CASMI identifies and funds research initiatives led by teams at Northwestern and partner institutions that advance the state of intelligent technology and answer key questions outlined in the Research Roadmap and Evaluation Framework. While the potential avenues of machine intelligence research are vast, the roadmap and framework provide a structure to identify gaps, key challenges, and under-addressed areas critical to operationalizing safety in AI and addressing the potential impacts of its use.
The evaluation framework provides a foundational structure for the design and evaluation of machine learning applications by decoupling fact-finding from evaluation. In the first phase of the framework, the focus is on articulating the core features of the machine learning (ML) system by understanding its three primary components: the data on which the system is based, the ML algorithms being utilized, and the design of the system’s interaction with human users. Given that set of facts, the second phase of the framework focuses on evaluation to assess the system in the context of the goals and values of the domain in which it will be deployed.
CASMI Projects are intended to further refine the roadmap or to address key problems and needs in one of the framework component areas.
