Playing with words
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00:00
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01:38
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04:36
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10:53
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16:48
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26:34
Revision controlGeneric programmingNormed vector spaceTerm (mathematics)MetreReceiver operating characteristicWordQuantum stateProduct (business)Cellular automatonWordRoutingFigurate numberKeyboard shortcutOcean currentShared memoryNatural numberArithmetic meanTerm (mathematics)CASE <Informatik>Metropolitan area networkContext awarenessCompass (drafting)GenderBoss CorporationLie groupNumberBlock (periodic table)MathematicsPerspective (visual)QuantumStandard deviationData compressionNetwork topologyDiagramMoment (mathematics)Source codeNormal (geometry)Disk read-and-write headComplex (psychology)Order (biology)Latin squareShift operatorPairwise comparisonInternet service providerRootGroup actionFormal languageWeb 2.0String (computer science)BitBuildingComputer animation
36:15
WordSystem programmingInterior (topology)OvalComa BerenicesRAIDArithmetic meanGeneric programmingTerm (mathematics)Musical ensembleLogical constantChemical polarityPoint (geometry)Physical systemComputer iconThumbnailContext awarenessArmFunction (mathematics)Matching (graph theory)Impulse responseData structureMilitary baseFormal languageObservational studyPoisson-KlammerWordSquare numberThermal conductivityHookingRule of inferenceInternetworkingResultantGroup actionSpectrum (functional analysis)Free variables and bound variablesHypermediaCASE <Informatik>Row (database)Arithmetic meanSpeech synthesisDifferent (Kate Ryan album)Keyboard shortcutProcess (computing)Term (mathematics)OrbitSummierbarkeitStatement (computer science)Lattice (group)FacebookUltraviolet photoelectron spectroscopyExpected valueNatural numberPairwise comparisonRepresentation (politics)BuildingoutputFocus (optics)MereologyDomain namePattern languageFunctional (mathematics)ExistenceOrder (biology)Source code
45:56
Logical constantOvalComputer fontSoftware testingComputer musicData typeElectronic mailing listUniformer RaumGroup actionNeuroinformatikVirtual machineComputer fontPower (physics)KnotMachine learningWordTable (information)Type theoryTheoryNegative numberSource codeComputer animationMeeting/Interview
47:40
WordTerm (mathematics)Normed vector spaceLogical constantLine (geometry)Data typeUniformer RaumElectronic mailing listGateway (telecommunications)Arithmetic meanMusical ensemblePoint (geometry)Computer fontFile viewerView (database)Right angleType theoryNatural numberVideo gameOrder (biology)Fitness functionWordFilter <Stochastik>Compass (drafting)Multiplication signGoodness of fitDifferent (Kate Ryan album)Automatic differentiationSource codeComputer animation
49:44
Data typeHypothesisWordFunctional (mathematics)Computer fontMetropolitan area networkLevel (video gaming)Formal languageComputer animation
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53:26
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55:03
Service (economics)Complete metric spaceMereologyExpressionWordSemiconductor memoryArithmetic meanGroup actionPoint (geometry)EmailType theoryMultiplication signTraffic reportingMixed realityGame theoryInformation2 (number)Film editingCommutatorContent (media)Video game consoleFormal languageInsertion lossVideo gameMathematicsBitTranslation (relic)Link (knot theory)Similarity (geometry)Metropolitan area networkSource codeComputer animation
Transcript: English(auto-generated)
00:16
Guten Morgen. Hi, good morning, everybody. Welcome you to the second day, first talk on this stage.
00:23
As well, it's quite early. It's still in the middle of the night for some of us, I believe. But yeah, I'm Peter. I'm the heritage for today's talk of Camille. And Camille is with us. Good morning, Camille. Good morning. Camille is giving us a talk about a very interesting idea.
00:42
We want to play with words. And actually, this is the first Congress of Camille. So it's the first time he's being on stage and at the Congress. So he's enjoying it so far, I hope. Camille is studying mathematics in Poland. And yeah, I think we will let you start with your talk.
