[User] Please transcribe this text

[Assistant] And always left the next morning too. Till I came here. And now I'm talking about a house with as much as three rooms.


[User] Please transcribe this text

[Assistant] And all over the country, most folks are glad of it and are trying to pick up where they left off. But there are some, instead of looking for friends or looking for trouble, I reckon they'll find it.


[User] Please transcribe this text

[Assistant] Listen, I knew how your pa was going to feel when he found out. I've been hoping he'd change so I could tell him other things as well. There's nothing I wanted more than to help him through the winter. I just had to. Get in there, this.


[User] Please transcribe this text

[Assistant] When I signed up with the Union Army, it wasn't for six months, or a year, or even ten. I said I'd stick till we won, and there was peace.


[User] Please transcribe this text

[Assistant] And this country was a good free place for everyone to live in.


[User] Please transcribe this text

[Assistant] We fought because we believed it didn't make any difference in this country what color a man's skin was.


[User] Please transcribe this text

[Assistant] Here we are now, six months later, battling over what color his pants are.


[User] Please transcribe this text

[Assistant] That's what I signed up for. And that's what I'm still fighting for.


[User] Please transcribe this text

[Assistant] That'd be nothing more to want. But we can't leave now, Lissy. I've gotta talk to your pa first. I've done too much to him already.


[User] Please transcribe this text

[Assistant] I wanted to listen ever since that first night, but I couldn't. I just couldn't.


[User] Please transcribe this text

[Assistant] All those nights away from the farm, I dreamed of nothing but being up here. Place all fixed up and you waiting for me as I came up the trail. It's ours, Lissy. Nothing's gonna keep us from having it now.


[User] Please transcribe this text

[Assistant] I couldn't tell you when I first came here, with you feeling the way you did about Northerners. Maybe you won't even believe me now. I hope you won't.


[User] Please transcribe this text

[Assistant] I've been teaching school over to Lorne Widow Croson, about 50 miles north and west of here.


[User] Please transcribe this text

[Assistant] I tell you what, you can teach me how to play that mouth organ.


[User] Please transcribe this text

[Assistant] It wasn't five minutes. We talked a long time. And from that day on, we were closer than any brothers. We ate out of the same tins, shared dry clothes and blankets when it was cold.


[User] Please transcribe this text

[Assistant] Trees were greening up. The earth was warm.


[User] Please transcribe this text

[Assistant] We knew it was just a question of hours before the war would be over. And Ben could think only of getting home. Plow on the earth with a corn and oats.


[User] Please transcribe this text

[Assistant] It was all you. Worrying about the two years without planting. How you've been needing this help.


[User] Please transcribe this text

[Assistant] That's when he asked me. And that's when I promised to come back and help with the work through the first harvest.


[User] Please transcribe this text

[Assistant] And my group is called Xsitu for Extreme Situated Interaction. Interaction située.


[User] Please transcribe this text

[Assistant] And we work with both creative professionals and uhm, we work with people who are involved in safety critical systems. And we develop a bunch of new design methods. Uhm, I have a book that I just gave a tutorial about in uhm,


[User] Please transcribe this text

[Assistant] Uhm, and the idea is that when we work with extreme users, they push the limits of interaction, which is what we're interested in, and extreme environments that push the limits of technology.


[User] Please transcribe this text

[Assistant] Uhm, interaction, collaboration, we have a large project, uhm, projects.


[User] Please transcribe this text

[Assistant] And we want to think about what does it mean to do generative theory.


[User] Please transcribe this text

[Assistant] You have two different things that happen. You have formation of theory, and you have empirical observation.


[User] Please transcribe this text

[Assistant] Formation of theory is often done where you talk about a theory


[User] Please transcribe this text

[Assistant] You test it with an experiment and then you go back and you revise your theory.


[User] Please transcribe this text

[Assistant] And there are a variety of sciences, natural sciences that work that way. So if you're in physics, for example, or if you're in biology, you might have the DNA, the double helix or something. You say, okay, we, we have this idea of how the DNA is structured and we're going to go and do studies of that. And then we're going to go back and revise it based on our empirical understanding.


[User] Please transcribe this text

[Assistant] So in those cases you have things like astrophysics, you have geology, you have, uhm, anthropology. Those are cases where you have to look at the real world and you want to get the richness of the real world. So what's really interesting in HCI


[User] Please transcribe this text

[Assistant] And there are physical properties to this.


[User] Please transcribe this text

[Assistant] And these artifacts that we create is, has to be dealt with in a slightly different way. This is what Herb Simon talks about in the sciences of the artificial. We are doing science, but with respect to created artifacts. They're not things that exist independently of us. They're things that we're involved with. So now what that means is that we have in HCI this theory


[User] Please transcribe this text

[Assistant] Empirical observation, we look at users, we create theories about what should be going, good ways of designing things, and then we actually build technology. And my argument to you, if you're doing research in HCI, is that you should be doing a complete path.


[User] Please transcribe this text

[Assistant] You're in industry. That's fine. That's good. You're just not doing research. And there are people who do things like a lot of AI is going from theory to artifact, theory to artifact. That's one kind of thing. Uhm, there's other people who go from


[User] Please transcribe this text

[Assistant] Observation to design, it's a different thing, but to do research in HCI, I will argue, there will be people who disagree with me, but I will argue that you should do the complete path.


[User] Please transcribe this text

[Assistant] Now, another way of looking at this is that we have a set of design methods, and again, that's what this book is about and the other kinds of things that we do. How do we interview people? How do we do a generative walkthrough? How do we think about gathering information from users and having that influence our designs and then figuring out whether those designs work?


[User] Please transcribe this text

[Assistant] There's a lot of that in HCI and there's a lot of that in UX design.


[User] Please transcribe this text

[Assistant] Some of it more rigorous than others, but basically there's a lot of that. What's often missing is this bit. How do we think about theory and how does that inform our design? How do we do what we call generative theory?


[User] Please transcribe this text

[Assistant] I spent a bunch of time in computer science, spent a little time in management, worked in industry, worked in academia. I've just gone back and forth and worked with lots of different people.


[User] Please transcribe this text

[Assistant] And what I learned in that is that the shape of theory matters and it's different. So we have descriptive theories and that's what you do when you're trying to, you see a phenomenon out there and you want to describe it. And you just want to see if it matches.


[User] Please transcribe this text

[Assistant] Then there's predictive theory, which is I can understand what's happening here, but I can predict what will happen next. And there tends to be a more quantitative element to that, but not always.


[User] Please transcribe this text

[Assistant] What we're talking about is something that's a little bit orthogonal, which is what we call generative theory. The idea is that we have theories that we can take from different places and use them to inform our design. So.


[User] Please transcribe this text

[Assistant] The idea of a generative theory of interaction, which is what's in this paper, is that we take empirical theories that exist outside of HCI. They can come from psychology, sociology, evolutionary biology, you name it.


[User] Please transcribe this text

[Assistant] The problem we generally have is those are broad theories and the researchers who create those theories do not create them with the idea of helping us design artifacts. They just don't. It's not their goal. They want to understand the world. They're natural scientists in that sense, or social scientists, but their goal is to understand the phenomenon.


[User] Please transcribe this text

[Assistant] So what we need to do is we take the next step. We start creating and developing concepts that allow us to articulate what's relevant from those theories that are well established but relevant to HCI.


[User] Please transcribe this text

[Assistant] And then, we create a set of generative principles. These are actionable principles. These are things that we can look at specifically and say, if I follow that principle,


[User] Please transcribe this text

[Assistant] I can take advantage of the knowledge that they've developed in these other fields and apply it to my design. Alright, so how do we do that?


[User] Please transcribe this text

[Assistant] Well, we argue that you can start with existing artifacts and apply an analytical lens, which is to basically take these analytical principles, look at that particular piece of technology, and figure out whether it's even there.


[User] Please transcribe this text

[Assistant] And here, basically, that can help us think about improving an existing system or creating a new one.


[User] Please transcribe this text

[Assistant] And finally, we have a generative lens, which is how can we use these principles to actually create something that's new.


[User] Please transcribe this text

[Assistant] What I'm going to talk about today is Human-Computer Partnerships, which is also another name for


[User] Please transcribe this text

[Assistant] The more precise name is reciprocal co-adaptation, but I'll get to that in a minute. And the grounding theories here are coming out of evolutionary biology. The way species and animals co-adapt. Not co-evolution, co-adaptation, starts with Darwin.


[User] Please transcribe this text

[Assistant] has been elaborated since, and the notion of the adjacent possible, which is in a, in a nutshell, if you imagine you have a single cell organism,


[User] Please transcribe this text

[Assistant] Or maybe I have a nucleus inside. And once I have the idea of multiple ones, then I have what's called the, I've made the adjacent possible bigger. So by having these theories, I can build on the set of things that are possible so that we can make a larger and larger design space for creating this.


[User] Please transcribe this text

[Assistant] I can think about me interacting with this as a tool. And that's basically where we've been historically in human computer interaction. We think about creating interactive tools that we can apply and use to solve different problems for ourselves. And a lot of what we do is create those tools in this field. Another one is the idea that we tell


[User] Please transcribe this text

[Assistant] And finally, there's the notion of computers as a medium for communication among people. Obviously social media is an example of that and uhm, this course is a hybrid course and so some of you are at a distance. That computer is serving as a medium for us to communicate. Even though I can't see you, you can see me.


[User] Please transcribe this text

[Assistant] Simplest way, we can think about how to place this technology with respect to the human being. It can be something that you wear. It can be something that you augment in the object itself. You can also augment the environment. These are all different ways that we can create for doing different styles of interaction.


[User] Please transcribe this text

[Assistant] Now, I'm gonna come in and be rather critical right now about the way that AI research is being done today, which I object to. Not because I don't think that there's some incredible potential for AI, but because the way that the research is done does not think


[User] Please transcribe this text

[Assistant] Enough about the role of the human being. So, a lot of AI systems that we see


[User] Please transcribe this text

[Assistant] So what's happening is the person's replying, oh wait, I mean, you know, dad's interested, sorry, I was in the bathroom, dad's interested in going to dinner tomorrow. Oh, you just took five years off my life. Thank you to autocorrect. All right. The problem that you get here is


[User] Please transcribe this text

[Assistant] Not how clever the algorithm is, but the way it's presented to the user. And it's correcting things for you.


