國立虎尾科技大學 |

The Role of AI in Complex Problem-Solving and Implications for Human-Centric AI /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	The Role of AI in Complex Problem-Solving and Implications for Human-Centric AI // Seo-young Lee.
Author:	Lee, Seo-young,
Description:	1 electronic resource (180 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 86-03, Section: B.
Contained By:	Dissertations Abstracts International86-03B.
Subject:	Information science. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=31333422
ISBN:	9798384049074

The Role of AI in Complex Problem-Solving and Implications for Human-Centric AI /
Lee, Seo-young,

The Role of AI in Complex Problem-Solving and Implications for Human-Centric AI /Seo-young Lee. - 1 electronic resource (180 pages)

Source: Dissertations Abstracts International, Volume: 86-03, Section: B.

This dissertation explores the current and potential roles of AI in complex problem-solving, especially focusing on how AI can support creative design and decision-making. Chapter 2 includes a systematic literature review and a design workshop with design experts to understand when and how to use AI in the design process. The results showed that most current AI design support systems focus on generating design solutions. More support is needed for providing inspiration, defining design problems with constraints, offering grounded metaphors, and exploring design materials.Chapter 3 compares the different roles of AI in creative design problem-solving. Two different roles of AI are compared depending on its proactivity in interaction: 1) Active AI, which helps humans understand design problems with constraints through mutual collaboration, and 2) Reactive AI, which helps only when humans seek it out. Results showed that participants generated a better quality and quantity of ideas when interacting with Active AI compared to Reactive AI. Working alone was even more helpful than working with Reactive AI.Chapter 4 examines how people make decisions in AI-assisted decision-making and its ethical implications. This chapter examines how the identity of the suggestion giver (AI vs. human experts) and the accuracy of the information (correct vs. incorrect) influence decision-making behaviors. Results showed that people trusted AI less than human experts, even when human experts provided incorrect information and AI provided correct information. Additionally, they significantly changed their decisions when receiving information from humans. The results also showed that decision-making changes varied depending on the objectivity and content of the task. Chapter 5 provides a summary of the main findings along with their design and practical implications.

English

ISBN: 9798384049074Subjects--Topical Terms:

561178
Information science.
Subjects--Index Terms:

Active AI

The Role of AI in Complex Problem-Solving and Implications for Human-Centric AI /
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520 $a This dissertation explores the current and potential roles of AI in complex problem-solving, especially focusing on how AI can support creative design and decision-making. Chapter 2 includes a systematic literature review and a design workshop with design experts to understand when and how to use AI in the design process. The results showed that most current AI design support systems focus on generating design solutions. More support is needed for providing inspiration, defining design problems with constraints, offering grounded metaphors, and exploring design materials.Chapter 3 compares the different roles of AI in creative design problem-solving. Two different roles of AI are compared depending on its proactivity in interaction: 1) Active AI, which helps humans understand design problems with constraints through mutual collaboration, and 2) Reactive AI, which helps only when humans seek it out. Results showed that participants generated a better quality and quantity of ideas when interacting with Active AI compared to Reactive AI. Working alone was even more helpful than working with Reactive AI.Chapter 4 examines how people make decisions in AI-assisted decision-making and its ethical implications. This chapter examines how the identity of the suggestion giver (AI vs. human experts) and the accuracy of the information (correct vs. incorrect) influence decision-making behaviors. Results showed that people trusted AI less than human experts, even when human experts provided incorrect information and AI provided correct information. Additionally, they significantly changed their decisions when receiving information from humans. The results also showed that decision-making changes varied depending on the objectivity and content of the task. Chapter 5 provides a summary of the main findings along with their design and practical implications.
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