if I could wave a wand like you said, I'd like there to be philosophically inclined, sophisticated, philosophically inclined people in the labs of the technologies that are going to define the next, you know, 20 years of our lives. Hello everyone, my name is Steven

Paron and you are listening to the Feedback Loop on Singularity Radio where we keep you up to date on the latest technological trends and how they're impacting the transformation of consciousness and culture. This week my guest is Christian Madsbjerg who is the

professor of Applied Humanities at the New School in New York and co-founder of the consultancy Red Associates. In this episode, we primarily discussed the ideas that are put forth in Christian's latest book, *Sensemaking: The Power of the Humanities in the Age of the Algorithm*

amongst other things. This includes exploring some of Christian's key principles such as how we should emphasize our focus on cultures instead of individuals, how we should look at people's experiences and their natural environment rather than in the laboratory, and how we should look at

thick data, which includes things like context and people's passions, instead of thin data which just includes cold hard facts. While most of this conversation explores the shortcomings of a data-obsessed decision-making process, we do start off the podcast with a conversation that Christian and I had

started before recording that deals with his latest fascination. So, without further ado, let's jump into that conversation everyone. Please welcome to the Feedback Loop, Christian Madsbjerg. I'd like to keep it casual and if we find a topic that's really, um, interesting to us, I'd like to run with

that so I'd love to hear more about your thoughts on attention right now uh how does that relate to your work um the way we talk about attention today is um it's very much about focus and concentration of our aware sort of awake awareness but

I think there's a much broader uh type of attention uh which has which is much more blurry and has to do with how we are familiar with something so we are familiar with streets and that's why we can operate in them without undivided attention if we have

undivided attention to a specific car or a specific part of the street uh we might end up running into people and or um driving into things um so all sort of focused concentrated undivided attention has this background um that is the context of it so so there's a sort of a

a ground and a figure and the figure only works on the background of a ground so when you see a triangle you see a triangle not the sides of the triangle right uh so our attention might work differently in that way it's much more blurry and viscous um in the sense that

it's not clear it's it's uh sort of almost like a panoptic kind of um kind of attention that you know if you see great sports people if you see a great basketball player a great football player they seem to pay attention to everything and

nothing at the same time I think a great investor pays attention to everything and nothing at the same time and they have a much broader much more we call sometimes intuition but I think it's better to call it familiarity um and that familiarity is based on um our

lives and how we how we are learning about things so um so so describing attention as one thing um which is certainly an important one is not accurate and I and I think there's there's a philosophical tradition that deals with this so the traditional

phenomenology that started with Martin Heidegger but particularly uh a French philosopher called Maurice Merleau-Ponty describes how perception and attention how seeing works um how how we see um literally how we see and how we listen and how you could say impressions from our

surroundings are perceived and how it's not empirical in the sense of uh in the sense of the actual um visual input that hits our retina or the sound that hits our eardrums um are always on a background of something so if you hear an F on a

piano it depends on very much on which kind of style that F is in depending on how we listen to it right so so if you if you listen to an F and has and it has your undivided attention you wouldn't understand whether it's within jazz or

or or uh or uh you know classical music if an opera singer sings it it's quite different than if a if a you know it's song on Broadway so so the an F is of course a century impression but the way we experience it is on the background of

musical styles and experiences and history and all kinds of other things so paying attention undivided concentrated focused on the sound waves of an F would completely misunderstand the world of meaning that we that we live in so the same sensory impression can be vastly

different things, even though scientifically a machine can't measure that, right? Is this, is this same train of thought kind of what's got you started with Red Associates and the books that you've written since co-founding the company? This idea that if you just have

this stimuli without context, that you're missing the bigger picture. Exactly, yeah. So I did, I never, I mean, I didn't start a comp, I started a couple of companies now, and I never had a plan or a vision or a strategy. It was just stumbling into it and

um, sort of confident in that it would work, but but never knowing that whether it would be the case or not. Instead of accepting if it didn't, then you know, I'd have to try again, but it was always on a particular philosophy. It was, it was the

idea that humans can be understood, not fully, but largely based on observation. So looking at them, and that's not just statistical observation, it's also in context observation of their meaningful world. And that's what good anthropology is. It doesn't happen much in anthropology, but when it does, it's

glorious. Um, it's what the kind of philosophical texts that I grew up on, uh, not grew up on, but we're excited about, um, uh, what they are about. So how our perception and experience work, um, and then use that to inform how we make things. Um, so how do we, when we make

