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Algorithmography: Intersections of Truth, Authenticity and Representation of AI Generated Visual Content in Journalism

Abuhamad, Ahmad LU (2024) MKVM13 20241
Media and Communication Studies
Department of Communication and Media
Abstract
As we are in 2024, it's worth noting that generative artificial intelligence technologies are marking their 10th anniversary despite being available online for less than half that time. The rapid adoption of these tools across various professional sectors has prompted researchers to delve into studying them. However, these studies are still in their nascent stages, highlighting the timeliness and importance of this study.
This study takes a different approach to enrich research in the field of generative artificial intelligence, as it does not focus on technology but on its philosophical aspects, mainly the aspects of truth, authenticity, and representation. Three areas intersect in this study: artificial intelligence, journalism, and... (More)
As we are in 2024, it's worth noting that generative artificial intelligence technologies are marking their 10th anniversary despite being available online for less than half that time. The rapid adoption of these tools across various professional sectors has prompted researchers to delve into studying them. However, these studies are still in their nascent stages, highlighting the timeliness and importance of this study.
This study takes a different approach to enrich research in the field of generative artificial intelligence, as it does not focus on technology but on its philosophical aspects, mainly the aspects of truth, authenticity, and representation. Three areas intersect in this study: artificial intelligence, journalism, and imagery. This qualitative study uses the workshops vignetter methodology to dig into these three areas. On the AI side, the study looks at ways journalists justify using these tools in their daily work. The study also examines how to give truthfulness to untrue content through journalistic performativity. The study also attempts to develop new academic concepts for visual content generated by artificial intelligence.
One of the key objectives of this study is to bridge the gap between the imaginary and constructivist approaches. Rather than treating them as separate entities, the study aims to foster a constructive discourse around the imaginary approach, thereby contributing to a more comprehensive understanding of generative artificial intelligence. (Less)
Please use this url to cite or link to this publication:
author
Abuhamad, Ahmad LU
supervisor
organization
course
MKVM13 20241
year
type
H2 - Master's Degree (Two Years)
subject
keywords
Keywords: journalism, generative AI, artificial intelligence, truth, photography, authenticity, representation, performativity, ethics
language
English
id
9151501
date added to LUP
2024-06-17 15:37:21
date last changed
2024-06-17 15:37:21
@misc{9151501,
  abstract     = {{As we are in 2024, it's worth noting that generative artificial intelligence technologies are marking their 10th anniversary despite being available online for less than half that time. The rapid adoption of these tools across various professional sectors has prompted researchers to delve into studying them. However, these studies are still in their nascent stages, highlighting the timeliness and importance of this study.
This study takes a different approach to enrich research in the field of generative artificial intelligence, as it does not focus on technology but on its philosophical aspects, mainly the aspects of truth, authenticity, and representation. Three areas intersect in this study: artificial intelligence, journalism, and imagery. This qualitative study uses the workshops vignetter methodology to dig into these three areas. On the AI side, the study looks at ways journalists justify using these tools in their daily work. The study also examines how to give truthfulness to untrue content through journalistic performativity. The study also attempts to develop new academic concepts for visual content generated by artificial intelligence.
One of the key objectives of this study is to bridge the gap between the imaginary and constructivist approaches. Rather than treating them as separate entities, the study aims to foster a constructive discourse around the imaginary approach, thereby contributing to a more comprehensive understanding of generative artificial intelligence.}},
  author       = {{Abuhamad, Ahmad}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Algorithmography: Intersections of Truth, Authenticity and Representation of AI Generated Visual Content in Journalism}},
  year         = {{2024}},
}