In a nutshell
- AI’s influence in video production is challenging how we use technology in our creative processes
- Video Producers can take specific steps to ensure their AI workflow is ethically grounded
- Cautious integration of generative AI tools in our workflows is crucial for responsible use
AI’s influence across work and society is undeniable. It has transformed the way we discover information and allowed us to complete what used to be advanced video production tasks with minimal effort. AI tools in video production are emerging fast and transforming the way we create videos and tackle technical obstacles. The harder question is whether using them is ethical. For most of what video producers actually do with AI, the answer is yes, and it has been for a long time.
Assistive AI has been here for years
AI’s impact is redefining authorship, transforming creative workflows and altering economic dynamics in the video industry. In fact, assistive AI has already been integrated into editing tools for many years, but it has gone by other names such as machine learning or neural engine.
Assistive AI is used for auto color balance, background noise removal, enhanced vocal quality, text-based editing, audio tagging, upscaling footage, magic masking, background removal, transcription-based editing and green screening. These assistive AI tools aid editors in doing their job while saving a lot of time and can prevent re-shoots. No one ever called them unethical. They do honest work in the background, and producers have relied on them for years without a second thought. That track record matters. The ethical use of AI in video isn’t a hypothetical we’re waiting on. It’s already here, and it has been for a decade.
With generative AI video tools, anyone can efficiently create high-quality video footage without picking up a camera. Generative AI has simplified scriptwriting and storyboarding, and allowed video professionals to easily create fast, affordable content such as social clips, product demos and how-to videos at the push of a button. For a solo creator or a small shop that could never afford a full crew, that access is a real good. This cultural shift is also challenging notions of how we view technology in our creative process.
Why generative AI remains controversial
While generative AI video tools can allow video professionals to focus more on creative aspects of their projects, these tools have been controversial for several reasons. Many companies that trained AI models to create generative AI video did so by using copyrighted works without the creators’ permission.
Some generative AI tools have been criticized for being trained with bias, which can reinforce stereotypes or exclude certain accents, appearances or perspectives. AI tools can lead to controversy when they are used to generate synthetic likeness (i.e. deepfakes) and spread misinformation. Convincing fakes can depict someone saying or doing things they never did, thus eroding trust between individuals and varying groups of people.
But here’s the distinction that often gets lost. These are objections to how some tools were built and how some people use them. They are not objections to AI itself. A producer who chooses a tool trained on licensed or proprietary footage sidesteps the consent problem. A producer who discloses an altered likeness isn’t deceiving anyone. The unethical version of AI is a choice, not a built-in feature, and you can choose not to use it.
Building an ethical AI workflow
How do video producers ensure AI in their workflow is ethical? While there will likely be ongoing controversy over the techniques tech companies use to create AI products, there are steps you can take to ensure your workflow is grounded in ethical considerations. Responsible use of AI preserves authenticity and instills trust with your audience. Ethical AI complements creativity rather than substituting for skilled video professionals.
Disclose meaningful changes to likeness
It’s essential that generative AI tools are disclosed in the workflow when there is a meaningful change in someone’s likeness. Before distributing a video, you must be able to confirm consent and explain how it was made. Viewers can often tell when something is off, though it is becoming harder to detect use of generative AI in video production. When AI changes what someone has said, how they said it or where they were located, then disclosure is critical to preserve audience trust. Explicit permission must be granted with written proof in case proof of authorship is necessary.
Verify your source footage
It’s also important to verify rights and investigate the source of the footage before repurposing a video. If the original creator cannot provide clarity regarding consent, do not move forward with the use of the video. As video producers, we know it would not be desirable if anyone stole our work, so taking the extra step to verify source material will keep your approval process ethically grounded.
Keep a human in the loop
A best practice is to always have a human review AI-generated video content before publishing or using it commercially. A human eye can catch subtleties that the AI might miss. Incorporate an approval step in your workflow for AI content, just as you would for any edited media. Have your content audited for bias by having someone outside your team review your videos. The person you choose for the review should not share the same background or ethnicity as people on your team.
AI and the future of video jobs
Generative AI video tools have already vastly increased productivity and removed much of the drudgery to enable video professionals to work on creative decision making. Fear of job loss has been a big concern across the video industry due to AI proliferation. However, AI can never replace the heart, soul and creativity of a human video producer. The taste to know which take lands, the read on a client’s unspoken note, the instinct for when a scene is working: that judgment is still ours.
It has become more valuable to hire talent who can bridge the gap between pure creativity and technical AI skills. Video production companies can create programs and initiatives to upskill their employees or freelancers by training them in AI skillsets.
Content credentials and the C2PA
The industry isn’t leaving any of this to chance. The infrastructure for trustworthy AI is already being built. A meaningful movement to track generative AI footage is being led by the Content Authenticity Initiative (CAI) and C2PA (Coalition for Content Provenance and Authenticity). Backed by a massive coalition that includes Adobe, Microsoft and the New York Times, the C2PA is developing universal adoption of content credentials. The open-source technology, similar to nutrition labels, embeds cryptography directly into video metadata to track a file’s journey from the camera sensor through the editing suite to the final export. It shows the viewer exactly what is real, what was edited and what was AI-assisted.
When an asset is dropped into an editing tool (like Adobe Premiere or Final Cut Pro) or passed through an AI generator, the software doesn’t overwrite the old history. Instead, it securely creates a chain of custody with a new trackable asset on top of the old one. This additive model builds an unbroken digital paper trail from the camera lens to the final viewer.
Google’s SynthID and Gemini Omni
Google’s recent Gemini Omni model, from Google DeepMind, takes a complementary approach with a safeguard called SynthID. This AI detection technology embeds an imperceptible digital watermark directly into the pixels of the video and the frequencies of the audio. Even if the video is compressed, cropped or heavily edited later, the watermark remains detectable. Omni clips also carry C2PA content credentials, so the two systems work toward the same goal. SynthID itself is a proprietary tool, and the broader video industry is still pushing for open-source AI detection that anyone can use in alignment with the C2PA standard. The direction of travel is clear. The ecosystem is moving toward transparency, not away from it.
Adapting to change
Recently, the term ‘clean AI’ has emerged, focusing on driving innovation through responsible use across the economy and environment. Video producers can learn about the developments towards Clean AI by following this initiative as well as the C2PA initiative. We can be active participants in discussing ethical AI in our day-to-day work life, in our communities and with our peers in the video industry.
Additionally, it’s true that generative AI runs on data centers that draw real power and water, and video is the heaviest load of the bunch. But that cost is shrinking, and it rarely gets weighed against the alternative. The companies running these data centers are racing to feed them cleaner power, signing major nuclear and renewable deals over the past year to do it. The grid behind AI appears to be getting greener even as it grows. Set that against traditional production, which was never free of footprint either. Crews fly to locations, gear ships across the country and a single reshoot doubles the load.
The long-term implications of AI advancements aren’t fully clear. That isn’t a reason to sit out. Video professionals can define the future of AI in this industry rather than wait to be shaped by it. These tools are ethical when we use them ethically, and the good news is we already know how.
