Language as we know it is messy and divisive. To transform it into a truly unifying factor, we need to create a new taxonomy that gets everyone on the same page. In this conversation with Warren Whitlock, copy director, writer and philosopher, Tomo Albanese argues that emerging technologies like machine learning, artificial intelligence and nanotechnology have the potential to help bring us closer to that reality. How exactly is this going to occur? Does this mean we are relinquishing our expression to machines? What does it mean for the future of contracts and agreements? Listen as Warren and Tomo engage in a deeply philosophical discussion about these questions and learn just how emerging technologies may hold the secrets to world peace.
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A New Taxonomy For The Future With Tomo Albanese
How Emerging Technologies May Just Bring World Peace
I’m here with my special guest, Tomo Albanese. We’re talking about the taxonomy of the future. They call it a weird topic. You might wonder, “What the heck are these guys talking about?” Tomo is a friend. He runs a writing service for content on the internet of WordsRWeapons, and does all interesting projects. We’ve worked together several times over the past decade-plus. One thing I could tell you for sure is he’s smart. He’s also sometimes out there a bit. Welcome to the show, Tomo.
Thanks for having me, Warren. I hope not to take you and your audience too far afield and we’ll keep it grounded in the here and now.
Some of the philosophical ideas behind what we’re talking about could go on for hours but I want to get at the basics. First of all, taxonomy being a word that I know but wasn’t a big fan of. It’s not a word I would use a lot until I started talking to you about this and it fits perfectly but let’s make sure, for the audience and for me, what’s your definition of taxonomy and how has that a foundation.
Foundation is a great word to be using when we’re talking about what a taxonomy is because it helps to ground us in utility. That should be at the forefront of what we’re thinking about. Taxonomy means categorization. To define what taxonomy is and why it’s irrelevant for this, it’s a form of categorization that allows us to establish the foundation for common ground. That’s important when we’re talking about language because if we’re talking about anything, it’s got to be something that matters to the people that are talking about it. Otherwise, what is the point of trying to get people to understand each other? Taxonomy is incredibly important because it’s how we’re talking about the categorization of the words that we’re using. How do we define the language itself to define reality?
I’m already thinking of several ways to go on. For instance, every word we use becomes something we have a discussion on. Foundation is that don’t build your foundation on sand. We could go off on discussing the actual metaphors of these things but let’s not go there. Let’s get right into what our audience wants to know. Why now? Why is emerging technology going to make this happen that we can take the mess which is our language? This does go beyond English but you and I, as English speakers, that’s our common ground, we’ll stick to that for now. How are we going to be able to take this mess, a jumble of words, and dictionary that’s only alphabetized doesn’t show you how words go together? How are we going to be able to do that better with the emerging technology?
What emerging technology solves is foundational to the core problem of why we don’t have a synthesized taxonomy of language and it comes down to complexity. Language describes the reality which is incredibly complicated. We’ve got 437 different ways of saying whether a house burned up or down, or you burned down to its foundations, what have you. That’s how complicated life itself is. To be able to deal with the incredible number of variables that are being put forth every single time, one individual is talking to another individual especially across time and space where we’re talking about reading the past or reading what somebody else is writing in another language in another region. We’re talking about finding what is common that needed to be expressed via language that allowed it to be ordered in some way where it can make sense and then be translated. This is exactly what machine learning can handle, looking for these patterns of what is concurrent, how they’re relevant, how they’re being used and how they’re possibly being expressed.
Any word has different roots of where it came about. It’s possible that a tribe 50 miles away from me may have a whole different way of describing the same things we encounter. I don’t think that that one guy said, “Fire would be a good idea.” Another guy said, “The wheel will be a good idea,” and we built from there. No. Several people were trying a whole lot of different things that became the wheel and fire existed before someone learned how to start a fire. It’s easy to imagine it happen to a lot of places and we’ve done well with some things. We commonly “know” that the Wright brothers invented the airplane. If you get into history at all, there’s a lot more to it.
There was a competition. There was somebody much better funded, had the government backing, and things like that. These guys maybe were the first ones to get off the ground. The story we know is the Wright brothers got off the ground and they were instrumental in the history but that history could have been a little bit different than we would still be flying on airplanes. That’s an easy one to remember because my grandparents were alive for that and even though what we’re going a little over 100 years now, there are things that we have a good history of. When we find out that the other guys were working on things, there was somebody in France and England, they didn’t talk to each other every day because they didn’t have email or Skype.
Did they influence each other? Probably, but it was an idea whose time came, the man wanted to fly and we got it. We take that example and apply it to just about anything. Once we’ve connected the whole world, it makes sense that we should try to all and get on the same page or whatever metaphor you use because pages weird. A hundred years from now, it won’t be what happens on the same page. Every TV show or whatever I see said in the future. I watched one where they were going to Mars and everybody had a book, photos they hang up in their cabin, and things that were very much the way that we picture how life is now but is funny.
