Prepare summary statistics of information regarding human genomes.

“Prepare summary statistics of information regarding human genomes.” is a supplemental task performed by Bioinformatics Scientists. Among the occupation's 20 rated tasks, workers place it 1st by importance (#20 most important). About 41% of workers say it is relevant to their job.

This is a single occupation-specific task statement from O*NET. The figures below describe how central the task is to the job and what independent studies measure about AI and this kind of work — not a prediction that the task will be automated.

Work activities this task rolls up to

O*NET groups concrete tasks into broader work activities shared across many occupations.

• Research biological or ecological phenomena. in Getting Information

AI exposure

The OpenAI / Eloundou “GPTs are GPTs” study rates this task E2. Exposure with tools — software built on top of a language model (not the model alone) could cut the time by at least half.

Exposure measures whether a model could meaningfully speed the task up — it is an estimate of overlap with model capabilities, not a measure of whether the work will be done by software. The study's intermediate score (β) for this task is 0.50. Automation potential label: T3.

How AI is actually used on this kind of task

The Anthropic Economic Index observes how people actually use AI on tasks like this one across millions of real conversations.

• 0.004% share of AI-use records mapped to this task
• 54% of that use is work-related
• Average autonomy of the AI: 3.1 (1–5; higher = more autonomous)
• 92% of interactions still needed a human in the loop

Observed AI use describes people choosing to use AI as a tool on this kind of task today. It is augmentation and assistance, not a measure of jobs replaced.

Other tasks in this occupation

• Develop new software applications or customize existing applications to meet specific scientific project needs. · importance 4.3
• Communicate research results through conference presentations, scientific publications, or project reports. · importance 4.3
• Create novel computational approaches and analytical tools as required by research goals. · importance 4.2
• Consult with researchers to analyze problems, recommend technology-based solutions, or determine computational strategies. · importance 4.2
• Analyze large molecular datasets, such as raw microarray data, genomic sequence data, or proteomics data, for clinical or basic research purposes. · importance 3.9
• Keep abreast of new biochemistries, instrumentation, or software by reading scientific literature and attending professional conferences. · importance 3.9
• Develop data models and databases. · importance 3.8
• Compile data for use in activities, such as gene expression profiling, genome annotation, or structural bioinformatics. · importance 3.8
• Design and apply bioinformatics algorithms including unsupervised and supervised machine learning, dynamic programming, or graphic algorithms. · importance 3.7
• Manipulate publicly accessible, commercial, or proprietary genomic, proteomic, or post-genomic databases. · importance 3.7
• Direct the work of technicians and information technology staff applying bioinformatics tools or applications in areas such as proteomics, transcriptomics, metabolomics, or clinical bioinformatics. · importance 3.5
• Provide statistical and computational tools for biologically based activities, such as genetic analysis, measurement of gene expression, or gene function determination. · importance 3.4
• Improve user interfaces to bioinformatics software and databases. · importance 3.4
• Create or modify web-based bioinformatics tools. · importance 3.4

See all tasks on the Bioinformatics Scientists page.

Sources for this page

Every figure above traces to a named public dataset and the exact release below — not hand-written opinion. See the full methodology for what each measure does and does not mean.

• O*NET 30.3 U.S. Department of Labor / National Center for O*NET Development
• Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27) Anthropic
• “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130 OpenAI / academic

Data compiled June 2, 2026. Figures are estimates, not advice.

@misc{singulariki-task-16782,
  title  = {Prepare summary statistics of information regarding human genomes.},
  author = {{Singulariki}},
  year   = {2026},
  note   = {O*NET 30.3; Anthropic Economic Index v4 (2026-01-15) + v2 (2025-03-27); “GPTs are GPTs” (Eloundou et al.) arXiv 2303.10130. Accessed June 7, 2026},
  url    = {https://singulariki.com/tasks/task-16782}
}