Computer and Information Research Scientists

Conduct research into fundamental computer and information science as theorists, designers, or inventors. Develop solutions to problems in the field of computer hardware and software.

The occupation "Computer and Information Research Scientists" has an automation risk of 45.7%, which is just under the base risk of 46.7%. This moderate risk level reflects the balance between the highly technical and innovative elements of the job and the presence of some structured tasks that are more susceptible to automation. The core responsibilities often require specialized knowledge and creative problem-solving, but parts of the role still align with activities that can be automated by advanced algorithms and artificial intelligence. The proximity of the risk percentage to the base value indicates that, while certain routine or well-defined functions in the occupation could be automated, others remain complex and dependent on human judgment. The most automatable tasks for Computer and Information Research Scientists include "Analyze problems to develop solutions involving computer hardware and software," "Apply theoretical expertise and innovation to create or apply new technology, such as adapting principles for applying computers to new uses," and "Assign or schedule tasks to meet work priorities and goals." These tasks involve systematic analysis and scheduling, operations that modern AI and software excel at, especially when clear parameters and objectives are defined. Automation systems can efficiently process large datasets, optimize scheduling, and even assist in developing or applying new technologies, particularly when precedents and established theories are available. As such, a significant portion of these responsibilities is vulnerable to being streamlined through AI-driven solutions or robust enterprise software. Conversely, the most resistant tasks remain distinctly human-centric. "Approve, prepare, monitor, and adjust operational budgets," "Participate in staffing decisions and direct training of subordinates," and "Direct daily operations of departments, coordinating project activities with other departments" are less automatable. These responsibilities often require nuanced understanding, negotiation, interpersonal skills, and a level of contextual judgment that current automation technologies cannot easily replicate. Furthermore, bottleneck skills like originality—measured by factors of 3.6% and 4.4%—act as natural barriers to full automation. These skills emphasize the need for creative thinking and innovation, which are still difficult for machines to emulate at a meaningful level, thereby preserving a significant human role in this occupation.