The recent controversy surrounding Figma’s AI tool, Make Designs, has sparked concern among users and raised questions about the company’s training practices. The tool, which was designed to help users generate design ideas, came under fire after it was discovered that the output closely resembled Apple’s weather app. This not only raised legal concerns but also questioned the source of Figma’s design training.
Figma’s CEO, Dylan Field, was quick to deny allegations that the tool was trained on Figma’s content or app designs. However, a statement released by Figma’s VP of product design, Noah Levin, admitted to oversight in vetting the design systems that Make Designs was based on. The addition of new components and example screens in the week leading up to the launch of the tool led to similarities with real-world applications, leading to the removal and disabling of the feature.
Following the identification of the issue, Figma has committed to improving its QA process before reenabling Make Designs. However, no specific timeline has been provided for the tool’s return. CTO Kris Rasmussen mentioned in an earlier interview that the feature was expected to be reenabled soon, but the company is taking a cautious approach to avoid any further controversies.
Figma clarified that the AI models powering Make Designs, including OpenAI’s GPT-4o and Amazon’s Titan Image Generator G1, were not trained on Figma’s designs. Instead, the models were fed metadata from hand-crafted design systems for mobile and desktop domains, allowing the AI to create designs based on user prompts. The company did not disclose the source of these design systems, raising questions about transparency in the training process.
AI Tools and Training Policies
Despite the controversy surrounding Make Designs, Figma announced the launch of other AI tools at its Config event, including a text generation tool. The company has also outlined its AI training policies, giving users the option to opt in or out of allowing Figma to train on their data for future models. This move towards transparency is a positive step for Figma in establishing trust with its users.
The controversy surrounding Figma’s AI tool highlights the importance of diligence in the development and training of AI systems. The oversight in vetting design systems and components led to a problematic feature that had to be disabled. Moving forward, Figma must prioritize transparency and thorough testing to prevent similar issues in the future. By learning from this experience, Figma can regain user trust and continue to innovate in the field of design tools and technologies.
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