01:01
Actually, it's kind of an interactive session. We have shared or he has shared a document we can use to follow him in his talk. It will be presented. But I think you can enter actually ideas and comments in the document as well. So please be polite. Don't erase anything. Otherwise, we need to shut it down and then stay with the copy, the read only copy.
01:22
So, Camille, yeah, so have fun. I hand over to you and let's start playing with words. I'm really interested to see what you want to talk about today. Yeah, thank you. Thank you. All right. So a few words about me. I'm considering mathematics before I had a one and a half year long break.
01:43
For optimal places and researching tons of curiosities. Curiosities is one of the reasons I ended up making this talk. Before I was a visual effects artist working in the film industry. And small disclaimer, I usually laugh a lot.
02:02
This is a simp party and encountering and entertaining ideas. So if I hear some stimuli questions for you and I will laugh. This is a compliment. So this is not only about me, but what I do.
02:23
I do this with in group. So I want to talk about this group a bit. We have five active members. We are from different backgrounds and we playing with words since a few months. The main idea of the talk is that I will
02:44
throw examples of what I mean by playing with words and how we do this. Then I will sum up and make it more general. Then, because we will generalize the topic,
03:00
we will be able to speculate about this and go like meta. And then I will be waiting for questions. All right, so examples. Here will be a pattern through the whole examples session. First, I will introduce a current word or words or phrases and say
03:29
what we think it's kind of wrong with them. Then I will say how we propose to fix it. And perhaps something more because some examples are like rabbit holes
03:44
and another one are quick and easy. All right, so let's start. First, first phrases like to age and to get old. What we think is wrong with it. First thing is that these are, at least in my culture,
04:05
these are charged words, kind of negative. And they are two main things people can mean when they say to age.
04:21
So first thing is that they can mean like age in the biological terms. So this is the fourth one, like accumulate cellular and structural damage as an anecdote. This is an ongoing debate in science.
04:44
What does it mean to age? Here is the link for paper. I hope it will load soon, from 2020, which is from December, I think, which is exploring what is aging in biological terms.
05:04
And authors mention a nice thing here, which is, quote, our mental categories tend to correspond to our linguistic categories. So what is how I read the sentence is that we are used to certain categories that words impose on us.
05:23
And then we expect from reality, from our measurements to match this. But actually, this is often the case that when we go and try to find what is aging, even aging, something that seems to be so fundamental and like natural and normal, we find that it's not that general.
05:47
It's harder to generalize and it's actually a few phenomena going on and different species maybe have different weights on different phenomena and so on and so on.
06:02
So to age, so one thing when we say to age, we can mean that we accumulate cellular damage. This is like the general biological meaning of this word. But people usually say something different, which is like we expect
06:21
from others to change in a certain way, like to behave in an old way, like to not exercise a lot or not to learn much. Like the 30 years universities, it's like universities for people older than 50, 60, 70 years old are kind of new thing as far as I know.
06:46
So we have many presuppositions of how people above 50, 60 years old should behave, so then they are in accordance to that.
07:00
So I think it's kind of nice to separate those two phenomena and I can make it clear what we mean. And the first one here is to get unwell as a result of unhealthy lifestyle. So this is kind of between this biological meaning and cultural meaning,
07:21
since like most causes of deaths in the West are due to unhealthy lifestyle, like smoking cigarettes and diet. So we actually now currently don't die from mostly from accumulation of cellular damage, so we don't die specifically from aging
07:44
in biological terms per se, but from like what we actually do. This is first example. So we basically when we are inside the group of our group with friends,
08:01
we try to avoid using this term and if somebody will use this term, we say, hey, what do you mean? And we actually expect from each other to be more precise when we speak about aging, like what do we actually mean? So instead of using shortcuts, we're using one of those four or more words.
08:28
Okay, so another word, this work or to work. So the thing with work is that usually when people say work,
08:45
they mean to earn money. So volunteering is often not understood as work and we kind of don't like it. And like, why is this the case?
