The idea of robots taking over the planet has been around for some time, but the recent AI boom has painted it a much different color. Artificial intelligence has made life easier for all of us, but it has also left many of us wondering if we’re going to lose our jobs to the machines’ superior efficiency.
Our own team at Picotion Studio consists of both creative and technical individuals, so we’re well-placed to take a look at the issue. Here’s our take on the status quo and future of animation jobs!
The Rise of AI in Animation
The animation industry has witnessed a significant surge in AI use, which has already revolutionized various aspects of the creative process from pre-production to release.
In this section, we’ll take a quick look at how AI is used in the animation pipeline. So, feel free to familiarize yourself with the pipeline using our guides to pre-production, production, and post-production. Then, we’ll take a closer look at CGI and motion capture as shining examples of AI-driven changes.
AI & the Animation Pipeline
There are three main stages in the pipeline:
1.Pre-production: Thanks to popular AI assistants, you can easily imagine how AI algorithms assist in idea generation, concept organization, script analysis, predicting audience preferences, and optimizing storylines. AI also contributes to character design by automating repetitive tasks and suggesting unique characteristics based on popular trends.
2.Production: AI-driven tools streamline the labor-intensive tasks of keyframing and in-betweening, significantly enhancing efficiency and reducing costs. If you’re using motion capture, you can also rely on machine learning algorithms to analyze vast mocap datasets to refine and generate more realistic character movements. This accelerates the production timeline and also frees up human capacity, which can be put to better use in creative endeavors.
3.Post-production: AI can also be applied in rendering and special effects, optimizing resource allocation and delivering visually stunning results. Many post-production activities, such as voice synthesis and lip-syncing, benefit from AI’s ability to generate natural-sounding dialogues, saving time and resources. Artificial Intelligence is also widely used in distribution and marketing.
Ultimately, the integration of AI in the animation industry has not only accelerated production processes but also opened new creative possibilities, pushing the boundaries of what can be achieved in animated storytelling. As technology continues to advance, the synergy between human creativity and AI innovation promises a dynamic future for animated content.
CGI Advancements: An AI Success Story
Computer-Generated Imagery (CGI) refers to the application of computer graphics to create or improve visual elements in films, television, and various media. Traditionally, CGI relied heavily on manual labor for modeling, texturing, animation, and rendering. Now, thanks to massive AI models, CGI has become much easier and even more accessible.
First, generative algorithms assist in the creation of lifelike images and textures, simplifying the process of designing and rendering intricate details. You may have even used some of these algorithms to generate images from text. Of course, everything gets much more technical in a creative studio!
Machine learning algorithms also enhance animation workflows by predicting movement patterns and automating keyframing, resulting in smoother and more natural animations. Deep learning models have also been instrumental in creating more realistic facial expressions and character movements, adding depth and authenticity to CGI characters.
AI-driven tools facilitate quicker and more efficient rendering processes, too. Optimizing every aspect of rendering hardware is virtually impossible for a person, but not for an AI. This not only accelerates production timelines but also allows for more iterations and creative experimentation.
Overall, it’s safe to say that the synergy of AI and CGI in the animation industry has elevated the quality of visual storytelling. Animators can focus on creative aspects while leveraging AI for labor-intensive and technical tasks, creating more stunning and immersive animated content.
Motion Capture: Where AI is Essential
Motion capture or mocap is a technology used to record and analyze human or object movements for various applications, such as animation, sports analysis, and virtual reality. Traditional mocap systems involve placing sensors on actors to capture their motions. These systems are still in use but are slowly becoming obsolete, thanks in part to artificial intelligence.
First, AI eliminates the need for physical markers on the subject and makes markerless motion capture much more efficient. This allows for more natural and unrestricted movement, enhancing the overall realism of captured animations. Plus, real-time processing capabilities powered by AI enable immediate feedback during performances, which is a valuable tool for remote motion capture, live events, and interactive applications.
AI has proven to be even more indispensable when it comes to facial motion capture. Placing sensors on an actor’s face used to be the only way to capture their facial actions, but that was never too precise or too comfortable. Nowadays, many companies simply record actors’ faces and rely on sophisticated AI models to map those movements on 3D models.
