Home AI News Safe and Responsible AI: Enhancing DALL·E 3’s Image Generation and Provenance Detection

Safe and Responsible AI: Enhancing DALL·E 3’s Image Generation and Provenance Detection

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Safe and Responsible AI: Enhancing DALL·E 3’s Image Generation and Provenance Detection

Enhancing Safety Measures in DALL·E 3 with User Feedback

OpenAI has implemented a multi-tiered safety system to ensure that DALL·E 3, our impressive AI model, does not generate harmful or offensive content. We prioritize the well-being of our users by subjecting their prompts and resulting imagery to safety checks. In addition, we collaborate with our early users and expert red-teamers to address any gaps in our safety systems.

One of the crucial aspects of this collaboration is identifying potential issues related to graphic content generation, including sexual imagery. By stress testing the model, we ensure that DALL·E 3 can produce convincingly misleading images, thus fortifying its abilities.

Preparing DALL·E 3 for Deployment

In preparation for DALL·E 3’s widespread deployment, we take various measures. Firstly, we limit the model’s capacity to generate content resembling the styles of living artists or images of public figures. Additionally, we strive to improve the representation of diverse demographics in the generated images. To gain deeper insights into our preparation efforts, check out the DALL·E 3 system card.

User Feedback and Continuous Improvement

Your feedback is essential to our progress. If you come across any outputs from ChatGPT that are unsafe or do not accurately reflect your prompt, please use the flag icon to share your concerns with our research team. We value the input of our diverse user community and consider it vital in responsibly developing and deploying AI.

Achieving Image Provenance

We are actively researching and evaluating an initial version of an internal tool known as a provenance classifier. This tool helps us discern whether an image is generated by DALL·E 3. Early internal tests indicate that the classifier is more than 99% accurate in identifying unmodified DALL·E-generated images and remains over 95% accurate even with common modifications. However, it cannot provide conclusive results. This classifier paves the way for a range of techniques that enable users to determine if audio or visual content is AI-generated. Addressing this challenge requires collaboration across the AI value chain, including with content distribution platforms. Through further refinements, we aim to enhance this tool and its usability.

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