Symbiotic Knowledge Graphs: A Vision for Semantic Brain-Computer Interfaces

Post-WWII: bottleneck shifts from scientific knowledge production → consumption

Vannevar Bush, Manhattan Project, NSF Photo: Office for Emergency Management, 1940–44 (Library of Congress, public domain)

Memex illustration by Alfred D. Crimi, LIFE, 10 Sept. 1945

• Bush argued the need for the Memex

  Device to store all forms of data, and links between them
  As We May Think, 1945 essay

Need for cooperative interaction between humans and machines

Joseph Carl Robnett Licklider, ARPA Photo: MIT Museum

• Computers should not only automate calculations

  Humans: creativity and intuition
  Computers: precise calculations and information
  Man-Computer Symbiosis, 1960 essay
  
  

Licklider, IRE Transactions on Human Factors in Electronics, 1960

Humans solving complex problems better by directly augmenting human cognition

• Do not only focus on making computers more intelligent

  Humans should also become better at solving complex problems
  → computer mouse, windowed interfaces, collaborative editing, …
  Augmenting Human Intellect: A Conceptual Framework, 1962 report
  
  

Douglas Engelbart, Augmentation Research Center Still from the 1968 SRI demo

Engelbart, Augmenting Human Intellect, SRI report, 1962

The Semantic Web → intelligent agents

Tim Berners-Lee, Jim Hendler, Ora Lassila Photos: Knowledge Graph Conference (KGC), 2025

Illustration © 2001 Scientific American (The Semantic Web, Berners-Lee, Hendler & Lassila)

• Machine-understandable layer on the Web

  Intelligence is external to humans (Licklider)
  The Semantic Web, 2001
  
  

• → Let's revisit Engelbart's vision!

  Not only increase artificial intelligence
  but also increase human intelligence.

Why does this matter now?

Google effect: we offload thinking to search engines and AI, causing our memory and skills to degrade (Sparrow et al., 2011).

Integrating Brain-based Knowledge with external Knowledge

Using a (hypothetical) Semantic Brain-Computer Interface

Opportunities using current BCI technology

BCIs can encode and decode sensory information

• 

  RQ1: “How can human senses and actuators be semantically modeled?”

  e.g. Robotic Teleoperation
• 

  RQ2: “How can link semantics aid humans in navigating data graphs using BCIs?”

  e.g. Web or Knowledge Graph navigation

Opportunities using future BCI technology

BCIs cannot extract or inject knowledge

• 

  RQ3: “How can biological semantic memory be mapped to and from symbolic knowledge?”

  Memories are stored differently across people
• 

  RQ4: “How can biological reasoning be mapped to and from symbolic and subsymbolic reasoning?”

  Languages to exchange reasoning and contexts
• 

  RQ5: “How can we model ownership and access control for biological memories?”

  Are current authorization mechanisms sufficient?

Call for action: augment Human Intelligence using SBCIs

• Towards Future 2: co-evolve AI and HI

  Following Engelbart's vision
  

• Strongly depends on BCI breakthroughs

  → Let's team up with cognitive neuroscience and BCI researchers