{"id":812,"date":"2024-11-04T13:40:17","date_gmt":"2024-11-04T12:40:17","guid":{"rendered":"https:\/\/visqual.leibniz-ifl-projekte.de\/methodbox\/?p=812"},"modified":"2025-06-27T13:26:08","modified_gmt":"2025-06-27T11:26:08","slug":"artificial-intelligence-and-photography","status":"publish","type":"post","link":"https:\/\/visqual.leibniz-ifl-projekte.de\/methodbox\/2024\/11\/04\/artificial-intelligence-and-photography\/","title":{"rendered":"ARTIFICIAL INTELLIGENCE AND PHOTOGRAPHY"},"content":{"rendered":"\n

Triggering reflections and debates in educational contexts<\/h2>\n\n\n\n

Author:
<\/strong>Greinke, Lena<\/p>\n\n\n\n

Citation:
<\/strong>Greinke, L. (2024): Artificial intelligence and photography: Use of AI in educational contexts. In: VisQual Methodbox, URL: https:\/\/visqual.leibniz-ifl-projekte.de\/methodbox\/2024\/11\/04\/artificial-intelligence-and-photography\/<\/p>\n\n\n\n

Essentials<\/h2>\n\n\n\n
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  • Use of Artificial intelligence as a helpful tool for reflection: <\/em>During discussions with students, AI-assisted imaging can stimulate critical reflections on specific topics.<\/li>\n\n\n\n
  • Use of Artificial intelligence and photography as a method to enhance creativity:<\/em> The use of AI to transform photos can help to be creative and think more broadly.<\/li>\n\n\n\n
  • Artificial intelligence as a support tool: <\/em>AI can support students, researchers, and practitioners in their research and planning processes (when it is fed with the appropriate prompts and critically reflected).<\/li>\n<\/ul>\n\n\n\n

    Description<\/h2>\n\n\n\n

    Admittedly, artificial intelligence (further: AI, and its terminology, such as LLM, AGI, etc.), its impacts for society and science, and its technological black boxes is a maze that many qualitative researchers have not, so far, been able to explore extensively. Whilst utopian and dystopian public narratives compete for framing an AI-future-driven public discourse, many disciplines have started to explore AI\u2019s potential for utilization in research processes, e.g., enhancing quantitative and qualitative data analyses and boosting literature-screening processes. In the following, I will detail a different approach to utilize AI-capabilities for visualization in educational contexts, e.g. to stimulate reflection discussions or to enhance creativity of students in environmental planning.<\/p>\n\n\n\n

    The historical development of AI goes back to the 1850s. In 1847, for example, a formal language for logic reasoning was described for the first time. AI gained momentum again almost 100 years later when the Turing machine was described in 1936, and the model of artificial neurons was created in 1943. However, the term AI was not used until 1956. Nowadays, however, AI has a different meaning: \u201ccreating intelligent agents to help us do our work faster and easier\u201d (Benko & L\u00e1nyi 2009).<\/p>\n\n\n\n

    Generating photos with AI is becoming increasingly popular. Often, AIs (such as DALL-E, Stable Diffusion) use web-based interfaces of which many are open source. Various AIs allow users to generate photos by entering prompts, which are textual descriptions of the image. In a course for students of environmental planning, AI was used to do so: In this example, the (in 2022) state-of-the-art text-to-image generator DALL-E 2 was used. Different word combinations and settings can be selected. For example, by entering the same prompt in five different AIs, G\u00f6ring et al. (2023: 38999-39000) showed that although the AIs can produce images that match the prompts, they do not all look realistic and are of good quality. In some cases, the AI developed somehow realistic flowers, but also created different colors than prompted (e.g. yellow instead of purple) or build artificial or artistic pictures (G\u00f6ring et al. 2023: 38999).<\/p>\n\n\n\n

    How the AI works and what the AI changes or reinvents in the photos is usually not explained on the AI websites. It therefore remains a black box as to how the AI reaches its results. Concludingly, it seems problematic to consider AI-images as evidence for something (e.g., the salience of a specific artifact), as the generating algorithms and complexities of information and learning processes in these neural networks resist retrospective dissection. Furthermore, AIs continuously improve with increasing data analysis, user interaction, and increased IT-capabilities.<\/p>\n\n\n\n

    This introduces us to a peculiar paradox: Despite AI\u2019s increased capabilities, its potentials use cases for data generation have, so far, not shown a comparable inflation. However, I will present one example where AI was used to trigger processes of reflection in an educational context.<\/p>\n\n\n\n

    Procedure<\/h2>\n\n\n\n

    Depending on the type and use, AI can take on different functions in teaching and learning (Girgensohn et al. 2023: 12f.). \u201c[the] AI model can be your friend, philosopher, and guide \u2026 and even your worst enemy\u201d (Chatterjee & Dethlefs 2023). For example, it can be used for inspiration, to concretize a research question or to structure texts as well as for literature research (Girgensohn et al. 2023: 12f.). In order to use AI to stimulate critical reflection by and with students on safety and crime prevention using the example of specific urban areas, different approaches can be applied.<\/p>\n\n\n\n

    The following example describes a critical reflection discussion on AI and the transformation of photos:<\/p>\n\n\n\n