Material Detail

RESEARCH PAPER (67 PAGES)

ABSTRACTThe sudden emergence of user-friendly, easily accessible AI platforms has ushered in a new era in visual media messaging. This paper explains the origins of AI image generation, including the training done to prepare platforms such as Midjourney, and then explores the techniques artists and media professionals use to create images using artificial intelligence tools. A significant part of the research delves into questions of authenticity and ownership and the resistance that AI imagery faces from traditional artists and communication professionals in the art, commercial, and media sectors of society. Concerns about AI's alleged lack of human intentionality and connection are confronted and addressed with examples of work by the author and by other professionals in the art and media world, including work being done by internationally renowned photographers with credentials that include the Magnum Photo Agency and National Geographic. With a lengthy career and background in photojournalism, documentary, and advocacy media work, Blumenkrantz conducts an in-depth study of the capabilities and limitations of AI imagery done in a "photorealistic" style and makes the case, based on his use of the tools, that there is no such genre as "AI Photography," since no camera, or "writing with light" is involved. Other styles of AI imagery are subsequently discussed, including those made to look like paintings, drawings, cartoons, and graphic designs. The ethical implications of "deepfakes" and other methods used to potentially mislead viewers or misrepresent subject matter are covered, as are issues related to copyright and ownership, concerning both the creation of content made through algorithms trained by AI companies and images created by AI platforms for sale or publication. The study also looks at some of the unfair labor practices that exploit workers in Kenya involved in the AI platform training process. A significant effort is made here to address issues of implicit bias in AI imagery, including the self-perpetuating "feedback loop" that AI image generation contributes to. The final section of this research looks at what experts are calling "Co-Intelligence," that is, the collaboration between human and machine learning, which in relatively simpler times was thought of as Singularity but now signifies the potential for constructive outcomes that can occur when we work together with AI platforms, to bring the human touch to complement the informational and creative outputs of artificial intelligence. This includes examples of how the author has introduced assignments to teach responsible use of AI image and text generation to university journalism students and goes into some fruitful collaborations that involve creating fiction and non-fiction storytelling that combine human and machine text and imagery. Finally, there are experimentations with platforms that analyze, critique, describe, and even compose poetry based on images, both AI and photography. 

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