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Human Recognition Theory and Facial Recognition Technology: A Topic Modeling Approach to Understanding the Ethical Implication of a Developing Algorithmic Technologies Landscape on How We View Ourselves and Are Viewed by Others

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Title: Human Recognition Theory and Facial Recognition Technology: A Topic Modeling Approach to Understanding the Ethical Implication of a Developing Algorithmic Technologies Landscape on How We View Ourselves and Are Viewed by Others
Authors: Albalawi, Hajer
Committee Members: Beever, Jonathan
Summary: The emergence of algorithmic-driven technology has significantly impacted human life in the current century. Algorithms, as versatile constructs, hold different meanings across various disciplines, including computer science, mathematics, social science, and human-artificial intelligence studies. This study defines algorithms from an ethical perspective as the foundation of an information society and focuses on their implications in the context of human recognition. Facial recognition technology, driven by algorithms, has gained widespread use, raising important ethical questions regarding privacy, bias, and accuracy. This dissertation aims to explore the impact of algorithms on machine perception of human individuals and how humans perceive one another and themselves. By analyzing publications from the National Institute of Standards and Technology (NIST) and employing topic modeling, this research identifies the ethical themes surrounding facial recognition technology. The findings contribute to a broader understanding of the ethical implications of algorithms in shaping human perception and interaction, with a focus on the multidimensional aspects of human recognition theory. The research also examines the ethical considerations in AI-AI interactions, human-AI interactions, and humans perceiving themselves in the context of facial recognition technology. The study establishes a framework of human recognition theory that encompasses the alteration and reshaping of fundamental human values and self-perception, highlighting the transformative effects of algorithmic-driven technologies on human identity and values. The dissertation chapters provide a comprehensive overview of the influence of AI on societal values and identity, the revolution of big data and Information and Communication Technology (ICT), the concept of digital identity in the fourth industrial revolution, and recognition theory in the era of algorithms. The research aims to inform discussions and policy decisions regarding the responsible development and deployment of algorithms in recognition processes, addressing the challenges and opportunities brought about by algorithmic systems in shaping human recognition, identity, and the social fabric of our increasingly algorithmic society.
URL: https://stars.library.ucf.edu/etd2020/1870
Database: OpenDissertations
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PubType: Dissertation/ Thesis
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  Data: The emergence of algorithmic-driven technology has significantly impacted human life in the current century. Algorithms, as versatile constructs, hold different meanings across various disciplines, including computer science, mathematics, social science, and human-artificial intelligence studies. This study defines algorithms from an ethical perspective as the foundation of an information society and focuses on their implications in the context of human recognition. Facial recognition technology, driven by algorithms, has gained widespread use, raising important ethical questions regarding privacy, bias, and accuracy. This dissertation aims to explore the impact of algorithms on machine perception of human individuals and how humans perceive one another and themselves. By analyzing publications from the National Institute of Standards and Technology (NIST) and employing topic modeling, this research identifies the ethical themes surrounding facial recognition technology. The findings contribute to a broader understanding of the ethical implications of algorithms in shaping human perception and interaction, with a focus on the multidimensional aspects of human recognition theory. The research also examines the ethical considerations in AI-AI interactions, human-AI interactions, and humans perceiving themselves in the context of facial recognition technology. The study establishes a framework of human recognition theory that encompasses the alteration and reshaping of fundamental human values and self-perception, highlighting the transformative effects of algorithmic-driven technologies on human identity and values. The dissertation chapters provide a comprehensive overview of the influence of AI on societal values and identity, the revolution of big data and Information and Communication Technology (ICT), the concept of digital identity in the fourth industrial revolution, and recognition theory in the era of algorithms. The research aims to inform discussions and policy decisions regarding the responsible development and deployment of algorithms in recognition processes, addressing the challenges and opportunities brought about by algorithmic systems in shaping human recognition, identity, and the social fabric of our increasingly algorithmic society.
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RecordInfo BibRecord:
  BibEntity:
    Languages:
      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: Algorithmic ethics; Facial recognition; Human identity; Social perception; AI interactions
        Type: general
      – SubjectFull: Graphics and Human Computer Interfaces
        Type: general
      – SubjectFull: Human face recognition (Computer science); Computer algorithms--Social aspects; Artificial intelligence--Social aspects; Image processing--Digital techniques--Moral and ethical aspects; Artificial intelligence--Moral and ethical aspects
        Type: general
    Titles:
      – TitleFull: Human Recognition Theory and Facial Recognition Technology: A Topic Modeling Approach to Understanding the Ethical Implication of a Developing Algorithmic Technologies Landscape on How We View Ourselves and Are Viewed by Others
        Type: main
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          Name:
            NameFull: Albalawi, Hajer
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          Dates:
            – D: 15
              M: 08
              Type: published
              Y: 2023
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