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Listen "Casey Hart: The Philosophical Foundations of Ontology Practice – Episode 38"
Episode Synopsis
Casey Hart
Ontology engineering has its roots in the idea of ontology as defined by classical philosophers.
Casey Hart sees many other connections between professional ontology practice and the academic discipline of philosophy and shows how concepts like epistemology, metaphysics, and rhetoric are relevant to both knowledge graphs and AI technology in general.
We talked about:
his work as a lead ontologist at Ford and as an ontology consultant
his academic background in philosophy
the variety of pathways into ontology practice
the philosophical principles like metaphysics, epistemology, and logic that inform the practice of ontology
his history with the the Cyc project and employment at Cycorp
how he re-uses classes like "category" and similar concepts from upper ontologies like gist
his definition of "AI" - including his assertion that we should use term to talk about a practice, not a particular technology
his reminder that ontologies are models and like all models can oversimplify reality
Casey's bio
Casey Hart is the lead ontologist for Ford, runs an ontology consultancy, and pilots a growing YouTube channel. He is enthusiastic about philosophy and ontology evangelism. After earning his PhD in philosophy from the University of Wisconsin-Madison (specializing in epistemology and the philosophy of science), he found himself in the private sector at Cycorp. Along his professional career, he has worked in several domains: healthcare, oil & gas, automotive, climate science, agriculture, and retail, among others. Casey believes strongly that ontology should be fun, accessible, resemble what is being modelled, and just as complex as it needs to be.
He lives in the Pacific Northwest with his wife and three daughters and a few farm animals.
Connect with Casey online
LinkedIn
ontologyexplained at gmail dot com
Ontology Explained YouTube channel
Video
Here’s the video version of our conversation:
https://youtu.be/siqwNncPPBw
Podcast intro transcript
This is the Knowledge Graph Insights podcast, episode number 38. When the subject of philosophy comes up in relation to ontology practice, it's typically cited as the origin of the term, and then the subject is dropped. Casey Hart sees many other connections between ontology practice and it its philosophical roots. In addition to logic as the foundation of OWL, he shows how philosophy concepts like epistemology, metaphysics, and rhetoric are relevant to both knowledge graphs and AI technology in general.
Interview transcript
Larry:
Hi, everyone. Welcome to episode number 38 of the Knowledge Graph Insights podcast. I am really delighted today to welcome to the show Casey Hart. Casey has a really cool YouTube channel on the philosophy behind ontology engineering and ontology practice. Casey is currently an ontologist at Ford, the motor car company. So welcome Casey, tell the folks a little bit more about what you're up to these days.
Casey:
Hi. Thanks, Larry. I'm super excited to be here. I've listened to the podcast, and man, your intro sounds so smooth. I was like, "I wonder how many edits that takes." No, you just fire them off, that's beautiful.
Casey:
Yeah, so like you said, these days I'm the ontologist at Ford, so building out data models for sensor data and vehicle information, all those sorts of fun things. I am also working as a consultant. I've got a couple of different startup healthcare companies and some cybersecurity stuff, little things around the edge. I love evangelizing ontology, talking about it and thinking about it. And as you mentioned for the YouTube channel, that's been my creative outlet. My background is in philosophy and I was interested in, I got my PhD in philosophy, I was going to teach it. You write lots of papers, those sorts of things, and I miss that to some extent getting out into industry, and that's been my way back in to, all right, come up with an idea, try and distill it, think about objections, put it together, and so I'm really enjoying that lately.
Larry:
And I'm enjoying the video-
Casey:
Glad to be on the show.
Larry:
Yeah, no, I really appreciate what you're doing there. One thing I wanted to, and I love that that's how you're getting back to both your philosophical roots, but also part of it is to evangelize ontology practice, which is that's what this podcast is all about, democratizing and sharing practice. But I think, and I just love that you have this explicit and strong philosophical foundation and bent to how you talk about things. I think a lot of times that conversation is like, "Yeah, ontology comes out of philosophy," and that's the end of the conversation. But you've mentioned the role of metaphysics, epistemology, logic, all of which, can you talk a little bit about how those, beyond just I think a lot of people think about logic and OWL and all that stuff, but can you talk a little bit more about the role of metaphysics and epistemology and these other philosophical ideas?