In summary, the synergy between motion capture and artificial intelligence has significantly elevated the precision, efficiency, and versatility of capturing and interpreting movements. This synergy has now opened new possibilities in fields ranging from entertainment to scientific research. Read more about motion capture’s applications here.
3 Popular Films that Used AI
As the use of AI becomes more widespread, it gets harder to pick and pinpoint AI use in animated productions. Still, here are three examples where a major AI system was used to enhance a production’s look and feel:
1.The Hobbit: The Battle of the Five Armies (2014): The film’s production team used AI to create the stunning visuals of the landscapes. They had a software developed called Massive which allowed them to create realistic crowds and armies for the film.
2.The Good Dinosaur (2015): The film’s production team used AI to create the stunning visuals of the landscapes. They used a software called Voxel Studio which allowed them to create realistic terrains and landscapes for the film.
3.The Mandalorian (2019): The series’ production team used a software called StageCraft which allowed them to create a virtual environment that could be manipulated in real-time. This helped the team to create realistic backgrounds and landscapes for the series.
Job Stealer: AI Taking Over
Now that we have established that AI continues to advance in animation, let’s address the original issue of job displacement. The anxiety is already sinking in. If AI isn’t putting us out of work already, it certainly is making us doubt our skillsets.
So, let’s take a closer look to understand what the issue is and which jobs are at risk.
The Creative Problem with AI
“There is not enough job stability in the creative industry anyway,” says Jason DeMarco to IGN, who is the senior vice president of action and anime at Warner Bros. “Now it’s going to be even harder, because to the degree you can make any money off of art, you’ll be challenged by machines that are copying what you do.”
DeMarco is referring to one side of the issue that might lead to job displacement in an indirect way: AI is essentially trained on original human art that doesn’t get enough credit for AI’s use. (We’d call it plagiarism if a person did it!) The other side is the fact that machines deliver quicker results with fewer resources, so they might lead to direct layoffs.
8 Traditional Animation Roles at Risk Because of AI
While some roles like directors, animators, and voice actors can’t currently be replaced by AI, some others are already in danger. Here are 8 of them:
- In-betweeners: AI can automate the process of generating frames between key frames, reducing the need for manual in-between animation.
- Clean-Up Artists: AI algorithms can refine and clean up animation or mocap frames, minimizing the manual effort required in this traditionally labor-intensive task.
- Rotoscoping Specialists: AI-driven tools can streamline the rotoscoping process by automatically tracking and tracing live-action footage, diminishing the demand for specialized rotoscoping artists.
- Colorists: AI systems can efficiently handle color grading and correction, potentially replacing some aspects of the traditional colorist’s role.
- Storyboard Artists: AI-powered algorithms can assist in generating preliminary storyboards based on scripts, impacting the demand for manual storyboard creation.
- Texture artists: Similar to generating images and sketches, AI can also create textures for 3D models.
- Lighting artists: AI models are as competent in lighting as they are in coloring, so they can also be used to light every scene accordingly.
- Compositors: Artificial intelligence can also efficiency combine different elements of objects in an animation.
Creative Collaborator: AI Joining the Team
Despite the very real ethical and technical considerations above, it’s possible to see AI in a different light. Change is always scary, but it is here. We could try to stop or deny it altogether (which has never worked) or we can acknowledge the benefits it brings and see how we can adapt.
This section is dedicated to what those benefits are and how we can run with them. After that, we’ll go to striking a balance between efficiency and human employment.
(Note: This article doesn’t have enough space to fully address potential plagiarism as mentioned in the above section. So, we’re skipping that side of the issue for now to focus on all the changes AI brings.)
AI As a Friend, Not a Threat
Let’s face it: artificial intelligence is a powerful tool. There’s a long way ahead before we can make self-aware, self-adjusting AI models. Right now, it’s human beings who decide how and when to use AI. Here are four reasons we could rely on AI to do our jobs for us, not in our absence:
- Automation: Before computers were invented, there were human beings who would spend hours solving complex mathematical problems, even though they might have been overly long and demanding. AI automates time-consuming tasks such as rendering, lip syncing, etc. much like computers. With these routine processes delegated to AI, creatives can redirect their focus towards more intricate and imaginative aspects of storytelling and character development.
