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"Initial text: We discuss reading methodologies. For both the text we will read and for each other. One of the challenges of a slow reading group during a pandemic: how to read each other if we are to read together. Extrasensory signals are not legible. A new sign language needs to be established. The nod, the shaking of the head, a facial tick, too subtle in a grid. We need unequivocal actions - the waving of hands to signify agreement, a thumbs up - so that meaning is transmitted automatically. When reading the group through the screen, we search for disturbances, anomalies in the field.
Reading between the lines, reading between the actions/unmuted words: What occupies that “between”? What does silence or inaction mean in this context? A bad connection? Hesitation? Uncertainty? I think about delays. The delay between thought and action. The delay of an extra stop because you gotta swing by the unmute button on the way to action. And when there’s the delay of bits transferred per second, so what you’re seeing has happened sometime in the past, how do you react to each other in a timely manner?
""" Generated text: (from https://deepai.org/machine-learning-model/text-generator)
Reading from both halves: What causes this delay? What is your understanding of this moment in time? Your understanding of the state and that it will change. What can you and I take for what you've just said?
Reading in the light"""
FEBRURARY 16 MEETING NOTES (reading of Computing Machinery and Intelligence, Alan Turing)
A. M. Turing (1950) Computing Machinery and Intelligence. Mind 49: 433-460.
6. Contrary Views on the Main Question
We are listening to the sound of the above server.
And then we will read the 9 Contrary Views.
Hello :)
Reading: Computing Machinery and Intelligence by Alan Turing. We start with the 9 objections to the view.
Introduction to Turing and his life.
Can machines think?
Opinions will differ on this problem, we need to pay attention to all views.
Turing's own belief: the question in 50 years will be different because we will have faster computers, which can play the imitation game, they will fool us.
The question is meaningless, at the end of the century (20th) we will be speaking of thinking machines.
Conjectures are of great importance, so let's consider the opinions which are opposed to my own.
1) The theological objection: God-given characteristic of intelligence. Turing calls bullshit. Also: if God is almighty, then he can give machines intelligence too. If humans can make children, they can make intelligent machines too.
But difficult to say things are to be seen in purely scientistic terms. What about spirituality?! (Danae) Vitalism also enabling more environmentally-conscious practices.
What about Shinto? (Sieta)
What is very nice about what he refutes is that he talks about Galileo, et al and says: you religious people are the flat-earthers... (Renée)
Quote from Margullis and Sagan on us being inventions of bacteria (Linda)
Yes! And the thrown-around AI trope "we won't be much else than the gut flora of AI" (Sonia)
The religious narratives remain present, whatever relations we speak of: humans and non-humans, machines and non-machines (Renée)
James Lovelock quote: we anthropomorphize machines, so our successors should be, too. The uncanny: strangeness arising from that which is not "quite right". But we cannot imagine anything intelligent that is not like "us". [Lovelock, James (2019). Novacene: The coming age of hyperintelligence. Allen Lane.]
2) The "heads in the sand" objection: scared of machines. Why should man be considered 'superior'? Consolation would be more appropriate than refutation in the case of this argument...
The anticipatory potential of doom-scnearios, it's not always technophobic (Danae)
3) The mathematical objection: in logic we can see that there are limitations to discrete state machines, e.g. Gödel. Something which remains unresolved, neither proved nor disproved, when we need "yes" or "no" answers. There are questions which of course require more, and machines may get stuck. There is certainly something to this conjecture. But in general, we can also classify it under the category of "human superiority" conjectures. The imitation game is also a refutation to this conjecture.
(Sonia) explains the Gödel problem, barbers.
(Agathe) nowadays we deal with different problems in AI, we're talking about patterns in data and less about logic problems. Humans can also give wrong answers, depending on the type of question and how it is posed.
(Danae) But this is the problem of discreteness, indeed, how do you get these static answers. The discreteness is not a problem, the meaning is contained within the interrogator.
(Sonia) yes! Meaning in the making. No capital M meaning.
(Michelle) if Turing was to rewrite this text now, how would he re-write it.
(Renée) I think he would use different pedagogy.
(Danae) Yes, but also, he's talking about how this question is not even really relevant.
(Michelle) Yes, this goes to the question of what is it to be human? In this very Euro-centric colonial landscape, it's very interesting to think about this aspect. If he would be embracing today's decentering, anti-racist practices, etc. Especially to the question of what is learning, etc. What does it mean to be alive/part of a society?
