How Close Are Computers to Automating Mathematical Reasoning? AI tools are shaping next-generation theorem provers, and with them the relationship between math and machine

Title:
How Close Are Computers to Automating Mathematical Reasoning?

Author:
Stephen Ornes

Published:
Quanta magazine, 27 August 2020
https://www.quantamagazine.org/how-close-are-computers-to-automating-mathematical-reasoning-20200827/

From the article:
A formidable open challenge in the field asks how much proof-making can actually be automated: Can a system generate an interesting conjecture and prove it in a way that people understand? A slew of recent advances from labs around the world suggests ways that artificial intelligence tools may answer that question.

Scholarly Article (PNAS, 2020) - Racial disparities in automated speech recognition

Title:
Racial disparities in automated speech recognition

Authors:
Allison Koenecke, Andrew Nam, Emily Lake, Joe Nudell, Minnie Quartey, Zion Mengesha, Connor Toups, John R. Rickford, Dan Jurafsky & Sharad Goel

Published:
PNAS (Proceedings of the National Academy of Sciences of the United States of America), 117(14): 7684-7689; first published March 23, 2020.
Available: https://doi.org/10.1073/pnas.1915768117

Significance:
"Automated speech recognition (ASR) systems are now used in a variety of applications to convert spoken language to text, from virtual assistants, to closed captioning, to hands-free computing. By analyzing a large corpus of sociolinguistic interviews with white and African American speakers, we demonstrate large racial disparities in the performance of five popular commercial ASR systems. Our results point to hurdles faced by African Americans in using increasingly widespread tools driven by speech recognition technology. More generally, our work illustrates the need to audit emerging machine-learning systems to ensure they are broadly inclusive."