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Operations System

In: Business and Management

Submitted By pushashi
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9/8/06

11:33 AM

REAL WORLD

CASE

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Page 386

2

Harrah’s Entertainment,
LendingTree, DeepGreen
Financial, and Cisco Systems:
Successes and Challenges of
Automated Decision Making

or over half a century, the field of artificial intelligence
(AI) has promised that computers would relieve managers and professionals of the need to make certain types of decisions. Computer programs would analyze data and make sound judgments whether it be to configure a complex computer, diagnose and treat a patient’s illness, or determine when to stir a big vat of soup with little or no human help.
But automated decision making has been slow to materialize. Many early artificial intelligence applications were just solutions looking for problems, contributing little to improved organizational performance. In medicine, for example, doctors showed little interest in having machines diagnose their patients’ diseases. In the business sector, even when expert systems were directed at real issues, extracting the right kind of specialized knowledge from seasoned decision makers and maintaining it over time proved to be more difficult than anticipated.
But now, automated decision making is finally coming of age. The new generation of applications, however, differs from prior AI-based decision support systems in several important respects. To begin with, the new systems are easier to create and manage than earlier ones, which leaned heavily on the expertise of knowledge engineers. What’s more, the new applications do not require anyone to identify the problems or to initiate the analysis. Indeed, decision-making capabilities are embedded into the normal flow of work, and they are typically triggered without human intervention: They sense online data or conditions, apply codified knowledge or logic

FIGURE 10.23

Business uses…...

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