It will be above the scroll instead of above the fold at some point.
New Taxonomy: Taxonomy is incredibly important because it is the categorization of the words that we use to define reality.
Digital picture frames have been clunky to date but when we can have something that’s a lightweight, transparent screen that we can paste on the wall, carry it with you, roll it up. There’s no reason to keep that one special picture of your children. You can take them all with you when you go to Mars assuming that Mars has to be somewhere in the future. We don’t know what the future’s going to hold but we can get together with the things that are past, present, and trying to redefine things. What I love about what you said though, we’re talking about finding common ground rather than splitting people apart where I go in say the president’s name and half my audience hates me. It doesn’t matter what else I say, just the word. They’ve already got these preconceived notions.
Language is going to be divisive because it’s inherently reductive. That’s one of the reasons why we need to have a way of enmeshing how our language is evolving with technology in general because what we’re doing with language is we’re rhetorically slicing apart reality but using a scalpel from our own perspective. We’re only slicing it apart as we see it. We’re not slicing it apart necessarily the way that the other person is looking at it from another person’s perspective, it could look like we’re butchering the poor thing rather than dissecting it.
I want to be careful not to get too far into the examples of this. We’ll end up triggering each other, let alone the whole audience with words and phrases we use from common events. You did mention before that machine learning can help with this. Are we going to let the machines tell us what the meaning of something is?
No, a far from it. Machines are tools. They help us shape reality. Does the radar tell a pilot how they should fly? Does the radar tell the pilot how not to crash? All that these machines will be able to do it with us with in terms of language by giving us a common framework for how our language is shifting, how language is being used, and what it’s referring to so that we can get more precise about the general ways we tend to differ around certain words and our relationships with them.
Radar can help you figure out what your path is going to be but it can’t tell you, you have to go a certain way.
It doesn’t tell you the path is worth traveling.
We do a lot more when they’re able to tell you what everything is going to happen. Machine learning knows that these are the possible things that can happen with a storm and plan out 4,000 different scenarios of what might happen on a plane trip. Autopilot is taking care of a lot of that already. It may be a while before I want to get on a plane without a pilot. A car without a driver, for sure, I got no problem there. Generally, I’m the guy who says planes are safer than travel on the road but there’s something about not having anyone in the plane in case this crew comes out.
Something that you know will be able to understand the importance of what it is that you’re saying. This is why communication, to me, always comes down to this. What we’re concerned with at the end of the day is when we tell an AI, “We need help. I need help. This is dangerous. This is going to hurt me in some way that matters to me.” We want the AI to be able to understand it as well as a human being. Even somebody with an incredibly low IQ, somebody who’s cognitively impaired, they can recognize when another human being is in distress. When you look at a super-intelligent AI, just because that’s super-intelligent AI is able to examine and predict the future, it doesn’t necessarily have what is necessary to understand what distress is for a particular individual, so how we can parse the language?
It won’t have the emotion ever. Any emotion you assigned to a machine is a fake emotion. They have to emulate emotion and no desire. The machine doesn’t care whether you get to Detroit at the end of the flight or wherever you want it to go. Once we decide that the words being something, phrases mean something, and then we start building that into our contracts. Let’s talk about that. That’s a smart contract. We’ll be able to depend on what the words mean. We’ll be able to go back to the taxonomy. We won’t need a glossary when we sign a three-page lease, a glossary with 3, 4 pages long.
This is the biggest problem. When we’re writing a contract, it’s the same problem that you have if you run into having a magic lamp, you can ask that lamp for anything, and they can grant you three wishes. It can only grant you what you ask for. Sometimes, if you ask for the wrong thing because you’ve asked for what you wanted in the wrong way, you don’t get the results that you’re looking for. That’s the great thing about when we’re dealing with managing language, its variances, and dealing with things like smart contracts. All of a sudden, we’ll be able to have an assignable variance for possible interpretation that allows for reasonable misunderstanding of an agreement. It’s something you could not possibly get to that you only hope for when people are hiring for the best lawyer to spar on their behalf.
Language is bound to be divisive because it is inherently reductive. Share on XThe whole idea of using the attorneys on this is that they’re going to be able to fight in the negotiation of what reality is and then see things from your side because you’re paying them to, but often relying on case law which is a taxonomy of language not near as efficient as what we’re going to be able to build in the future. An attorney can help guide you through all of that by having the knowledge of gone on the path before rather than trying to invent new ways to get around certain aspects.
If I have an agreement with you, I’ve always liked to use the word agreement instead of contract, but there’s a subtle difference there, at least in my usage of it, is that we’re agreeing. The agreement is going to get stronger. If something goes wrong, it’s covered in the agreement. We’re disagreeing if we have to pull out the contract and look at it. We should be able to have the contract take care of that and we set the limits if certain things happen like, “The rent is due and I don’t pay you after many days, we know what’s going to happen.” The same thing about this at a big discussion once about real estate in the future, all the escrow, all the documentation will be in smart contracts.
