K-point
AI gains, dependence and recovery
What happens to a team’s work and knowledge when AI assistance is withdrawn?
Study design in development
Explore the programme →Research programmes
Questions worth investigating.
We study how people and organisations use knowledge, what AI changes and whether the ArtiProof method helps assess that knowledge. Explore the research programmes below.
Method research
What does the ArtiProof method add?
Does the method add value to existing practice? Do assessors reach similar conclusions? Are the benefits worth the extra work? We also examine how often it flags a problem that is not there.
v0.8 Empirical Challenge
Explore the programme →Knowledge distribution
How does knowledge reach the right people?
Exploring the difference between distributing information and making usable knowledge available for a role or decision.
Exploratory research direction
Explore the programme →Cases as a starting point
The 31 cases bring together stories and sources. They help us ask questions and explore possible explanations.
Open the case library →Contribute to research
Have a useful source, counterexample or question from practice? Get in touch. If you want to run a study or pilot, we can discuss the approach together.
Contribute →What evidence is available?
Available work includes method design, source research and internal development checks. A study design, simulation or internal review does not establish broad effectiveness or independent replication. Each study and its conclusions must be assessed against its own evidence.
For K-point, a dry walkthrough using input constructed by ChatGPT is available. It involved no participants or human timing measurements. It helps clarify the protocol and provides no empirical participant findings.
The cases bring together existing literature, stories and our synthesis. Their number is not a count of independent discoveries. A proposed test only becomes completed research when its execution and results have been recorded.