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AI exposure report
Will AI replace Forensic Science Technicians?
Some of your tasks will be automated. People who use AI will have the edge.
Task exposure to today's AI
Moderate exposure
This is the occupation's typical task mix. Your own score can be up to 30 points higher or lower depending on how you work: routine share, people contact, judgment and how much you already use AI.
Get your personal scoreWill AI replace Forensic Science Technicians?
Not entirely. Today's AI tools can take on about 33% of the typical work in this occupation, mostly: keep records and prepare reports detailing findings, investigative methods, and laboratory techniques. The parts that stay human include: Collect evidence from crime scenes, storing it in conditions that preserve its integrity.; Operate and maintain laboratory equipment and apparatus.; Use chemicals or other substances to examine latent fingerprint evidence and compare developed prints to those of known persons in databases..
People who learn to use AI for the automatable parts keep the edge. The 3-phase plan below shows where to start.
Which tasks AI can take on
The largest tasks in this occupation, their share of the working week, and how much of each today's AI tools can do.
+ 18 more tasks (43% of the week) in the full test.
Your human edge
- Collect evidence from crime scenes, storing it in conditions that preserve its integrity.
- Operate and maintain laboratory equipment and apparatus.
- Use chemicals or other substances to examine latent fingerprint evidence and compare developed prints to those of known persons in databases.
AI tools to try
ChatGPT / Claude for literature and writingAI research tools (e.g. Elicit, Consensus, Semantic Scholar)Copilot for data analysis code (Python, R)Related roles
A 3-phase AI learning plan
Phase 1
Faster literature and writing
- Literature search and summaries with AI, always checked against the papers.
- Drafts of methods, reports and grant text.
- Reference management and formatting.
Project
Use AI to draft a standard operating procedure for one latent print development method, citing 10 verified published validation papers, and compare drafting time against your last manual SOP.Phase 2
AI for data analysis
- Analysis code in Python or R written with AI help.
- Visualisation and statistics explained step by step.
- Reproducibility: version code and prompts.
Project
Build an AI-assisted Python or R script that plots and statistically compares GC-MS or fingerprint quality scores from 50 de-identified casework runs, versioned in a repo with saved prompts.Phase 3
AI as a research method
- Classification, extraction or modelling with AI on your data.
- Validate against human labels or ground truth.
- Ethics, data protection and disclosure of AI use.
Project
Train and validate an AI image classifier on 200 anonymised test-impression prints against your own expert labels, reporting accuracy, error types, and an AI-use disclosure statement.