[User] Please transcribe this text

[Assistant] And it's not very smart about people. It doesn't know that that's a stupid thing. There is no such thing as stupid or not stupid for the, on the AI side.


[User] Please transcribe this text

[Assistant] The system is taking control, and it's doing things, and I have to actively shift and say, is that the right thing? And I let it go out, and I'm just a very different role, okay?


[User] Please transcribe this text

[Assistant] So when we're thinking about dealing with AI systems, we have to think about how is that embedded in real world context? How does that make us interact for better or for worse?


[User] Please transcribe this text

[Assistant] And it matters what those errors are. It can help us even something that is 99% right, which these are not.


[User] Please transcribe this text

[Assistant] Now part of the reason for this is the way that machine learning algorithms and all of that stuff work. There's basically the idea is that you


[User] Please transcribe this text

[Assistant] You read your data, you calculate it, you find some patterns, and then you produce the result. And it's very linear. You know, I send you something, calculate, calculate, send it back.


[User] Please transcribe this text

[Assistant] To define the user's role as either a source of data to help your algorithm, because you're getting measured on the quality of your algorithm, not the interaction, the quality of the algorithm. So you want better data for your algorithm, please.


[User] Please transcribe this text

[Assistant] Or a source of error to be resolved. So if you look at people in cryptology or cyber


[User] Please transcribe this text

[Assistant] Cybersecurity. They're the ones who are talking about, you know, the main source of error is the person in the seat, in the chair.


[User] Please transcribe this text

[Assistant] Users as a source of error, really annoying, messes up my algorithm.


[User] Please transcribe this text

[Assistant] But none of those are very productive ways of thinking about it if you're doing an HCI perspective. You really want to think about what is the impact on the user.


[User] Please transcribe this text

[Assistant] So there's a number of things, I won't go into detail on all of this, but basically there are


[User] Please transcribe this text

[Assistant] But there's somebody in Kenya who's working at $2 an hour who is being forced to be in a situation where they're dealing with toxic information. Is that a good balance in terms of


[User] Please transcribe this text

[Assistant] There's other things where, I've studied this a lot, it's the Boeing 737 Max, you may have heard about this, this is the one where they, by the way, how many of you think that aircraft have a lot of AI in the cockpit?


[User] Please transcribe this text

[Assistant] Because the answer is no. Uh-uh. They don't. They really don't. They have to go through a certification process and so on.


[User] Please transcribe this text

[Assistant] They're automated. They are not intelligent.


[User] Please transcribe this text

[Assistant] And when they put in intelligence, like in the MCAS system here, this is basically a detector and you've got the nose of the aircraft going down and if it thinks that it's doing the wrong angle, it pulls the nose down because it thinks you've gone up too high.


[User] Please transcribe this text

[Assistant] Except that it can be wrong. And Boeing did it so it didn't have any replications, just one source of error when it went down.


[User] Please transcribe this text

[Assistant] And you have 14 seconds, the pilot had 14 seconds to fix the problem. And we have two deadly, fatal crashes because of this. So this was AI being introduced with the assumption it's correct, without telling people it existed, without training them.


[User] Please transcribe this text

[Assistant] And it shut down Boeing and those planes for two years and cost, I think, what, $20 billion in fines? Massive, massive error.


[User] Please transcribe this text

[Assistant] As HCI people who are going to sometimes be doing AI yourself and sometimes working with people who do AI, is keep in mind that a different algorithm with the same interaction can produce the same result. So what matters overall is the interaction.


[User] Please transcribe this text

[Assistant] Classic example, uhm, not a classic example, a good example. Think of...


[User] Please transcribe this text

[Assistant] Ship captains going into the harbor and they've got to plot a route into the harbor. And they've got this nice AI system and it comes in and it tells them a route.


[User] Please transcribe this text

[Assistant] And it took them about two weeks before they just said nope, nope, nope, nope. Because what it's doing is de-skilling them. And they don't know why it produced that thing.


[User] Please transcribe this text

[Assistant] Same algorithm, same system, different interaction, slight difference. Now the pilot


[User] Please transcribe this text

[Assistant] Is neither necessary nor sufficient.


[User] Please transcribe this text

[Assistant] There is this notion of human in the loop. Here the idea is...


[User] Please transcribe this text

[Assistant] The perspective from AI is we're going to measure success. If you go to a NeuroOps conference, you're going to be measured on how good is your algorithm. Did it perform better?


[User] Please transcribe this text

[Assistant] And what I suggest we should have is something closer to computer in the loop where we think about the measure of success is, is the human being better off? And that's a critical shift. It's not necessarily fundamentally different in terms of that loop. It's still a loop. Human, computer, human, computer. But it's a different way of thinking about it.


[User] Please transcribe this text

[Assistant] And the fact that people change their behavior over time. And this is starting to get to this idea of human computer partnerships. So there's an interactive loop, and we're responding, the computer is responding to the user's actions, but the user is also responding to what the computer does. Alright.


[User] Please transcribe this text

[Assistant] Now, I want to say one last thing, which is from a research perspective, we are always facing a challenge, which is when we're trying to design a new system, we want to have, give the user the maximal power of expression. Number of different ways of doing things and giving them a powerful way of doing that. Programming languages do this really well.


[User] Please transcribe this text

[Assistant] They're not easy to do, right? Now, what you get in contrast is what's on your phone. This has a lot of buttons, and those are easy to push.


[User] Please transcribe this text

[Assistant] But very low power of expression. So we have this compromise between power of expression and simplicity of interaction. And I would argue that that trade-off is always there.


[User] Please transcribe this text

[Assistant] However, as researchers, we have a challenge, which is, can we move that curve? We can't get rid of the trade-off, but we can move the curve. So we can do things where we keep simple things simple,


[User] Please transcribe this text

[Assistant] And we allow complex things to be possible. And for a system that's this level of complexity,


[User] Please transcribe this text

[Assistant] In terms of power of expression, can I make it simpler or can I add power to something that's that level of simplicity? We have a number of different examples of that in our, uh, you can look on our website if you want to see some examples.


[User] Please transcribe this text

[Assistant] How do we create interactive systems where we have AI integrated? So we want to combine this idea of the computer is a tool. It's an interactive tool that we can manipulate and do things with. And we want to think about how we can use those tools to augment our human capabilities.


[User] Please transcribe this text

[Assistant] Well, I argue that we create these things that we call human-computer partnerships. And the idea is to take advantage of the best features of both. Because human beings and computers are very different. They have some shared skills, but a lot of very different capabilities. So let me think about what do I mean as a metaphor here for what is a partnership.


[User] Please transcribe this text

[Assistant] You say, I wanna go to that place. And say it's been Saturday night and I'm out drinking and I really shouldn't drive. I wanna delegate the driving to somebody else. And so a taxi lets me do that. I can give that control over to somebody else. And I just give them the address and hope that they'll get me there.


[User] Please transcribe this text

[Assistant] By contrast, you have something where you really enjoy.


[User] Please transcribe this text

[Assistant] And I would argue that the metaphor here is one of a horse. So a horse is intelligent, but not the way you're intelligent.


[User] Please transcribe this text

[Assistant] Both of you learn to each other, you adapt to each other, you learn to get better riding the horse, the horse learns to interact with you and learns things from you.


[User] Please transcribe this text

[Assistant] And the idea is can we create partnerships that have some of these characteristics where there's some intelligence.


[User] Please transcribe this text

[Assistant] Human computer partnerships is the marketing term for what we call reciprocal co-adaptation. And co-adaptation, as I mentioned before, comes from evolutionary biology, but it's been applied to how we co-adapt


[User] Please transcribe this text

[Assistant] With technology, not with species and individuals, uh, co-adapting in a...


[User] Please transcribe this text

[Assistant] Well, in evolutionary biology terms. So the idea is that there's four different relationships you can have. I, as a user, can adapt to the technology that's there, which means I adapt my behavior, I learn how the system works.


[User] Please transcribe this text

[Assistant] And if you're in UX design, you're always thinking about, ooh, create the user experience. And it's this very simplistic kind of, okay, that's one thing we'll do, we will let people learn the right thing.


[User] Please transcribe this text

[Assistant] Uhm, actually I realized that I should have had all four, so I'm going to have to say the four and then the other thing that you can do


[User] Please transcribe this text

[Assistant] Is you can adapt the technology. You can appropriate it. You can change it. You can make it different. And so if I have, for example, this water bottle.


[User] Please transcribe this text

[Assistant] It's a phenomenon that happens in, you know, evolutionary terms and on local terms. And the thing is we can take advantage of that. Now that's co-adaptation from the human perspective.


[User] Please transcribe this text

[Assistant] Interestingly, you have the reverse, which is the system can learn from us as users. It can collect data about us and it can figure out things about us and it can modify its behavior according to what we do.


[User] Please transcribe this text

[Assistant] It can adapt us. It can appropriate how we're working and make us do things. Now that could be good.


[User] Please transcribe this text

[Assistant] All I'm doing is touching things, maybe I swipe, I slide, I poke at a menu. It's very, very, very limited interaction. So how could we make interaction much more


[User] Please transcribe this text

[Assistant] The gestures, right? We need to learn them. So, we have this idea of doing progressive feedback, what gesture have I already done, discover what the system understood about what I've already done, and progressive feed forward, which is to identify what's possible.


[User] Please transcribe this text

[Assistant] And here in this example, the width of the path shows me sort of


[User] Please transcribe this text

[Assistant] Unconscious, it does the right thing when I'm not thinking about it, but it also is something that I can be conscious of and I can choose to put my finger down and pause and it will do the right thing. So here we have this example, uhm, this is implemented on a phone and we have a set of things here.


