Origins

Artificial intelligence (AI) is transforming the way we structure and categorize knowledge. One of the key areas where AI is making a big impact is in ontology creation. Sounds like the perfect job for AI, right? Not quite.

While AI is great at processing massive amounts of data and identifying patterns, creating a truly useful ontology requires something AI still lacks: human intelligence, intuition and contextual understanding. Instead of replacing humans, AI should be seen as an incredible assistant, helping speed up the process while still relying on human oversight to make sense of it all. This interesting topic came to us from DataConomy in their article, “This AI claims it can build ontologies better than you.”

The most effective way to build ontologies isn’t AI vs. humans. It’s AI working alongside humans. AI can handle the heavy lifting of data processing, pattern recognition and structure suggestions, while humans bring the critical thinking, contextual awareness and ethical considerations needed to refine the final ontology.

In other words, AI gives us speed, efficiency and scalability, but human intelligence ensures accuracy, meaning and usefulness. When combined, they create a much stronger, more reliable knowledge system than either could alone.

So, should we trust AI to build ontologies? Maybe, as long as we keep humans in the loop.

The main issue is that data science has not changed, and scientific content is very complex and needs more attention to get the most out of the new AI engines. This is not new for Access Innovations.

Melody K. Smith

Data Harmony is an award-winning semantic suite that leverages explainable AI.

Sponsored by Access Innovations, uniquely positioned to help you in your AI journey.