Frank van Harmelen, a leading AI professor at Vrije Universiteit in Amsterdam, discusses the integration of human and machine intelligence. He emphasizes the importance of hybrid collaboration, advocating for AI systems that enhance rather than replace human capabilities. Topics include the emergence of neuro-symbolic systems, the evolution of conversational interfaces, and the challenges of managing interdisciplinary research teams. He also highlights innovative applications of AI in healthcare and the need for a shared worldview to foster effective collaboration.
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insights INSIGHT
Hybrid Intelligence Defined
Hybrid intelligence means forming teams of humans and AI that collaborate on tasks together.
This approach focuses on AI supporting people, not replacing them.
insights INSIGHT
Complementary Strengths of Humans & Machines
Machines have perfect memory and don't suffer cognitive biases like humans do.
Humans provide context, purpose, and understand social norms that machines cannot grasp alone.
insights INSIGHT
Shared Worldview Enables Collaboration
Collaboration requires a shared worldview and awareness of each other's goals and intentions.
This alignment is critical for both human teams and human-AI hybrid teams to function effectively.
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In this book, Daniel Kahneman takes readers on a tour of the mind, explaining how the two systems of thought shape our judgments and decisions. System 1 is fast, automatic, and emotional, while System 2 is slower, effortful, and logical. Kahneman discusses the impact of cognitive biases, the difficulties of predicting future happiness, and the effects of overconfidence on corporate strategies. He offers practical insights into how to guard against mental glitches and how to benefit from slow thinking in both personal and business life. The book also explores the distinction between the 'experiencing self' and the 'remembering self' and their roles in our perception of happiness.
Frank van Harmelen
Much of the conversation around AI architectures lately is about neuro-symbolic systems that combine neural-network learning tech like LLMs and symbolic AI like knowledge graphs.
Frank van Harmelen's research has followed this path, but he puts all of his AI research in the larger context of how these technical systems can best support people.
While some in the AI world seek to replace humans with machines, Frank focuses on AI systems that collaborate effectively with people.
We talked about:
his role as a professor of AI at the Vrije Universiteit in Amsterdam
how rapid change in the AI world has affected the 10-year, €20-million Hybrid Intelligence Centre research he oversees
the focus of his research on the hybrid combination of human and machine intelligence
how the introduction of conversational interfaces has advance AI-human collaboration
a few of the benefits of hybrid human-AI collaboration
the importance of a shared worldview in any collaborative effort
the role of the psychological concept of "theory of mind" in hybrid human-AI systems
the emergence of neuro-symbolic solutions
how he helps his students see the differences between systems 1 and 2 thinking and its relevance in AI systems
his role in establishing the foundations of the semantic web
the challenges of running a program that spans seven universities and employs dozens of faculty and PhD students
some examples of use cases for hybrid AI-human systems
his take on agentic AI, and the importance of humans in agent systems
some classic research on multi-agent computer systems
the four research challenges - collaboration, adaptation, responsibility, and explainability - they are tackling in their hybrid intelligence research
his take on the different approaches to AI in Europe, the US, and China
the matrix structure he uses to allocate people and resources to three key research areas: problems, solutions, and evaluation
his belief that "AI is there to collaborate with people and not to replace us"
Frank's bio
Since 2000 Frank van Harmelen has played a leading role in the development of the Semantic Web. He is a co-designer of the Web Ontology Language OWL, which has become a worldwide standard. He co-authored the first academic textbook of the field, and was one of the architects of Sesame, an RDF storage and retrieval engine, which is in wide academic and industrial use. This work received the 10-year impact award at the International Semantic Web Conference. Linked Open Data and Knowledge Graphs are important spin-offs from this work.
Since 2020, Frank is is scientific director of the Hybrid Intelligence Centre, where 50 PhD students and as many faculty members from 7 Dutch universities investigate AI systems that collaborate with people instead of replacing them.
The large scale of modern knowledge graphs that contain hundreds of millions of entities and relationships (made possible partly by the work of Van Harmelen and his team) opened the door to combine these symbolic knowledge representations with machine learning. Since 2018, Frank has pivoted his research group from purely symbolic Knowledge Representation to Neuro-Symbolic forms of AI.
Connect with Frank online
Hybrid Intelligence Centre
Video
Here’s the video version of our conversation:
https://youtu.be/ox20_l67R7I
Podcast intro transcript
This is the Knowledge Graph Insights podcast, episode number 33. As the AI landscape has evolved over the past few years, hybrid architectures that combine LLMs, knowledge graphs, and other AI technology have become the norm. Frank van Harmelen argues that the ultimate hybrid system must also include humans. He's running a 10-year, €20 million research program in the Netherlands to explore exactly this. His Hybrid Intelligence Centre investigates AI systems that collaborate with people instead of replacing them.
Interview transcript
Larry:
Hi,