“AI may help a photographer refine what the camera captured, but the moment it begins inventing what the camera never saw, the image crosses from photography into creation. In a competition, that distinction is not technical. It is a matter of trust.” – MJ Martin
Photography Has Always Involved Interpretation
Photography has never been completely untouched by technology. Film photographers selected emulsions, filters, exposure times, developers, and darkroom techniques. Digital photographers adjust white balance, contrast, colour, noise, sharpening, and dynamic range. The ethical question surrounding artificial intelligence is therefore not whether technology may be used, but whether technology changes what was actually photographed.
That distinction is becoming critical for photography competitions. A camera traditionally acts like a witness. The photographer chooses where the witness stands, when it looks, and how it interprets the light, but something existed in front of the lens. Generative AI can cross that boundary by manufacturing information that the camera never recorded.
The Nikon Controversy
The issue became dramatically visible following Nikon’s 2026 Small World in Motion competition. As reported by TechRadar on October 1, 2026, scientists questioned aspects of the winning microscopic video showing airway cilia at 100x magnification. Critics cited unusual biological behaviour, including structures apparently appearing, disappearing, or moving in ways they considered inconsistent with normal ciliary behaviour. One researcher also claimed to have detected a SynthID indicator associated with synthetic content.
The entrant, Dr. Ning Xu, has denied using AI to generate the experimental movie, cilia, or their movement, while acknowledging AI-assisted processing to help distinguish and visualize features in reconstructed grayscale images. Nikon stated that it was re-reviewing the original submission information and additional technical documentation. Therefore, allegations should not be confused with a finding of misconduct.
The TechRadar article provides an excellent illustration of the problem facing modern competitions. Read the TechRadar article
Where Should the Ethical Line Be Drawn?
The clearest ethical standard is preservation of photographic evidence. AI that helps select a subject, remove sensor noise, adjust exposure, mask an area, or balance colour may function much like an extraordinarily sophisticated darkroom assistant. Generative AI that invents feathers on a bird, reconstructs missing stars, creates facial detail, manufactures background objects, or generates microscopic structures is fundamentally different. It is no longer simply interpreting captured photons. It is creating information.
World Press Photo makes this distinction explicitly. Its 2026 rules prohibit synthetic images and generative fill, while permitting limited AI-assisted adjustments when they neither introduce nor remove information captured by the camera. Nikon’s current Small World rules similarly state that AI-generated images and videos are prohibited and reserve the right to request originals for verification.
Canada Is Already Drawing the Boundary
Canada offers an important example. The Canadian Association for Photographic Art strengthened its competition requirements in 2026, prohibiting AI-generative creation and requiring photographic components to originate in the scene captured by the photographer. CAPA also introduced stronger metadata and authentication requirements.
This approach recognizes that the problem is not AI itself. The problem is authorship and disclosure. A photographer should be able to use computational tools without surrendering creative control, but the winning photograph must remain substantially a photograph.
Trust May Become Photography’s Most Valuable Asset
AI will make extraordinary imagery inexpensive. Authenticity may therefore become increasingly valuable. Competition organizers should require original RAW files where appropriate, complete metadata, processing disclosure, and clear declarations of generative AI use.
The deeper question is worth considering. If an AI-generated image is more beautiful than anything a photographer could capture, should it compete against photography, or should it have its own category? Should competitions permit AI denoising but prohibit generative sharpening? And, most importantly, when viewers admire an award-winning photograph, are they rewarding the photographer’s ability to observe reality, or the computer’s ability to redesign it?
Photography can accommodate AI. What it cannot afford to lose is the trust that something extraordinary really stood before the lens.
NOTE: A Pentapixel report from October 9, 2026 states:
The winner of the Nikon Small World in Motion competition has been disqualified after Nikon determined that the winning video broke its rules regarding artificial intelligence.
About the Author
Michael Martin is Vice President of Technology at Metercor Inc., a Canadian systems integrator specializing in smart metering, the Internet of Things, and Smart City technologies. With more than 40 years of experience in technology and systems design, Martin has worked extensively with broadband networks, optical fibre, wireless communications, digital technologies, and complex utility infrastructure. His career has combined engineering, technology strategy, business leadership, consulting, and continuous learning.
Martin spent 15 years as a senior executive consultant with IBM, working within the GBS Global Center of Competency for Energy and Utilities and the GTS Global Center of Excellence for Energy and Utilities. His work focused on the intersection of technology, telecommunications, energy, utilities, and digital transformation.
He is a founding partner and President of MICAN Communications. Earlier in his career, he served as President of Comlink Systems Limited and Ensat Broadcast Services Inc., both divisions of Cygnal Technologies Corporation, formerly traded on the Toronto Stock Exchange.
Martin has extensive experience in corporate governance, standards development, and post-secondary education. He served on the Board of Directors of TeraGo Inc. and Avante Logixx Inc. He has also participated in international technology standards development as a member of SCC ISO/IEC JTC 1/SC 41, which addresses the Internet of Things and related technologies, and contributed to the NIST SP 500-325 Fog Computing Conceptual Model developed by the United States National Institute of Standards and Technology.
His commitment to education has included service on the Board of Governors of the University of Ontario Institute of Technology, now Ontario Tech University, as well as advisory roles supporting Centennial College, Humber College, George Brown College, Durham College, and Ryerson Polytechnic University, now Toronto Metropolitan University. For 16 years, he also served on the Board of the Toronto Section of the Society of Motion Picture and Television Engineers.
Martin holds three master’s degrees: a Master of Business Administration, a Master of Arts in Communication, and a Master of Education. He also holds three undergraduate diplomas and seven major professional certifications spanning business, computer programming, internetworking, project management, media, photography, and communications technology.
A strong advocate of lifelong learning, Martin has completed more than 80 continuing-education and MOOC programs covering subjects such as economics, Python programming, the Internet of Things, cloud computing, artificial intelligence, cognitive systems, blockchain, Agile methodologies, Power BI, Big Data, Design Thinking, cybersecurity, and Indigenous Canada awareness. He continues to explore emerging technologies and their practical application to business, utilities, infrastructure, and society.
Beyond his professional career, Martin describes himself as a volunteer, photographer, lifelong learner, technologist, pilot, philosophizer, and romantic optimist. His enduring interest is not simply in how technology works, but in how knowledge, curiosity, and innovation can be applied to make complex systems, organizations, and communities work better.