Creative AI: Text and Transformations

Übersicht

This course explores how artificial intelligence is reshaping the way we write, read, and engage with language. Focusing on generative text models, creative writing, and critical perspectives, you’ll learn how language models are trained, how artists and writers are using them in practice, and what social, ethical, and cultural questions they raise.

By the end of the course you will be able to:

Explore how AI can generate and manipulate language using tools like RNNs, LSTMs, and large language models such as GPT. Understand how machine learning systems represent meaning, similarity, and structure in text through vector spaces and model training.

Evaluate the social and ethical implications of language models, including disinformation, bias, surveillance, and the future of authorship. Experiment with code-based and web-based tools for generating text, and reflect on how AI might expand or challenge your own writing practices.

Through creative walkthroughs, coding demos, and critical discussions, you’ll learn how language models function, reflect on how they relate to broader histories of text production, and examine the cultural impact of machine-generated language in media, publishing, and online discourse. Featuring insights from leading researchers, technologists, and experimental writers, this course provides both the conceptual grounding and practical tools to begin working with AI in your own creative text-based projects.

No coding experience is required, just curiosity and a desire to explore new forms of writing and expression.

Lehrplan

• Introduction to text generation with recurrent neural networks
In this first module, we explore how large language models like GPT generate and understand text, and how these systems are being used by artists and writers in creative and experimental ways. You’ll learn how AI is trained on text data, the differences between generative and retrieval-based models, and begin to reflect on the ethical and creative implications of AI-generated language.
• Bias and disinformation
In this module, we explore how AI language models can encode and reinforce social bias, and examine the role of AI in amplifying or combating disinformation. Through hands-on activities, you’ll learn how word vectors work and how they can reflect underlying gender, racial, and class bias. You’ll experiment with tools that expose bias in word embeddings, investigate AI’s tendency to hallucinate or generate false information, and consider how artists and researchers are using AI to track and challenge misinformation online.
• Large Language Models
In this final module, we focus on large language models (LLMs) like ChatGPT and explore how they are reshaping creative writing, communication, and authorship. You’ll learn how these models are built, how they process prompts, and how artists and writers are working with them in experimental and collaborative ways. Through code walkthroughs and creative activities, you’ll reflect on what it means to “write with” AI, and consider how these systems raise new questions around originality, labour, and voice in contemporary writing.

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Unterrichtet von

Terence Broad

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Fachgebiete

Computer Science