Mynd Labs ResearchIn brief
Each Mynd Labs field has a plain guiding question. Fieldwork is the practice of taking those questions to the people who live with them, before building anything.
Illustration of the idea. Not a result.
The problem
Research that starts from a technology looks for problems. Research that starts from a field finds the ones that matter.
Approach
How we are going about it.
- 01
Ask the question in the field
Each of the fifteen sector programs begins with a guiding question. Fieldwork tests whether it is the right question.
- 02
Share the instrument
What the AI Lab builds, such as replay, memory and evaluation, is shaped by what these fields need.
- 03
Write down what was learned
Findings go into notes and open questions, including the questions that turned out to be wrong.
Limits
This is a working method, not a finished one. It will change as we meet real practitioners.
Landscape
What already exists, and where we start.
Regulation and standards describe obligations by sector. Fieldwork is earlier than that: asking practitioners what problem is worth solving before a system exists.
- StandardNIST (2023). AI Risk Management Framework (AI RMF 1.0).
A voluntary US framework for mapping, measuring and managing AI risk.
- RegulationEuropean Union (2024). Regulation (EU) 2024/1689, the Artificial Intelligence Act.
The EU's risk-based law for AI systems. Sets record-keeping and oversight duties for high-risk uses.
- StandardISO/IEC 42001:2023. Information technology, Artificial intelligence, Management system.
A management-system standard for organisations that develop or use AI.
- PaperMitchell et al. (2019). Model Cards for Model Reporting.
A documentation format for what a model is for and where it fails.
Notes