we work on free software, we are interested in critical views of technology.. we have been working with a group of 50 artists on the first floor.. the topic cqrrelations. ....waiting that the apparatus is explained... ... .... :) if you are wondering what happened over there...
I would like to invite Silvio, Dave?
Hello Myself and silvio for the last couple of days we have been workin on it.. as a speed project. it is a response to some software, called Pattern
we have been looking at sentiment and modality assessment.. it could be a whole book how objective the author might be
objective is already a philosophical mind field so, pattern writing coach, is linked up to a script if you are annotating this talk annotating this talk on the etherpad this would take the last line of text.. and be judged by the coaches.. this will take the line of the text what do we got? a critic counter! and then we have the diarist share your feelings not be too afraid not be too afraid to show ytour true self especially looking for emotions she is looking for emotion we didn't draw ourselve we didnt draw ourselves I think that is it you are observing us all night long? everything we say will be algoritmitisized?
these guys are artificial intelligence watch what you say! there's a warning there are four academics on the stage three of these tend to speak rather fast three of these slog to mutilate rather fast because i was digusted by law the way how techniques shift the way we relate to the world there are signs without signification, without meaning there is nothing left to represent, there is just data we forgot the specific issue of today, discrimination they dont relate yo anything that people can feel categories are not like ethnic categories
we live in the epoch of the database
there is no national discourse, we are all niche-marketed work through the political system instead of taking data, 'what is given', let's use 'capta', that that we choose to take when we work on the classification of diseases.. the capta that we have is based on specific theories... we are building up medical system according to the data produced.. the particular problem here.. if youre not being captured by big data, you're even more invisible it becomes even more distriminating. eugenics never went away| its been still alive and kicking instead.. what if we can use big data to predict schizophrenia.. thats kind of problematic.. to 'stop it before it starts'. we are using big data to performativ ea particulare normative society to some extent we can challenge big data in insteresting ways. thats why cqrrelations. hardcore analytical philosopher. getting upclose to the techniques spent lot of my time trying to learn in the community of data miners in new york much of my work has been to bring to earth some of the assumptions and omission involved in these kinds of practices consequences often look like discrimination most of these techniques are supposed to be for discrimination i spent some time recently how these kinds of assumption that often look like cases of discrimination, are discrimination largely data driven decisions prejudice, bias in decision making. there is worries about these techniques, but also enthusiasm. employment for example looks excusively at those methods. either consciously or unconsciously there are serial potential for these tools to address these problems even seemingly objective ways can nevertheless be vulnerable to other problems i'll mention a few two ways to be discriminatory to say one is subject to discrimination, and it shouldnt. type 1 error not accurate inference second set of issues dealing with the process being too precise able to carve through population but it might be simple a way to reproduce the problems in society while already being in disadvantage accuracy of these models. we need to be very suspicious to what it means for something to be accurate people who apply this tools, what do they mean with accurate? the labeling of the examples is objective. a matter of fact. to rely on labels as matters of fact
Breslau who interchange this tools , what work up they fall over backwards with accurate ? subjective decisions on what is a good employee what is a bad employee while building models, we rely on these annotation and in order to test the model, we test on things from which we know it's positive. you do not mention datamining or machine learning datamining is something that you mind the word we chose in describing this problems determines how we engage in ti you brought other elements! can you say something about selection of these words? who wants to go first? the idea behind the words I use, is that they denote a translation or transformation in the use of studies it is a LITTLE LITTLE bit technical Robert Musil is the famous author of the man without qualities you can rea dhis fascinations with statistics if theories of probability exist traditional staitstics were selective eveything that was far from average was considered as noise in big data there is illusion of exhaustivity traditional statistics were valid only for great numbers with big data we can take into account wha tis the most far removed from the average idea of average or 'the