09:01
Because historically speaking, there was a distinction and the culture shift of understanding of work happened in like 19 to 20. So now we can feel regret that we don't earn money, that we don't work too much at actually because we earn big DD
09:27
by working and stuff and we say, oh, let's make it clear. Like let's get work to work, which is like volunteering, raising children, learning and so on and so on.
09:41
And labor, which is strictly speaking, money earning activity. So by this, we want to be more precise about what we mean by work. And also like shift connotations, because like now we cannot say, ah, you don't, you're so lazy, you don't earn money.
10:01
Now, this sounds ridiculous, but I'm so lazy, you don't work. This is like normal. It's much harder to say, oh, you're so lazy, you don't earn money, you don't learn or, you know, organizing community made people happier. This is considered as weird.
10:22
One of the readings is a short essay by a guy standing. This is a person who is into UBI and stuff. So he obviously likes to write about work. And what he writes is that for many decades,
10:41
the term in employment was a matter of regret, a recognition of low social status, typically applied to single women obliged to take low paid positions, serving household headed by the bourgeoisie or aristocracy. So this is to underline the shift in the, like we have the same word,
11:05
but the background, but the background, like what are, what are our feelings toward it, are completely different. And he also writes a nice thing down here to our context.
11:21
And this is also the same vein. Like now it's, now it's kind of, now we earn as citizens, we earn dignity by working. But because working shifts this definition only to money earning activity, we end up that we earning dignity by earning money.
11:41
And this is like ridiculous situation, at least for us. So he's basically the author of this essay advocating that we shouldn't like vilified work or not romanticize it. So yes, we propose to, yeah, I see somebody added,
12:08
yes, the physical, physical, yes, of course, is a technical term, labour, us, we just make here what we mean by labour, money.
12:26
Yes, of course, we don't want to erase the physical interpretations of what we meant here in culture, this was in background. All right, so let's go to another case.
12:50
Sorry for typos. So interesting, we propose to ban word interesting. So when we are inside our group, we don't use the word interesting,
13:02
or at least we try not to use this word. And this is controversial often when people first heard about it, but let me explain this. So interesting is used in a context when somebody is presenting some idea
13:22
and you can say it's interesting. So we consider this as meaningless, because somebody can say if they are interested or not. So if the person is really interested in what we are presenting to them,
13:40
it's obvious, it's like saying, like, this is like people, you know, you see by their body language that they are actually interested and want to know more about something you are presenting to them. So it's much better to just ask a particular question,
14:03
you know, express this enthusiasm, just mere saying that something is interesting. Okay, another example. To like, to have a taste, et cetera. So actually this is how the thing with playing with words started.
14:24
I read about mere exposure effect. So mere exposure effect is a kind of bias, which says that if you saw something before, there is a much greater probability that you will like it
14:41
if you will see it a second time, even though you consciously wouldn't remember that you saw for this thing. So I thought, okay, so maybe when people say I like something, they actually mean that they are used to this thing, at least in certain cases.
15:05
So then I was speaking with people and when they say I like, I just inside my brain, it was automatically like they just, they say I like, like, I like Brussels. And in my head, I heard I am used to Brussels.
15:25
And sometimes this thing is used to make much better sense. And actually what it does, if you replace some occurrence of like to have a taste, you will discover that this is much more flexible topic,
15:41
that it's not that you have to like something and it's closed, it's under, it's when you say I am used to something, you want to underline that what you actually currently like is the output of the past, is the product of the past.
16:04
Thus you can try to change it, like easier. So by changing like to being used to, we try to like underline or highlight that the future
16:22
don't have to be the same as the past. What's another thing? Thank you. You can make comments because this is as the definition, but appreciated. What other thing is that about like is that if you see it how the frequency
16:45
of like how it's used in a corpus in the body of language is that we are, there is a spike in the occurrence of like. Of course, some of it can be explained with Facebook,
17:03
but you see that the liking is sharply increasing even before Facebook and actually the tempo, you can see this is very sharp decrease, steady decrease and Facebook only changed this maybe even more.