vehicles or software or, you know, uh, music, you can understand that background upon which things are meaningful to us and, and so on. And in that way, make better things and imagine better things. So, so it's just a, a particular view of humans, um, that is not the only one, but

one that um I understand and feel comfortable in and and so on so I think I think you're right that it was certainly informing it yeah well so you you started reading Associates 15 years ago you wrote *Moment of Clarity* in 2014 you

wrote *Sense Making* in 2017 and all of these have that central theme of the social sciences uh guiding business uh and strategy did you have of a specific background then was it was it that early love of philosophy that got you motivated to engage the business world

in this way or were there other ideas that motivated you to work on these subjects it was kind of the other way around it was I needed to make a living and somehow and there are different ways you could use the kind of things I was interested

in and knew a little bit about and one was you could be an academic and and that wasn't didn't look very attractive um when I was in the middle of it it looked as if people weren't enjoying themselves very much um and then you could be a writer right you

could you could be a journalist or something like that um and that was in the middle of seeing the media world as you know the 20th century kind of media institutions just falling apart and it was only the beginning of it but it was pretty clear where where it would go you

know the internet was around and the logic of the internet seems to did quite well with completely changing that picture so I thought why would you bet on a on a really bad horse in that sense um and then what was left was trying to figure out something on my own and then sort of

stumbling into companies I didn't know anything about companies before that but it was quite obvious that companies are extraordinarily resourceful, um, resourced well in a way that universities weren't and the media world certainly wasn't resourced in that way and suddenly you could do things

that were much longer term and you could imagine things that millions and millions of people would, you know, would de, would be relating to or somehow be meaningful in their lives. So I worked a lot with Samsung at that time and reimagining the TV and what how we how

we deal with what we today call content, um, we used to call it TV and movies and so on but, you know, imagine how we change our behavior around that, um, or you know when the smartphone came around and everybody was laughing at it, they certainly were at Nokia and Samsung and

other places and you know reimagine or try to imagine what that meant for people. So, so you could both live a sort of, I found that you could live a, uh, uh, you could make a living and lead and a life of ideas or sort of an intellectual

life, um, at the same time which was what I wanted, so it was more like a stumbling into it, needing it and then, um, somehow finding a way in, in it. Yeah, I love that you say that sense making is, I believe, a deep nuanced engagement with culture,

language and history. Can you explain a little bit what you mean by that? Yes, let's take history, um, history is a collapsing, um, thing. It's people are not interested in studying it, um, parents are not interested in investing in their children studying history. We look down upon history today.

as if you know that's kind of a loser topic um financially in every way yeah I think the skills you get when you are a historian or study history or art history or anything like that are very practical um not only I mean the normal story is that if you forget

the past you're condemned to repeat it um which I think was Santayana that said that but that's one which is pretty crucial right understanding what it was like to be um fighting during the First World War or what it was like in the 50s or in

the 80s informs many things that we sort of misunderstand today I think but the skill you have as a historian is you put you can put things together right so a statistician can put numbers together and have very sophisticated ways of doing that um and

that's very helpful but a but a historian can put together let's say you want to you want to understand what it was like in the punk movement you know during the late 70s you can put together together music visual things videos uh notes

critique um um the reactions to it the reviews of it um the places where it happened which are all things you can't put into a spreadsheet and add add it all up you you have to somehow interpret it and try to put yourself into into

that world of you know a scene that happened in London and in New York and other places at that time and and understand it understand that world and I would imagine or I think that's also understanding that is also a way to maybe understand parts of the future you

understand the structure of a style of music and how it disrupts, you know, the way you think about things and the emotion that comes out of it. You can then use those tools to understand the world of cars or cities or the lives of

teenagers or, you know, and so on. And doing that is good for understanding what to, what it is like to live today, but it's also an understanding you could use to not predict the future but imagine futures, because we don't know what the future will be and anybody that

says so, you know, you should look skeptical at. So um, so you could, you can sort of creatively imagine things if you have the skill sets of a historian. So that's what I mean. It's, it's not that you know you have to engage with the

history of communication and phones if you want to imagine the future of phones in some way or another, but certainly the tool set can be used um, and that's very much what I try to say. Yeah, it, it sounds to me like when you're saying this that history in

this sense gives you a the ability to construct a map and understand how pieces fit together. And the problem perhaps that we're in and that you touch on in sense making might be the fact that when there's so much new stuff coming your way from algorithms in