normal man', the most common are completely avoided in big data with big data we can make do into lucrativeness wha tis the most far removed from the average it seems anormative, without norm, beyond critique of course they are always results of onventions in old days statistics, mainly women had the task to put the categories where do we put that woman who escapes the category? they discussed that amongst themselves! they could be taken as targets for public contestation contestatibility was inherent in classical statistics now we escape this burden it appears anormative at the same time the average man was the ideal man! he had most qulities of human kind for some it was the complete opposite it was felt as oppressive this shift to automatic datamining is emancipatory the categories do not preexist to collection of data they emerge from the data this refers to the dreams of the sixties peace & love! Felix Guattari, Gilbert Simondon idea of dissolution of objects and subjects, replaced by processes of individuation replacement of objects and subject by processes it looks emancipatory I have to convince myself that it is the opposite of emancipation algorithmic government does not target the present, the individuals their objective is to neutralize the virtual, the potential, the things that are not yet there they beat in marketing, surveillance life is recalcitrant to any attempt of excessive organisation anyway that's a bit abstract shall I tell you why I think it is not emancipatory? no do I agree or disagree with what you say? every age says 'we're different' a good worker the definition of good worker feeds back in the moral categories we are using.. ..deviant etc remain constant during the last hundred years.. transformation in statistics has being key how we analzye the data, the huge amounts.. this wonderful concept that bruno latour has.. the oligopticon we are moving away the foucauldian notion of the panopticon that what state wants to do is seeing everything all the time, on all citizens somehow we are not moving in thta big brother world.. oligopticon is something else to take a small amount of information that is enough tp control you there is a strong notion of what constitutes normalities the accepted behaviours going out of which, you get punished. may I? yes you may of course it does not replace other forms of governmentality its the justaposition of course we have standards of normality how do htese standards evolve? they evolve in a viral manner deviating from profiles the algorithm will not detect the deviatio nas failure just another occasion to improve the pattern improve your profile there is a lot of performativity a rebours! nevermind what you trying to do. there will be nothing like an event, breaking out of the profile not conceivable in the digital universe a mere occasion to render the system more efficient the more you disobey, the more you participate it does not go throug the visual episteme at all. we have been rendere invisible to what counts for us benjamin has the desription fo the bourgeois interieru of the 19th century souvenirs, cushions, etc the consolation for the growing anonymity in the public space the assurance of still existing with small objects in the private sphere replaced by blogs facebook etc a subjective interpretation, of course! not by exhibitionism etc.. its just they need the proof to have an interiority. temporaryu aggregates of data, manageable at an industrial level thats the very paradoxical situation a fantastic book about how las vegas uses algorithms to evacuate the interiority they turn you in a collection of data points what they want is to put you in a zone where precisely you have no subjectivity if you take gambling as the image of our time. most of the people in this room are studying.. ? big data big data is marketing speak general purpose artificial intelligence the oriignal work was based on logical expressions that would culminate in "consciousness" hardcoded lines to describe reasoning with enough data, better algorithms! quickly it became evident it was a failed enterprise part because of the program wont work people spread elsewhere teaching machines by example thats rather than deductive reasoning.. just show enough examples after showing enough examples, it learns the feature of a cat a process of induction what is important about this is that there is very traditional categorization a good worker a bad worker defines a set of examples the feature of the good worker can only be with categorizing all the examples is the kind of category that depends on human subjective categorization but its producing something alien the category is indebted to the human but is something alien reasoning distinct from human generally speaking the whole atraction is to depart from how human think new kinds of things that arent categories can you give an example? the employment example I learned recently. TERRORIST you can either pass over the case, or consider an innocent as such what is even an example of a terrorist? people that want to use these techniques have to justify the categories in first place.. rather than harcoding the definition of terrorist you set some examples as ground truth..
