Astronomers
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Observe, research, and interpret astronomical phenomena to increase basic knowledge or apply such information to practical problems.
The occupation "Astronomers" has an automation risk of 46.1%, which is slightly below the base risk of 47.1%. This means astronomers face a moderate likelihood of automation affecting aspects of their work. The relatively balanced risk reflects that, although computational and procedural tasks are increasingly handled by artificial intelligence and automation, significant elements of astronomy still fundamentally rely on unique human skills and insight. Advances in machine learning enable faster data analysis and improved automated control over equipment and systems, but not all responsibilities can be easily replaced by machines. Among the most automatable tasks for astronomers are those that involve predictable or data-driven operations. For instance, directing the operations of a planetarium can often be managed by pre-programmed sequences or automated systems. Analyzing research data to determine its significance, especially using computers, is also highly susceptible to automation as AI algorithms become better at processing large datasets and identifying patterns. Presenting research findings—whether at scientific conferences or in written papers—can be partially automated through automated report generation and data visualization tools, though nuance and interpretation still require human judgment. However, several critical tasks continue to resist automation, largely due to their need for advanced cognitive and interpersonal skills. Conducting question-and-answer presentations with public audiences demands adaptive communication and personal engagement, which current AI lacks. Calculating orbits and determining properties of celestial bodies requires not just computation but also innovative analytical thinking to interpret complex, ambiguous data. Additionally, serving on professional panels and committees involves decision-making, negotiation, and domain expertise that depend on originality—a bottleneck skill scored at 3.8%-4.1%. These tasks highlight why human astronomers remain vital, even as automation becomes more sophisticated.