each event to me?
 
p.6 One difficulty often encountered in constructing a decision tree is that likelihoods and utilities are often not easy to assess... Because the helpfulness of a decision tree is based largely on the accuracy of the likelihoods and utilities used, every effort should be made to obtain good estimates.
 
p.7 In other words, judgments are made from tangible data, which serve as cues to intangible events and circumstances.
 
p.10 The simplest and best way to discover the cues, differential weights, function forms, and consistency of a person's judgment process is to use a computer to present a number of cases to the person making the judgment. After the judgments have been made, a computer program can readily decompose the judgment process into weights, function forms, and consistency.
 
p.115-116 We define an objective as a statement of something that one wants to achieve... We distinguish between fundamental objectives and means objectives. Fundamental objectives are concerned with ends rather than means. Ends are the fundamental objects of value that stakeholders care about in a specific decision context, while means objectives are methods to achieve ends... Strategic objectives should have the following characteristics. They should be relevant to a wide range of decision contexts, to a long time period, and to many levels in an organization... Strategic objectives should be deliberately general to enhance flexibility, which comes at the cost of detail.
 
p.121 For each of the lowest level objectives... we need to specify an attribute to measure the degree to which the objective is achieved. Specifying attributes is the most effective way to make the objectives hierarchy useful for subsequent analysis of strategic decisions... With attributes, the objectives can be used as a framework to evaluate alternatives.
 
p.305 A fundamental and critical component of expert judgment is the ability to appropriately use available information which varies in its relevance.
 
p.324-325 The expert must identify information or cues from the multidimensional stimulus he encounters. These cues are diagnostic (i.e., contain information) about the final decision or judgment... While each cue is related to the final categorization, it also serves the function of leading the expert to other cues that will also be of importance in the determination of the final categorization... While cues are being identified and clustered together, the expert is measuring the amount of the cue... After cues are identified, measured, and clustered, the important cognitive work of weighting and combining to form a global evaluation follows.
 
p.349 To make a sensible decision one needs to make two sorts of predictions: What will happen if I do X? And will I like it?
 
p.390 Decision [making] involves predicting our future "states of mind."
 
p.391 evaluations and weights [in a linear model of decision making] that are "reasonable" provide outcomes very close to those based on optimal ones.
 
p.395 In any field requiring judgmental forecasts, the performance of professional forecasters depends jointly on (1) the environment about which forecasts are made, (2) the information system that brings data about the environment to the forecaster, and (3) the cognitive system of the forecaster.
 
p.399 Since the forecast event is not fully determined by the cues, it cannot be predicted with certainty. Similarly, because some inconsistency is pervasive in human judgment, forecasts also are not perfectly related to the cues. Therefore, the relations on both sides of the lens model are probabilistic; that is, there is an element of uncertainty in the relation between the cues and both the observed event and the forecast.
 
p.406 Forecasting skill may be degraded if the information system that brings data to the forecaster does not accurately represent actual conditions.
 
p.407 An obvious way to improve the environment/ forecaster match is to have the forecaster learn more about the nature of the environmental system... Increasing the forecaster's experience with the task... is another obvious way to improve
 
p.409 Reliability of information acquisition is the extent to which the forecaster can reliably interpret the objective cues. The evidence suggests that unreliability of information acquisition is pervasive.
 
p.609 When people are asked to generate an estimate, they frequently anchor on an obvious or convenient number (e.g., the mean, the mode) and then adjust upward or downward if there is a reason to believe that the correct number should be moved in either direction. In many situations, that strategy works well

Enter supporting content here