data, you don't actually build a complete map because you're constantly taking in the stuff that the algorithm feeds you and it's distorting the image and I, it seems like that would be disorienting. Does that sound accurate? Uh, it can and certainly at the state it's in right now

it can, I mean if you look at the pandemic, I wish that AI could have done more, you know, in terms of predicting what on Earth was happening and what was going to happen. And you know, in the end we informed policy and behavior based on good old-fashioned

statistics, right? There wasn't much AI involved in how we did things. You can say, was it too little? Did we not rely on it enough? I don't know, but certainly there was a complete absence of it. And I was called in the beginning of the pandemic

people called me sort of out of the blue saying, "We've made hundreds of millions of dollars in investments in predictive algorithms and what they called AI, yet we have to scrap it now because it didn't predict anything and we don't know how to use it. Um, we can't see a use

of it right now, maybe in the future, but right now I need to talk to a social scientist. You know, has this happened before? When it happened, what did people do? And it turns out the situation isn't new. You know, it's happened many times before that we've been scared of a

particular bacteria or disease and some kind of another, and there are patterns of behavior and so on. So so you can use that to help inform you know major decisions in very large companies. And so so I think with algorithms that they have, at least the way they are now,

have a limit and um work to be done. Um, so so I'm not against AI in any way. I think it's an exciting technology and I think it might have very large consequences for even what it means to be human. Um, but in the state of affairs it's, it was

oversold, um, and it was oversold particularly by very large IT firms that, you know, something like Watson was supposed to predict everything and fix our broken healthcare system and cure cancer and lots of things, and it just turned out not yet. Yeah, what is that, what does that

struggle look like to you because the subtitle of your book is 'The Power of Humanities in the Age of the Algorithm.' How is the relationship between the humanities and the algorithms playing out right now? Do you think that we're losing parts of ourselves or we are not performing

at our best because of our over-reliance on algorithms? Um, I think the humanities are collapsing. I think we are under-investigated, um, but it's also not good. Um, I think the social sciences have also painted itself, not a large part of the social sciences

have painted itself into a corner, um, which means that there's uh two things I think: there's an over-reliance of, no, there's not an over, there's an overselling of algorithms as helpful with everything, um, not just parts, but everything. And I and I think there's

an under-reliance on the interaction between what we can broadly call the humanities, an understanding of humans and our worlds and our history and our songs and our, you know, emotional states, um, under-reliance on that and the interaction between, let's call it software engineering or computer science

and humanities, is would be very helpful. Um, and I think the way you want to feed algorithms, the way you want to interpret outcomes, needs context. And without that context, just relying on the machine doing it on its own is not reflective enough in terms of

both both limiting uh negative consequences and creatively imagining you know great things it could do so that's probably the way I see it I'm excited about the tech I don't understand it beyond simple I understand the concepts I understand the fundamental statistics of

it and the mathematical ideas behind it but I would never be able to do it um and would never claim to but I think I understand humans a little bit and can see the difference between the two yeah in a time where it feels like we have so much energy towards authentic

marketing towards people gravitating towards you know YouTubers and influencers and people who are just in podcast yeah like we're we're becoming attracted to I think these very humanized versions of the business world and yet it seems like a lot of companies

and tech companies as well aren't really making that shift why why do you think there is such a hesitance to I don't I guess just be human I mean is it just a fear of losing profits or uh being vulnerable like what do you think's

happening here um so you ask about marketing just just the um I guess the business world's hesitant to embrace the social sciences to embrace the more human side of things yeah um I think partly it's because the people that run many companies and particularly in

Silicon Valley are not from the humanities and feel um distant to it um I think they were excited about computers and less about maybe novels when they grew up and fantastic I mean good for them but I think so so there's that there's also the humanities have gone

into a very political space right so a lot of the study of history has a very political slant to it and the same with anthropology and sociology and many other things that that there are there's a particular framework that is uh applied to everything and that

framework is fundamentally negative to the business world and the world of Commerce and if you come with that attitude to someone that might not be very interested in in that area and needs to be excited about it if you come with that attitude that is not helpful

but is talked to talked about as critical thinking it's not always critical it's it's not it's critical but it's not always independent you could say um then why on Earth would you want to work with someone like that you know it just creates conflict um and

isn't very helpful so I think there's this sort of dual problem of supply and demand that Supply is not trying to make itself available and demand is fundamentally skeptical for reasons that I I understand um so but when it happens when you can connect a great engineer

and a great you know philosopher they can see more than they could Alone um and the what the philosopher gets is the ability to make things right and what the what the engineer gets is the ability to see what it is when you're making let's say technology for surgery