If a light bulb goes out, the tenant knows he’s got to replace it. If the sconce falls off the wall and it’s one way or another, but that’s already been defined. If there’s a plumbing leak then the plumber is called and we don’t even need to worry about how that is in the contract. The other efficiencies we get from nanotechnology, building stuff fast, we don’t have to worry about a plumbing leak, we build a whole new building. That’s a little farfetched. It’s got way off the topic there. Those things if we know what it is. Imagine closing an escrow with a thumbprint as you reviewed all the things and your attorneys made sure they put in all the right smart contracts and we know then we meet not to argue over the details. We meet to find more common ground. You’re talking about a difference and a lot of ways we go about doing business.
It’s the ways that we relate. Language is about anything, it’s about relationships. You don’t use language with something that’s trying to eat you. You use a spear or you use your feet. That’s how you express yourself. If anything else, in reality, that you’re going to use language with, it’s because you’re attempting to have some relationship or cooperation to solve a mutual problem. It’s only a problem because you both agree that it’s a problem. Otherwise, you both don’t agree it’s a problem we’re solving.
I think about the personal relationships that people drift apart and don’t get along for whatever reason. Often, it’s not anything to do with you cheated and now I’m leaving. It’s not that cut and dry. You’ve done a series of things like, “I never did like the way you squeeze the toothpaste.” They build up and then emotions takeover over time and you go like, “How did I ever get involved with this person?” That happens in friendships. We’re not talking about a romantic relationship.
I have friends that sometimes I wonder like, “Why have I wasted years being this person’s friend?” Generally, that’s because of whatever’s going on at that moment. I think about it and that goes away. I’m a little bit better than this than the norm but I’m sure me too, but I’ve seen in other people were like, “Why are you two people fighting? You both want the same thing.” It’s a big goal there that if it’s a public good in common, you’re not talking about a company coming out with this and profiting every time I use a definition.
It will ultimately be useless to any single company because you would want universal adaptation. It’s about bringing people together in the way that we do it best by using our mouth.
The thing we’ve got to get to is how is this going to happen if a company doesn’t want to do it? Open-source software happens. These things where there’s got to be some governing board or something to start this.
Libraries, cross-disciplinary researchers, and people that want to prove that vaccines cause autism. All of these different people in these different groups with all these competing interests have a system like this in their best interest. If there’s anything that we can say that’s true, it’s that what predicts the future is certainly worth considering as true. When you have a system like this, that’s organizing language in a way where you’re able to look at its parts and its pieces and distill it according to how complex a particular word or an idea is.
What happens is you have a way of being able to visualize how these things correlate whether or not those correlations made accurate predictions. The more of those predictions clustered together around certain types of language and areas, the more credibility something should reasonably have. Instead of us relying on our gut instinct about what that might be based off of our research, however limited into a particular field, we can go ahead and look at it collectively and say, “What it makes sense across all humanity and what’s getting the best results?”
We’ll have the AI helping us there because if we go Wikipedia style and all start putting in entries of what we think a word should mean or what a concept is and object or anything, we’ll be going on going on forever.
The AI would let us know about how much it can help you predict the future. If you use it in a way that’s not useful for helping you predict the future and it’s showing you that you’re predicting the future incorrectly, you would be dumb to keep on using the same wrong thing that’s helping you miss the future.
The psychology of that, that’s a whole another show. I read a book on the history of the Oxford Dictionary. It turned out there was that smart guy, let’s say doctorate of something who had murdered somebody and was in prison. He was a correspondent to the dictionary. It turns out many of the breakthroughs but in describing this tale, they had to talk about the work of putting it together. This is back before we had a dictionary. The work of doing that and the decades it took to put together the Oxford Dictionary. Fast forward now, that doesn’t need to happen. First of all, we have dictionaries. I assume that Watson has read the dictionary so we have a basis there. Is this going to inevitably happen or do we need to put together a movement to make it happen?
It’s better if there’s a movement to make it happen because it will be inevitable that it does happen. You do not want to have the wrong foundation, the wrong taxonomy for language set up, orchestrated, and centralized in a way that creates a monopoly from any one particular group or idea. It’s the diversity of ideas that makes language what it is and make us who we are as individuals. What we need to make sure is that we have a balanced approach towards centralizing how language is organized and categorized in a way that’s useful that doesn’t allow anybody to have an outside influence over limiting how that language can be used.
