Visualising an undergraduate geography field class using generative AI: Intent, expectations and surprises about the racial depiction of students

IF 1.6 2区 社会学 Q2 GEOGRAPHY
Area Pub Date : 2025-01-30 DOI:10.1111/area.12996
Terence Day, James Esson
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引用次数: 0

Abstract

This commentary reflects on an attempt to use ChatGPT to generate an image for a geography textbook. We explore why the image that was produced provoked surprise and intrigue and think through how our reactions revealed ingrained assumptions about educational spaces. Our discussion highlights the importance of intentionality in prompt design and offers a reminder of how seemingly neutral prompts can reproduce dominant narratives. We conclude by proposing that as generative AI becomes more prevalent in geography education, this take-up needs to critically engage with the ethical and societal implications of AI use so we can actively challenge ourselves as well as the technology.

Abstract Image

使用生成式人工智能可视化本科地理课程:学生种族描述的意图、期望和惊喜
这篇评论反映了使用ChatGPT为地理教科书生成图像的尝试。我们探讨了为什么产生的图像引起了惊讶和好奇,并思考了我们的反应如何揭示了对教育空间根深蒂固的假设。我们的讨论强调了提示设计中意向性的重要性,并提醒我们看似中性的提示是如何再现主导叙事的。最后,我们提出,随着生成式人工智能在地理教育中变得越来越普遍,这种接受需要批判性地参与人工智能使用的伦理和社会影响,这样我们才能积极地挑战自己和技术。
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来源期刊
Area
Area GEOGRAPHY-
CiteScore
5.20
自引率
13.60%
发文量
80
审稿时长
24 weeks
期刊介绍: Area publishes ground breaking geographical research and scholarship across the field of geography. Whatever your interests, reading Area is essential to keep up with the latest thinking in geography. At the cutting edge of the discipline, the journal: • is the debating forum for the latest geographical research and ideas • is an outlet for fresh ideas, from both established and new scholars • is accessible to new researchers, including postgraduate students and academics at an early stage in their careers • contains commentaries and debates that focus on topical issues, new research results, methodological theory and practice and academic discussion and debate • provides rapid publication
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