Episode 117 of SLP Full Disclosure dives into the critical issue of bias in speech-language pathology. Hosts Michelle and Dr. Marisha Speights explore how biases influence speech screenings and evaluations, including the impact on clinical practice and the importance of cultural representation in assessments. They address challenges with outdated screening measures and discuss the integration of artificial intelligence in identifying speech disorders. Together, they emphasize the importance of mindful, equitable care, encouraging clinicians to critically evaluate the tools they use.

Chapters

• 00:00 Understanding Bias in Speech-Language Pathology
• 07:30 The Impact of Cultural Representation in Assessments
• 15:00 Challenges with Outdated Screening Measures
• 21:59 The Role of AI in Speech-Language Pathology
• 30:01 Navigating Bias in Clinical Practice

About Dr. Marisha Speights

Dr. Marisha Speights, a speech scientist and pathologist, specializes in pediatric speech biomarkers and AI-driven detection of speech disorders. She leads the Pediatric Speech Technologies and Acoustics Research Lab, where her team develops computational tools to improve speech disorder classification, refine automatic speech recognition models, and apply machine learning for equitable early screening. She is a key contributor to the NIH’s AIM AHEAD initiative, focusing on reducing biases in AI-driven technologies for children’s speech.

Central to her work is the Speech Exemplar and Evaluation Database (SEED), a diverse child speech dataset addressing critical gaps in existing resources. Supported by the Bill and Melinda Gates Foundation and global collaborations, Dr. Speights aims to advance culturally responsive, AI-powered tools to ensure equitable early detection and intervention for children across diverse communities.

Supporting Resources to Learn More 

Northwestern University Faculty Page
Pediatric Speech Technologies and Acoustics Research Lab

Learn more about the show: SLP Full Disclosure Podcast
 

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