Figma, a popular design tool, recently faced criticism over its AI tool, Make Designs, which was pulled after it was discovered that it was generating designs similar to Apple’s weather app. This incident raised concerns about potential legal implications and led to the tool being disabled temporarily.

One of the main issues highlighted in this incident is the lack of proper training of the AI models powering the Make Designs tool. Figma’s CEO, Dylan Field, was quick to deny training the tool on Figma content or app designs, but it raised questions about the source of training data and the design systems used.

The statement released by Figma’s VP of product design, Noah Levin, mentioned that the company had carefully reviewed the underlying design systems during development and private beta testing. However, the oversight in vetting new components and example screens led to assets resembling real-world applications being included in the tool’s output.

Once the issue with the design systems was identified, Figma took immediate action by removing the problematic assets and disabling the feature. The company is now working on implementing an improved quality assurance process before reintroducing Make Designs to ensure that such incidents do not occur in the future.

Despite the incident, Figma has been transparent about the processes involved in training the AI models and the design systems powering the tool. However, the lack of information about the entities commissioned for creating the design systems raises concerns about accountability and external influences on the tool’s functionality.

This incident serves as a learning experience for Figma in terms of the importance of thorough review processes and proper training of AI models. The company’s commitment to enhancing its QA process and ensuring user data privacy is commendable, but there is still a need for more transparency in its operations.

Figma’s Make Designs incident highlights the challenges and potential risks associated with AI-powered design tools. While the company’s response to the issue is appreciated, there is room for improvement in terms of transparency, accountability, and user data protection. It serves as a valuable lesson for tech companies to prioritize ethical AI practices and comprehensive review processes to prevent similar incidents in the future.

Internet

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