[User] Please transcribe this text

[Assistant] And we can call Alice, so this is this thing here, and you notice that it gets thinner, and then disappears, so this set of options disappears as we get further along in the algorithm. And so, we just go here, and here's somebody doing it with a partial.


[User] Please transcribe this text

[Assistant] So we studied, uh, authors, professional writers, and we discovered as part of our work with them that they like to hear their dialogue.


[User] Please transcribe this text

[Assistant] So the idea here is very simple and it's the same principle that you just saw. Imagine that this is a, there's a little coaster here called the Sonami, my, my, my sound friend. It's a coaster and it detects whether the coffee cup is there or not. So the idea is that when I take a sip of coffee, it means I'm taking a break. And so,


[User] Please transcribe this text

[Assistant] That's a nice time to launch the audio and it plays the sounds in my dialogue. So it's a case of, and I can intentionally do it and play a bunch of them, or I can turn it off, but the idea is that I can maintain my flow of activity and have these lightweight little things that are integrated into the flow of activity.


[User] Please transcribe this text

[Assistant] And here, we can do that in a very explicit way, which is like defining your own commands. So here we have a way of personalizing gestures. And say I didn't like the set of gestures that I saw before, I want to make my own gestures. How would I do that?


[User] Please transcribe this text

[Assistant] We have this compromise that we have to make. There's, from the users perspective, I need to make gestures that I can easily remember. Things that make sense to me.


[User] Please transcribe this text

[Assistant] And the system has to distinguish among these different gestures. And if you think about it, like if I say here's a circle and here's a square,


[User] Please transcribe this text

[Assistant] For me as a human being, I can easily distinguish that. Most algorithms cannot.


[User] Please transcribe this text

[Assistant] But if I make a line like this, or a line like that, the system can easily distinguish those two, but I think of it as just a line, unless I know something about the algorithm.


[User] Please transcribe this text

[Assistant] So we have these things, we have to make it clear to the system and to the user what is an appropriate kind of gesture. So we put a heat map up and we have blue means the gesture has been recognized.


[User] Please transcribe this text

[Assistant] Let's see if we can, yes, if you can adjust the sound a little bit, sorry.


[User] Please transcribe this text

[Assistant] Alright, I think I'll stop there because it's very loud. And this is an example of the gesture going up. It ends in red. That tells me...


[User] Please transcribe this text

[Assistant] Nope, that one's already been taken, but if it goes down and ends in blue, that means it's fine. Okay, there we go, and then go back down. Right, two different gestures.


[User] Please transcribe this text

[Assistant] So, we want to take advantage of the fact that human beings operate in different ways. So if I'm writing on my phone and I write a gesture,


[User] Please transcribe this text

[Assistant] Many of you may know about swipe typing, gesture typing. The idea here is that there are very clever algorithms. Schumann-Schei is the one who did this, uhm, originally. And this idea that if I want to say the word pepper, I can have it go down, go up, go all the way around. All of those are very cleverly identified.


[User] Please transcribe this text

[Assistant] Uhm, in each of these cases you can see those all say the same word.


[User] Please transcribe this text

[Assistant] The alternative is to do what we've done here, which is we keep the recognizer as before, but we also interpret different characteristics of each gesture. We map that onto characteristics of the, uhm,


[User] Please transcribe this text

[Assistant] The final output. So we can do R and G and B, which is curviness, inflation and speed variation. We map onto red, green and blue and we can get the entire set of colors just through gesture. We also map it onto a font.


[User] Please transcribe this text

[Assistant] So you can see here that she's just typing, she's just gesture typing, but she's controlling through how much effort she's putting into it, the output. And you can see, uhm, your...


[User] Please transcribe this text

[Assistant] There's a variety of different things. We've also implemented this in something called command board, which is a way of giving you the power of a command line, um, uh,


[User] Please transcribe this text

[Assistant] I'm doing here, I start writing the word brightness and then I can adjust the brightness. It gives me that. This is a font and I can change the font. I can do a marking menu. We have a variety of different ways of basically using this space here.


[User] Please transcribe this text

[Assistant] As the keyboard entry and here is an output space, but we've made that interactive and so we have this whole way of creating an interactive space.


[User] Please transcribe this text

[Assistant] Alright, I'm gonna not show that. Another one that we've done is working with choreographers and dancers and the idea is that they create professional, they create individual sketches of what they want to do and then we have the ability to do something called notation where we transform their sketches


[User] Please transcribe this text

[Assistant] Into interactive elements that they can manipulate here and, and let's see, so let's see if we can get that working. So here's somebody drawing.


[User] Please transcribe this text

[Assistant] Uhm, and this is the layout of how they would do this on the, uh,


[User] Please transcribe this text

[Assistant] You know, on the floor of the, of the stage and then how they, they operate together and then here are some.


[User] Please transcribe this text

[Assistant] of the choreographers who are actually showing their actual work and we can embed video in there and they can dive in and do various things. So there's lots more to say about that but I will just keep going.


[User] Please transcribe this text

[Assistant] Uhm, if I show a photo with both a dog and a cat, that's noisy and it's ambiguous, and that's a different kind of uncertainty than showing a photo of a completely different animal, which would be a panda. So we have this system, what we're trying to do is get, uhm,


[User] Please transcribe this text

[Assistant] Uhm, so there's an example of showing the training example.


[User] Please transcribe this text

[Assistant] If they then show an example with two cards that are ambiguous, that's a different kind of uncertainty, and there's an example of putting your hand in there, and that's yet another type of uncertainty. So the idea is thinking explicitly about what's going on when a human expert is trying to teach these algorithms, and that's another area that we need to play with.


[User] Please transcribe this text

[Assistant] Alright, another one, the system adapting to the user, the system learning. I'll do this quickly, I hope. Uhm, so we did work with graphic designers and all kinds of different designers working on mood boards. And the idea is to think about how you share agency between the user and the system. This was done before


[User] Please transcribe this text

[Assistant] And in this case we just have a cascade of images and they get to choose different images and look at different things and so on. So that's basically what you would expect. Uhm, and then they're going to create the mood board on the right.


[User] Please transcribe this text

[Assistant] And this is something called semantic collage. This is all part of something called image sense. But this particular bit, as you can see, searching with images, because we found that graphic designers don't like to type things. They like to search with images. They think visually. So we give them the ability to do that. We also give them words back that they can say more of this, less of that.


[User] Please transcribe this text

[Assistant] Uhm, and they can identify elements of the images, reuse their search history.


[User] Please transcribe this text

[Assistant] Alright, the last one is the system can modify the user's behavior. So it's teaching or manipulating the user. Here,


[User] Please transcribe this text

[Assistant] We're using principles that come out of experimental psychology. And the idea here is we worked with a theater company and they built this wonderful, magnificent, uhm, Christmas display that was up in a shopping center for a month and we have a couple of other installations. And the idea is that somebody comes up


[User] Please transcribe this text

[Assistant] And they want to manipulate Santa and make Santa do a particular move.


[User] Please transcribe this text

[Assistant] Now we want to teach them to make the right kind of movement but we don't want to use words and we won't even tell them that they're being manipulated. So, we created this wonderful


[User] Please transcribe this text

[Assistant] This is what it looks like. That's, making that thing go is really fun. So if you're in a shopping center and that's a thing, kids love that.


[User] Please transcribe this text

[Assistant] Get the idea. And then here's Santa just sitting there in the middle and he just sits there and then if you walk up to it, he'll stand up and he'll start following what you're doing and there we go. Alright, so.


[User] Please transcribe this text

[Assistant] And if Santa gets bored because you're not doing something interesting, then he goes back down or he falls through the floor and the whole thing stops. So.


[User] Please transcribe this text

[Assistant] The idea is that we want to find the correct movements through trial and error. And we start out by drawing them in and we mirror their behavior. That gets their attention. So if I go like this, Santa does this and he follows me for up to 30 seconds. But at that point, then Santa starts doing this.


[User] Please transcribe this text

[Assistant] And now what we're doing is taking advantage of something called extinction behavior. So Santa stops paying attention and starts looking bored and wants me to do something else. Now what happens is if you stop getting reinforced for doing something,


[User] Please transcribe this text

[Assistant] And when you've got lots more behavior, then we can shape that behavior. This is exactly what happens. And so what we do now is Santa starts rewarding behavior. So our thing was to try to get people to make their hands over their head to do this. Just random people coming in off the street and within a minute and a half, we get them doing this. That's our goal.


[User] Please transcribe this text

[Assistant] This is mapping whether it's good or bad, and she's doing this. She's a little bit bored, she kept coming back day after day. Uhm, but she knows that Santa will just follow her, so that's like not interesting. Okay, we can do that.


[User] Please transcribe this text

[Assistant] Now she's doing that, but every movement she makes. Now once this comes up, now she knows she's got to start figuring out what kind of movement. And we've got it programmed on the right here. And we're continuing here.


[User] Please transcribe this text

[Assistant] So we're mapping what she's doing. Notice that she's sometimes got her hands above, sometimes not, so it's a little ambiguous.


[User] Please transcribe this text

[Assistant] And then you see virtual one and it starts going. There we go. Alright, uhm.


[User] Please transcribe this text

[Assistant] When we think about how to deal with, uhm, HCI and AI, we need to think about it at different levels of scale and different levels of time.


[User] Please transcribe this text

[Assistant] That is positive, neutral, or negative. And over time that can get better or worse. And we should be tracking that. We should be keeping, uhm, ways of measuring whether these interactions are positive or negative.


[User] Please transcribe this text

[Assistant] And so, we want to think of interaction as a phenomenon that you can study. We want to think about how to measure it, both qualitatively and quantitatively, and think about it in the short, medium, and long term.


[User] Please transcribe this text

[Assistant] And we want to think about how using the same algorithm with a different form of interaction can create a different, more productive and better interaction. And different algorithms can create the same interaction. So we might find simpler and easier algorithms. We don't necessarily need the most costly ones.


