This presentation provides professionals with a practical overview of smart devices that support accessibility, safety, and independence for people with disabilities across the lifespan. Participants are introduced to key categories of smart home technologies, assistive devices for daily living, and mobile apps and wearables commonly used in residential settings. The session emphasizes person-centered device selection, implementation considerations such as privacy, training, and ongoing support, and real-world applications through examples and discussion. Attendees will leave with actionable strategies for matching smart devices to individual client needs and with reliable resources to support client and caregiver education and successful long-term use.
Learning Outcomes
- Identify and describe at least three categories of smart devices commonly used to support independence and accessibility
- Explain at least three key considerations involved in implementing smart devices in a client’s home.
- Identify at least three reliable resources for client and caregiver education, training, and ongoing technical support.
The presentation features Bradford Smith, a person living with ALS, sharing his personal experience with Neuralink’s brain-computer interface technology. He describes how the tiny implant reads brain electrical signals and translates them into actionable commands, enabling greater independence and communication despite severe motor limitations. He’ll highlight the transformative potential of this neurotechnology for individuals with paralysis and neurodegenerative conditions. Presentation will be with assistive technology using presenters voice recreated through AI.
Learning Outcomes
- Understanding the Impact on Independence and Quality of Life with BCI
- Insights into Practical Functionality and Applications of BCI Technology
- Knowledge of Technical Challenges, Risks, and Mitigations
For many students, generative AI chatbots have become a regular part of school life, whether as learning supports or always-on homework helpers. While educators likely understand the potential for “chatbot cheating”, these tools can also pose less obvious risks for young learners, including:
- Attention drains from endless chatbot conversations
- Oversharing personal information (which chatbots store in memory)
- Influence by chatbot’s authoritative “voice”, even when it shares misinformation or bias
- Humanlike empathy (“That’s a great idea!”) that encourages interaction like a trusted friend.
AT consultant Shelley Haven will demonstrate chatbot features, settings, and practices that can help educators reduce these risks while supporting more effective student use.
Learning Outcomes
- Identify key safety and trust-related risks students may face when using generative AI chatbots
- Run a “safety audit” of chatbot settings and create guardrails for student use
- Teach students how to improve their fact-checking and sourcing habits
Artificial Intelligence (AI) is constantly evolving technology, which is commonly used in the workplace. Employers utilize AI for a growing number of functions. Employees with disabilities can utilize AI as a reasonable accommodation to assist in completing required job tasks. However, inaccessible AI programs can also pose barriers for employees with disabilities.
This session will provide information about some of the uses of AI to assist employees with disabilities in the workplace, and barriers that AI may pose to applicants and employees with disabilities. This session will also provide information about the rights of employees with disabilities under the Americans with Disabilities Act to request and receive reasonable accommodations in the workplace. Additionally, this session will explore some recent developments around AI in the workplace.
Learning Outcomes
- The various forms of AI that are used by employers and employees in the workplace, and potential barriers posed by AI to employees with disabilities.
- The rights of employees with disabilities to request and receive reasonable accommodations, and some examples of AI as a reasonable accommodation.
- How AI can be used to assist people with disabilities to prepare for employment.
- Recent developments within the past year of AI in the workplace.
Even though Artificial Intelligence (AI) is reshaping education at every level, students with disabilities remain an afterthought in most implementation conversations. This session bridges Universal Design for Learning (UDL) and emerging AI tools to help educators, disability service professionals, and administrators critically evaluate, adopt, and implement AI tools in their learning environments. Participants will explore how AI can expand access and reduce barriers for students with disabilities and explore how it can quietly create new ones when implemented without an equity lens. This session draws on research in inclusive education, disability studies, and emerging AI literature to move beyond surface-level AI enthusiasm and offer an honest look at what these tools mean for students with disabilities. Grounded in UDL, participants will gain a practical, student-centered.
Learning Outcomes
- Identify ways AI tools can either expand or limit access for students with disabilities when evaluated through a UDL framework across educational settings.
- Examine current or planned AI tools and policies in their own educational context to determine whether they are proactively designed to include students with disabilities or require modification to meet equity and access standards.
- Develop a practical action step for implementing or revising an AI-related practice, policy, or learning experience in their setting that centers student voice, reduces barriers, and aligns with UDL principles.
