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Healthcare

Oncologist

Based on 36 assessments

25% Moderate risk

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

Raw potential
46%
Realistic risk
25%
Research benchmark ?
32%

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

Distribution across 36 profiles. Middle half of Oncologists score between 22% and 29%.

0% 50% 100%
p10 · 18%
33% · p90
On-screen work 23%

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

In-person + screen 44%

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 34%

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

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

Task Time Type Exposure
Developing and updating personalized treatment plans (e.g., chemotherapy, radiation, immunotherapy, surgery) based on patient history, cancer type, and stage
deep expertise social element
32% AD 16%
Conducting patient consultations to explain diagnoses, discuss treatment options, address concerns, and provide emotional support
deep expertise
29% AA 0%
Collaborating with multidisciplinary teams (e.g., surgeons, radiologists, pathologists, nurses) to coordinate care and adjust treatment strategies
deep expertise
15% AA 0%
Monitoring patients during treatment for side effects, complications, or changes in condition, and adjusting care as needed
13% AD 38%
Staying updated on the latest cancer research, clinical trials, and emerging therapies to incorporate evidence-based practices into patient care
6% DD 54%
Documenting patient records, treatment plans, and progress notes in electronic health records (EHR) systems
1% AD 52%
Reviewing and interpreting medical imaging (e.g., CT scans, MRIs, PET scans) and lab results to diagnose cancer or assess disease progression
1% DD 47%

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