17:24
And I also feel because of the pressure to like and this gives, this takes us to another and this is my personal favorite, which is meta prefix. This is actually a prefix that we created.
17:41
So what I wanted to say that like is used more like so often and I feel like obligated to like so many things, but what actually I would like to is not to like to like things. So this takes us to meta prefix.
18:03
So here are examples of meta prefix in action. So meta prefix is about like self-referencing words. So you can say I like shopping and then I like to like shopping
18:20
and I like to like to like shopping. So with meta prefix, you can make this sentence shorter by adding like to like, which means like double like, which is like to like shopping. So it's a bit of a headache at the beginning,
18:41
but then you, yes, yes, this can be done, of course. So what's, but I'll explain what, we'll soon go to why making is and like making it much more rigid and like a number here
19:07
is actually might be a good idea as a way to generate more ideas, but I will go to that soon. Anyway, so we have this meta prefix which allows us more easy to say like to like shopping
19:21
and it's a bit of a headache at the beginning, but then you start to wonder why it wasn't normal before. Like consider the case that you are in the kitchen and preparing brussels, dish with brussels and the person sits next to you and you ask them,
19:42
do you like brussels? And they answer you, no, I don't like brussels. So like what are you supposed to do with this information? What it scans is that do they like brussels and do they like to like brussels?
20:01
Because if they don't like brussels, but don't like to don't like brussels, this means that they want to change this liking. So with this meta prefix going to these directions during conversation, it's much easier
20:22
because it's just like normalizing. So this is a term in design, affordance. Just because something is easy to afford, you do it more often. And it works obviously with negation and this is also a nice question about notation, like what's the best notation for it?
20:44
Okay, so why should we, like what do we gain by making a number in here? So question, the meta prefix generated. Can you go further?
21:03
Like we like to like to like, if you stop and think about it, makes sense. But then you hit the ceiling, like like to like to like, not to like. It's just like complete garbage. So is it because the word itself,
21:20
the phrase itself loses meaning or is that it's our limited capacity? So for humans, it's easy to like, to like, to like and to like, to like, to like, but it's harder, you know, you hit certain ceiling.
21:41
Okay, so what other things it generated? So it started from liking, but then we generalized it to prefix. So we can think what are other examples of this meta prefix in use? I find example with tolerance nice. So it's saying that tolerance
22:06
requires intolerance of intolerance. So in order to have tolerance, you have to have intolerance of intolerance. So I think this sounds less paradoxical with this meta prefix.
22:21
Also being used to. So are you used to being used to, you know, again, opening to possibilities, okay, you are used to something, but maybe your addiction is new. So you can ask, are you used to being used to? Also to believe, like, do you believe that you believe?
22:43
This is, this is, this is, then we thought about this belief and then I found reading as Mulligan, this is a logician, a mathematician, that he make a whole field of doxastic logic and where he wants to categorize type of reason.
23:05
So a normal reasoner is a person who, while believing, P also believe, they believe P. And there is also an opposite one. So by believing P, do not believe P. And this is a well-known paradox in philosophy.
23:21
So making this, making this prefix allowed us to, like, apply this mechanism to the other words and make it more fun, basically. And this is the most abstract thus far and we want to go further probably.
23:43
Can we go to the opposite direction? So you see, we use numbers here. So like to like is to like. I like to like to like is free like. So we can obviously go, like we can increase.
24:00
We can increase this but can we decrease? So what would be to minus one, to minus two, to minus three like? So thus far we think this is garbage but we keep an eye, maybe some words we would be, it would be applicable,
24:22
this kind of trick. Thus far we have only one example of this but this requires a bit of introduction. So imagine a language which, in which like means like to like. So when people using this language which says like,
24:44
they use like to like and they just don't use this one like, only to like. So they could also wonder, can we go to the opposite direction? And they would discover that they actually kind of like things as well.
