Tootfinder

`Socheton': A Culturally Appropriate AI Tool to Support Reproductive Well-being
Sharifa Sultana, Hafsah Mahzabin Chowdhury, Zinnat Sultana, Nervo Verdezoto
https://arxiv.org/abs/2506.12357

`Socheton': A Culturally Appropriate AI Tool to Support Reproductive Well-being
Reproductive well-being education in the Global South is often challenged as many communities perceive many of its contents as misinformation, misconceptions, and language-inappropriate. Our ten-month-long ethnographic study (n=41) investigated the impact of sociocultural landscape, cultural beliefs, and healthcare infrastructure on Bangladeshi people's access to quality reproductive healthcare and set four design goals: combating misinformation, including culturally appropriate language, profe…

AI Tutors vs. Tenacious Myths: Evidence from Personalised Dialogue Interventions in Education
Brooklyn J. Corbett, Jason M. Tangen
https://arxiv.org/abs/2506.09292

AI Tutors vs. Tenacious Myths: Evidence from Personalised Dialogue Interventions in Education
Misconceptions in psychology and education persist despite clear contradictory evidence, resisting traditional correction methods. This study investigated whether personalised AI dialogue could effectively correct these stubborn beliefs. In a preregistered experiment (N = 375), participants holding strong psychology misconceptions engaged in one of three interventions: (1) personalised AI dialogue targeting their specific misconception, (2) generic textbook-style refutation, or (3) neutral AI d…

Optimal Non-Adaptive Group Testing with One-Sided Error Guarantees
Daniel McMorrow, Jonathan Scarlett
https://arxiv.org/abs/2506.10374 https://

Optimal Non-Adaptive Group Testing with One-Sided Error Guarantees
The group testing problem consists of determining a sparse subset of defective items from within a larger set of items via a series of tests, where each test outcome indicates whether at least one defective item is included in the test. We study the approximate recovery setting, where the recovery criterion of the defective set is relaxed to allow a small number of items to be misclassified. In particular, we consider one-sided approximate recovery criteria, where we allow either only false neg…

Enduring Disparities in the Workplace: A Pilot Study in the AI Community
Yunusa Simipa Abdulsalam, Siobhan Mackenzie Hall, Ana Quintero-Ossa, William Agnew, Carla Muntean, Sarah Tan, Ashley Heady, Savannah Thais, Jessica Schrouff
https://arxiv.org/abs/2506.04305

Enduring Disparities in the Workplace: A Pilot Study in the AI Community
In efforts toward achieving responsible artificial intelligence (AI), fostering a culture of workplace transparency, diversity, and inclusion can breed innovation, trust, and employee contentment. In AI and Machine Learning (ML), such environments correlate with higher standards of responsible development. Without transparency, disparities, microaggressions and misconduct will remain unaddressed, undermining the very structural inequities responsible AI aims to mitigate. While prior work invest…