when the CIA decided falafel eaters=terrorists... these techniques that are learning from examples.. mean that we can learn only things with good examples for the majority it might work good but if you are part of aminority group.. if you are in the segment of the population out of the norm you won't be assessed. these techniques are directly proportional to the population dealing with employment categories might be terrible if you have credentials from south america.. just because they cant be assessed. problems perceived as necessitating strong intervention from the state are now being refigured as things to be solved with more data data is contributing to the retreat of the state and the dismantling of welfare example? in uk. the way to deal with global warning.. nudging http://lib.estrorecollege.org/view.php?id=425109 you use more energy than your neighbour that should encourage you to use less energy instead it could be influencing decision making.. evgeny morozov. click here to save everything extending the critique to this kind of solutionism. the results are pretty lousy. how much of this is simply simbolic? how much is just showing off? they now create radio stations that automatically define what music you want to listen to without music categories there was a huge push for big data, whether or not it would work. it wont go away, doesnt matter how successful it is. good ol fashioned AI is still getting money whats the impulsion that gets us to go for these techniques? even though they arent working? though some are.. whether it works or not is not the question we have given away the exegesis of truth its a truth regime in a foucauldian way whether it works or not, the predictions will impact the reality it creates the world of today, its behaviours a form with a lot of holes it doesnt contain you completely but traces the future trajectory in blurring ways doesnt matter if it works.. digital market manipulation digital market manipulation ryan calo new techniques of personalized marketing the goal of the practice is not to make you buy something directly but to discover what time of the day you are the most supceptible to some triggers resistance is something that gets tired the more you use it the less you have it by refusing offers for 6 hours, the 7th you will click ? we are not even the authors of our own desires impulses. alerts to react to.. reflex mode rather than reflection in real time. the capacity to recognize oneself in the motives of our actions.. i will buy the chocolate i will eat it as quickly as possible. am i autonomous? i would have wished not to be motivated by such addiction. transform my pulsions into desire. very important capability. lots of definitions around is it just running algorithms and finding the result, or looking at a database? personally i think that profiling and AI is a pharmakon..horrible word? sometimes i have to correct lot of nonsense.. i must admit that at 23 i might no be as objective as the students writing there is software that after correcting the first 50, learn how i correct.. it checks the next 50 and i can correct those.. reinforce what is going well. i'm convinced that we will be using this. somebody said that this will be horrible. it's very important that we move from thinking that these machines are using us, and that we are using them. have a conversation with them. they are anticipating us. they have no interior.. japanese animism. people deal with things as if they are animated we can learn that to contest the machines but by interacting with them we can learn that to social function the machines but by interacting with them people are tired of making choices what a fantastic point! one of the skills we don't learn in colleges is critical reading of databases it is a core role of the humanities in the future if you want to contest a database, you need to understand what kind of queries work, what misses I like the idea of the top 5 and bottom 5% grading is always a subjective phenomenon the problem is funding for education we need to challenge the problem it does work providing we've got the skills what are the skills that allow us to question and challenge? lots of the public say they can't understand YES, YOU CAN it is like before the printingpress we need to democratize the process there is distinction between supervised (with examples) and unsupervised learning (show me the examples you find) there is new approach: deep learning it is a breakthrough Google was able to train a machine to recognize cats it was able to define the features without anyone telling them what they might be this is applied in speech & image recognition it is possible with hugh datasets will be quickly adopted in commercial applications this idea of interacting with the model that you've trained even if you cannot have a comprehension of it allows for something else that is interesting tempt to bring some kind of objectivity techniques can mutliply the interpretations of something bring new perspectives reflects something you don't recognize make you learn something about yourself that you didn't know if personal information is involved, this is dealt with in the law I would use a software for automatic recommendation but you should keep for yourself the capacity to justify the grounds on which you have trained these systems if they make us believe that they dispense us of decisions and errors everything is forgiven in advance because it has been recommended by a machine imagine a context of the prison, risk of recidivism there is much more pressure on the personnal you praise objectivity which I praise as well there is elegance in algorithm the marionette's theater, Kleist why do you go and look at dancing marionettes, because you dance so well because the grace of an inanimated body is so much higher because they're not affected by emotions that is why they're naturally balanced in order for humans to succeed this they must be or completely ignorant or they must be god we have the impression of having all the data and at the same time we do'nt know will datamining