[User] Please transcribe this text

[Assistant] Are we trying to just use AI to replace us and we have this wonderful life envisioned by the movie WALL-E, Pixar, everybody's just sitting there drinking their coke. Uhm, not really my thing. Uhm, do we want to have robots that replace us or do we want to think about how do we create


[User] Please transcribe this text

[Assistant] Users spoke in a much simpler way, which made it a whole lot easier for us to interpret what was going on. And it's like the idea that, and that was at the time what they call habitable sub-languages, but the idea is that you create these environments and you can


[User] Please transcribe this text

[Assistant] I don't know, I, I mean, I think you're right. I think we constantly, one of the things that worries me about these chat-based, uh, systems is that we are so


[User] Please transcribe this text

[Assistant] legislate that in some way because I think that we can't understand it all because it's super complicated.


[User] Please transcribe this text

[Assistant] And highly context driven. But I do think we should at least be thinking about interaction as something that is fundamental to what should be legislated and thought about. Yeah.


[User] Please transcribe this text

[Assistant] But I think, I, I feel like I want to appeal to my InfoViz colleagues because there's a certain element of just what is it that you reveal to the user about what's going on. And part of the problem is, like, so for example,


[User] Please transcribe this text

[Assistant] In the Octopocus example, the, the width of the gesture is getting thinner and thinner and then it goes away and that's revealing to the user in a way that the user can understand that the algorithm is saying you're getting further and further away from that being a legitimate gesture.


[User] Please transcribe this text

[Assistant] At the moment in that, but I think you're absolutely right that it's a really critical area to look at.


[User] Please transcribe this text

[Assistant] I don't even know if that would be a good thing if that were a good thing, if it were possible, but it just isn't. But think about the notion of introducing the feature of like.


[User] Please transcribe this text

[Assistant] So if you talk about in psychology terms, it means that, you know, I feel a little bit better. I get to like something or people liked my stuff and that's great. But over time, it creates an addictive behavior and people end up doing things just for the likes and so on.


[User] Please transcribe this text

[Assistant] And you can go down a rabbit hole and we've seen a really large negative effect of that happening.


[User] Please transcribe this text

[Assistant] That was pretty predictable. Any, any, uh, psychologist worth their salt who'd studied this at all would have predicted that, right?


[User] Please transcribe this text

[Assistant] We shouldn't be throwing things out into the world and hoping for the best. We should be trying to at least get some sense based on all that we know from the social sciences, uhm, about making some predictions. And this is why I was talking about different kinds of theory. There's descriptive and predictive and control theory and, and so on. We should be taking advantage of our knowledge to be able to do that.


[User] Please transcribe this text

[Assistant] I completely agree that we're not going to come up with, you know, the perfect solution and anytime you put a complex system out in the world,


[User] Please transcribe this text

[Assistant] They're going to be unforeseen things happening. And actually part of the argument behind code adaptation is that your users are going to adapt your technology.


[User] Please transcribe this text

[Assistant] In ways that you don't expect. My favorite example is the spreadsheet where people, it was originally designed, uh, I think it was Dan Brickman, uh, wanted to save time. He was at Harvard and he didn't want to add up columns of numbers.


[User] Please transcribe this text

[Assistant] Cross-referencing and formulas embedded and then that turned into what if budgeting which completely changed industry in terms of how people do things and then you can do it to run circuits, you can make posters, you can do all kinds of things in a spreadsheet because it's got a structure that we can manipulate and adapt.


[User] Please transcribe this text

[Assistant] And so one of the questions we face when we're building, I didn't talk about this in this talk, but the generative theory thing, the whole thing on instrumental interaction in substrates is about how we build


[User] Please transcribe this text

[Assistant] So, there's lots to be said. I mean, it's a very rich question and there's a lot, I don't know if I've answered it for you, but I think, I think we should be thinking about that and that's the kind of question that HCI as a field should be asking those questions. So, that's good.


[User] Please transcribe this text

[Assistant] Hey, I'm just now leaving. Can I come around later on this evening? Or do you need time?


[User] Please transcribe this text

[Assistant] Dude, you've only got what? Four more left.


[User] Please transcribe this text

[Assistant] Fuck. Yo! Twelve down, four to go, right?


[User] Please transcribe this text

[Assistant] Actually, I'm not so opposed to people doing it as I am like when they do it over and over.


[User] Please transcribe this text

[Assistant] Trying to get to the Colossi temple. Maybe they're from the village that Wanda came from.


[User] Please transcribe this text

[Assistant] And they're like, no, don't let him go. Maybe that's what they're doing.


[User] Please transcribe this text

[Assistant] Just shows up with like, a fucking book in one hoof, and he like, slowly puts on some reading glasses, like,


[User] Please transcribe this text

[Assistant] Horses love to do that shit, don't they? What? Yeah, because they go


[User] Please transcribe this text

[Assistant] Oh, okay, that's real nice of you, dude. I just- I'm glad that you respect your animals that way. He's not real. If you, uh, had a dog- See, that's how-


[User] Please transcribe this text

[Assistant] Yeah, but I think it's a cliff, so you might not want to go that way. This like, this will go out, but yeah, there's like a cliff and it just ends.


[User] Please transcribe this text

[Assistant] Yeah, so I think you wanna, uhm, go around? Alright. I will take the reins of aggro.


[User] Please transcribe this text

[Assistant] Be sure to tip your waitress. Uhhh, spay and neuter your pets, folks. Who said that, Bob Barker? Yea, it was Bob Barker. Yeaah.


[User] Please transcribe this text

[Assistant] Why give them the urges and make them suffer? Subject them to the torture of blue ball in it.


[User] Please transcribe this text

[Assistant] No one knows. Hey, look at that little temple area. That's pretty cool, right? What's going on there? This thing? Yeah.


[User] Please transcribe this text

[Assistant] I love him. A flying leviathan.


[User] Please transcribe this text

[Assistant] He's like a Leviavian. Levavian.


[User] Please transcribe this text

[Assistant] Oh snap, snippety snap. Pop his little gobules. Globules.


[User] Please transcribe this text

[Assistant] I think that'll make him fall, cause I think that was like holding him up. Oh, he's like gasplatters?


[User] Please transcribe this text

[Assistant] They're, they're on his butt. Oh, you're right. Look at how pussy and gross they are. Karen. What?


[User] Please transcribe this text

[Assistant] I'm not grossing you out, the game is grossing you out. Look at how pussy they are. Popping all of his fucking bubbles and shit.


[User] Please transcribe this text

[Assistant] Agro, chill. Chill for a sec. I think you might want to get the, uhm, the glowy parts. I think like the sandy parts are actually like armored.


[User] Please transcribe this text

[Assistant] That's why. It was to teach you. To teach you.


[User] Please transcribe this text

[Assistant] Yeah, well, not when he comes and fuckin' tries to attack you, like right now.


[User] Please transcribe this text

[Assistant] Oh, damn, damn. Yeah, yeah, yeah, yeah. Oh, you gotta lead it, dude. I see. Yeah. Snap! Oh, I thought that was it. I'm so sure. Oh, you got that one.


[User] Please transcribe this text

[Assistant] Well they're vegetarians, so it wouldn't smell that bad. They're vegetarians? Well, you don't see them eating animals, do you? I don't see them eating-


[User] Please transcribe this text

[Assistant] Next time on Game Grumps, we'll experience the true wrath of the flying avian Leviathan. Oh god, he's gonna slice you.


[User] Please transcribe this text

[Assistant] Ah, good morning, Mr. Bumble, sir. Good morning. I've just taken the measure of the two women that died last night. Coffins are looking up, Mr. Sabre. Ah, thank you.


[User] Please transcribe this text

[Assistant] He says his name's Tom White, to your worship. Very well. Where does he live?


[User] Please transcribe this text

[Assistant] Where do you live? Uh, where he can you worship?


[User] Please transcribe this text

[Assistant] As a military leader, Ieyasu was a courageous man who never hesitated in battle.


[User] Please transcribe this text

[Assistant] Everyone was watching to see how the great Ieyasu would ride his horse over this dangerous bridge. To his men's surprise, Ieyasu dismounted.


[User] Please transcribe this text

[Assistant] Took the horse's reins in his hands and carefully led the horse over the bridge to the other side of the river. That's how vigilant he was.


[User] Please transcribe this text

[Assistant] I believe this kind of caution helped him to be victorious in battle.


[User] Please transcribe this text

[Assistant] There's a story about a low ranking samurai who has to meet with him. He also listened attentively.


[User] Please transcribe this text

[Assistant] Lords and vassals, superiors and inferiors, must observe what is proper within their position in life.


[User] Please transcribe this text

[Assistant] Without authorization, no retainer may wear fine white damask, white wadded silk garments, purple silk kimonos, purple silk linings, and kimono sleeves which bear no family crest.


[User] Please transcribe this text

[Assistant] Because you are my descendants, you will become shogun.


[User] Please transcribe this text

[Assistant] As shogun, it is important that you rule the country for the benefit of the people, or you will be punished by heaven.


[User] Please transcribe this text

[Assistant] Any informer revealing the whereabouts of the followers of priests must be rewarded accordingly.


[User] Please transcribe this text

[Assistant] Wives and daughters must make meals three times a day, put on red headbands, and take the meals to the fields.


[User] Please transcribe this text

[Assistant] Sisters-in-law and female cousins must put the chap feet of the man on the stomach of his wife and massage them.


[User] Please transcribe this text

[Assistant] A similar penalty will be suffered by all who come to these shores from Portugal, whether they be ambassadors or sailors, whether they come by error or driven by storm.


[User] Please transcribe this text

[Assistant] They would all pay the very same penalty.


[User] Please transcribe this text

[Assistant] The alien barbarians of the west, the lowly organs of the legs and feet of the world are dashing across the seas, tramping other countries underfoot, and daring with their squinting eyes and limping feet to override the noble nations.


[User] Please transcribe this text

[Assistant] We should build warships. Then if barbarians come to our sea, we should shoot every single one of them.


