Mind the data gap(s): Investigating power in speech and language datasets

Markl, Nina

doi:10.18653/v1/2022.ltedi-1.1

Cited by 2 publications

(1 citation statement)

References 27 publications

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“…A comprehensive discussion of stakeholders, emphasizing their relative power, is crucial for understanding the associated risks. As various researchers have articulated, it is essential to underscore power inequities by considering what might be absent from a dataset [62,102]. We build upon this observation, and various other insights on the relations between power structures and socio-technical algorithmic systems [21,84,86], structuring our analysis around the inclusion or exclusion of various groups in the development and deployment of these models.…”

Section: Stakeholders and Power Dynamicsmentioning

confidence: 99%

Typology of Risks of Generative Text-to-Image Models

Bird,

Ungless,

Kasirzadeh

2023

Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society

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This paper investigates the direct risks and harms associated with modern text-to-image generative models, such as DALL-E and Midjourney, through a comprehensive literature review. While these models offer unprecedented capabilities for generating images, their development and use introduce new types of risk that require careful consideration. Our review reveals significant knowledge gaps concerning the understanding and treatment of these risks despite some already being addressed. We offer a taxonomy of risks across six key stakeholder groups, inclusive of unexplored issues, and suggest future research directions. We identify 22 distinct risk types, spanning issues from data bias to malicious use. The investigation presented here is intended to enhance the ongoing discourse on responsible model development and deployment. By highlighting previously overlooked risks and gaps, it aims to shape subsequent research and governance initiatives, guiding them toward the responsible, secure, and ethically conscious evolution of text-to-image models.CCS Concepts: • Human-centered computing → Human computer interaction (HCI); Text input; • Applied computing → Media arts; • Social and professional topics → User characteristics.

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