Center for Equitable Artificial Intelligence and Machine Learning Systems
The Center for Equitable AI and Machine Learning Systems (CEAMLS) seeks to facilitate the research, development of standards, identification of new methods, and advancement of innovative technologies that benefit everyone on the planet. CEAMLS will serve as an interdisciplinary nexus for thought leadership in the application of fair and unbiased technology and its applications. The Center will remain rooted in scholarly stewardship, cultivating the next generation of students at all levels, as well as life-long learners across industries and areas of study.
The Center for Equitable Artificial Intelligence (AI) and Machine Learning (ML) Systems (CEAMLS) specializes in the mitigation of algorithmic bias through continuous research and engagement of academic and industrial leaders.
CEAMLS conducts research on:
- How to improve transparency and clearly articulate purpose in AI models
- How to include fairness as an optimization objective
- How to develop new tools and techniques for detecting bias and reducing the disparate impact caused
- How to develop adversarial tools to stress-test models.
CEAMLS will be a resource for both developers and the public by promoting the development of models that are open for analysis and are linked with visual analytics so that everyone is more knowledgeable about the capabilities, limits, and biases that these models may possess. CEAMLS will also analyze new AI innovations to determine ways in which they could become problematic or damaged due to algorithmic bias, either actual or perceived.