7/11/2025 - 7/11/2025
11:00 AM - 12:00 PM Central

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Presenter:

Imran Musaji, PhD, CCC-SLP
The presenter has no financial or non-financial relationships to disclose.

Session Summary:

Explore the evolving landscape of AI in Communication Sciences and Disorders (CSD) in this session. We will demystify AI terminology, explore AI applications in CSD, and examine the current ways the technology is being translated into clinical practice. We will address critical implementation issues, such as bias, transparency, and ethics, and consider the technology in the context of diversity, equity, and inclusion. A new segment will also address growing public and professional misconceptions about AI, helping attendees distinguish between fact and hype. The session concludes with professionally aligned guidelines and a curated list of accessible AI tools for immediate exploration. Join the discussion on how AI can impact clinical services for good, and ill.

Learning Outcomes:

By the end of this session, participants will be able to:

1. Define core AI terminology and distinguish between different AI approaches relevant to CSD.
2. Identify common myths and misconceptions about AI and explain their implications for clinical decision-making.
3. Recognize ethical risks in AI implementation, and describe frameworks to guide responsible use.

Expanded Description:

Artificial Intelligence (AI) holds enormous potential for transforming clinical care, research, and administrative practices in CSD. However, the field faces challenges around ethics, inclusion, misuse, and miscommunication. This session provides a foundational overview of AI models and terminology, introduces frameworks for ethical evaluation, and explores real-world examples from research and clinical domains. We will also address the critical translational gap between promising research and real-world integration.
New to this session is a focused segment on debunking growing misunderstandings regarding AI. These misconceptions often hinder effective implementation and inflate expectations. Key myths addressed include:

• AI is constantly learning from users (Most models, like ChatGPT, are static after training).
• AI understands language like humans (It predicts based on patterns, without comprehension).
• AI is unbiased or neutral by design (Bias is embedded in training data).
• Bigger models are better (Not always true for specialized clinical applications).
• AI has internet access or awareness (It doesn’t unless explicitly connected).
• AI is fully autonomous (Most systems rely heavily on human constraints).
• AI-generated content is easy to spot (Not necessarily, especially in speech or writing).

These clarifications will be embedded within broader discussions of ethics, DEI, and clinician responsibility, and some of the most recent advances in AI utilization within CSD.
This session emphasizes clarity, caution, and clinician agency—giving participants the tools they need to engage with AI without being overwhelmed or misled.
 
Keywords:
Artificial intelligence; Diversity, equity, and inclusion (DEI); ethics; implementation; clinical integration; misinformation
 
Professional Development Topics for Certification:
The content will focus on Diversity, Equity, and Inclusion and Ethics.
 
Proposed Session Focus:
The session does not focus on any one approach, product, tool, technique, or model.
 
Time-Ordered Agenda (1-Hour Presentation):
Introduction – (5 minutes)
• Welcome, disclosures, objectives overview
• Interactive poll on AI familiarity + discussion
Segment 1: Introduction to AI – (15 min)
• AI terminology and concepts (10 min)
• AI architectures and components (5 min)
Segment 2: Research-to-EBP Pipeline – (15 minutes)
• Current state of AI in CSD (10 min)
• Translational gaps and future potential (5 min)
Segment 3: Common AI Myths – (10 minutes)
• Fact-checking myths around AI learning, objectivity, autonomy, and size (15 min)
Segment 4: Implementation Challenges & DEI Risks – (10 minutes)
• Bias, consent, accessibility, and clinician responsibility (5 min)
• Real-world DEI failures and semantic bias demonstrations (5 min)
Conclusion and Wrap-Up – (5 minutes)
• Recap, resources, open floor for Q&A
Total: 60 minutes
 

 

Registration fee:
$20 for KSHA members
$35 for non-KSHA members
Free for students who are KSHA members

Refund policy:
No refunds on webinars unless KSHA cancels the event. 

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7/11/2025 - 7/11/2025

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