How to Prompt? Opportunities and Challenges of Zero- and Few-Shot Learning for Human-AI Interaction in Creative Applications of Generative Models
September 03, 2022 Β· Declared Dead Β· π arXiv.org
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Authors
Hai Dang, Lukas Mecke, Florian Lehmann, Sven Goller, Daniel Buschek
arXiv ID
2209.01390
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.CL
Citations
144
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Deep generative models have the potential to fundamentally change the way we create high-fidelity digital content but are often hard to control. Prompting a generative model is a promising recent development that in principle enables end-users to creatively leverage zero-shot and few-shot learning to assign new tasks to an AI ad-hoc, simply by writing them down. However, for the majority of end-users writing effective prompts is currently largely a trial and error process. To address this, we discuss the key opportunities and challenges for interactive creative applications that use prompting as a new paradigm for Human-AI interaction. Based on our analysis, we propose four design goals for user interfaces that support prompting. We illustrate these with concrete UI design sketches, focusing on the use case of creative writing. The research community in HCI and AI can take these as starting points to develop adequate user interfaces for models capable of zero- and few-shot learning.
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