Clearer summaries
Can a suggested summary retain the location and practical concern without adding facts that were not supplied?
AI & trust
Intelligence that assists.
Judgement that stays human.
Our technology direction explores how AI could help organise road-safety information while keeping people responsible for interpretation and decisions.
AI-assisted workflows / Development directionMake the information
Make the information
easier to work with.
A description may be incomplete, ambiguous or difficult to compare with another. AI could help suggest a concise summary, identify missing context and propose a category for review.
These are areas for development and evaluation. The current website provides a structured brief builder and a contact workflow; it does not analyse observations with an AI model.
Assistance is useful
when its limits are clear.
A suggestion is not a verified finding. Any future model output should be reviewed against the original observation and the local context.
- Preserve the original description
- Make uncertainty visible
- Keep the reviewer accountable
Where AI could help
Practical questions
for careful development.
Consistent categories
Can category suggestions make observations easier to organise while letting the reviewer correct them?
Missing context
Can the workflow ask a useful follow-up question when an observation lacks time, location or a clear description?
Available today and what comes next
A clear view of the scope.
| Area | Current scope |
|---|---|
| Observation builder | A working browser tool that formats the details you provide into a downloadable brief.|
| Contact workflow | A form that saves an enquiry for Hawk Eye and returns a reference.|
| AI assistance | A development direction. No AI model processes data on this website.|
| Authority integrations | Not connected through this website. Any proposed integration requires a separate agreement and validation.|
| Decisions and enforcement | No automatic assessment of offences, fines, emergency dispatch or identification of individuals.
Start small.
Test with care.
A useful evaluation needs a defined setting, appropriate sample data, agreed review criteria and a way to handle mistakes. We welcome conversations about those foundations.
Discuss a research collaboration- Agree a clear purpose for the data
- Use only what is necessary for the task
- Review accuracy and failure cases
- Set responsibilities before deployment
A better way forward
Let’s make the next
conversation count.
Have a road-safety challenge, a community initiative or a collaboration in mind? We would like to hear about it.