25:02
This one like, not only two likes. So this is going to opposite direction. And I think similar things happen already with the word see. So when I say I see a screen, a camera, what I mean exactly is that I am aware of seeing.
25:21
It's kind of I'm seeing that I see the camera. So to be more specific, I have a model of myself which is aware of seeing and now I see this. But we have blind spot in the eye. So in a way on the low level we see this
25:41
but our model of ourselves, our model is making it smoother. So if we agree that we already using seeing in this meta prefix way,
26:01
we can go to the opposite direction and say that I don't see that I see a blind spot because the information is there, it's just being erased before it gets to the model. Okay, so because the meta prefix is my favorite,
26:21
there is a whole big document with it and feel free to go there and make a comment. Okay, another word comunitas. This is example of taking back archaic words. This is a word of a Latin root.
26:41
Let me find the beautiful. Comunitas means unstructured community in which people are equal and the second meaning is that diverse spirit of community. So we encourage use of comunitas again
27:00
and we do it. It's not that we can catch actually, probably like who cares, we are already doing this inside our group. Another one, this was a quick one. This was before we have examples of erasing words or redefining them and using those definitions
27:22
but now it's an example that we took back archaic words. Okay, another word. This is comparison. And this word was invented, if I remember correctly, in something like 1980s in New York City
27:42
by some polyamorous community, they felt that they need the opposite of jealousy. So here we have a little diagram. Maybe I make it bigger if somebody has a small screen.
28:01
So here is my partner. My partner's happiness or success and my partner's happiness or misfortune. And here is me axis. Me happy, me unhappy. So jealousy is when you are unhappy because your partner is happy.
28:21
I didn't know this word. It's kind of nice word which is not in English. I mean it's just borrowed from German. So it's when you are happy that your friend is unhappy. And compassion is when you are happy because your partner is happy.
28:40
This is usually used in the context of polyamory so that your partner has had sex with somebody and you are happy, not jealous about this. So this is next background story. We were just sitting on the balcony and thinking like, wait a minute,
29:00
what's the opposite of jealousy? Can we name it? Do we really have to say the opposite of jealousy or inventing a long string of words to mean this single thing that is normal to us? And so we first leave thinking,
29:21
okay, we have to invent new word. But then I search the web and figure out that there is already such a word. And there was a community who also was trying to invent new words and using it. So we just took it. And this was a very nice moment,
29:42
a revelation kind of. And this is a subtle thing now, the subtle remark about this because we started to thinking about comparison as the opposite of the jealousy. But now we're thinking about the jealousy
30:00
as the opposite of comparison. So by this, we normalize the word comparison. So this is the comparison, this is this thing. And the jealousy, this is the opposite of that. And this shift of words reminds me of adding cisgender to vocabulary to normalize that gender.
30:21
So again, this is, you know, you're not that weird, you know, because you can be transgender or there is no word for that. So they added the words cisgender and this normalized transgender. So this is also for this kind of shifting of weight. Okay, so now two easy and quick examples.
30:45
So the first one is the phrase, Latin phrase, I probably misspelled this. So we just proposed to vulgarize Latin and get away with it.
31:01
Like before, it doesn't mean because, end of the story. Don't use Latin. Nobody knows it. Even academics don't know this language anymore. And another one is a swearing. I'm sorry, I'm not sure if I can swear here. So I just say that this is a word
31:24
in order to, this is a phrase to replace being angry towards animals other than human in cities. So one of our friends, one of us spotted that people get angry about animals
31:43
but come on, like the whole context. About animals in the cities that we've headed to the city and now we have to figure out the way to live there. So this was traumatizing experience for them and now we are swearing at them. Like, come on. So we prefer to say, I would prefer if pigeons
32:04
would adapt in other ways to living in a city. All right. So this is the end example. Now I will try, I will sum up what those examples were about
32:22
and also generalize what we were doing, what we are doing. So from the linguistics perspective we are changing multicultural keywords. So we don't change the like primitive words
32:43
like a group or numbers or place because there is no need for that. They are as basic as possible. You probably cannot go and do anything with them. And what we change is the cultural keywords.