you know understanding health is a you know human health and healing how we heal how we deal with diseases and how families dis you know deal with diseases can be helpful if you want to design the machines or the technology for exactly that so so it's just when it happens it's magical

when it doesn't I understand why so yeah are there any great examples of that relationship that you can point to in the business world any companies or uh moments of innovation where that happened I mean the classic example is of course the former Apple CEO saying

that Apple is the crossroads of technology and the humanities um which includes aesthetic right includes beauty um and beauty is yet still difficult to capture in algorithms um that can be beautiful algorithms in terms of how they're constructed that the code is great um

but is a is a beautiful thing there's such thing as a gorgeous line of code um but but that's not what they meant I think I think that's one example uh I think um a lot of uh trying to deal with the techlash or

the backlash on tech is now including um thoughts about ethics thoughts about societies and democracy and so on and a lot of that input uh comes from people that know about those things so I think there's also a sort of a reckoning um I think the whole uh the whole

tradition you can call it now because it's probably started in the 80 1980s um of user experience or customer experience or you could even say human experience is comes out of a social science tradition of observation so the ability to look and I think when let's

say a big search firm a very large company that primarily relies on search are looking into what their video platform let's say um is doing and what is should be allowed on it and what the limits of what should happen there they are also looking to um studies about the people

that might put up things that aren't, you know, that we shouldn't see, as certainly our kid shouldn't see. So, lots is going on now from the focus only on technology to the focus of technology as it's placed in society. Um, so I think that's

another good example, you know, a company like Samsung, um, has at its heart technology and manufacturing, but there is no project, there's no major product coming out of there that's not sensitive to culture and aesthetics and beauty. Um, whether you like it or not, it's um, it's

certainly what they're trying. Um, so I think the the whole focus on design is a, you know, a question of of how engineering products, engineer well engineered, or engineered products, living our life um, beyond sort of banal marketing talk, uh, is a is a a

combination of that. Yeah, you mentioned there briefly with Samsung, the idea of culture, and it makes me think of your five principles that you mentioned in sense making, and uh, I believe the first principle is culture and not individuals. What does that um principle mean, mean to

you? Well, that's important to me. So, I'm actually not very interested in individuals. I I don't I don't find individuals very interesting. Um, I think it's not there is there is this assumption in a lot of marketing and a lot of trying to get input into a company

that is about asking people what they think. So, we spend spend 25, 30 billion do a year in the world on asking people what they think. So, that would be surveys and questionnaires and focus groups and so on where the assumption is that we know what we want, and and that isn't not the

Case, I mean, it is sometimes, but most of the time, we can't imagine the future and we don't have direct access to our needs, whatever they might be. And so, asking us is not the best way to look at us because we don't have access to our wants and needs

and desires, and um, we don't, we don't, I don't know how I ended up, you know, here. It just happened, and it was a series of not aware, not, you know, rational, not linear decisions that just ended up like that. And when you ask, when you fig, when

you look at most people, that's the case. Um, we might rationalize it, but that's often just a fiction we create. So, if you want to understand people, you have to observe us and observe us with sort of the skill of a historian, let's

say, and there you see that humans are not islands. We interact with others, and we adjust to others in everything we do. So, when you, you know, an example is when you move to New York, like I did 10, 12 years ago, you see things that you

don't see after you lived here for a while. So, one thing that you end up doing, for instance, in a, you know, in an elevator, the only, the only thing in an elevator, I have, the only place I've seen that the close button on the elevator is worn

out, because people, so panicking, sort of want to get two seconds ahead, is in New York City. I haven't seen that other places. Uh, so, just that is something that creeps into you. So, now I do it after having lived here for a while, and I have to

sort of stop myself and arrest myself for getting the people around me to do things that I wouldn't otherwise have done. Um, the same in traffic, people drive in a particular style in California as opposed to what they do in France, and as a driver, you just

adopt that thing. Um, the way you stand in an elevator, if you look at people going into an elevator, you'd see people occupy one corner, then they occupy another corner, then you go in the middle, then people get nervous and they try to adjust for each other, and the the more

full it becomes, you can see people move around. So there's an appropriate distance to stand in, and there's appropriate sound to create inside of a inside of an elevator. So they're rules, and those rules can be observed, and those rules are between us, they're not

in us in that sense, and the access to them is to look between us humans and not at one singular individual or the aggregate of the opinions of those individuals. Is this very much like the third principle in the book, *The Savannah and Not the Zoo*, the idea that you're you

need to see things in the wild and and not in kind of the structured focus groups and the labs. Yes. Yeah. I mean, an example I don't I don't think I have in the book is behavioral economics, right? So which has been fashionable for 10 years now since

