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Why AI Is WEIRD and Shouldn’t Be This Way: Towards AI For Everyone, With Everyone, By Everyone
Mihalcea, R Ignat, O Bai, L Borah, A Chiruzzo, L Jin, Z Kwizera, C Nwatu, J Poria, S Solorio, T
Mihalcea, R
Ignat, O
Bai, L
Borah, A
Chiruzzo, L
Jin, Z
Kwizera, C
Nwatu, J
Poria, S
Solorio, T
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Natural Language Processing
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Conference proceeding
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Abstract
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<sup>1</sup> 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).
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Proceedings of the Aaai Conference on Artificial Intelligence
Conference
AAAI Conference on Artificial Intelligence
Keywords
Information and Computing Sciences, Human-Centred Computing, Health Disparities, Machine Learning and Artificial Intelligence, Health Disparities and Racial or Ethnic Minority Health Research
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AAAI Conference on Artificial Intelligence
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Association for the Advancement of Artificial Intelligence (AAAI)