It seems almost pointless to argue about the impact artificial intelligence is going to have on content creators, for the simple reason that AI is going to have a wide range of effects, including displacing some human jobs; augmenting human labor and reshaping content creator functions, as well as creating wholly-new functions and jobs.
Most likely, “all of the above” are likely outcomes, as has been the case with other new technologies applied to content creation.
Technology | Displaced Roles | Augmented Roles | Reshaped Roles | Created New Roles |
Printing Press (15th century) | Hand-copying scribes and illuminators, who manually reproduced manuscripts | Authors and scholars, by enabling mass distribution of their works to wider audiences | Writers shifted focus from rare, elite manuscripts to broader, accessible literature; encouraged standardization of texts | Printers, publishers, bookbinders, and editors to manage production and distribution |
Photography (19th century) | Portrait artists and miniaturists, whose realistic depictions were largely supplanted by photos | Painters and illustrators, who used photographs as references for more accurate or complex compositions | Artists moved toward impressionism, abstraction, and conceptual art, emphasizing emotion over literal replication | Photographers, darkroom technicians, photo retouchers, and later film directors |
Phonograph and Audio Recording (late 19th-20th century) | Some live performers in theaters or salons, as recordings reduced demand for repeated live shows | Musicians and composers, by allowing preservation and global sharing of performances | Performers adapted to studio techniques, focusing on perfect takes rather than live endurance | Sound engineers, music producers, record label executives, and radio DJs |
Typewriter (late 19th century) | Professional hand-writers or copyists for official documents | Journalists and authors, with faster drafting and easier revisions | Writing became more iterative and professionalized, with emphasis on typing speed and clarity | Typists, secretaries, and stenographers specialized in machine operation |
Word Processors and Computers (late 20th century) | Dedicated typists and manual typesetters in publishing | Writers and editors, through tools for easy editing, spell-checking, and formatting | Content creation became digital and collaborative, with focus on multimedia integration | Desktop publishers, web designers, software documentation specialists, and digital archivists |
Internet and Digital Platforms (late 20th-21st century) | Traditional print journalists and classified ad writers, as online formats reduced print demand | Bloggers and independent creators, by providing free or low-cost global publishing tools | Creators emphasized interactive, real-time content like social media posts over static articles | Social media influencers, SEO content strategists, podcasters, and user-generated content moderators |
And all that will happen irrespective of today’s efforts to “protect” human jobs.
Netflix, for example, has guidelines for use of generative AI based on five main points:
The guidelines also caution against creating content that could be mistaken for real events, people, or statements.
Of course, as a practical matter, all that will have to be monitored and verified. Perhaps the areas of greatest concern are final character designs and key visuals; talent replication and use of unowned training data.
Proposed Use Case | Action | Rationale |
Using GenAI for ideation only (moodboards, reference images) | ✅ | Low risk, non-final, likely not needing escalation if guiding principles are followed. |
Using GenAI to generate background elements (e.g., signage, posters) that appear on camera | 
| Use judgment: Incidental elements may be low risk, but if story-relevant, please escalate. |
Using GenAI to create final character designs or key visuals | 
| Requires escalation as it could impact legal rights, audience perception, or union roles. |
Using GenAI for talent replication (re-ageing, or synthetic voices) | 
| Requires escalation for consent and legal review. |
Using unowned training data (e.g., celebrity faces, copyrighted art) | 
| Needs escalation due to copyright and other rights risk. |
Using Netflix's proprietary material |  | Needs escalation for review if outside secure enterprise tools. |
Some observers might liken the use of generative AI to the use of computer-generated graphics. It might be argued that CGI did not broadly automate creative work, as AI might threaten to do, in some cases.
While CGI technology does automate certain repetitive or technical tasks, the work typically requires direct human input, creative intent, and iterative collaboration, some would argue. And while CGI shifted some jobs from traditional effects (such as practical props) to digital, it did not broadly automate creative work.
AI, on the other hand, arguably can drastically reduce the need for human artists, writers, and designers, especially for routine or template-based tasks. A reasonable view held by creatives is that generative AI creates extensive automation threats to creative jobs, challenging the role, compensation, and rights of human creators in ways CGI never did.
Issue | CGI | Generative AI |
Labor Replacement | Redistributes labor, limited direct job loss | Automates substantial creative tasks, risks widespread job loss |
Human Creativity | Essential for most tasks | Can fully automate or diminish creative input |
New Job Creation | Created new specialist roles | Some new roles, but net job losses expected |
Worker Rights/Ethics | Tied to work conditions, overtime | Issues of data exploitation, loss of control, IP and consent |
Value Perception | Value linked to expertise and collaboration | Value eroded by commoditization, especially for freelancers |
Legal Uncertainty | Relatively mature standards | Significant legal and ethical ambiguity |
Content workers may not like it, but AI is going to reshape human roles and human jobs. New technology always has done so.