[User] Please transcribe this text

[Assistant] Their deportment and manner of expressions were exceedingly arrogant, and the resulting insult to our national dignity was not small.


[User] Please transcribe this text

[Assistant] After the barbarians had retired, a certain person drew his sword.


[User] Please transcribe this text

[Assistant] Therefore if we don't drive them away now, the other foreign powers will follow. We are in a dangerous situation.


[User] Please transcribe this text

[Assistant] Fearing that Jamie might get nothing to eat until dinner otherwise. Seated on the grass, watching him eat.


[User] Please transcribe this text

[Assistant] I asked him why he'd been living in the roughs, raiding cattle and thieving over the border.


[User] Please transcribe this text

[Assistant] I had seen enough by now both of the folk that came and went from the nearby village and of the castle dwellers to be able to tell that Jamie was both higher born and much better educated than most.


[User] Please transcribe this text

[Assistant] It seemed likely that he came from a fairly wealthy family, judging from the brief description he had given me of their farm estate. Why was he so far from home? I'm an outlaw, he said, as though surprised that I didn't know.


[User] Please transcribe this text

[Assistant] The English have a price of ten pounds sterling on my head. Not quite so much as a highwayman, he said, deprecatingly, but a bit more than a pickpocket. Just for obstruction, I said unbelievingly.


[User] Please transcribe this text

[Assistant] Ten pounds sterling here was half the yearly income of a small farm.


[User] Please transcribe this text

[Assistant] I couldn't imagine a single escaped prisoner was worth that much to the English government. Och, no! Murder! I choked on a mouthful of bread and pickle.


[User] Please transcribe this text

[Assistant] Jamie pounded me helpfully on the back until I could speak again. Eyes watering, I asked, wh-who did you kill? He shrugged, Well, it's a bit odd.


[User] Please transcribe this text

[Assistant] Didn't it actually kill the man whose murder I'm outlawed for?


[User] Please transcribe this text

[Assistant] Mind you, I've done for a few other redcoats along the way, so I suppose it's not unjust.


[User] Please transcribe this text

[Assistant] He paused and shifted his shoulders, as though rubbing against some invisible wall.


[User] Please transcribe this text

[Assistant] I had noticed him do it before, on my first morning in the castle, when I had doctored him, and seen the marks on his back.


[User] Please transcribe this text

[Assistant] I could hardly move for a day or two after I'd been flogged the second time, and then I had fever from the wounds. Once I could stand again, though, some friends made shift to get me out of the camp, by means I'd best not go into. Anyhow, there was some ruckus as we left, and an English Sergeant Major was shot.


[User] Please transcribe this text

[Assistant] By coincidence, it was the man that gave me the first flogging. Had not a shot him, though.


[User] Please transcribe this text

[Assistant] I had nothing personal against him, and I was too weak to do more than hang on to the horse in any case. The wide mouth tightened and thinned.


[User] Please transcribe this text

[Assistant] Though had it been Captain Randall I expect I'd have made the effort. He eased his shoulders again, stretching the rough linen shirt taut across his back, and shrugged. There it is, though. That's one reason I do not go far from the castle alone.


[User] Please transcribe this text

[Assistant] This far into the Highlands there's little chance of running into an English patrol, but they do come over the border quite often. And then there's the Watch, though they'll not come near the castle either.


[User] Please transcribe this text

[Assistant] Colum's not much need of their services having his own men to hand. He smiled.


[User] Please transcribe this text

[Assistant] Running a hand through his bright cropped hair, till it stood on end like porcupine quills.


[User] Please transcribe this text

[Assistant] On Oliver's ninth birthday, Mr. Bumble the Beadle came to the house to see Mrs. Mann.


[User] Please transcribe this text

[Assistant] It was always kept locked to prevent official visitors walking in unexpectedly.


[User] Please transcribe this text

[Assistant] I have business to talk about," Mr. Bumble told Mrs. Mann as he entered the house.


[User] Please transcribe this text

[Assistant] He was a big fat man, often bad-tempered, and was full of self-importance. He did not like to be kept waiting at a locked gate.


[User] Please transcribe this text

[Assistant] Mrs Mann took his hat and coat, placed a chair for him, and expressed great concern for his comfort.


[User] Please transcribe this text

[Assistant] You've had a long walk, Mr. Bumble," she said, and you must be thirsty. She took out a bottle from the cupboard. No, thank you, Mrs. Mann, not a drop. He waved the bottle away.


[User] Please transcribe this text

[Assistant] Just a little drop, Mr. Bumble, with cold water," said Mrs. Mann persuasively.


[User] Please transcribe this text

[Assistant] The samurai would work only in the morning and then go home for lunch. At around two o'clock in the afternoon, they would go out on the town.


[User] Please transcribe this text

[Assistant] To Edo people, the Kabuki actors were like Hollywood stars.


[User] Please transcribe this text

[Assistant] The fans would collect woodblock prints of their favorite actors, not only for the fun of collecting them.


[User] Please transcribe this text

[Assistant] If the fans really liked a certain style or design, in a flash, it would become the newest fashion trend.


[User] Please transcribe this text

[Assistant] None except God for his own record while he lived. He could do nothing dishonorable.


[User] Please transcribe this text

[Assistant] There's so many people in the cast, and uh, we're talking to Kent last night about how, you know, there are certain people that you don't realize, characters that have never been in scenes together, that are major characters, and it's kind of weird when you think about it because you're all in the same show together, but who do you hang around with the most when it comes first off camera goes?


[User] Please transcribe this text

[Assistant] Hi, I'm Jimmy Kimmel. If you like that, click the subscribe button below and good things will happen forever.


[User] Please transcribe this text

[Assistant] Kya bataa hoon? Tume dekhe mera dil chahta hai ke?


[User] Please transcribe this text

[Assistant] Saath toh tumhe dena hi hoga. Agar tumhe mera saath chahiye tum.


[User] Please transcribe this text

[Assistant] Okay Fatima, stop it. Leave it.


[User] Please transcribe this text

[Assistant] Leaving the picnic basket in the kitchens, I returned to the late, beaten surgery, now dustless and pristine after a visitation by Mrs. Fitz's energetic assistants.


[User] Please transcribe this text

[Assistant] Even the dozens of glass vials in the cupboard gleamed in the dim light from the window.


[User] Please transcribe this text

[Assistant] The cupboard seemed a good place to start, with an inventory of the herbs and medicaments already on hand.


[User] Please transcribe this text

[Assistant] I had spent a few moments the night before, before sleepover came me.


[User] Please transcribe this text

[Assistant] Thumbing through the blue leather bound book I had taken from the surgery.


[User] Please transcribe this text

[Assistant] This proved to be the physician's guide and handbook.


[User] Please transcribe this text

[Assistant] A listing of recipes for the treatment of assorted symptoms and diseases.


[User] Please transcribe this text

[Assistant] The ingredients for which were apparently displayed before me.


[User] Please transcribe this text

[Assistant] The book was divided into several sections, Centuries, Vomitories, and Electuaries, Trokes and Lodox, Assorted Plasters and their Virtues, Decoctions and Theriacs,


[User] Please transcribe this text

[Assistant] And a quite extensive section ominously headed with the single word purges.


[User] Please transcribe this text

[Assistant] Reading through a few of the recipes, the reason for the late Davey Beaton's lack of success with his patients became apparent. For headache, read one entry.


[User] Please transcribe this text

[Assistant] Take ye one ball of horse dung, this to be carefully dried, pounded to powder, and the whole drunk stirred into hot ale.


[User] Please transcribe this text

[Assistant] Decoctions made of the roots of selendine, tumeric.


[User] Please transcribe this text

[Assistant] And juice of 200 slaters cannot but be of great service in a case of jaundice.


[User] Please transcribe this text

[Assistant] I close the book, marvelling at the large number of the late doctor's patients who, according to his meticulous log, had not only survived the treatment meted out to them, but actually recovered from their original ailments.


[User] Please transcribe this text

[Assistant] There was a large brown glass jar in the front containing several suspicious looking balls, and in view of Beaton's recipes, I had a good idea what it might be.


[User] Please transcribe this text

[Assistant] Turning it around, I triumphantly read the hand-lettered label. Dung of horses.


[User] Please transcribe this text

[Assistant] Reflecting that such a substance likely didn't improve much with keeping, I gingerly set the jar aside without opening it.


[User] Please transcribe this text

[Assistant] Subsequent investigation proved pearly's ovus to be a latinate version of a similar substance, this time from sheep.


[User] Please transcribe this text

[Assistant] Mouse ear also proved to be animal in nature, rather than herbal.


[User] Please transcribe this text

[Assistant] I pushed aside the vial of tiny pinkish dried ears with a small shudder.


[User] Please transcribe this text

[Assistant] I had been wondering about the slaters, spelled variously as slatters, splaters, and slate ears, which seemed to be an important ingredient in a number of medicines.


[User] Please transcribe this text

[Assistant] So I was pleased to see a clear cork stopper vial with this name on the label.


[User] Please transcribe this text

[Assistant] The vial was about half full of what appeared to be small grey pills. These were no more than a quarter inch in diameter.


[User] Please transcribe this text

[Assistant] And so perfectly round that I marvelled at Beaton's dispensing skill.


[User] Please transcribe this text

[Assistant] I brought the vial up close to my face, wondering at its likeness.


[User] Please transcribe this text

[Assistant] Then I saw the fine striations across each pill, and the microscopic legs folded into the central crease.


[User] Please transcribe this text

[Assistant] I hastily set the vial down, wiping my hand on my apron.


[User] Please transcribe this text

[Assistant] And made another entry in the mental list I'd been compiling. For slaters, read Woodlice.


[User] Please transcribe this text

[Assistant] There were a number of more or less harmless substances in Beaton's jars.


[User] Please transcribe this text

[Assistant] As well as several containing dried herbs or extractions that might actually be helpful.


[User] Please transcribe this text

[Assistant] I found some of the oris root powder and aromatic vinegar that Mrs. Fitz had used to treat Jamie McTavish's injuries.


