Creative AI: Text and Transformations
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There are 3 modules in this course
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.
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.
What's included
11 readings2 assignments3 ungraded labs
11 readings•Total 110 minutes
- Introduction to text and transformations•10 minutes
- History of communicating with text •10 minutes
- Text as characters, characters as numbers•10 minutes
- Text as words, words as numbers•10 minutes
- Text as a sequence•10 minutes
- Introduction to markov chains•10 minutes
- Introduction to recurrent neural networks•10 minutes
- Variations of RNNs•10 minutes
- Creative uses of RNNs•10 minutes
- Introduction to CharRNN and wordRNN•10 minutes
- Module 1: Recap - Predicting text •10 minutes
2 assignments•Total 40 minutes
- Predict the next word in a sequence•10 minutes
- Understanding Recurrent Neural Networks•30 minutes
3 ungraded labs•Total 180 minutes
- Code walkthrough: Markov chain notebook•60 minutes
- Code Walkthrough: CharRNN•60 minutes
- Code Walkthrough: WordRNN code notebook•60 minutes
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.
What's included
3 videos9 readings2 assignments2 discussion prompts1 ungraded lab
3 videos•Total 18 minutes
- How does AI reinforce bias?•10 minutes
- Could AI amplify disinformation?•3 minutes
- Interview with the artist Gaëtan Robillard•5 minutes
9 readings•Total 90 minutes
- What is a vector?•10 minutes
- Representing words as vectors•10 minutes
- Bias in word vectors•10 minutes
- Addressing bias in data and AI•10 minutes
- Disinformation on the internet•10 minutes
- Generative text and hallucinations•10 minutes
- Showcase: Critical Climate Machine•10 minutes
- How can AI be used to track disinformation•10 minutes
- Module 2 recap: AI, truth and text•10 minutes
2 assignments•Total 60 minutes
- Reflect on similarity•30 minutes
- Should AI disinformation be regulated?•30 minutes
2 discussion prompts•Total 20 minutes
- Reflecting on Bias in Word Vectors•10 minutes
- New Discussion Prompt•10 minutes
1 ungraded lab•Total 60 minutes
- Code walkthrough: word vector notebook•60 minutes
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.
What's included
1 video12 readings1 assignment1 discussion prompt1 ungraded lab
1 video•Total 7 minutes
- Does AI perpetuate western bias?•7 minutes
12 readings•Total 120 minutes
- New Reading•10 minutes
- Attention is all you need•10 minutes
- The exponential rise of LLMs•10 minutes
- Introducing nanoGPT•10 minutes
- Training and fine-tuning LLMs•10 minutes
- The value of open source models•10 minutes
- The Broader Impacts of Generative AI•10 minutes
- The ecological impacts of AI•10 minutes
- Creative uses of LLMs•10 minutes
- LLMs impact on the creative industries•10 minutes
- Future of LLMs•10 minutes
- Course summary•10 minutes
1 assignment•Total 30 minutes
- What impacts of LLMs are most concerning to you?•30 minutes
1 discussion prompt•Total 10 minutes
- Do you use LLMs?•10 minutes
1 ungraded lab•Total 60 minutes
- Code Walkthrough: LLM's•60 minutes
Instructor
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- Status: PreviewU
University of the Arts London
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- Status: Free TrialS
Saïd Business School, University of Oxford
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- Status: PreviewU
University of the Arts London
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