Date of Award

2022

Document Type

Dissertation

Degree Name

Ph.D.

Organizational Unit

Daniels College of Business

First Advisor

Daniel Baack

Second Advisor

Lisa Victoravich

Third Advisor

Dennis Wittmer

Keywords

AI, Artificial intelligence, Reciprocity, Social capital, Trust

Abstract

People have historically used personal introductions to build social capital, which is the foundation of career networking and is perhaps the most effective way to advance a career (Lin, 2001). With societal changes, such as the pandemic (Venkatesh & Edirappuli, 2020), and the increasing capabilities of Artificial Intelligence (AI), new approaches may emerge that impact societal relationships. Social capital theory highlights the need for reciprocal agreements to establish the trust between parties (Gouldner, 1960). My theoretical prediction and focus of this research include two principles: The impact of reciprocity in evaluating trust of the source of the introduction and the acceptability of AI in interpersonal relationships. I test this relationship through the creation of plausible vignettes that the participants may have encountered in business. The results show that a higher trust of AI and could replace one side of the relationship, thus reducing the dependency on or eliminating reciprocal behavior.

Publication Statement

Copyright is held by the author. User is responsible for all copyright compliance.

Rights Holder

Peter Tripp

Provenance

Received from ProQuest

File Format

application/pdf

Language

en

File Size

169 pgs

Discipline

Artificial intelligence, Social structure

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