Professionals who support people with disabilities regularly navigate complex questions about assistance, accommodation, and independence: When does support enable participation, and when does it risk replacing skill or judgment? Generative AI introduces similar tensions into professional practice, documentation, training, and evaluation. This interactive session invites participants to examine how emerging AI tools intersect with long-standing principles of accessibility, support, and human judgment. Rather than focusing on specific technologies, the session centers on design questions: what counts as meaningful competence, how professional reasoning can be made visible, and how supports can be structured ethically and transparently. Participants will engage in guided reflection and redesign activities applicable to training, assessment, and service contexts, leaving with practical frameworks for integrating AI in ways that align with disability-centered values.
Learning Outcomes
- Participants will be able to identify parallels between traditional accommodation/support decisions and emerging questions about AI assistance, drawing on their existing expertise in disability services.
- Participants will apply at least two evidence-based design strategies (explain-the-decision, contextual constraints, or critique-the-support) to strengthen professional practices, training, or assessment in their own contexts.
- Participants will distinguish between AI uses that support professional judgment and those that risk obscuring reasoning, replacing skill development, or undermining disability-centered values such as self-determination and dignity of risk.
- Participants will leave with one concrete redesign of a practice, training activity, or assessment approach that makes human judgment visible while ethically integrating AI-based support tools.
Universal Design for Learning’s (UDL) principle of designing multiple means of engagement offers educators practical ways to foster motivation, relevance, and persistence among students. This session highlights strategies that help students connect emotionally and intellectually with learning by offering choices, building relevance, encouraging collaboration, and supporting self-regulation. Research shows UDL improves student engagement and academic success by proactively addressing learner variability and reducing barriers that can limit participation. Examples from elementary, middle, and high school classrooms will illustrate how designing for engagement supports a diverse student body. Participants will have an opportunity to explore with other participants how to apply the principle of engagement in their own setting during this hands-on session.
Learning Outcomes
- Participants will be able to apply UDL-aligned strategies to increase learner autonomy, demonstrate relevance, and support persistence within an inclusive learning environment.
- Participants will be able to evaluate engagement strategies and make recommendations for enhancing engagement given commonly witnessed barriers to engagement.
This session explores how emerging technology can support students with disabilities in K–12 education, including AI-powered tools and educational apps. Participants will learn practical strategies for integrating technology to enhance communication, engagement, academic access, and independence, while also saving educators time in planning, instruction, and assessment. The session emphasizes tools that are free, widely available, or easily implemented in school settings. Real classroom examples demonstrate how these technologies have successfully supported learning, expanded participation, and reduced teacher workload. Attendees will gain actionable ideas for leveraging AI features, interactive apps, and accessible digital resources to meet diverse student needs. By the end of the session, participants will leave equipped to empower students, streamline instruction, and create more inclusive, efficient classrooms.
Learning Outcomes
- Participants will be able to identify AI-powered tools and educational apps that support student learning, engagement, and communication.
- Participants will be able to apply strategies to integrate technology effectively into classroom routines, enhancing instruction while reducing planning and administrative time.
- Participants will be able to implement examples of AI and educational apps to improve both student outcomes and instructional efficiency.
Ethical practice within the field of assistive technology continues to evolve and tested due to continued advancement of the solutions and strategies. As practitioners we have the opportunity and obligation to use an ethical lens in our work as we provide assistive technology services. Ethical guidance can direct how we inform those that we work with on the pros, cons, and in-betweens around AT, the internet, and AI. This session will use decision making models, the CRC Code of Ethics, the RESNA standards, and Wisconsin’s Best Practice guides to discuss AT service delivery. An active dialogue and case examples will be a key component of this session.
This session is based upon established ethical guidance and service delivery models published by CRCC, RESNA, and WisTech.
Learning Outcomes
- Participants will be able to list three ethical best considerations regarding artificial intelligence.
- Participants will be able to list three ethical decision-making models as they apply to AT, the internet, and AI.
- Participants will apply AT and AI service provision as it relates to the CRC Code of Ethics.
Feeling overwhelmed by lesson planning that checks all the boxes—state standards, UDL principles, and individual student needs? You’re not alone! This hands-on, beginner-friendly session is designed for educators who are new to using AI and want practical, easy-to-use tools they can apply right away. Participants will actively explore AI resources that support lesson planning, differentiation, and accessibility, with a focus on simple steps that save time and boost student engagement.
Learning Outcomes
- Use beginner-friendly AI tools to create standards-aligned lesson plans with guided support.
- Practice modifying and differentiating lesson content using AI to meet diverse learning needs.
- Create at least one AI-supported instructional resource they can use immediately in their classroom.
