Hollywood Group Launches Tool to Measure AI Impact on Creative Jobs

For months, discussions about artificial intelligence in Hollywood have been dominated by broad fears and unverified claims. A new public project launched this week seeks to change that dynamic by offering a structured way to assess which jobs are most vulnerable to automation. The Creators Coalition on AI, a group formed nine months ago by industry figures including Daniel Kwan and Ted Tremper, has released a web portal designed to bring clarity to a rapidly shifting landscape.

The initiative, known as the Standards & Definitions Project, includes a glossary of 180 terms and a visual tool that rates the likelihood of AI replacing human workers in various roles. According to GN technics/ai (en-US), the goal is to move the conversation from nebulous anxiety to grounded discussion, allowing creators and unions to negotiate with specific data rather than general uncertainty.

Quantifying Risk for Creative Roles

The core of the new tool is an impact visualizer that scores 150 different job categories across eleven creative areas, including directing, writing, and sound design. Each role is assigned a score from zero to five, where zero indicates no overlap with AI capabilities and five suggests the entire job could potentially be performed by a machine. This granular approach allows users to see exactly where human input is still critical and where automation is becoming a realistic threat.

However, the tool currently lists many of these roles as requiring further information, reflecting the early stage of the data collection process. While over 250 industry professionals have been polled so far, the founders are aiming for thousands of responses to make the assessments more robust. This ongoing feedback loop is designed to keep the data relevant as AI capabilities evolve quickly.

Creating a Shared Industry Language

Beyond the risk scores, the project introduces a standardized glossary to define complex terms like human-authored content and AI digital performance. These definitions were developed through conventions with delegates from various guilds and are intended to provide a common vocabulary for contract negotiations. For example, the group defines human-authored work as creative output where no generative AI contributed expressive content, even if technical tools were used.

Limitations of the Current Model

Despite its utility, the assessment has clear trade-offs. The founders acknowledge that the model does not account for every eventual scenario. For instance, a role might score low for direct AI replacement but still face significant disruption if the working environment changes, such as the shift to virtual sets. This gap highlights the difficulty of predicting long-term industry shifts based on current technology alone.

The initiative also operates independently of major labor unions, which may limit its immediate influence on broader contract disputes. However, supporters argue that having a neutral, data-driven resource can help individual talent and smaller productions understand their risks. The ultimate hope is that this shared framework will foster more precise communication about the future of work in entertainment.