(Sonia): it would be really interesting to think about an event where we invite speakers to think about what Turing would have thought of X or Y.
(Renée): (after we talked about hormonal castration) what is very interesting is also "oestrogen". Hormones are literally what wire and rewire us. It's interesting to think about the answers would be, to some questions we can speculate about.
(Agathe): nowadays computers scientists wouldn't really be encouraged to write these texts, so I wonder if that's the case he published it it in a psychology/philosophy context. In CS nowadays you need to build new tools and not reflect on existing ones. I wonder how this was in his time.
(Danae): nowadays things have become very segregated, and in the humanities we demand interdisciplinarity. But there's very few people who are actually doing that. There are not many people doing interdisciplinary work.
(Agathe): it's very frustrating, when I work on more critical stuff, I get told that I shouldn't because I should be finding solutions to things and not coming up with more problems. It's a political question in the end, people have agendas.
(Sonia): yes, the main line of attack from the humanities is indeed this idea that we have to counter this scientism-solutionism... etc etc.
4) The argument from consciousness: "Not until a machine can write a sonnet...." The refutation for this conjecture is solipsism: we also don't know what and if people feel when they feel.
5) Argument from various disabilities: (Sonia:) the modern version of this is the "AI is whatever we still can't do with machines". No support is offered for these statements, acc. Turing. Induction is the key issue w/ this conjecture. One has not yet observed a machine that can do X, so a machine "can't do X".
our notes drop out as Sonia reads half of Arguements from Various Disabilities and Renée picks up. Sonia will write these after the meeting! The machine is its operation, and the operation is the machine.... These are the possibilities of the near future, rather than Utopian Dreams
6) Lady Lovelace's objection: a machine can do whatever we know how to order it to perform! Refutation to the conjecture: yes, but this doesn't meant that we know exactly what the consequences of our order are. So, we may be surprised by the result of what we order!
7) Argument from continuity in the nervous system: the nervous system is not a discrete-state machine. But looking at randomness in pi, we cannot actually distinguish between the behavior of a human or a machine.
8) The argument from informality of behavior: the endless possibilities of behavior. There are no rules to behavior, so the human cannot be a machine, the human is free to act. (Sonia: side note, the chemical basis of morphogenesis from Turing is also a beautiful refutation of this)
9) The argument from extra-sensory perception: telepathy, clairvoyance, etc. Unfortunately: we cannot take this seriously thus far, we cannot observe any of these things as actually existing.
Michelle intervenes with Sadie Plant's Zeros and Ones, reading from the section on Ada Lovelace and Babbage: Complete text found here: https://monoskop.org/images/1/17/Plant_Sadie_Zeros_and_Ones_Digital_Women_and_the_New_Technoculture_1997.pdf
*Some more notes while going through the 9 points:
Point 1.
Thinking about religion and its relation to science is in many respects is indicative of his time.
The text was not only meant for other scientists, but also accessible to people outside these circles (still Western though).
A refute of religion based on the belief that only humans have souls.
It is worth asking the question of whether we see ourselves in the center being beyond or above machines. Danae refrenences a text on space settlements that she is reading. And she quotes Carl Sagan saying that it was challenging to create the settlement as it was too difficult to recreate the earth.
Danae opens up the question about religion, not in terms of its restraints or prohibition, but instead its potentialities.
Sieta raises Shintoism. To be burried with your computer as a kind of life force. Perhaps the animisim of the machine. The vital force in everything.
Vitalist materialism.
Straw Dogs by John Gray - we are ourselves techonological devices - and here, he speaks of bacterias as technology (from Sagan and Margulis)
Humans being the gut flora of AI.
Sieta reads from James Lovelock:
referencing Freud and the uncanny - of dolls and robots and their resemblance.
Point 2.
Being scared of machines....
Is this a Luddite arguement?
Danae proposes a speculative approach - one which is anticipatory and is not technophobic.
Point 3: The mathematic objection:
What is the scope of the objection - is it about simply limitations or more profound?
Gödel's incompleteness theorems:
https://en.wikipedia.org/wiki/G%C3%B6del%27s_incompleteness_theorems
Agathe speaks about contemporary machines functioning in a very different way than they were in Turing's time. Now machines can break this paradox, but perhaps with the wrong answer.