[User] Please transcribe this text

[Assistant] But it proved to be nothing more than the tender tips of fir branches.


[User] Please transcribe this text

[Assistant] And a pleasant balsamic fragrance floated out of the unsealed bottle.


[User] Please transcribe this text

[Assistant] And set it on the table to perfume the air in the dark little room as I went on with my inventory.


[User] Please transcribe this text

[Assistant] People are writing these Dear Ivanka letters on social media and leaving them outside of a Kushner-owned building in Manhattan. I think it makes people feel like they have someone in that Trump orbit who, at least, she's a former Democrat.


[User] Please transcribe this text

[Assistant] So I don't see us getting hooker in the 29th pick in the first round. I just don't see it.


[User] Please transcribe this text

[Assistant] From the philosophical, Buddhist philosophical perspective are all resultant states of a person consistently trying to look at what is not true.


[User] Please transcribe this text

[Assistant] We talk about three fundamental truths. That things are impermanent.


[User] Please transcribe this text

[Assistant] Secondly, the fundamental principle of everything is said to be emptiness.


[User] Please transcribe this text

[Assistant] Build something that makes us forget about this. We try to make things permanent. And that struggle creates the third truth of this suffering. We begin to then hang on to things. I'll give you an example. You know, if I have a shirt,


[User] Please transcribe this text

[Assistant] And every time I go out to do some shopping, you buy another shirt. You may have 12 in your closet, but you'll buy the 13th just so that you have a sense of


[User] Please transcribe this text

[Assistant] You'll live long enough to wear all 13 shorts, or perhaps even more than that.


[User] Please transcribe this text

[Assistant] So there's a sense of everyday consistently doing something because of which we may be able to more solidify.


[User] Please transcribe this text

[Assistant] Consistently builds up all these neuroses and the prominent one of them becomes the greed.


[User] Please transcribe this text

[Assistant] I think the key for the material society is that it will always tell you that there's something missing. You need something else.


[User] Please transcribe this text

[Assistant] Someone who's trying to sell you something. So demand and supply.


[User] Please transcribe this text

[Assistant] You know, we're all sort of supporting each other in it. And we've all gotten into this cycle that we are unable to find ourselves free from.


[User] Please transcribe this text

[Assistant] And by samsara I mean the habitual patterns. And you keep thinking, they're calling me.


[User] Please transcribe this text

[Assistant] No Jumper, coolest podcast in the world and, uh, I'm here with Injury Reserve and they're eating gummy bears, sour gummy bears.


[User] Please transcribe this text

[Assistant] Crazy. Crazy with durags on. Durags, crown, royal, and sour gummy bears. That's what we're working with tonight.


[User] Please transcribe this text

[Assistant] So we should go through the, uh, the names here first of all. So, Richie with a T, Parker Corey, Stepa.


[User] Please transcribe this text

[Assistant] Do you prefer people to call you Richard with a T, like say it like that all the time?


[User] Please transcribe this text

[Assistant] Okay. Wait, but how do you have two, you're a Richie and an 8? So my last name is Richie. Oh, okay. Yeah, yeah, yeah. But is that kind of your rap name?


[User] Please transcribe this text

[Assistant] I think that's consistent. That's like, consistent branding. Like, if you come on here, like, House Phone got mad about it the other day because we called it Monte on the podcast a bunch of times. It's not Monte. Uhm, but you gotta be conscious of that stuff. Like, I don't know. To me, that consistent branding is very important.


[User] Please transcribe this text

[Assistant] So you don't like buy into the whole idea that you basically have to be like a wrestling performer in order to be a rapper in 2017?


[User] Please transcribe this text

[Assistant] You're Everyman. Yeah, yeah. The Everyman, but I guess you'd pluralize it to the Everyman.


[User] Please transcribe this text

[Assistant] I feel like at this point I accept it so much and I'm so used to people playing these crazy characters, but I remember a friend of mine telling me that he was backstage with Ghostface Killa.


[User] Please transcribe this text

[Assistant] And he was like, yeah, he was just dressed like a totally normal dude. And then right before he went on stage, you like put on the bathrobe, put on all the chains and he's like, he was like, that was weird for me. And I was like, but at the same time, like what you think ghosts, you thought ghostface killer has been hanging out with 10 chains on his whole life.


[User] Please transcribe this text

[Assistant] Yeah, it's weird too because there's been dudes I've had on the podcast that all their lyrics are about killing people and selling crack and then I'm sitting there across from them and I have like questions written down that are sort of like street related questions and I start to think in my head like, it's almost going to seem offensive if I ask this guy about selling crack because it's so obvious that he's never sold crack.


[User] Please transcribe this text

[Assistant] So, you guys wanna get that out of the way? I've never sold crack. What about you? There's been no crack sales. No crack sold. No crack, yea. So what is there to rap about even then?


[User] Please transcribe this text

[Assistant] But I think people want that or at least there's a lane for that within rap for sure. Like if there's the guy who's going to completely lie and say, I just chopped a thousand bricks, et cetera, there's definitely a place for the dude who says something more relatable.


[User] Please transcribe this text

[Assistant] Like you'd have to cancel this interview if I came and called you out on that?


[User] Please transcribe this text

[Assistant] I mean, I'm not gonna test them, they look nice to me. See, I feel, you know what, shoes are just like guns to me, where it's like, okay, if I never, if I don't take photos with guns, if I don't pose with guns, then...


[User] Please transcribe this text

[Assistant] I don't feel like I need a gun. But as soon as you get into the arena, like, yo, I'm a shoe guy, boom, I got 50 dope pairs of shoes, then you gotta start keeping up.


[User] Please transcribe this text

[Assistant] Yeah, because you know, like, it's like you either are that kind of guy or you aren't that kind of guy. And I always kind of feel bad when I see like 16, 17 year old kids and they're around the homie who's got a gun and then they just start posing with the gun. And it's like, you don't want to put yourself in that category because some guy's going to press you.


[User] Please transcribe this text

[Assistant] Uh, drugging a girl in her drink. That wasn't the hip hop journalist calling him out for that because the hip hop journalists are used to hearing Rick Ross say shit like that, used to rappers saying crazy shit like that. It came from outside. I don't know if that's a good thing or not.


[User] Please transcribe this text

[Assistant] Yeah, like if you're on your Instagram stream or lives tomorrow or you know, someone who's like on DJ academics is radar. And I just notice always that like, you know, it'll be a tiny five, 10 second clip from like amigos.


[User] Please transcribe this text

[Assistant] Instagram live stream and boom it's a whole 10 minute video and then Complex has got a video and everybody's got a video over Rich Homie Kwan San like ah fuck that dude, you know, it's like nothing but it's


[User] Please transcribe this text

[Assistant] Yeah, like this is music that actually is speaking the voice of a lot of people who are in positions where they feel like they have to do certain things to get by. So it's, it's kind of, it's just not authentic, I think, to like pretend that, you know, that you should expect the same thing from 21 Savage that you expect from


[User] Please transcribe this text

[Assistant] The president. Although our president is objectively probably worse.


[User] Please transcribe this text

[Assistant] And then what? You were like, I feel like we might work together on a more consistent level.


[User] Please transcribe this text

[Assistant] Do you think you guys are more powerful as a group dynamic than you could be on your own? Are you more than the sum of your parts as they say?


[User] Please transcribe this text

[Assistant] You know, think about when you really have to be that one guy that goes out there and you just have to be this giant personality, but like as a group, you're able to sort of maybe fall back and be a little bit more like have the part that the fans like about you be the unity and the group thing in a way, because that is very relatable in the sense that, you know, people


[User] Please transcribe this text

[Assistant] They relate to groups, you know, people like to join into little cliques. That's just what happens in high school, wherever it is. And like, I don't know, in a way, I guess people could kind of see their own friend group in you guys, I guess, because you are very everyman-esque.


[User] Please transcribe this text

[Assistant] You guys both smoke weed or don't smoke weed? Oh, I'm straight edge. You're totally straight edge. You smoke weed?


[User] Please transcribe this text

[Assistant] Alright, I found out about you guys, the two, two of the most, uh, prevalent tastemakers in the game. Number one, Anthony Fantano. Number two, the no jumper comments section. So.


[User] Please transcribe this text

[Assistant] I thought for a while that injury reserve was a skate crew and then I realized I was confusing it with a legal sieve for a period of time. I'm good, I don't smoke, yeaah.


[User] Please transcribe this text

[Assistant] I don't know, do you feel like, so that's very interesting because you have Anthony Fantano who's clearly, you know, a music industry plant who's been put here by the government to make people listen to weird eclectic indie hip hop.


[User] Please transcribe this text

[Assistant] Just kidding. And then also we have like the streets, the no genre comments section who they knew about XXXtentacles ten years before he actually was even born, they were commenting about him.


[User] Please transcribe this text

[Assistant] Cause I feel like you guys have that die hard like cult probably often local fan base and then you also have a shit load of people writing articles about you like why is Injury Reserve the most talked about hip hop group right now? Like you guys have gotten a surprising amount of media coverage like I don't know what it is that the critics just seem to like see what you guys are doing on a local level and be like that's the shit.


[User] Please transcribe this text

[Assistant] I feel like his production is like almost like dead set on like challenging you as rappers a lot of times where it's like I'm listening to it and I'm like man they got on this beat because it's like a motherfucking obstacle course.


[User] Please transcribe this text

[Assistant] Yeah, and that's why if you listen to like, you listen to an album from a year or two ago, a lot of times you can just hear the beats and it just automatically sounds dated to you because the production even just like advances so constantly, you know?


[User] Please transcribe this text

[Assistant] Yeah, but so okay, do you know exactly when and how Fantano discovered you guys and what was your first reaction when you first saw one of his videos? Was that how you found out about his channel? By the way, we're talking about the needle drop if anybody wants to search his YouTube channel. Get him to a million subs. He's almost there. He's right there. He's right there.