Kahneman wrote his, otherwise I mean, brilliant book about *Thinking, Fast and Slow*. The behavioral economics is based on a set of experiments often with the professor's students, uh, which is in itself a very limited sample where they get to choose between a couple of things, so

would you buy this wine if it was $5 versus $7 and so on and that's not how we shop you know so so they they isolate a situation away from the *savanna* you know away from the context away from the background that we're familiar with

towards a situation where we make rational choices between you know transparent options which is absolutely not how we behave in the world so the same thing is with focus groups or surveys or many other things that they have this problem in in them methodologically so yes it's a

third kind of knowledge right so the first kind would be inner so you would know if you hurt your foot if you knock your foot against the the door you would know and I I'm not it's not appropriate for me to challenge you on whether it

hurts or not so that's sort of an inner kind of of knowledge and that's sub you can call it subjective right um the second kind would be objective so that would be 76% voted for someone or um last month we

The Humanities vs Algorithms | Christian Madsbjerg, ep 38

Singularity University

주의 집중의 재정의: 초점 너머

전통적인 주의력 관점은 집중과 집중력을 강조합니다.

보다 광범위하고 확산적인 유형의 주의력에는 주변 환경에 대한 친숙함이 포함됩니다.

이 '지면과 그림' 개념은 주의 집중이 배경 맥락에 얼마나 의존하는지 보여줍니다.

이러한 유형의 관심은 숙련된 운동선수나 투자자의 관심처럼 흐릿하고 점성이 있습니다.

현상학과 같은 철학적 전통은 주의력에 대한 이러한 폭넓은 이해를 뒷받침합니다.

레드 어소시에이트와 컨텍스트의 중요성

맥락 없는 자극은 더 큰 그림을 놓치게 합니다.

회사의 설립은 관찰과 맥락을 통해 인간을 이해하는 데 기반을 두고 있습니다.

이 접근 방식은 인류학적 방법과 철학적 텍스트를 바탕으로 합니다.

목표는 이러한 이해를 바탕으로 더 나은 제품을 만들고 더 나은 미래를 상상하는 것입니다.

역사는 저평가되어 있지만 그 기술은 매우 실용적입니다.

과거를 이해하면 실수를 반복하는 것을 방지할 수 있습니다.

역사가들은 다양한 정보를 종합하여 일관된 내러티브를 만드는 기술을 가지고 있습니다.

이 기술은 현재의 다양한 측면을 이해하고 미래의 가능성을 상상하는 데 적용할 수 있습니다.

미래를 상상하려면 과거 트렌드의 구조와 영향을 이해해야 합니다.

인문학 대 알고리즘: 필요한 협업

인문학은 과소평가되고 알고리즘은 과대평가되고 있습니다.

알고리즘의 기능이 과대 포장되고 인간의 이해에 대한 의존도가 낮습니다.

컨텍스트는 알고리즘 결과를 해석하는 데 매우 중요합니다.

컴퓨터 과학과 인문학의 협업은 부정적인 결과를 완화하고 창의성을 키우는 데 필수적입니다.

센스메이킹의 다섯 가지 원칙: 개인보다 문화

개인이 아닌 문화에 집중하여 인간 행동에 대해 더 깊이 이해합니다.

개인에게 원하는 것이 무엇인지 물어보는 것은 사람들이 자신의 요구 사항을 직접적으로 파악할 수 없기 때문에 최선의 접근 방식이 아닙니다.

인간의 상호작용을 관찰하면 문화가 행동에 미치는 영향을 알 수 있습니다.

인간은 고립된 존재가 아니라 다른 사람들과 상호작용하고 적응하는 존재입니다.

행동에 영향을 미치는 문화적 영향의 예: 엘리베이터 버튼 사용, 운전 스타일, 대인 관계 거리.

씬 데이터는 표면 수준의 관찰(예: 근육의 움직임)을 설명합니다.

두꺼운 데이터는 이러한 관찰의 의미와 맥락을 해석합니다(예: 윙크의 의미 이해).

윙크는 문맥에 따라 다양한 해석이 가능합니다.

인류학에서 두꺼운 설명은 맥락에서 행동의 의미를 이해하는 것을 강조합니다.

현재 기계는 두꺼운 데이터를 해석하는 기능이 부족합니다.