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Center for Advancing Safety of Machine Intelligence

Exploring the human impact of machine intelligence

CASMI is seeking a postdoctoral research fellow!

Please see the postdoctoral fellow position description for all the details and contact us if interested.

About CASMI

Machine learning (ML) is the basis for a wealth of transformational technologies from facial recognition to self-driving cars to medical diagnostic systems. The rapid adoption of ML-driven applications has outpaced efforts to understand how these technologies are shaping our digital realities with real impact on our individual lives and communities.

The Center for Advancing Safety of Machine Intelligence (CASMI) is a collaboration with the UL Digital Intelligence Safety Research Institute, building on UL’s 128-year mission to create a safer, more secure, and sustainable future. CASMI evaluates the human impacts of intelligent technologies and develops best practices for the design, development, and evaluation of systems to help ensure they are safe, equitable, and beneficial to all. CASMI builds on the foundational evaluation framework of the Machine Learning Impact Initiative and supports a growing network of investigators advancing the research vision of operationalizing safety in machine intelligence.





CASMI is a Northwestern Engineering project sponsored by Underwriters Laboratories Inc.

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Collaboration

Connecting a network of researchers

CASMI builds connections and collaboration among researchers and experts of different disciplines and backgrounds at Northwestern, Underwriters Laboratories, and partner organizations.

Projects

CASMI funds research that advances the state of the art and answers key questions in the field. A set of initial catalyst projects has been selected to begin in spring 2022 across six universities. We anticipate the next call for project proposals to open in fall 2022.

View our projects

Workshops

CASMI hosts semiannual thematic workshops exploring the human impact of machine intelligence, new research connections, and opportunities.

Explore our workshops

Outcomes

CASMI projects deliver outcomes for machine intelligence research and practitioner communities.

Review our Outcomes

Research

An Evaluation Framework

One of CASMI’s goals is to develop repeatable and operational processes for the identification and mitigation of negative impacts of machine learning applications and the causes of those impacts. To this end, we have developed an evolving evaluation framework to guide the work and vision.

The evaluation framework provides a foundational structure for the design and evaluation of machine learning applications by decoupling fact-finding from evaluation. The framework divides the task of evaluating the human impacts of machine learning (ML) systems into two phases:

  1. Fact-finding related to three primary components:
    1. Data and how it was sourced and manipulated
    2. Central ML algorithms and how they were applied
    3. How the resulting systems are designed to interact with human users
  2. The evaluation phase examines how, given those facts, the system impacts the goals and values associated with a particular domain or field of use.

The framework is also the starting point for CASMI’s research roadmap, a set of specific research problems necessary to further operationalize the design, development, and evaluation of AI systems from the perspective of human health and safety.

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