33:02
The words that are charged. The words that don't only refer to... This was the case with aging. It's not only a word in biological terms
33:22
but it's very much culturally charged. And our attempt to change words stems from the feeling that many things in culture we just find them ridiculous. And these cultural keywords are just spreading this ridiculousness.
33:47
So we try to change the culture keywords. The words we find seekers into community sharing of mental world. So we're making a bubble, a nice bubble for ourselves. So our goal is to provoke thoughts,
34:02
promote shift of perspective and make us to avoid or provide shortcuts because words are shortcuts. So we are doing this by redefining words
34:25
with building blocks words. These semantic primitives, as they are called in linguistics, to denormalize. So, for example, country or nation.
34:40
This is one word. But if you start to define this, it's starting to be more and more weird and you see more and more opportunities of how this could be otherwise. So now everybody is using nation and it's very smooth
35:03
and you can say such a ridiculous thing very quickly. So we are attempting to ban words like this or change their definitions and use the definitions instead of the words.
35:21
So you have to say what actually country is and it makes you think about this a bit more. So we are redefining words using the phrase instead of one word. This is an example. We have much more examples before,
35:41
but let's go another one. Natural. We try not to use the word natural. This is a password, a visual word. So we propose to say instead of natural that fits in imaginary order originating from the comfort of the post-industrial world.
36:04
Yes, so instead of natural you just have to say this whole phrase. Because what does it mean natural? It's like no meaning. We like to hear this word
36:22
because we are living in the buildings and we have technology which protects us from nature. That's why it has good connotations. We are reconsidering basis. So for example,
36:42
the use of the first person and thinking about people as individuals instead of as a group in the context. It's also in language. We have grammatical structures to speak about singular individual people
37:00
but we don't have grammatical structures to easy and quickly speak about somebody inside a group or somebody within a context. One thing we propose is a new conduction
37:21
which means in the context of. We can say I con crowd tend to be withdrawn. I con crowd is a singular subject here which means I in the context of a crowd
37:44
and so it's again affordance. So because we have this conduction function it's so easy and this word actually suggests you to use this. The mere existence of it suggests you to use this.
38:03
This makes sentences much more precise and not that longer. We are also trying to ban weasel words so you can see that some rules are similar to the Wikipedia editing rules.
38:21
Another thing that we are doing is creating new words in order to match them to what we actually do. So this was the case for example with this compression word. We have this feeling a lot but there is no word for this feeling. So we're making this word.
38:40
No problem. And we promote this word as I'm doing right now. If it's hard for you to empathize with it you can consider archaic word amnion. This is a Greek word which means a ball in which the blood of victims was caught.
39:02
Now for most of us this word makes no sense. We don't have to have a word for this because the use of it is like minuscule. But if you are in some subculture you have the reverse thing. So you want to have quick words
39:23
to refer to what are you doing. This is a regular thing when you work for example in some specific domain and you work within a group so you are making your own shortcuts, your own word.
39:42
And we are making it also. But what's different is that there are not technical terms but cultural terms. So sometimes they are not referring to the outside to describe quickly some phenomena or some process
40:02
but to reflect how do we think. And thus they are shareable. I can say to you what is a comparison and you will understand it and you can actually start using it. So this is the difference between
40:22
making a word within some specific domain which is not generalizable. Okay. So we finished the part with examples and make a sum up like what linguists could say about this.
40:42
What are patterns that can be spotted? Like what words are we changing? In what ways are we changing them? And now we are slowly going to the end which is shifting between vocabs.
41:00
I refer to vocabs as this creative vocabulary, this body of new words and styles and phrases. So what do I mean by shifting between vocabs?
41:29
So consider politics. Let me take a Christian example which is abortion. So when one side of the political spectrum
41:41
hears this word, they mean pro-life and another side of the political spectrum hears pro-choice with this word. So even though the word is this one they are referring to two completely different words
42:00
and often there is no intersection between these words. So they are using the same word but speaking of different things. It's kind of similar to what we have done. We are changing the background sometimes behind the words. So you can...
