Who is #KnowledgeEngineer ?
Recently I was called for interview for this job profile. Honestly I heard this term for the first time then. I did my part; Googling. Here’s summary:
Knowledge Engineer is someone who creates, maintains and uses the knowledge base for artificially intelligent systems/applications. His responsibilities revolve around obtaining data, applying logical rules, creation of knowledge base. They come up with systems that automates the process of collection of data and storing it in a structured format as required, by applying logic based inferences. They are also given problem statements and asked to produce knowledge systems accordingly.
This gave me some idea, but still there are too many confusing/complex definitions out there and I really wished to know what a KE does? How it is related with data science? Can this profile help in growing as #datascientist or this is another path altogether. I asked some of the industry experienced on LinkedIn and got these following replies:
That’s a new term for me. Sorry, I have tumbleweed blowing in the desert over here with that term…
The term “Knowledge Engineering” has its origins in Expert Systems, which were a generation before current day Machine Learning systems. Remember systems like Eliza that did medical diagnosis? Essentially a knowledge engineer’s job was to sit with a human expert and extract their knowledge, codify it into a form that was amenable for computation (e.g., set of rules or a Bayesian network). Once this extraction of human expert knowledge was available, it formed the basis for an automated expert system.
That is a good explanation. I would add a comment as well: The new AI wave has eschewed knowledge engineering to its own detriment. Not everything can be elicited from data effectively. Where human knowledge is available, it needs to be incorporated into models. Otherwise, we are losing a lot of information.
When you say AI or Data Science its a broader spectrum. KE more over revolves around the Knowledge Extraction and Knowledge Understanding which is NLP, NLU i.e., Natural Language Understanding involving deeper concepts like Deep Learning as well; along with older techniques Information Retrieval, Text Mining, etc. Now, coming to your second question: Me having done my masters in KE, I started my career in AI Labs of DESS, TCS. So I can confirm you that its one of the main steams of AI just like DS, even though DS has now become the buzz word in the IT industries.
Never heard of the term before but it seems more like a data engineer/developer who automates data feeds at scale and cleans it up somewhat to enable further analysis to solve the business problem.
While some of them were like me, bit lost in the jargon others really helped to clear the confusing smoke around the term Knowledge Engineer. Follow #LearnWithAkansha on LinkedIn for more knowledgeable updates. You can follow me on Twitter, my work on Github, and connect professionally with me on LinkedIn.
