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Media

Subtitler

Based on 38 assessments

56% High risk

Average realistic automation risk across all Subtitler profiles in the dataset.

Raw potential
74%
Realistic risk
56%
Research benchmark ?
84%

Raw potential = I/O automation ceiling. Realistic risk = adjusted for informal knowledge and social context. Research benchmark: Eloundou et al. (2023)

Distribution across 38 profiles. Middle half of Subtitlers score between 52% and 60%.

0% 50% 100%
p10 · 47%
62% · p90
On-screen work 67%

Done entirely on a computer. High AI exposure — these tasks are already in the automation zone.

In-person + screen 26%

Physical sensing, digital output — e.g. interviewing someone then writing a report. Partially protected.

Computer + action 0%

Computer input, real-world output — needs someone to act on it, not just software.

Fully in-person 7%

No computer required. Furthest from automation — the strongest human advantage.

3 synthetic profiles for a Subtitler, ordered by automation exposure. Tab between them to see how task mix drives the score difference.

Task Time Type Exposure
Edit and proofread subtitles for clarity, conciseness, and readability, ensuring they fit within screen space limits (e.g., 2 lines of ~37 characters each)
30% DD 62%
Synchronize subtitles with the audio track, adjusting timing so text appears and disappears in sync with speech
22% DD 86%
Transcribe spoken dialogue from video or audio recordings into written text, ensuring accuracy in timing, spelling, and grammar
21% AD 41%
Translate subtitles from one language to another while preserving meaning, tone, and cultural context (for multilingual subtitling)
deep expertise social element
14% DD 24%
Communicate with clients or team members to clarify unclear dialogue, confirm style preferences, or resolve technical issues
deep expertise social element
9% AA 1%
Format subtitles according to client or platform specifications (e.g., font, color, position, or file format like SRT, VTT, or STL)
0% DD 70%
Review and correct automated transcription or translation outputs (e.g., from AI tools) to fix errors or improve natural flow
0% DD 61%

Work as a Subtitler? Map your specific role.

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