42:27
What else you could do with vocabulary, with language? You could try to erase nouns OK, this is a very crazy idea but consider this.
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Your friend is posting on Facebook wall or whatever that they don't know what to do next and are asking for advice should I go to the neuroscience to make a PhD? And somebody answers why go to neuroscience?
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It's like go there, it's a bullshit. Go there, go to IT instead. So this advice, like actually I don't mean anything. You don't have any reasons.
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There is no explanation. It's just like a sentence that means nothing. It's just like go to the place like this. The X is bullshit. So you are erasing the noun. The X is bullshit. Go to where I prefer instead. So you can imagine that there is a filter that erases.
43:44
Here are more examples here in this essay. You can think of it as a filter that filters out certain nouns and making a pattern there. So the noun becomes, for example, what I like.
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So don't go to IT. Don't go where I don't like to be. You know, what I don't sympathize with. So the essay is here and it describes in more detail what I mean here.
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I think the example is exactly the same. Yes, should I get a PhD in neuroscience? So the input sentence is don't go in this neuro-something. Focus on IT instead. So the nouns here are meaningless.
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There is no explanation given. There is no meaning in this word in terms of advice, having an advice. So the output of such a filter without nouns would be don't go into and in square brackets insert what the interlocutor plans to do and add something.
45:03
And then focus on what speakers sympathize with instead. So this is pretty paradoxical because we erased nouns or more specifically we put a placeholder for nouns
45:24
and we actually censored them and now actually we have a sentence which makes much more sense which actually conveys the meaning. So this could be also thinking about playing with words,
45:41
erasing some words and making generic statements what they actually represent. This can be applied in some cases. Another example of this is depolyte type. And this is the initiative in its infancy. It's like the first stage.
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And what they did, what this group did is they created something which is technically a font. So you can install most machines, most computers. And this font is not only about look.
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This font has find and replace algorithm. Very basic find and replace. They have tables with thousands of thousands of words that this font is replacing. So if you type with this font ugly,
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you see you are not, like, you are. So you see, again, you are. This font is not changing this. But when you type ugly, the phrase is not traditionally beautiful, this place.
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And if you try to make like swearings here that we brew or like stuff like that. So in the future, they want to replace the simple find and replace algorithm, which is like totally dumb,
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with a machine learning and apply this as a font. So I'm not saying that this is a nice initiative. I have actually, it's interesting theoretically. I have no idea would it work and would the outcome will be positive or negative.
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But consider that the whole idea in its generality. Like you have a font which applies certain point of view. And it could work from both from the writer and from the viewer. So you could imagine now that you have such a font
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which is, you know, made from particular subculture. So if you type in this font, you know, natural, it's replace fit in imagined order originating from the comfort of the post industrial life.
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Or you type opposite of jealousy and it's replace it with compression. Or, you know, you type to work and it's asking do you mean to work or to labor? You mean work or labor? So this is very scary, especially if we go back,
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as I said, that we go back to the politics when you could imagine such filters for, you know, the ideologies. So you can imagine person on the left typing something and on the right person reading with, you know, right wing new filter
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and they will see completely, two completely different body of text. So this is very scary. But on the other hand, this is kind of thing we have currently but it's not formalized.
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So, as I said before, now people from two different ideologies see the one word which is abortion and the two persons think completely different, they have completely different things in their mind.
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So you could formalize, you could try to formalize this and, you know, make these functions like explicit. And now we're going to the end. And now you can wrap it even more and say like how discussions would look like if you could,
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if you, you know, if you have such a filter like this, like would arguing make sense? Like arguing could be so obvious, like, I mean, arguing this, you know,
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low level, like low, like not like intellectually stimulating discussion about politics, like they could be easily, my hypothesis is that they could be easily reduced to this kind of font which, you know, automatically replace ugly to not traditionally beautiful,
50:45
blurs the words that some speakers don't like and so on and so on. So maybe then the new kind of debates would emerge which would be, you know, actually speaking about language.