She brings up the point that sometimes the question itself is unclear.
Danae declares her love of math. And she connects it to her work on oracle bots.
Rather than a problem of the mathematical capabilities of the machine, it can instead (missed this part) (be a problem of the receiver?)
machines produce mathematical fictions
If Turing was to re-write this text in the present, how would he re-write it?
What is it to be human?
Would he reframe his work under more post colonial framework.
What would be the questions you would ask him if he were here?
We can't speak for the dead. But if he were in the room, what would be the questions we would ask him? For example, what would he think of drones?
Mr. Turing
Hormones. In relation to Turing's castration.
Questions as a form of reading.
Nowadays, scientists would not be encouraged to ask the same kind of questions. He wouldn't have many incentives to do that.
Sonia wonders about reading Kittler (thanks) and suggests reading Alicia Juarrero.
Agathe - mentions the trenches of disciplinarity
For next week we are going to read: Alicia Juarrero's Dynamics in Action (Chapter 15):
https://aliciajuarrerodotcom1.files.wordpress.com/2012/02/dynamics-in-action-pdf1.pdf
Michelle suggests and adjacent reading of Juarrero-and...? Sonia and Danae lean towards Maturana.
Sonia suggests we read the last chapter (15) of DiA. If you want to familiarize yourself a bit with the context of the book, do have a look in advance, but the last chapter is relevant to the questions we were left with after reading Turing's objections, so it's gonna be useful I think!
FEBRUARY 23 MEETING NOTES by Anna (Reading Introduction to Autopoiesis and Cognition: The Realization of the Living by Humberto Maturana and Francisco Varela)
[Maturana, H. R.; Varela, F. J. (1991-08-31). Autopoiesis and Cognition: The Realization of the Living. Springer Science & Business Media.]
- (Danae) both Chilean biologists, their theories have been very influential
example of autopietic systems can be Bots.
- 1st chapter is about how life is organasised when does the organism end and the envirohnment begins, are they part of tha same systems? to answer we must have clear the idea of what is a living thing and what isn't
- Introduction: the concept of unity coexists with the concept of diversity, only then you can consider the concept of infinity.
- (Michelle) where is the direction of the text going? the concepts are presented in a binary sense.
- (Sieta) we are reading these texts to understand life better. WE ARE THE OBSERVER AND THE OBSERVED. It is dualistic but in a way it feels unifying.
- (Cristina) unity is an interesting choice of word.
- (Renee) examinating the quote from Henderson. (Sonia) you think that in order to understand Life there needs to be a division in variables of different types of existince.
- (Michelle) Mark Lewis (Lynn Margulis), the questioning of the evolution tree. There is a hierarchical way of looking at the concept presented in the introduction, which is presented in a binary way. Lynn Margulis', evolutionary biologist, research has shown that the evolutionary tree is not an accurate model. Instead of a paradigm of verticality where species move up the evolutionary tree, her research has shown that a majority of organisms practice a horizontal transfer of genes.
- (Danae) Reading this text in a less human-centred way through the shared unserstanding that we are 21st Century evolved beings, therefore shifting the understanding of the binary way in which the concept is presented. The text has a philosophical framework in order to relate to the understanding of livig systems substaining themselves. Also including non living things and systems.
- (Sonia) Aristotle in relation to causes: humans choose their own causes (?).
- (Sieta) the separation from the mind makes me feel like that it is very mindbased, when I read Meeting the universe halfway, she writes clearing up the concept of separation, and shift to a paradygm of thinking, and talks about this unified field that exists whit the idea of separation
- (Michelle) "sympoiesis means to make from, it is a word for worlding" Haraway
- (Sonia) we are chosing to identify ourselves as different from what surrounds has.
- (Noemi) some times it feels forceful to draw this (imaginary) line.
- (Michelle) The paradigm is focusing on a specific area, however, if we make the scope of the research wider, then there is a shift, from micro to macro.
- (Renee) This distinciton can be alienating andf have a negative impact, but at the same time it allows us to find the universe in the particular.
-(Agathe) defining entities, you have a set of attribute that you can perform, then later categorise them and chose the image you want to give to classification. Many don't question subjectivity.
-(Sonia) Leopard and tree example. We are atoned with the concept of leopard because it is part of an collective instinct.
