In this episode of AI in Action, Dr. Sidney Shapiro sits down with Mahammad Ayan Shaikh, Computer Programming student and CPIN Lab Monitor at Cambrian College, to explore how artificial intelligence and the Internet of Things are converging to power the next generation of embedded systems. Drawing from his hands-on experience designing and troubleshooting IoT prototypes, Mahammad discusses how AI enhances connected devices by transforming real-time sensor data into intelligent, autonomous decision-making.

The conversation highlights one of his most ambitious projects: a real-time collision-detection and automated emergency-notification system. Designed to activate in the event of an accident, the system detects impact, captures GPS location and environmental data, and transmits critical information to emergency contacts or services. Through this example, listeners gain insight into the technical and operational challenges of integrating hardware, sensors, edge processing, and secure data transmission into a reliable safety solution.

Dr. Shapiro and Mahammad also examine broader trends shaping the industry, including the rise of edge computing, increased device-level intelligence, and the shift away from cloud-dependent architectures. They address the growing importance of cybersecurity, encryption, and responsible data governance as IoT devices collect and process sensitive information at scale. The episode further explores the gap between academic prototypes and real-world deployment, outlining the technical, organizational, and talent-related barriers businesses face when adopting AI-driven IoT solutions.

For students and professionals entering the field, Mahammad shares practical advice on building foundational programming skills, working with microcontrollers such as Arduino and Raspberry Pi, and gaining hands-on experience through applied projects. This episode provides a grounded perspective on how embedded systems, AI, and IoT are reshaping industries through intelligent automation, real-time responsiveness, and connected innovation.

Find out more at https://ai-in-action.pinecast.co

In this episode of AI & Impact, Dr. Sidney Shapiro speaks with Janelle Marietta, PhD candidate, instructor, and nonprofit leader, about the growing role of artificial intelligence in nonprofit organizations, education, and community-based work.

The conversation explores how AI tools can help nonprofits address long-standing capacity challenges, improve marketing and donor engagement, and support evaluation and analysis—while also highlighting the risks of over-reliance on automation, biased data, and inauthentic communication.

Key topics include ethical considerations in AI adoption, the limits of AI in qualitative and community-engaged research, and the importance of maintaining human-centered approaches in equity-focused and decolonization work. Janelle also discusses the skills nonprofit leaders and emerging professionals need to use AI effectively and responsibly, even in low-resource environments.

This episode is particularly relevant for nonprofit leaders, educators, researchers, and students interested in social impact, community development, and responsible AI use.

Find out more at https://ai-in-action.pinecast.co

AI in the Classroom and Beyond

In this Season 2 premiere of AI in Action, Dr. Sidney Shapiro is joined by Dr. Jason Satel to examine how artificial intelligence is reshaping education, research, and professional expertise.

The conversation explores the realities behind AGI hype, the rapid adoption of AI tools in universities, and why traditional assessment and certification models are under growing pressure. Dr. Satel discusses practical approaches to teaching students how to use AI effectively, rather than attempting to prohibit it, and explains why iteration, context, and critical judgment are now core skills.

Key topics include:

• AI’s impact on higher education and assessment design

• Teaching AI literacy to students and faculty

• The limits of current models in creativity, humor, and context

• AI as a research assistant: literature review, coding, and data analysis

• Hardware constraints, industry–academia gaps, and access to compute

• Bias, synthetic data, and model alignment

• What AI means for future careers, expertise, and certification

This episode offers a grounded, candid discussion on adapting educational and research practices in a world where AI is becoming a standard tool rather than a novelty.

Find out more at https://ai-in-action.pinecast.co