[User] Please transcribe this text

[Assistant] Okay, so you guys are those kind of rap fans, cause you gotta be a pretty in-depth rap fan to care about a critic, nevermind a YouTube critic.


[User] Please transcribe this text

[Assistant] Wait, who else did it? Cause someone did do something similar, didn't they? Uhm, dumbfounded did it. Oh, yumjake did one, didn't he?


[User] Please transcribe this text

[Assistant] It pays to play with the aspect ratio. I mean, now you see all the Snapchat stories, I don't even, I haven't watched one of them in years, but the fucking thing where you can watch videos from Vice and MTV and everything, you have to like format it to that, that, it's interesting.


[User] Please transcribe this text

[Assistant] You guys are probably such nerdy Fantana fans that you know about the second channel too, huh? The meme channel? Okay, you fan of that?


[User] Please transcribe this text

[Assistant] I'm down. I like him. I think he's cool. It always weirds me out that like I meet people in the music industry that are like, that think he's like the worst thing that's ever happened to music criticism. And I'm like, I mean, to me it's like, even if you don't like his personality that much, you got to admit that this is a good idea and other people should be doing what he does.


[User] Please transcribe this text

[Assistant] It was weird. I mean, the Zach one was huge at the time. Especially because at that time, people were putting us in the box of like, the cool new Streetwear podcast, which I really don't feel like I kept up on, because I really don't give a shit about that so much. You know, I want, I think it's cool, but it's not like my thing, you know. More of an underground rap fan, I guess you could say.


[User] Please transcribe this text

[Assistant] So, let's talk about Phoenix, and just what the influence is of Phoenix on your sound, and what your crazy fan base is like in Phoenix, but in particular, I've seen these videos of your live shows out there that look pretty wild.


[User] Please transcribe this text

[Assistant] It's just a kind of dull spot. If you're interested in the culture.


[User] Please transcribe this text

[Assistant] That was crazy by the way. Lack of influence. So you feel like the kids out there are what? Sort of like... It has nothing to do with the kids. Okay.


[User] Please transcribe this text

[Assistant] Yeaah. I mean, I think that's cool. Like I said this on the DJ Lucas podcast the other day, but I think it bears repeating is that like, I think a lot of like people from the outside now are not trying to like find the new hip, cool kid in LA who's like the 700th most interesting rapper in LA and like instead go and like look at smaller scenes and be like,


[User] Please transcribe this text

[Assistant] Let's find somebody who's actually like building up an interesting scene around him and even if it's like a hundred kids in a basement show, it's like that's really fucking cool and authentic and builds a scene which is still important regardless of how big hip hop is and it's just cool to see that because then you actually get


[User] Please transcribe this text

[Assistant] Some sort of local flavor because those hundred kids in the basement are going to have a different effect on you as a performer than the, you know, playing shows in LA to the same warehouse to the same 500 kids, you know.


[User] Please transcribe this text

[Assistant] It's crazy like, the way that like hip hop over the years and it's almost like, I feel like hip hop is becoming much bigger now, like this specific moment or like over the last year it's becoming way bigger.


[User] Please transcribe this text

[Assistant] Even when I talk to people at labels, they're like, oh my god, like the charts now, the streaming charts are fucking, they're over 50% rap, all of a sudden pop and EDM are like falling off. And I feel like hip hop is becoming so gigantic that it's almost like splintering off into


[User] Please transcribe this text

[Assistant] Sort of like different genres that nobody has names for because everybody in hip hop tends to dismiss or not have any interest in genre names, like people say mumble rap.


[User] Please transcribe this text

[Assistant] And then it's like, oh, that's like an offensive term, but in, in metal, they embrace that, you know, it's like, oh, this is grind core. This is death core. This is metal core. And it's like, they like the fact that they can segment shit up into different genres. And when I look at what you guys are doing, you, you have a very punk ethos to you. And then you also have like clear punk element into your sound.


[User] Please transcribe this text

[Assistant] And then like even with the live shows and everything. And I see a lot of band, a lot of rap groups that I really think are going in such a specifically punk direction in a way that it's almost becoming something that's really


[User] Please transcribe this text

[Assistant] Removed from like the typical hip hop core when you think about it.


[User] Please transcribe this text

[Assistant] Is so expansive and there's so many different sounds, like so many different sounds are allowed to be hip hop at the same time. So many different types of lyricists and performers and stuff and that is what keeps it eternally going.


[User] Please transcribe this text

[Assistant] EDM, I get dance music to a certain extent, but it just, after a short period of time, I feel like you started to feel like they had kind of pushed to the very boundaries of what the new sounds were going to be with this boring-ass fucking breakdown thing that they do, or drop, whatever the fuck they call it. Whereas with hip-hop, it's like,


[User] Please transcribe this text

[Assistant] Kendrick Lamar is so fucking different than Playboy Cardi in every conceivable way.


[User] Please transcribe this text

[Assistant] And there were no rules to hip hop at that time, so it wasn't like, oh that's not hip hop. It was like, we aren't, they weren't necessarily 100% aware that they were making hip hop. They were making music, they were going by the rules that the music industry and the people in the music world that they knew had, which was like, it's okay for someone to write your shit.


[User] Please transcribe this text

[Assistant] You're talking about the first mixtape, like the one with the fucking bun B feature and everything? No, you're talking about- Uh, no, that was the third. Okay, that to me will always be the best. That was the third.


[User] Please transcribe this text

[Assistant] Because I forgot about those two mixtapes because I went back and listened to those after I found out about the third one. No, because I realized like I downloaded a Wayne and him on the ignorant shit beat, you know, the Jay-Z one. And I was sitting there listening to it and just was like,


[User] Please transcribe this text

[Assistant] This is incredible. And then went home and Googled it and was like, this is the fucking guy from that fucking stupid show my ex girlfriend used to watch all the time.


[User] Please transcribe this text

[Assistant] What are you telling people when you have a durag in 2017? I feel like it's a very, it's a statement about how true to the culture you are.


[User] Please transcribe this text

[Assistant] Wait, you don't do skinny jeans and shit? Oh no, I got some little iron hearts on me.


[User] Please transcribe this text

[Assistant] That's a lot of what I came from like when I was in like high school and stuff is I was all about hardcore and what's crazy is that the big hardcore crew gang as some people will call it where I grew up on the East Coast is like that's what they were known for is like they beat up the skinheads and made it so that the Nazis couldn't go to shows.


[User] Please transcribe this text

[Assistant] Nobody will beat somebody's ass for you faster than a hardcore kid. They love fighting.


[User] Please transcribe this text

[Assistant] You guys are we gonna fight? With each other? With each other? No. We gotta close.


[User] Please transcribe this text

[Assistant] No, but I was gonna go to this music festival with this girl, and her mom was all stressing out. I'm like, why don't you just tell her you're with me? Like, what the fuck? And she's like, I don't want to tell my mom about you because you guys are the same age.


[User] Please transcribe this text

[Assistant] And I was like, fuck. She was 19 and her mom was 33. I'm like, your mom was fucking way too young.


[User] Please transcribe this text

[Assistant] That was cool, cause she hid me from her mom I guess at that time.


[User] Please transcribe this text

[Assistant] That's what I've been listening to. We've been banging that in the store all day. Like what, what is the progression to like from that album? Like what, what is different about that album from your last album? And maybe after that, you can tell us like where you go from here, musically.


[User] Please transcribe this text

[Assistant] That's gotta be like the thing that is, kinda, stands out a lot about you guys. You're very, very project oriented. Yeaah. Yeaah. That's quite different for the average Soundcloud rapper. Do you guys drop a lot of Lucy's in between albums and stuff? Never.


[User] Please transcribe this text

[Assistant] See that's, I don't know, I don't know what the fuck they're doing on there. I heard the deep web is what the fucking, the weird porn is, like the horse porn and shit.


[User] Please transcribe this text

[Assistant] And it makes it like, well, I'm not sure how much you're considering this, but it makes it such like a cleaner experience when you're like a new fan of a group or artist who already has three projects out and where it's relatively easy to listen to that project as a whole.


[User] Please transcribe this text

[Assistant] Know where they're at, listen to the other project, realize how much they changed in between that, what changed, stuff like that. Where it's like, there's a lot of rappers I like, where you gotta be fucking scouring. Like if you were a huge YouTube or a Young Thug fan and you just wanted to know about every single song, I mean, it's like,


[User] Please transcribe this text

[Assistant] I wish I could turn this to you, but there's a lot of stuff plugged in here. But I confirm that this does exist.


[User] Please transcribe this text

[Assistant] I was super fucked up on cocaine and mushrooms and Tecate at, uh, Coachella and I did this podcast and like I got our standing ovation from everybody who was in the room. And then at that, I think at that moment, like given how fucked up I was, I was just like, you know what? I'm a rapper now. I don't give a fuck. I'm, I'm confident enough that I might as well be a rapper.


[User] Please transcribe this text

[Assistant] My rap name would be I Am White, I Don't Rap, the end. Uh, my mom called me one time and was like, Adam, I know the rap podcast thing is going good, but can you please promise me that you're not gonna start rapping?


[User] Please transcribe this text

[Assistant] Maybe at a certain point I get alright, but I don't really wanna like have to go through the pain of finding that spot. I'm okay with the drunk freestyle in the car.


[User] Please transcribe this text

[Assistant] Best case scenario is that I rap like Logic. That is weird to think that like, you have that much faith in me.


[User] Please transcribe this text

[Assistant] But don't you think that, cause I don't listen to him, I'm assuming from what I kind of hear is that like the reason why he's so obsessed with the fact that he's biracial is probably cause he has like one like very black looking parent and one very white looking parent so he's constantly stuck in this like space where he doesn't really know who he is.


[User] Please transcribe this text

[Assistant] Interesting. What year were we talking here? Do you remember the Icon comic series for DC? Who they had all colored superheroes?


[User] Please transcribe this text

[Assistant] How do you feel about like the Ghostbusters being cast as women in the most recent one?


[User] Please transcribe this text

[Assistant] I promise you, I write a couple tweets for everyone that I send because I look at it and I think, okay, people are not gonna take this away. I'm thinking it in my own head, you know?