- (Agathe) there is more reflection to sub jectivity now, but it is still more to work on. Now there isn't the category "clutter".
- (Cristina) collective data collection; there is this separation between background and foreground collection now.
- (Sonia) realisng that the Captcha has a small American data set.
- (Renee) Book about the concept of undifferentiated and indistngusheable
- (Danae) theory about contingency, how it is important to recognise the existence of relations.
- Telenomic - carried out with a goal
- Hazard - Arabic root Haz-zahr - dice game of chance
- (Michelle) how much of this concept of contingency is taken into the research process?
- (Sonia) life is self contained, we cannot ignore that there is a chain of events but we must consider that these events matter
- (Sonia) contingency is a necessity when looking at the universe. Its a very pragmatic approach. Reformulating explanations.
- (Danae) The notion that living systems allow for comparative analysis. Vital force in non animistic.
- https://www.youtube.com/watch?v=gJSJ28eEUjI&ab_channel=BanffEvents intersting related to the idea of animistic view in science
-(Michelle) Arturo Escobar's book where indigenous knowledge (feminist indigenous knowledge) is brought into the scientific conversation.
Renée and Anna's notes done in the form of a telegraph where all:
Danae introduces Autopoiesis and Cognition: The Realization of the Living
Book by Francisco Varela and Humberto Maturana
|||STOP||||When you try to arrive at a definition of intelligence, much falls through the cracks.|||STOP||||
|||STOP||||Where does the organism begin or end? What is necessary is to have clear ideas about what life is? |||STOP||||
|||STOP||||We have this idea of unity. And autonomy as a property. In order to have anything, there first must be differentiation or difference.|||STOP||||
|||STOP||||How is this system relational?|||STOP||||
|||STOP||||Embodied shift.|||STOP||||
|||STOP||||Programatic language present in the text |||STOP||||
|||STOP||||Historical bias manifested in dualist thinking, relationship to "unities". Viruses are living forms too|||STOP||||
|||STOP||||Are dualities gradients?|||STOP||||
|||STOP||||Thinking through parallels to the Genesis story, how it also resulted in differenciations|||STOP||||
|||STOP||||Descartes' bad rep. Language of science as being a unifying language. Rationalism. |||STOP||||
|||STOP||||Karen Barad's Meeting the Universe Half Way is not putting away rationality. Paradigms of categorisation.|||STOP||||
|||STOP||||Sympoesis - nothing is autopoiesis, things are never alone. A word for worlding.|||STOP||||
|||STOP||||Fruit flies. How is contingency defined within the models presented in the text? Seems to be missing at the moment.|||STOP||||
|||STOP||||In AI certain decisions are a bit random.|||STOP||||
|||STOP||||Clutter - what models do not account for in separating objects within an image (but also what humans do not account for).|||STOP||||
|||STOP||||Clutter in relation to the text.|||STOP||||
|||STOP||||Necessity and contingency are the same depending what is the starting point; how you look at the universe.|||STOP||||
|||STOP||||Etymology of 'hazard' - the name of a game of dice|||STOP||||
|||STOP||||Chains of events matter|||STOP||||
|||STOP|||| Renée loves this sentence: An explanation is always a reformulation of a phenomenon showing how its components generate it through their interactions and relations.||||STOP||||
||||STOP||||Machines and living systems allows for comparative understanding of both||||STOP||||
||||STOP||||When trying to paste the last question from the text, I get: 2Uc 4Sc U0&c HO/G7_ U4HBc H)c<4Y4E/cS^SU&>Sc\0Uc ;7B#cH)c> 04B&ScO&cU0&^cB#c0H\c4ScU0&4OcK0&BH>&b BH4B&#c ^cU0&4Oc WB4UO^c HO/B8aU4HBc||||STOP||||
MARCH 2 MEETING NOTES by Anna (Reading of Dynamics in Action by Alicia Juarrero, Chapter 15: Agency, Freedom, and Individuality)
[Alicia Juarrero, Dynamics in Action: Intentional Behavior as a Complex System, MIT Press, 1999]
Sonia: introducing text. Conception of limits, how constraints affect each other within organisms and advances. When is something called intelligence? Deterministic result of perception.
Renee: difference between wink and blink?
Sonia: its confusing. It all depends on the context. information theory ex. you try to define signal and noise, when communication is made. In order to understand you need to take into account the meanings and context where the communication lies.
