Typology of risks of generative text-to-image models

Charlotte Bird, Eddie Ungless, Atoosa Kasirzadeh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

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.
Original languageEnglish
Title of host publicationAIES '23
Subtitle of host publicationProceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society
EditorsFrancesca Rossi, Sanmay Das, Jenny Davis, Kay Firth-Butterfield, Alex John
Place of PublicationNew York
PublisherAssociation for Computing Machinery (ACM)
Pages 396–410
Number of pages15
ISBN (Electronic)9798400702310
DOIs
Publication statusPublished - 29 Aug 2023
EventSixth AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society - Palais des congrès de Montréal, Montréal, Canada
Duration: 8 Aug 202310 Aug 2023
https://www.aies-conference.com/2023/

Publication series

NameProceedings of the AAAI/ACM Conference on AI, Ethics, and Society
PublisherAssociation for Computing Machinery (ACM)
ISSN (Electronic)2168-4081

Conference

ConferenceSixth AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society
Abbreviated titleAIES 2023
Country/TerritoryCanada
CityMontréal
Period8/08/2310/08/23
Internet address

Keywords / Materials (for Non-textual outputs)

  • generative AI
  • generative models
  • text-to-image models
  • responsible AI
  • AI ethics
  • AI safety
  • AI governance
  • AI risks

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