Create a new thread. As indicated above, select two of the six cases and compare and contrast them, explaining how clear authority affected the outcomes.

Attaching the six case studies pdf.

Chapter 10 presents six case studies where the trustworthiness of data were at varying levels with high margins of error. Pick one case with high trustworthiness of data and one with lower trustworthiness and compare and contrast them, clarifying how the “lines of authority” dictated the outcomes.

To complete this assignment, you must do the following:

A) Create a new thread. As indicated above, select two of the six cases and compare and contrast them, explaining how clear authority affected the outcomes.

ITS 832 Chapter 10

Values in Computational Models Revalued

Information Technology in a Global Economy

Dr. Mike Peterson

Introduction

• Technology perceptions • Technology and public decision making • Methodology • Case studies • Analysis • Summary and conclusions

Technology Perceptions

• Debate on underlying assumptions of models • Are models biased?

• Is technology biased? • Are model builders biased? • Are model users biased?

• Technological determinism • Technology is not neutral of value-free

• Social construction of technology • Technology is designed with bias, or values

• Technological instrumentalism • Technology is neutral and value-free

Technology and Public Decision Making

• Policy making involves complex systems • Model bias must be understood to evaluate results • Bias, or value can be categorized

• Values of the data

• Values of the model

• Values of the decision-making process

Methodology

• Select six case studies • Carry out secondary analysis of results • Identify cases with three basic characteristics

• New model designed for case

• Relate to policy issues with the natural or built world

• Highly complex and controversial issues

Case Studies

• Morphological Predictions in the Westerschele (Belgium and the Netherlands)

• Morphological Predictions in the Unterlbe (Germany) • Flood-Risk Prediction (Germany and the Netherlands) • Determining the Implementation of Congestion Charging

in London (UK)

• Predicting and Containing the Outbreak of Livestock Diseases (Germany)

• Predicting Particular Matter Concentrations (the Netherlands)

Analysis

• Analyzing empirical data resulted in several findings • Values in data

• Cases 1-4 exhibited higher trustworthiness of data

• Margin of error high in all cases

• Values in the model • Similar to values in data findings

• Values in the decision-making process • Clear lines of authority in cases 1, 4, and 5

• Lack of clear authority (cases 2, 3, and 6) leads to conflict

Summary and Conclusions

• Model effectiveness is impacted by bias • Values can originate from multiple sources

• Data

• Model design

• Model use

• Outcome validity requires a clear understanding of values put forth by model use

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