Casey:
Yeah, definitely. You mentioned this in the pre-notes, "Here's a topic we'd like to get to," and I got into a lot of imposter syndrome on this, right? I'm trying to talk myself out of this, but I think most ontologists have this feeling there's no solid easy pipeline into becoming an ontologist, right? It's a very eclectic group of us. My background's in philosophy, you run into a bunch of librarians, you've got computer scientists who do DB administration, you've got jazz musicians I've run into, it's a weird group.
Casey:
I say that just to be, sometimes when I get asked about, "Okay, how does ontological practice work?" I think, well, I didn't actually train to be an ontologist. I fell into it, so I'm ill-equipped to say things about what role ontology or philosophy plays in ontology.
Casey:
I just know I learned philosophy, and then I'm using some of those tools here, so there's two different answers. One is historically, how does philosophy inform and shape the nature of ontology practice? And the other part is just, okay, if you've got a philosophical toolkit of metaphysics and epistemology and logic, how does that apply and make you a better, I mean, the obvious connection is that ontology is a philosophical term. It comes from metaphysics. We look back to Aristotle, and it's the study of that which exists, so do we want to say there's fundamentally fire, air, earth, water or something like that? Or fundamentally, there are these atoms and those are the sorts of things that are part of the inventory of reality. It's not physics, it's metaphysics. It's the thing that in I think for Aristotle is just, it's the book that sits next to his physics in all of his category, in his library of everything.
Casey:
But when we move that forward to computer science and data modeling, then we're thinking, okay, maybe not for all of reality, although maybe it depends on how big you want your data model to be. But if I'm a retailer, what are the terms and ontology, what are the terms that I care about, the things that I need to model the constituents of reality that matter to me? That might be types, if you're Amazon, it's okay, medium-sized dry goods versus sporting equipment versus something else. If I'm doing a medical ontology, it's patients and payers and providers, et cetera. In philosophy, in ontology, there's a bunch of different tools and examples, but we think about, okay, what are some fundamental distinctions that we want to make? How can we carve nature at its joints in really sensible ways? That's a phrase that you'll hear a lot. We could say more about it if you want.
Casey:
But what I found is being a philosopher goes into an ontology space is that I have this inventory of examples from all of my grad seminars and various things that I'm looking through and going through whether I want to talk about gavagai and undetached rabbit parts, if that makes sense to anybody, or whether I want to talk about grue as a color, here are some examples, ways that we can chop up the world in unnatural ways versus chopping it up in natural ways and how do we make those distinctions? That applies straightforwardly when you get into building an ontology model for an oil and gas industry or something like that. There's a bunch of ways that we can divvy up all the things you care about, what's the right and sensible way to do it?
Casey:
I guess that's the metaphysics, ontology way. Logic you mentioned, right? We need to think about reasoning. I don't just want to assert a bunch of things about my data. A fundamental premise of an ontology is that we want to understand our data, we want to confer meaning on it, and that means that we have to be able to leverage the structure of the ontology to infer things smartly. Simple things like set containment are fine if all persons are animals, and then we say something about animals, they're creatures. Then when I say that persons are a subclass of that, then I get for free that persons are spatio-temporal things as well. But we get a lot more complicated inferences as we go. We have to think about statistical reasoning. Just in general, if logic is the study of what makes for good arguments, what follows from what, that's obviously got a lot of applications in ontology, AI.
Casey:
And then the third piece that we talked about is epistemology. Epistemology is the study of knowledge and belief, roughly about what it means to be justified. The classic example there is, if I know something, what exactly does that amount to? And then Plato says it's justified true beliefs. And then the history of epistemology is littered with examples of trying to cash out exactly what does it mean to be justified. And if you get new information, how can that undercut your justifications? How do you update your beliefs?
