Trust in CINTEL

Understanding which contextual factors may contribute to, influence or erode how trust in CINTEL is established and maintained

The challenge

Collaborative intelligence requires humans to trust the technology with which they are collaborating. If people do not trust a technology they may avoid using it, or use it in a way which limits its overall effectiveness, for example by withholding relevant information. Too much trust can also be a problem, as humans may not be sufficiently watchful for mistakes made by an artificially intelligent technology. Designing CINTEL systems and workflows in ways which promote the appropriate level of trust between human and machine collaborators is therefore a key part of the CINTEL challenge.

Our response

This project will build on previous research (in a field of science known as Human Factors) on how and why people trust technology to consider the needs of CINTEL systems, in which humans are not simply users of technology but rather active and (hopefully) engaged collaborators. This research starts by developing a broad understanding of what constitutes a CINTEL system from a Human Factors point of view and which contextual factors may contribute to, influence or erode how trust in CINTEL is established and maintained. We are also investigating how these contextual factors are similar to or different from factors contributing to trust in Artificial Intelligence or automation more broadly. This will include an examination of user expectations, requirements and interactions with respect to tolerance for risk, need for information, and confidence in reliability, for example.

Impact

Insights from both qualitative and quantitative studies across a range of proposed use cases (including other projects with the CINTEL Future Science Platform) will allow us to develop a deeper understanding of contextual variables that enable (or hinder) trust in CINTEL and work towards establishing an empirically validated model of trust in and adoption of such technologies.