Summary of A Fourth Wave Of Open Data? Exploring the Spectrum Of Scenarios For Open Data and Generative Ai, by Hannah Chafetz et al.
A Fourth Wave of Open Data? Exploring the Spectrum of Scenarios for Open Data and Generative AI
by Hannah Chafetz, Sampriti Saxena, Stefaan G. Verhulst
First submitted to arxiv on: 7 May 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
GrooveSquid.com Paper Summaries
GrooveSquid.com’s goal is to make artificial intelligence research accessible by summarizing AI papers in simpler terms. Each summary below covers the same AI paper, written at different levels of difficulty. The medium difficulty and low difficulty versions are original summaries written by GrooveSquid.com, while the high difficulty version is the paper’s original abstract. Feel free to learn from the version that suits you best!
| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary As the world rapidly adopts generative AI tools like ChatGPT, Gemini, and Claude, it’s crucial to explore the intricate relationship between open data and these models. This white paper aims to unpack this connection and examine the potential for a new Fourth Wave of Open Data. Specifically, it investigates whether open data is becoming AI-ready, moving towards a data commons approach, or making data more conversational. The authors introduce a Spectrum of Scenarios framework outlining various intersection points between open data and generative AI, requiring improved data quality and provenance to make open data ready for these scenarios. These scenarios include perturbation, adaptation, inference, data augmentation, and open-ended exploration. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Generative AI is changing how we access information! Imagine a world where you can ask questions and get answers like a conversation with a human expert. This paper explores the connection between open data and generative AI, asking big questions about what happens when these two technologies combine. The authors think about scenarios where open data and AI could work together to make information more accessible and useful. They also highlight five key areas that need improvement before we can fully unlock the potential of open data and AI: making data transparent, ensuring quality, promoting standards, making it easy to use, and addressing ethical concerns. |
Keywords
» Artificial intelligence » Claude » Data augmentation » Gemini » Inference