Casey:
More recent stuff, and this is what I did in my dissertation,
Ontology engineering has its roots in the idea of ontology as defined by classical philosophers.
Casey Hart sees many other connections between professional ontology practice and the academic discipline of philosophy and shows how concepts like epistemology, metaphysics, and rhetoric are relevant to both knowledge graphs and AI technology in general.
We talked about:
his work as a lead ontologist at Ford and as an ontology consultant
his academic background in philosophy
the variety of pathways into ontology practice
the philosophical principles like metaphysics, epistemology, and logic that inform the practice of ontology
his history with the the Cyc project and employment at Cycorp
how he re-uses classes like "category" and similar concepts from upper ontologies like gist
his definition of "AI" - including his assertion that we should use term to talk about a practice, not a particular technology
his reminder that ontologies are models and like all models can oversimplify reality
Casey's bio
Casey Hart is the lead ontologist for Ford, runs an ontology consultancy, and pilots a growing YouTube channel. He is enthusiastic about philosophy and ontology evangelism. After earning his PhD in philosophy from the University of Wisconsin-Madison (specializing in epistemology and the philosophy of science), he found himself in the private sector at Cycorp. Along his professional career, he has worked in several domains: healthcare, oil & gas, automotive, climate science, agriculture, and retail, among others. Casey believes strongly that ontology should be fun, accessible, resemble what is being modelled, and just as complex as it needs to be.
He lives in the Pacific Northwest with his wife and three daughters and a few farm animals.
Connect with Casey online
ontologyexplained at gmail dot com
Ontology Explained YouTube channel
Video
Here’s the video version of our conversation:
https://youtu.be/siqwNncPPBw
Podcast intro transcript
This is the Knowledge Graph Insights podcast, episode number 38. When the subject of philosophy comes up in relation to ontology practice, it's typically cited as the origin of the term, and then the subject is dropped. Casey Hart sees many other connections between ontology practice and it its philosophical roots. In addition to logic as the foundation of OWL, he shows how philosophy concepts like epistemology, metaphysics, and rhetoric are relevant to both knowledge graphs and AI technology in general.
Interview transcript
Larry:
Hi, everyone. Welcome to episode number 38 of the Knowledge Graph Insights podcast. I am really delighted today to welcome to the show Casey Hart. Casey has a really cool YouTube channel on the philosophy behind ontology engineering and ontology practice. Casey is currently an ontologist at Ford, the motor car company. So welcome Casey, tell the folks a little bit more about what you're up to these days.
Casey:
Hi. Thanks, Larry. I'm super excited to be here. I've listened to the podcast, and man, your intro sounds so smooth. I was like, "I wonder how many edits that takes." No, you just fire them off, that's beautiful.
Casey:
Yeah, so like you said, these days I'm the ontologist at Ford, so building out data models for sensor data and vehicle information, all those sorts of fun things. I am also working as a consultant. I've got a couple of different startup healthcare companies and some cybersecurity stuff, little things around the edge. I love evangelizing ontology, talking about it and thinking about it. And as you mentioned for the YouTube channel, that's been my creative outlet. My background is in philosophy and I was interested in, I got my PhD in philosophy, I was going to teach it. You write lots of papers, those sorts of things, and I miss that to some extent getting out into industry, and that's been my way back in to, all right, come up with an idea, try and distill it, think about objections, put it together, and so I'm really enjoying that lately.
Larry:
And I'm enjoying the video-
Casey:
Glad to be on the show.
Larry:
Yeah, no, I really appreciate what you're doing there. One thing I wanted to, and I love that that's how you're getting back to both your philosophical roots, but also part of it is to evangelize ontology practice, which is that's what this podcast is all about, democratizing and sharing practice. But I think, and I just love that you have this explicit and strong philosophical foundation and bent to how you talk about things. I think a lot of times that conversation is like, "Yeah, ontology comes out of philosophy," and that's the end of the conversation. But you've mentioned the role of metaphysics, epistemology, logic, all of which, can you talk a little bit about how those, beyond just I think a lot of people think about logic and OWL and all that stuff, but can you talk a little bit more about the role of metaphysics and epistemology and these other philosophical ideas?