[User] Please transcribe this text

[Assistant] Cause it's like, at the end of the day, you really are kind of like the victim of your own comment section. Like, if I have a woman on the podcast and there's 2000 comments calling her a whore and 400 nice comments that are very thoughtful, it's like,


[User] Please transcribe this text

[Assistant] You know what was weird on the Suicide Boys one though, is that Jerm and Jay Green were both sitting there, both black, everybody else is white, and we were talking about white privilege and people, you know, not saying the N words, stuff like that, and Jerm was just chilling and like, there's a couple different times where he looks at the camera just like,


[User] Please transcribe this text

[Assistant] I'm used to hearing that from white girls. In the bay, I think like, cause that was my experience. I grew up outside Boston.


[User] Please transcribe this text

[Assistant] My girlfriend's Armenian and the other day we had a party and like some people who also, who are not black, but were, you know, some sort of person of color came up to her and were like, Hey, we just wanted to really thank you for what you're doing for the people of color all over the world. And she was just like, she asked me later. She's like, so I'm a, I'm a person of color, huh? I'm like, I don't know either. I didn't know Armenian counted.


[User] Please transcribe this text

[Assistant] Question, did you guys grow up around, like, Hispanic people being called spics? Cause that was very big where I grew up, and then I came out here, and I like, mentioned it, and people were like, that's not really an L.A. thing.


[User] Please transcribe this text

[Assistant] You know what I think is funny about you guys calling or you guys being IR is because that's what girls in porn say like when they are talking about doing interracial and they say like have you ever done AR or IR?


[User] Please transcribe this text

[Assistant] I like it though, it says something about who you guys are, like yea, we got a ginger friend, big fucking deal, there's something about it.


[User] Please transcribe this text

[Assistant] I didn't even look at half the questions I wrote. Yeah, sorry if you were trying to get something done. No, I thought this was great. What else, uh, what else should we talk about? When, so from your perspective, the most recent album has been out for how long? It's been like five, six months. We go on tour tomorrow.


[User] Please transcribe this text

[Assistant] We dropped the record six months ago. Uhm. But how long do you need before another album? Like in your mind is it a yearly thing on average or?


[User] Please transcribe this text

[Assistant] Woah, you did that? Yeah, that's before I ever did Coke too, yeah.


[User] Please transcribe this text

[Assistant] Yeah. Fuck. So, you're out here, you guys are socializing, hanging out, hanging out with people now, we're friends now.


[User] Please transcribe this text

[Assistant] You got any like sneak peaks on who the collabs could possibly be on the next tape?


[User] Please transcribe this text

[Assistant] Well, how about this, how about you do a vlog every day and you also like announce whenever you're gonna interview people and then you just don't and then you just have to live with the fact that you just have like said.


[User] Please transcribe this text

[Assistant] I was supposed to, and then he just started ghosting on me. But I said it in the podcast, in the vlog the whole day, and then I get home, I'm like, wow, I'm not deleting it, so fuck it, I just left it in.


[User] Please transcribe this text

[Assistant] Shoutout to Chuck Engels. His, his cool kids interview was the most fucking crazy interview I ever did that. He was so full of fucking genius opinions on everything. I wish he could be like, on the show constantly.


[User] Please transcribe this text

[Assistant] They were the first one through the door in a lot of ways in terms of just being like really weird, unique kids from a certain different area and just coming out and just going crazy.


[User] Please transcribe this text

[Assistant] A certain amount of greed is instilled into you. That was true for me too, I have to admit.


[User] Please transcribe this text

[Assistant] We have previously seen how to compute the column space for a matrix.


[User] Please transcribe this text

[Assistant] However, in the previous video, we only looked at it when the matrix was already in RREF form. And in that case, we just said we looked at the leading ones, and then the columns that had leading ones formed a basis for the column space.


[User] Please transcribe this text

[Assistant] I've got some particular matrix, and you could do the calculation if you wish, and it would go out into this RRef form.


[User] Please transcribe this text

[Assistant] Again, if I want to look at the RREF form of it, we notice that there's two different columns that have leading ones. This column here, the first column, and this column there, the third column.


[User] Please transcribe this text

[Assistant] And well, maybe the solution set to AX equal to B doesn't change. If you do a row operation that interchanges two rows, then the Bs are gonna change as well, so the column space is gonna change. However, this is the important result.


[User] Please transcribe this text

[Assistant] If we take this matrix A and we look at it as RREF and it's the first and third column of the RREF that have the leading ones, then what we get to look at is that the first


[User] Please transcribe this text

[Assistant] And third column of the original matrix A, those are going to be the columns for our basis for the column space. And so that we can say if this matrix on the left is A,


[User] Please transcribe this text

[Assistant] To figure out the column space, you do row reduce it.


[User] Please transcribe this text

[Assistant] And you do look at the RREF form and you say, where are the leading ones?


[User] Please transcribe this text

[Assistant] Everything was just too small, but after a time I realized that no matter where I go, the life here will always be a part of me.


[User] Please transcribe this text

[Assistant] That someone like me has returned to the islands in their mid-20s is actually quite unusual.


[User] Please transcribe this text

[Assistant] Oh, it's you. Haven't I told you to keep out of this park? You know the mayor's orders.


[User] Please transcribe this text

[Assistant] And I was just wearing a shirt and nothing else and I was wearing a grilled cheese. I was making a grilled cheese, not wearing one. I was making a grilled cheese alone.


[User] Please transcribe this text

[Assistant] Home alone, and I, you know, avocados are good. And especially they're good with grilled cheeses.


[User] Please transcribe this text

[Assistant] And I didn't know where they were, so I shouted, where are the avocados? And I searched the freaking house for so long.


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[Assistant] I've played it. My mom teaches an improv class. So I've played improv.


[User] Please transcribe this text

[Assistant] The heat in the gallery was stifling and the rising smoke was making my headache before the oath-taking finally came to an end with what I assumed were a few stirring words by column.


[User] Please transcribe this text

[Assistant] And affected by six shared quakes of spirit, the strong voice still reverberated off the stones of the hall.


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[Assistant] At least his legs wouldn't pain him tonight, I thought, in spite of all the standing.


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[Assistant] There was a massive shout from the floor below, an outbreak of skirling pipes, and the solemn scene dissolved into a heaving surge of riotous yelling.


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[Assistant] An even louder shout greeted the tubs of ale and whisky that now appeared on trestles.


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[Assistant] Accompanied by platters of steaming oatcakes, haggis, and meat.


[User] Please transcribe this text

[Assistant] Mrs. Fitz, who must have organized this part of the proceedings, leaned precariously across the balustrade, keeping a sharp eye on the behavior of the stewards. Mostly lads, too young to swear a formal oath.


[User] Please transcribe this text

[Assistant] And where's the pheasants got to, then? She muttered under her breath, surveying the incoming platters. Or the stuff deals, either.


[User] Please transcribe this text

[Assistant] Making up her mind, she turned and began to squeeze toward the back of the gallery, plainly unwilling to leave administration of something so critical as the feasting in the untried hands of Mongo Grant.


[User] Please transcribe this text

[Assistant] Seizing the opportunity, I pushed along behind her, taking advantage of the sizeable wake she left through the crowd.


[User] Please transcribe this text

[Assistant] Others, clearly thankful for a reason to leave, joined me in the Exodus.


[User] Please transcribe this text

[Assistant] Mrs. Fitz, turning at the bottom, saw the flock of women above and scowled ferociously.


[User] Please transcribe this text

[Assistant] UV lasses clear off to your rooms right sharp, she commanded.


[User] Please transcribe this text

[Assistant] If you'll not stay up there safe out of sight, you'd best scamper a war to your own pieces. But no lingering in the corridors nor peeping round the corners.


[User] Please transcribe this text

[Assistant] There's not a man in the police who's not half in his caps already, and they'll be far gone in an hour. Which is no place for lasses tonight.


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[Assistant] Pushing the door ajar, she peered cautiously into the corridor.


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[Assistant] The coast apparently clear. She shooed the women out the door, one at a time.


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[Assistant] She shook her head, but smiled at the offer. Nay, there's no need lass. Get along with you now. You're no seefer than the rest.


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[Assistant] And a kindly shove in the small of the back sent me hurtling out into the dim passage.


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[Assistant] The men in the hall were rioting, dancing, and drinking, with no thought of restraint or control. No place for a woman, I agreed.


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[Assistant] Finding my way back to my room was another matter altogether. I was in an unfamiliar part of the castle.


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[Assistant] And while I knew the next floor had a breezeway that connected it to the corridor leading to my room, I couldn't find anything resembling stairs.


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[Assistant] Given the carryings on of the night before, I had expected most inhabitants of the castle to lie late the next morning.


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[Assistant] Possibly staggering down for a restorative mug of ale when the sun was high, assuming that it chose to come out at all, of course.


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[Assistant] But the Highland Scots of Clan Mackenzie were a tougher bunch than I had reckoned with, for the castle was a buzzing hive long before dawn, with rowdy voices calling up and down the corridors, and a great clanking of armoury and thudding of boots as men prepared for the tinchel. It was cold and foggy.


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[Assistant] But Rupert, whom I met in the courtyard on my way to the hall,


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[Assistant] The beasts is such a thick coat that cause no hindrance to them, he explained.


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[Assistant] Sharpening a spear point with enthusiasm against a foot driven grindstone.


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[Assistant] I forgot to point out that this meant the hunting men wouldn't be able to see the boar they were approaching either, until they were upon it. As the sun began to streak the mist with blood and gold,


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[Assistant] I was glad to see that the women were not expected to participate.


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[Assistant] But contented themselves with offering bannocks and draughts of ale to the departing heroes.


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[Assistant] Seeing the large number of men who set out for the east wood, armed to the teeth with boar spears, axes, bows, quivers and daggers, I felt a bit sorry for the boar.


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[Assistant] And yanked tight the compression bandage I had wound about the injured calf.