The basics. depending on the information you are trying to get you will either undesrtand 'wink' or 'blink'
Renee: adjacent reading. question to Danae
Sonia: randomness in terms of quantum floctuation is what gives life to consiousness and free will. and if we are determinsit beings it doesn't really matter based on ethic.
there's a conversation, you become a person out of 2 people's cells, but then you become something that has an influence on your cells. (food, habits...) It used to be very DNA centric, but epigenetics came by to kind of dismantle that idea.
in the case of singular progress, as we become more autonomous (zigot) it becaomes more self sufficient, but as organisms we are inclosed in an environment. we adapt. so the more autonomous an organism is the more it needs to externalise its needs. (discovering fire to be able to make meat more digestive)/ that puts the stomach out of the body. (car are the legs) and this is relateed to observing related to environment.
example about the super inteligenc book. Creating an AI that goes out of control. papaerclip scenario, it goes out of control and turns the whole world into paperclips. but that is THE GOAL, the more robust the more we as humans think about the result coming out of maximisation.
Danae: autonomous providers. Some people in this network are trying to produce some type of computation under the logic of containerisation. To organise systems today, which can be related to the idea in the text, the logic that if the goal is met the system will be freer. Therefore, you will battle between the level of freedom and systems. MAybe we do not desire the system to be autonomous, because it has a political effect.
Sonia: she's not necessarily connecting freedom as 'good'. but she's more quantizising the levels of freedom.
Danae: its easy to connect 'free' with 'more objective'
Sonia: in anarchist systems i was working with systems.
Cristina: i was curious about containerisation. and how would that be worrying?
Danae: containeristation requires an amount of new skills, so we are in the midst of this problem, sustaining a more conservative system or embrace a new one? MAny people were worrying about the provision of safe systems within containerisation.
MARCH 9 MEETING NOTES (continuing to read Dynamics in Action by Alicia Juarrero, Chapter 15: Agency, Freedom, and Individuality)
[Alicia Juarrero, Dynamics in Action: Intentional Behavior as a Complex System, MIT Press, 1999]
Renée: value-ladenness and Aristotle, what about the specifity of relying Aristotle, external values and internal values versus what we would consider now as different approaches to the concept of freedom/action.
Text: human ability to project meaning (Dupré). We excercise free will when we project meaning; this is autonomous. Self-organized systems act from their own point of view. The more complex its behavior, the more autonomous. The more complex an organism, the freer it is, because it has many states it can access. Intentional human action is free to the degree that we put values and morals to control. These levels free up qualitatively more. [referring to Juarrero, para 1, pg. 249]
Sieta: I read this as the freedom of taking an action in the sense of two ways: depending on neurological organization (physiological functions), we either have more of this, or also the point of expressing your values; if one is free to express oneself.
Anna: I think I agree, if you are the product of your context, you act in a certain way, but also you are the product of your physiology.
Cristina: I was thinking about acting randomly or acting intentionally, in the sense of acting according to your values and the development of an intentional trajectory.
Sieta: but an intentional trajectory would be within the context of the environment that also constraints, does that allow for less or more freedom?
Text: robustness and akrasia, the central lesson of complex adaptive systems is that when everything is connected to everything else, we cannot isolate the problem. We have to take dymanics and context-dependence seriously. Attention must be given to developmental settings of complex beings. Why do people become who they are?
[referring to section Robustness and Akrasia, pg. 249]
Sonia: time, trauma, experience and the influence of media: https://asc-cybernetics.org/2008/HM-08WienerComments.pdf
Michelle:
"Transformation doesn’t happen in a linear way, at least not one we can always track. It happens in cycles, convergences, explosions. If we release the framework of failure, we can really that we are in iterative cycles, and we can keep asking ourselves—how do I learn from this?
Emotional growth is nonlinear. It feels really important to me to include pieces on grief and emotions in this book because, as people participating in movements, we are faced with so much loss, and because we have to learn to give each other more time to feel, to be in our humanity. Not to come to a standstill as a movement, but to take turns actually feeling what is happening to and around us, and letting our feeling help us understand what we much do. Because that is what we are creating, a world where we can feel ourselves and each other and do less harm and generate more freedom." [adrienne maree brown. Emergent Strategy: Shaping Change, Changing Worlds. AK Press. 2017]
Michelle
4:51 PM
adrienne maree brown - Emergent Strategy
mi
Michelle
4:52 PM
NONLINEAR AND ITERATIVE
The pace and pathways of change."