Casey:
Yeah, definitely. You mentioned this in the pre-notes, "Here's a topic we'd like to get to," and I got into a lot of imposter syndrome on this, right? I'm trying to talk myself out of this, but I think most ontologists have this feeling there's no solid easy pipeline into becoming an ontologist, right? It's a very eclectic group of us. My background's in philosophy, you run into a bunch of librarians, you've got computer scientists who do DB administration, you've got jazz musicians I've run into, it's a weird group.
Casey:
I say that just to be, sometimes when I get asked about, "Okay, how does ontological practice work?" I think, well, I didn't actually train to be an ontologist. I fell into it, so I'm ill-equipped to say things about what role ontology or philosophy plays in ontology.
Casey:
I just know I learned philosophy, and then I'm using some of those tools here, so there's two different answers. One is historically, how does philosophy inform and shape the nature of ontology practice? And the other part is just, okay, if you've got a philosophical toolkit of metaphysics and epistemology and logic, how does that apply and make you a better, I mean, the obvious connection is that ontology is a philosophical term. It comes from metaphysics. We look back to Aristotle, and it's the study of that which exists, so do we want to say there's fundamentally fire, air, earth, water or something like that? Or fundamentally, there are these atoms and those are the sorts of things that are part of the inventory of reality. It's not physics, it's metaphysics. It's the thing that in I think for Aristotle is just, it's the book that sits next to his physics in all of his category, in his library of everything.
Casey:
But when we move that forward to computer science and data modeling, then we're thinking, okay, maybe not for all of reality, although maybe it depends on how big you want your data model to be. But if I'm a retailer, what are the terms and ontology, what are the terms that I care about, the things that I need to model the constituents of reality that matter to me? That might be types, if you're Amazon, it's okay, medium-sized dry goods versus sporting equipment versus something else. If I'm doing a medical ontology, it's patients and payers and providers, et cetera. In philosophy, in ontology, there's a bunch of different tools and examples, but we think about, okay, what are some fundamental distinctions that we want to make? How can we carve nature at its joints in really sensible ways? That's a phrase that you'll hear a lot. We could say more about it if you want.
Casey:
But what I found is being a philosopher goes into an ontology space is that I have this inventory of examples from all of my grad seminars and various things that I'm looking through and going through whether I want to talk about gavagai and undetached rabbit parts, if that makes sense to anybody, or whether I want to talk about grue as a color, here are some examples, ways that we can chop up the world in unnatural ways versus chopping it up in natural ways and how do we make those distinctions? That applies straightforwardly when you get into building an ontology model for an oil and gas industry or something like that. There's a bunch of ways that we can divvy up all the things you care about, what's the right and sensible way to do it?
Casey:
I guess that's the metaphysics, ontology way. Logic you mentioned, right? We need to think about reasoning. I don't just want to assert a bunch of things about my data. A fundamental premise of an ontology is that we want to understand our data, we want to confer meaning on it, and that means that we have to be able to leverage the structure of the ontology to infer things smartly. Simple things like set containment are fine if all persons are animals, and then we say something about animals, they're creatures. Then when I say that persons are a subclass of that, then I get for free that persons are spatio-temporal things as well. But we get a lot more complicated inferences as we go. We have to think about statistical reasoning. Just in general, if logic is the study of what makes for good arguments, what follows from what, that's obviously got a lot of applications in ontology, AI.
Casey:
And then the third piece that we talked about is epistemology. Epistemology is the study of knowledge and belief, roughly about what it means to be justified. The classic example there is, if I know something, what exactly does that amount to? And then Plato says it's justified true beliefs. And then the history of epistemology is littered with examples of trying to cash out exactly what does it mean to be justified. And if you get new information, how can that undercut your justifications? How do you update your beliefs?
Casey:
More recent stuff, and this is what I did in my dissertation,
In God we trust