As artificial intelligence (AI), machine learning (ML), and Large Language Models (LLM) technologies continue to evolve, they offer new possibilities for humanities research, from large-scale text and image analysis to generative AI applications that synthesize and extrapolate knowledge. This workshop introduces key AI/ML/LLM concepts, including neural networks, large language models, and large image models, while exploring their potential for enhancing research methodologies in the humanities. Participants will examine case studies, such as computational literary analysis and image recognition in spatial studies and art history, and engage in hands-on exercises to compare models, craft prompts, and assess AI-generated outputs. Beyond technical applications, the workshop will also address critical ethical concerns surrounding AI, including bias, the network effects of dis- and misinformation, and the authenticity of historical records.

Discussions will highlight issues of fairness, intellectual property, and academic integrity, drawing from key scholarship in algorithmic ethics and data justice. By the end of the session, participants will gain a foundational understanding of AI’s role in the humanities, along with practical tools and frameworks for critically engaging with these technologies in their own research and teaching.

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