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Extending the discipline: how software can help or hinder human decision making (and vice-versa)
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Source International Conference on Software Engineering archive
Proceedings of the 27th international conference on Software engineering table of contents
St. Louis, MO, USA
SESSION: Extending the discipline table of contents
Pages: 36 - 36  
Year of Publication: 2005
ISBN:1-59593-963-2
Author
Peter Ayton  City University, London, UK
Sponsors
ACM: Association for Computing Machinery
SIGSOFT: ACM Special Interest Group on Software Engineering
Publisher
ACM  New York, NY, USA
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ABSTRACT

Developments in computing offer experts in many fields specialised support for decision making under uncertainty. However, the impact of these technologies remains controversial. In particular, it is not clear how advice of variable quality from a computer may affect human decision makers. Here I review research showing strikingly diverse effects of computer support on expert decision-making. Decisions support can both systematically improve or damaged the performance of decision makers in subtle ways depending on the decision maker's skills, variation in the difficulty of individual decisions and the reliability of advice from the support tool.In clinical trials decision support technologies are often assessed in terms of their average effects. However this methodology overlooks the possibility of differential effects on decisions of varying difficulty, on decision makers of varying competence, of computer advice of varying accuracy and of possible interactions among these variables. Research that has teased apart aggregated clinical trial data to investigate these possibilities has discovered that computer support was less useful for - and sometimes hindered - professional experts who were relatively good at difficult decisions without support; at the same time the same computer support tool helped those experts who were less good at relatively easy decisions without support. Moreover, inappropriate advice from the support tool could bias decision makers' decisions and, predictably, depending on the type of case, improve or harm the decisions.