How much of this occupation’s work can be materially affected by current AI systems.
How likely exposure is to translate into reduced human demand.
Includes provisional estimates for AI adoption pressure and labour-market resilience. How this is measured
Confidence reflects task coverage, mapping and capability-evidence quality, and how much of the score rests on provisional inputs.
What is driving the score?
Occupation scores are built from the task mix—not a single prediction about a job title.
Where AI can do more
Routine, digitized, and highly repeatable tasks face the greatest pressure.
- Compile terminology and information to be used in translations, including technical terms such as those for legal or medical material.75
- Follow ethical codes that protect the confidentiality of information.74
- Check translations of technical terms and terminology to ensure that they are accurate and remain consistent throughout translation revisions.74
- Compile information on content and context of information to be translated and on intended audience.74
Where people still matter
These tasks score lowest on automation feasibility—physical presence, judgement, accountability and real-world variability all resist end-to-end automation.
- Translate messages simultaneously or consecutively into specified languages, orally or by using hand signs, maintaining message content, context, and style as much as possible.01
- Educate students, parents, staff, and teachers about the roles and functions of educational interpreters.02
- Follow ethical codes that protect the confidentiality of information.03
- Listen to speakers' statements to determine meanings and to prepare translations, using electronic listening systems as necessary.04
- Identify and resolve conflicts related to the meanings of words, concepts, practices, or behaviors.05
Related occupations
Occupations O*NET links to this one. Relatedness reflects shared work, not a claim that these roles are safer.
Speech-Language Pathologists
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Compare these careers →Adoption and labour-market outlook
Structural factors are kept separate from raw capability so you can see what actually resists automation. Adoption pressure and labour-market resilience are still provisional models—25% of this occupation’s replacement-risk weight rests on them.
O*NET 30.3 occupational data interpreted through the JobsVsAI capability, automation and structural-constraint models.