Sieta: how does the body relate to this also, because memory happening in the body is indeed not a movie playing 'in the environment' but memory at a cellular level.
Linda: I think it's interesting that we're talking about reliving the memory, it's not a filing cabinet, you relive it and you also change it as you relive it, your physical response is a kind of motor that drives the story, there's the feedback cycle of your body makes your neuros fire, which make the body respond, which makes your neurons fire, etc.!
Noemi: the breath and going deeper into the body, we can look at it as something that relates the mental and the physical, not just as something that contracts and expands. And of course the breath is also influenced by the environment. You breathe differently if you are in the city or in a forest, that makes me personally very aware of my breathing as well.
Sieta: So, the human having this autonomy, having free will, alright, but if you look at the relationship between you and the environment, and you understand that your well-being is related to the air in your environment. It's not just me being autonomous, it's my dependancy on the environment.
Michelle: whether it's bad air or good air, the time when you stop breathing is when you take your last breath. Breathing is automatic and out of our control. You can try to control it, but breathing in and of itself, you can't control.
Renée
4:59 PM
btw: this is one of the most moving books I've read about breathing... Blackpentecostal Breath: The Aesthetics of Possibility
Book by Ashon T. Crawley
Text: I cannot decide the stability of my plan, depends on dynamics, dispositions, contextual constraints. The system should be buffered from perturbations of all sorts. Robustness is the sedimented result of an agent's original internal dynamics and the environment. Exactitude of action is robustness.
Sonia: Robustness as resilience: how long can you stay under water, how long will you resist in the cold, etc. The plan being in agreement with the result of the action is a form of robustness.
Linda: perhaps animals that are not humans can be considered as freer than humans, because they are not constrained by the limits of morals etc. We have contextual constraints that limit our behavior, even in tiny niches: even here! The anarchist values, the feminist values, etc. Q-anons are free, perhaps, they believe this "system" and they just act on it.
Sonia: Agreed. Which one is top down & which one is bottop up? Eg: communists gain the freedom to operate within a collective as opposed to the libertarians. In the sense of comparisons between human and non-human freedom, the perspective of the dynamical system matters. Sometimes a system of morality is also inhibiting action
Linda: so the freedom we are talking about then, is it the freedom to be a finger while knowing that you are attached to a body?
Sieta: people who stick to one ideology often think that there's only the finger, it seems to me. It comes down to separation or networking, if I think of the whole system of fingers I cannot say that there's no structure, for me that's the way that I relate to it. What is the truth of freedom in this?
Michelle: Hardt and Negri on love, forms of assembly and the robustness of a system. The system of the fingers being the same, but also the diversity of a system where the fingers are not the same. (i.e. diversity = robustness)
Cristina: there's also other animals who collaborate, it would be interesting to look into that as well.
Michelle: what is the relation of the individual to the collective.
Renée: akrasia and weakness of will and freedom, are both equally dependent. "The intention 's overall robustness is the weighted
sum of its robustness under each of those conditions . In other words ,
whether or not an intention is robust will be a function of the historical
and contingent sedimentation of ongoing , unique interactions between
the agent's dynamics and his or her environment : how vulnerable it is to
noise and equivocation , in short . The degree of robustness of individual
attractors , therefore , is not a feature intrinsic to them but is dependent
rather on the overall system's "general, underlying " nature . So is akrasia,
or weakness of will. (Juarrero, 250)" So the random or the movement of a jellyfish, they're both bound to the completeness of the system.
Text: Robustness/vulnerability is bound to many factors. Environment and internal dynamics, individual attractors cannot be isolated from others: warp and woof of a fabric. The ambiguity of the term "integrity", used to describe a person's character or a system, spans both these meanings.
Cristina: ADHD for example can be seen as something which relates to the environment much more than previously discussed. Distraction and attention in relation to the will.
Michelle: the dialectics of attention and orientation, thinking in terms of transformation and emergence. The dialogical in lieu of the dialectical. guerra di movimento vs Guerra di posizione (Gramsci).
---break----
Text: one advantage of dynamical systems theory is that it can handle self-cause.
Interjection: everyone looking into Ruth Benedict guilt-based versus shame-based.
Anna: apparently Benedict talks about Americans as guilt-based, Japanese as shame-based.
