From Melting Pots to Misrepresentations: Exploring Harms in Generative AI
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arXiv
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| Format: | Preprint |
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2024
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| _version_ | 1866917616369532928 |
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| author | Gautam, Sanjana Venkit, Pranav Narayanan Ghosh, Sourojit |
| author_facet | Gautam, Sanjana Venkit, Pranav Narayanan Ghosh, Sourojit |
| contents | With the widespread adoption of advanced generative models such as Gemini and GPT, there has been a notable increase in the incorporation of such models into sociotechnical systems, categorized under AI-as-a-Service (AIaaS). Despite their versatility across diverse sectors, concerns persist regarding discriminatory tendencies within these models, particularly favoring selected `majority' demographics across various sociodemographic dimensions. Despite widespread calls for diversification of media representations, marginalized racial and ethnic groups continue to face persistent distortion, stereotyping, and neglect within the AIaaS context. In this work, we provide a critical summary of the state of research in the context of social harms to lead the conversation to focus on their implications. We also present open-ended research questions, guided by our discussion, to help define future research pathways. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_10776 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | From Melting Pots to Misrepresentations: Exploring Harms in Generative AI Gautam, Sanjana Venkit, Pranav Narayanan Ghosh, Sourojit Human-Computer Interaction Artificial Intelligence Computers and Society Machine Learning With the widespread adoption of advanced generative models such as Gemini and GPT, there has been a notable increase in the incorporation of such models into sociotechnical systems, categorized under AI-as-a-Service (AIaaS). Despite their versatility across diverse sectors, concerns persist regarding discriminatory tendencies within these models, particularly favoring selected `majority' demographics across various sociodemographic dimensions. Despite widespread calls for diversification of media representations, marginalized racial and ethnic groups continue to face persistent distortion, stereotyping, and neglect within the AIaaS context. In this work, we provide a critical summary of the state of research in the context of social harms to lead the conversation to focus on their implications. We also present open-ended research questions, guided by our discussion, to help define future research pathways. |
| title | From Melting Pots to Misrepresentations: Exploring Harms in Generative AI |
| topic | Human-Computer Interaction Artificial Intelligence Computers and Society Machine Learning |
| url | https://arxiv.org/abs/2403.10776 |