The word taxonomy has a great one. I double click on the word, a message from you, go look up what the definition is and make sure that jive with what I know with what I think you were saying and what the dictionary says. In the case of that example close, it’s all the same. How have I described this before when I didn’t use taxonomy? I learn something in the process but I find myself doing that in a Kindle reader. You can click on a word, look it up, and you can get a Wikipedia entry. If you get somebody’s name, there’s going to be something about it, historical character or this is the guy that did this. I wonder, “I’ve never got around studying the life of somebody.” I went most of my life without knowing who Richard Feynman was. He worked on the nuclear bombs. He won Nobel Prizes and still stating things that are ahead of us now. The guy has been dead for years.
As I studied his life, I learned new things, new ways of thinking. One of those is a lot of what we’re talking about is going to already be covered someplace and please comment, reach out, talk to us, let’s learn from that. Whatever we built for the future got to be built on that. This is a rare occasion when I wind up talking to a guest and they’re not either selling a product or looking for funding for their startup in this space. That may happen. You and I will start the great taxonomy of the future and put it in company form which is a service system to make it work for the people.
We won’t be like the Oxford Dictionary. We won’t be hiring people and try to figure it out. The way Wikipedia took over from encyclopedias is close to what it is but the infighting that goes on with Wikipedia will go away because there will be a chain. Anybody wants to put a footnote on any entry can and it will be totally available which is in Wikipedia but you get to the point where an editor has to make a decision. Now we’re talking about it’ll be left open. Every word will be a controversial entry on Wikipedia as we learn, grow, and choose whether or not we want to use this to define words in our contracts and whatever else happens in life.
Wikipedia and what occurs with it will play an influence. It will play its role because those conversations don’t end up going away. They become enmeshed in the larger value of what’s happening unless you have people having those discussions, you do not have enough data to properly map the living changes of language as it’s evolving. Our language must change because we’re going to be understanding more about the world and we’re going to be creating new technologies that are going to utterly change the problems that we’re facing and we will find new problems. We are incredibly innovative as a species at finding new problems. That means we’ll find new solutions.
There’s always something new to do. My favorite example of AI is the doctors being able to improve their bedside manner. There’s something about whether or not surgeons, the personality, there’s ever going to be the best for bedside manner. Again, that’s another show. Assuming that the best doctor and we’ve seen studies that show the healing rate goes up however you measure healing rate, there’s a phrase that needs to define. Healing works better when the doctors pay attention. As simple as they touch your body while they’re talking to you. You touch the elbow or put the stethoscope on your chest.
Whatever they do, they give you some reassurance that they are there taking care of you. That’s something that the AI doesn’t do. It may possible because the doctor will have every article on whatever your disease is at his fingertips already analyzed by the AI and come up with these most probable answers. One of the big problems we have in today’s world is the uncertainty. The 2020 world coming apart was all because of the uncertainty of what to do about the virus but we have that in everything. We don’t know what will happen if one candidate is president over the other one.
Language is ultimately about relationships. Share on XIt keeps things interesting. Uncertainty is the problem of perfection but perfection is the problem of boredom. If everything is perfect, everything is going to be boring at some point.
You have to either mess things up or go after some new problem to keep things interesting, new challenges and things like that. Better tools that are going to accelerate.
At least we can create healthier problems for ourselves.
This is a basis for a way that we start talking about all the emerging technology. How do we define it? Is AI a robot coming to kill us? Is it a tool that makes using your cell phone a little easier? The jury is out on whether or not Siri is better because of the AI but it’ll get there. They’re learning a lot faster than you and I can learn as they’re taking all the samples of everything that’s going on in life. We’ll be surprised and we don’t want to leave it to the machine learning to figure this out.
We’ve got to get better at communicating with the machine when we’ve taught it something by mistake. That’s where we get better at.
It’s hard to divorce a machine.
Especially if you’re a chronic saver.
This isn’t working out. I’ve been using the Google machine learning. I’m going to switch over to Amazon because it looks sexier. We’re not going to be able to do that. I’m going to throw away this pencil and pick up a pen. That’s the analogy we have to look at that these are tools and we’re not going to lose everything because we’ve invested in this tool. Again, a topic for another discussion. We’ll have to do this again sometime. We can’t end the show without some plug. Tell us again where we find you and who you’re looking for.
You can find us at WordsRWeapons, www.WordsRWeapons.com.
You help people create content.
New Taxonomy: It’s the diversity of ideas that really makes language what it is.
We help put words into people’s mouths, the ones they want.
Hopefully, ones that are following the taxonomy of the future.
Inevitably so.
It’s a delight talking to you as always, Tomo. I’m Warren Whitlock, WarrenWhitlock.com. Look for me on the internet, say hello, let’s have a discussion, and let’s see if we can get an agreement whether a fight going which is the biggest promise of the world that we live in now that we can be positive, help each other, and find common ground. Until next time. Bye.
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About Tomo Albanese
Copy Director, Writer, and Philosopher in the school of life, Tomo believes that honesty, transparency, and logic should be always balanced with compassion.
