Ning Xu Claims Victory at Small World in Motion 2026
Ning Xu, an engineer from the National University of Singapore, was announced as the winner of the Small World in Motion 2026 competition in mid-September 2026. His winning entry features a video capturing the movement of cilia in lung tissue samples from a child diagnosed with primary ciliary dyskinesia. Despite the achievement, Xu's submission is currently under investigation due to suspicions that generative artificial intelligence (AI) was used in the video processing.
Investigation into Xu’s Submission
Nikon, the organizing company, is conducting a thorough review of Xu’s work following allegations related to the use of generative AI. The scrutiny intensified after Ian Donovan, a graduate student at UT Southwestern Medical Center, detected a SynthID watermark on the video. SynthID is a technology developed by Google's DeepMind research lab designed to identify content created or modified by AI. Xu acknowledged employing AI tools during the video processing stage but emphasized that the original footage depicting cilia movement is authentic.
According to Nikon, the post-processing involved an unsupervised neural network technique to highlight and differentiate features in grayscale. Xu has also provided comprehensive technical documentation detailing the microscopy equipment, imaging methods, and processing techniques used to produce the original video.
“Xu has cooperated fully and submitted detailed technical records outlining the microscopy apparatus, image acquisition methods, and processing procedures employed to generate the source video.”
Nikon
Despite this, concerns have been raised by experts in the field. Edward Phelps, a bioengineering researcher at the University of Florida, pointed out that certain structures in the video do not align with biological realities. Melanie White, a biologist at the University of Queensland, emphasized that scientific images represent data and must be grounded in actual measurements. These critiques add a layer of complexity to the review process and raise questions about compliance with competition rules, which prohibit the use of generative AI for image creation.
This case highlights the critical importance of ethics and authenticity in scientific research, especially as AI technologies rapidly evolve. The debate over the potential AI involvement in scientific imagery not only challenges the legitimacy of this competition result but also impacts the broader trust in scientific data, carrying significant implications for medical and biological research fields. Furthermore, this situation may prompt revisions of standards and regulations governing the application of AI in scientific work.