- Superior Processing: Machine learning algorithms can sift through massive datasets to, for instance, identify patterns, preferences, and trends in audience behavior. This information becomes a valuable resource for creatives, allowing them to tailor their creations to audience expectations and preferences. The alternative would be to spend ten times more human hours for possibly less precise results.
- Brainstorming: Creative algorithms can generate ideas, suggest story arcs, or propose design elements based on historical data and trends. AIs don’t have stories, cultures, and emotions of their own. They can’t do the A-Z of a project, but they can be part of a dynamic synergy between us and them, where the strengths of both parties are leveraged to create compelling and innovative content.
- Democratization: As AI tools become more accessible, artists with varying skill levels can use these technologies to bring their visions to life. This accessibility fosters a diverse and inclusive animation landscape, where creativity is as boundless as it is in our own minds.
In essence, AI is very much a catalyst for creativity in the animation industry. We could embrace it as a creative collaborator, while choosing where we would like human control and exactly how much.
5 Examples of AI-driven Tools for Artists
There are many AI projects for artists out there, aside from widespread AI models like ChatGPT or DALL-E. Taking a look at these may help realize just how useful AI can be to artists if it’s treated as a collaborator. Here are 5 we like:
- Runway ML: An easy-to-use, code-free tool that allows artists to experiment with machine learning models in quite a number of creative ways, like generating videos and reimagining images in different styles.
- Artbreeder: A tool that allows you to blend two images to create novel new ones.
- Magenta: An open-source research project exploring the role of machine learning as a tool in the creative process, aiming “to demonstrate that machine learning can be used to enable and enhance the creative potential of all people.”
- Processing: A flexible software sketchbook and language for learning how to code within the context of the visual arts. Processing does not use AI, but it’s a great tool to keep up with the AI-driven art world.
- ml5.js: A library that “aims to make machine learning approachable for a broad audience of artists, creative coders, and students” through the web.
We realize that you might not like zeros and ones as an artist, but the last two examples here require you to have or acquire coding skills. Let’s explore that in the next section.
The Solution: Holding Animation Jobs in an AI-Driven World
The bottom line is that we advise everyone, creative or otherwise, to learn how to code! Remember the at-risk jobs we explored before? We believe that people currently holding those positions don’t have to be laid off; they could just be operating the respective AI tools that do the bulk of their jobs for them.
What’s more, AI models aren’t perfect. The results they turn in will always need adjustments, whether to correct inaccuracies or to align with new project goals. When changes are needed, the same people who operate them would have the knowledge and skills to adjust the results as needed.
More specifically, here’s what we recommend to individuals and organizations alike:
- Embrace Adaptability: Adopt this as a core principle and soft skill as the animation industry navigates the dynamic landscape of technological advancements. Adaptability makes you quicker on your feet when changes come.
- Upskill & Invest in Training: Individuals could start by following the news on AI and art to get in that headspace while also learning to code. (The coding language Python is among your best options.) Creative studios should invest in training programs to equip their teams with the skills necessary to effectively collaborate with AI tools, especially the ones they are going to use internally.
- Experiment & Innovate: Studios should encourage experimentation with AI-driven tools, even on the company’s budget. It could be part of the upskilling process, and it will definitely pave the way for new possibilities in animation.
- Make Collaborative Workflows: Teams should decide on which AI tools they’re going to use, then implement them seamlessly into the existing workflows. Soon, the use of AI won’t be much of a choice. We might as well have a plan for it!
- Address Ethical Concerns: We could sit and lament what once was, or we could decide what our ethical standards are, how we define creative integrity, and how we believe our countries should regulate AI development.
Conclusion
The debate over job security and creative autonomy is new and is not expected to end anytime soon. As AI seamlessly infiltrates the animation pipeline, it accelerates processes, reduces costs, and opens new creative realms while also putting many traditional animation roles at risk.
AI is too useful to be rejected entirely. So, we advise individuals and studios to maintain a healthy amount of skepticism, but upskill relentlessly. That way, people who are already holding endangered jobs can operate new AIs in those positions and offer precious insight into the end results
We see a dynamic, innovative future ahead for animated storytelling as human creativity merges with AI processing power!
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