Why AI Is WEIRD and Should Not Be This Way: Towards AI For Everyone, With Everyone, By Everyone
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arXiv
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| Main Authors: | , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2024
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| _version_ | 1866917812308541440 |
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| author | Mihalcea, Rada Ignat, Oana Bai, Longju Borah, Angana Chiruzzo, Luis Jin, Zhijing Kwizera, Claude Nwatu, Joan Poria, Soujanya Solorio, Thamar |
| author_facet | Mihalcea, Rada Ignat, Oana Bai, Longju Borah, Angana Chiruzzo, Luis Jin, Zhijing Kwizera, Claude Nwatu, Joan Poria, Soujanya Solorio, Thamar |
| contents | This paper presents a vision for creating AI systems that are inclusive at every stage of development, from data collection to model design and evaluation. We address key limitations in the current AI pipeline and its WEIRD representation, such as lack of data diversity, biases in model performance, and narrow evaluation metrics. We also focus on the need for diverse representation among the developers of these systems, as well as incentives that are not skewed toward certain groups. We highlight opportunities to develop AI systems that are for everyone (with diverse stakeholders in mind), with everyone (inclusive of diverse data and annotators), and by everyone (designed and developed by a globally diverse workforce). |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_16315 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Why AI Is WEIRD and Should Not Be This Way: Towards AI For Everyone, With Everyone, By Everyone Mihalcea, Rada Ignat, Oana Bai, Longju Borah, Angana Chiruzzo, Luis Jin, Zhijing Kwizera, Claude Nwatu, Joan Poria, Soujanya Solorio, Thamar Computers and Society This paper presents a vision for creating AI systems that are inclusive at every stage of development, from data collection to model design and evaluation. We address key limitations in the current AI pipeline and its WEIRD representation, such as lack of data diversity, biases in model performance, and narrow evaluation metrics. We also focus on the need for diverse representation among the developers of these systems, as well as incentives that are not skewed toward certain groups. We highlight opportunities to develop AI systems that are for everyone (with diverse stakeholders in mind), with everyone (inclusive of diverse data and annotators), and by everyone (designed and developed by a globally diverse workforce). |
| title | Why AI Is WEIRD and Should Not Be This Way: Towards AI For Everyone, With Everyone, By Everyone |
| topic | Computers and Society |
| url | https://arxiv.org/abs/2410.16315 |