51:01
So look, like in my vocabulary when you say this thing, I hear this phrase, like this is what I actually hear, like what I actually feel when I hear what you are talking about. So you could have these things explicit. I think this could make discussions easier.
51:28
Yeah, so maybe another example of, so you could also, so you could see, you know, think about like more functions, like how to move from one vocabulary to another
51:40
and like where are isomorphisms, like in what vocabularies you can go to and then back and stay with the same place when no information is lost. So I think this would be, this interests me, this like makes me, like I want to see it happening.
52:07
Okay, so maybe another example because I think it might be a bit confusing. So context. Alex wants to use gender neutral pronouns.
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Unfortunately, they aren't used to them yet. Moreover, they think it would be funny to change some occurrence of like to use to. They have read about the mere exposure effect recently. Alex is also a fan of satirical novels. Input is what they write in the diary. So here is the input.
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Yesterday Safi was cooking a dinner for everybody. She prepared traditional dishes. I like them so much. They are from my country. And the output, so the output is what this filter, what this kind of font which not only, you know, changes the words like ugly to not traditionally beautiful,
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but it's much, much more advanced could display. Yesterday Safi was cooking dinner for everybody. So this is unchanged. This is like very neutral. Like it's hard to, you know, to change anything there. But you could like if you want to. They, so you see that the filter change she today
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prepared traditional dishes. Like this is also like generic. You could actually implement. The depoly type is the open source. So you could actually try to implement this right away. And now it's, now the funny part. So the filter change, I like them so much. They are from my country too.
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I am used to them so much. They are from my Grand Falun. So first thing it change, the filter change it's like to used to. And second thing is that the filter change country to Grand Falun. So as it was in the context,
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the Alex likes certain satirical novels. So they read the Kurt vonnegut. And the Grand Falun is the word from Kurt vonnegut books and it means Grand Falun, non. Group in which meaning is established
54:21
by a virtue of being in that group probably as a result of the random process. So you see that it would, such a tool would be also a, could be also used in creative ways. Like somebody has read Kurt vonnegut and wants to implement this language to their use.
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So they can just go to openfilters.com and org and just download and apply the Kurt vonnegut's filter and see what some phrases would be changed to if they write like normal stuff.
55:06
All right. So this was the intense part. I think that this is the end. I have nothing to add. So thank you for participating and now I'm waiting for Kurt. Yeah. Thank you Camille.
55:22
Thank you very much. This was interesting and way more complex than expected. I think we have a few minutes or seconds to go for a question. I think I have a question here from the internet. It's linked to your like. It's a little bit like a comment maybe because it would take more time. The question is could you explain
55:41
the widely used word like in sentences like it's just like your opinion, man. So it's part of it. Ah, yeah, yeah, yeah. Yes, yes, yes, sure, sure. So this as far as I understand this means like like as something similar.
56:01
So obviously we don't like change something similar to the phrase used to. This was like implicitly. So like sure we don't want to change this. We meant only with this sympathy meaning of this word. Yeah, it was more like a discussion point maybe there may be some more occurrences
56:22
like this one used as part of a complete sentence. Okay, one more question. It's a little linked to your polite type example because it looks to be very complex and the question is playing with words in other languages. So localizing content is a very complex problem
56:41
and it is often used completely misleading translations. So have you seen other groups like yours playing with words or could your group be starting point to get more information how to avoid these mistakes? Sorry, it was a bit jacked.
57:02
You can contact me with this email because I don't know how much time we have. But here we also have something about this. Yeah, it was about your group and if you maybe a good starting point for other resources. Yes, you can join us. You can send me an email and I basically send you all the links
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and you go to the group and introduce you to the group. So everybody away. Okay Camille, I think that's all for now. So I hope you enjoyed your first talk at the Congress and you will hopefully have more. So next time we see you in person in Leipzig again. Yeah, I hope so. Thank you very much.
57:40
Thank you everybody. Bye now.