Anjana Susarla
@asusarla.bsky.social
Omura-Saxena Professor of Responsible AI at the Broad College of Business at Michigan State University.
Some of my general writings can be found at: https://anjanasusarla.substack.com
Some of my general writings can be found at: https://anjanasusarla.substack.com
Reposted by Anjana Susarla
Our forthcoming NeurIPS position paper, led by @aolteanu.bsky.social, makes this argument (along with several related ones) in more depth. Rigorous AI/ML work should flow from explicit and rigorous premises, not just have a final evaluation that checks some rigor boxes. arxiv.org/abs/2506.14652
Rigor in AI: Doing Rigorous AI Work Requires a Broader, Responsible AI-Informed Conception of Rigor
In AI research and practice, rigor remains largely understood in terms of methodological rigor -- such as whether mathematical, statistical, or computational methods are correctly applied. We argue th...
arxiv.org
November 7, 2025 at 12:19 PM
Our forthcoming NeurIPS position paper, led by @aolteanu.bsky.social, makes this argument (along with several related ones) in more depth. Rigorous AI/ML work should flow from explicit and rigorous premises, not just have a final evaluation that checks some rigor boxes. arxiv.org/abs/2506.14652