be more often in a relationship with us where it dominates us? or will it be used as tools that anhance us? what kind of relationship do we want? we've been looking at the figure of the annotator, the person that scores the training data in that difference between a conversational relationship and training relationship there is the difference how you can relate to the tool think about the context this software has been produced in the political ideology of the persons who annotate, or do the grading the conversation should allow you to stop as a feature inside the software thanks I share your sentiment wht is dangerous about discussion that focuses on the performativity of these toold, we focus on the foreground, not the background predictions will prove to be true if the background conditions will remain the same we're failing to ask: why don't we focus on the background of these tools that some people have more difficulty to access to good education government by the fact facts are governing us facts being data without explaining why these data are how they are the fact has not by itself any value it presents the background as something natural we cannot change the neoliberal society as the natural landscape some people prefer to have algorithmic discrimination because it will allow them not be screened out the most normal people in this case the tiranny of majority algorithmic screening will increase indirect discrimination against the most vulnerable people that is convenient for the majority what is lost here, is the idea that pretended objectivity is not judged and the possibility to contest the categorization traditional mechanisms can still apply here we can perform research that shows that a part of population is burdened more than others it is important that analogue techniques can still do that some seemingly neutral decision has impact on part of the population people who can assess these decisions, their impact, can do a lot of good work it will be difficult because algorithms use different kind of data some are structured, some are less structured there are different logics implied when machine learning is involved things become more opaque it needs time to prove that it is discriminating you can look at actual decisions and run experiments on that social scientists are happy to treat decision making processes as black box how does this all afffect ways that human hebaves? using categories schemas etc, we still keep thinking in that terms.. we are ? using these for thousands years ? even as a children, continously asking whys.. we try not to go into a system. but it will make mistakes the moment of the decision if a prisoner would be released or not this gravity moment, that carries some autonomy, the decision has to be attached to knowledge otherwise there would be no autonomy.. the iron cage of bureaucracy prescriptive for human behaviour. lets imagine a discrimination on the base of an algorithm. who do I sue? state/company/coder/etc.. who do I shout at? :a very sexist slide. language use by female and male users of social networks shopping/cute/cats vs fuck/football/sports who do we shout at then? the nature of knowledge.. one condition is very connected with ethnic categories.. but ethnicity is not a genetic category. so they deliberately produced other graphs no mention of ethnicity.. interpreting the graphs reinserted them though it's very hard to get out of these categories. one of the problems is: what does it mean to be human? seeing myself to be a unit might be a category error.. i'm being created by a system.. we should reconsider the claim that data is the end of theory i want somebody to shout at. it's behaviourism gone wrong.. isome similarities. first step: don't assume you are autonomous then start to reconstruct the causalities etc.. //has to deal with the phenomenology of the machines.. i like this tumblr where face detection is applied and it finds non humans. what is interesting is that then you kind of compare the times that humans find faces as well and some that are completely absurd. reveals something of the phenomenology of machines. not treating classifications as errors or symptoms of something we dont have access to another important study related about accountability/shoutability itold by a colleague that name on google suggested an arrest record using distinctively black names, there was a difference, in being more likely to have arrest records than with white names. by multiplying the amount of advertisements and the likelyhood somebody would click on it.. so people who have been exposed to these ads were clicking.. so prejudice of the users filteres as prejudice of the algorithm! who is responsible in this case? users/company/algorithm/robots? a minimum discrepancy when advertisement have to deal with race.. unclear who is responsible google corrected that "mistake" about human stereotypes.. they live long that's for sure. but in fact there is a competition between two semiotics. the semiotics through which people experience discrimination and the machinical layer as well, with a-significant semiotics made of 1 and 0 writing degree 0 there is a gap two modes of expression and experience can we call stereotype somethgin made of 1 and 0? 001010101110101010101010101010101 we want reality. not realism, reality as such. we don't want to touch reality yhrough language. the refusal of representation as such, and all mediations. too late compared to real time facts. we will keep stereotypes at human semiotic level.. but the other leve lis something else. about the role of knowledge in decision; uncertainty is what gives decision the value politicians obviously forgot about this. the gesture of decision always fails. the tragedy of failure we want to expel from human experience.. errors failure we all die. 01 i completely agree. algorithmic normativity appears as anormative consequence and naturalizaiton of social normativities, that become unspeakable and unvisibile cos they have been translated in 1 and 0s 1010101010101001010101101 don't rely on unreliable sources