Summary of Autalic: a Dataset For Anti-autistic Ableist Language in Context, by Naba Rizvi et al.
AUTALIC: A Dataset for Anti-AUTistic Ableist Language In Context
by Naba Rizvi, Harper Strickland, Daniel Gitelman, Tristan Cooper, Alexis Morales-Flores, Michael Golden, Aekta Kallepalli, Akshat Alurkar, Haaset Owens, Saleha Ahmedi, Isha Khirwadkar, Imani Munyaka, Nedjma Ousidhoum
First submitted to arxiv on: 21 Oct 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed research presents a benchmark dataset for detecting anti-autistic ableist language in context, which is critical to improving the accuracy of natural language processing (NLP) models. The AUTALIC dataset consists of 2,400 autism-related sentences from Reddit, accompanied by surrounding context, and is annotated by experts with backgrounds in neurodiversity. The evaluation reveals that current language models struggle to reliably identify anti-autistic ableism and align with human judgments, highlighting their limitations in this domain. This research aims to develop more inclusive and context-aware NLP systems that better reflect diverse perspectives. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This study creates a special dataset called AUTALIC that helps computers understand when people are using language that is not respectful towards autistic individuals. The data includes 2,400 sentences about autism from the internet, along with the surrounding text. Experts who understand neurodiversity helped label these sentences to show whether they contain harmful or offensive language. Researchers found that current computer models struggle to accurately identify this kind of language and agree with human judgments. This study is important because it can help develop better computer systems that are more considerate and inclusive. |
Keywords
» Artificial intelligence » Natural language processing » Nlp
