Start Date
November 2025
End Date
November 2025
Keywords
AI empathy, digital pedagogy, ethical AI, multimodal learning, human-centered design, participatory AI, no-code tools, Neo4j, n8n automation, knowledge engineering, experiential learning, higher education innovation, collaborative teaching, interactive curriculum, story-driven learning, computational thinking, faculty development, educational technology, student engagement
Abstract
From Words to Wisdom: Design Principles for the Next Era of AI.
What happens when an AI system grows beyond chatbots and begins to think, connect, and empathize like a true learning partner? This presentation explores the AI Brain—a new frontier where knowledge graphs, large language models, and ethical design converge to transform higher education.
Using a “Titanic Knowledge Graph” (a mini AI-brain built from historical data, survivor accounts, and multimedia), I will demonstrate how digital tools can help students not just learn facts, but grapple with human dilemmas, resilience, and compassion. In a live session, participants will see how AI-enhanced knowledge graphs shift learning away from static content and into dynamic dialogue—where history becomes a stage for inquiry, critical thinking, and empathy.
Faculty will be invited to co-create scenarios that explore how AI “brains” can be adapted across disciplines—spanning healthcare, engineering, business, and beyond—to foster deeper student engagement and authentic learning. Practical pathways will be shared, beginning with no-code tools such as the free Neo4j LLM Knowledge Graph Builder and extending into advanced hybrid workflows (n8n + Python). These faculty-guided AI systems have the potential to surpass even the most capable research teams, while ensuring that humans remain at the center—defining goals, safeguarding ethics, and interpreting results.
This talk challenges us to see AI not as automation, but as augmentation: an empathetic partner that can elevate both teaching and scholarship when designed with wisdom and integrity.
Learning Outcomes
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Learn the basics of creating a collaborative, multimodal knowledge graph using the free Neo4j LLM Knowledge Graph Builder as a simple no-code entry point.
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Experience how a “Titanic Knowledge Graph” can act as a mini AI-brain and empathetic learning partner in higher education.
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Explore strategies for integrating knowledge graphs to emphasize humanity, ethics, and storytelling in digital education.
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Gain practical resources and inspiration to reimagine digital learning as a co-creative partnership between humans and AI.
Track
Teaching & Learning Technologies
Session Type
50-Minute Session
Beyond Chatbots: Designing the AI Brain of True Intelligence
From Words to Wisdom: Design Principles for the Next Era of AI.
What happens when an AI system grows beyond chatbots and begins to think, connect, and empathize like a true learning partner? This presentation explores the AI Brain—a new frontier where knowledge graphs, large language models, and ethical design converge to transform higher education.
Using a “Titanic Knowledge Graph” (a mini AI-brain built from historical data, survivor accounts, and multimedia), I will demonstrate how digital tools can help students not just learn facts, but grapple with human dilemmas, resilience, and compassion. In a live session, participants will see how AI-enhanced knowledge graphs shift learning away from static content and into dynamic dialogue—where history becomes a stage for inquiry, critical thinking, and empathy.
Faculty will be invited to co-create scenarios that explore how AI “brains” can be adapted across disciplines—spanning healthcare, engineering, business, and beyond—to foster deeper student engagement and authentic learning. Practical pathways will be shared, beginning with no-code tools such as the free Neo4j LLM Knowledge Graph Builder and extending into advanced hybrid workflows (n8n + Python). These faculty-guided AI systems have the potential to surpass even the most capable research teams, while ensuring that humans remain at the center—defining goals, safeguarding ethics, and interpreting results.
This talk challenges us to see AI not as automation, but as augmentation: an empathetic partner that can elevate both teaching and scholarship when designed with wisdom and integrity.