Text: the implications of dynamical systems for human development are vast. "We still cannot identify those thresholds of psychological or
emotional disequilibrium when intervention would be most effective
. Making matters worse is the fact that since in practical terms, each
run of a complex adaptive system is unique, educational and child -rearing
techniques that might work for a Hannah may not work for a Gabriel .
And techniques that might have worked for Hannah yesterday may not
today ." (Juarrero, 252)
Renée: interesting how knowledge acquisition is different at every stage, every day you are a new learner.
Linda: I'm trying to wrap my head around attractors: at the conscious and unconscious level, there are things we decide upon and there are unconscious things that are happening in the background. In the case of shame and guilt, these are things that you integrate at a very early age, so they become part of the background dynamics that influence your behavior unconsciously. But the top-down influences the bottom-up, and vice versa.
Sieta: I would love to read a bit of this book on conditioned behavior: "an overstimulated nervous system". (Sieta can add note later?)
Sonia: If you are sensitive to complex systems dynamics, reproducibility is harder to achieve.
Linda: RE: ethics in AI. At which stage do you introduce the ethics and that framework? Is it too late to introduce them now? Do they have to be introduced in the beginning or can they be encoded later?
Sonia: When working at UN, they wanted to be THE people who make THE ethical guidelines for AI. But what she's underlinning with wink and blink: from the moment you act, the ethics are already baked into the act. An action will already exclude other possible actions. Transparency is better than unbiased, because it is impossible to be unbiased. But of course AI capital making relies on secrecy to make monetary gains.
Anna: Is ethics the potential of making an unbiased system?
Sonia: yes, it's part of it. Eg: what is a cancerous cell? A doctor would have the expertise to say which it is, but someone else's expertise might have another opinion.
Anna: machines are unethical. To create a machine that is potentially unbiased machine can be addressed with a representative team.
Sonia: yes, but how many people do you include? Do you include nonhumans? That's part of the complexity of that choice. Sometimes the case is ethics-washing.
Agathe: how to relate machine learning to this complex system theory? Also AI is a form of complex system, it learns from what it knows previously. There was a paper about robustness recently. But it doesn't discuss that different people have different biases. When we talk about fairness in ML the decision is usually to "de-bias" the system but without reflecting that you will not be able to take into account all possible contexts. ML has its own constraints. It requires you to categorise the world in order to make decisions. Vocabulary is similar to ML communities.
Question: How does this notion of bias relate to machine pedagogies (also relating to Linda's question about when to introduce these 'ethics' into AI), could a machine also be learning over time and space?
Renee: Renee talked about the video with Maya Indira Ganesh in conversation with Nishant Shah on: do datasets just grow? Are they responsive or inclusive? Renee found the names of the researchers mentioned. She reads out part of the discussion. Speech vs silence: if you have speech you are an author, if you are silent, it is a pathology which needs to be cured. To force somebody into speech is yet another act of violence. Don't fall into politics of hope or despair, but look at politics of reticence. Give ppl safe spaces where they can say: I have a voice, but I refuse to make it heard to you. I refuse to make my language palatable to your ears. I am here but I do not want to be included, to be counted. What appears to be inaudible, what appears to be out sight still influences the system.
https://www.youtube.com/watch?v=Dwr5ax3zek8
Linda: I also have this problem of being involved. Talking as a dyke, there is an aspect of performativity that you need to have. It becomes more constrictive due to what the system allows for queerness. That the silence can have some influence or power is interesting.
Sonia: When you think you are being inclusive, you may also exclude the people you are not aware of. Anecdote about NY: wonderful communities of minorities that were never previously visible before becoming visible, but also wars about who can be where. Recreating systems of oppression.
Linda: the freedom of not being nameable.
Renee: what does that mean in terms of datasets? Conundrum.
Cristina: reading from a text by Mimi Onuoha:
https://github.com/MimiOnuoha/missing-datasets
"Missing data sets" are my term for the blank spots that exist in spaces that are otherwise data-saturated. My interest in them stems from the observation that within many spaces where large amounts of data are collected, there are often empty spaces where no data live. Unsurprisingly, this lack of data typically correlates with issues affecting those who are most vulnerable in that context.
The word "missing" is inherently normative. It implies both a lack and an ought: something does not exist, but it should. That which should be somewhere is not in its expected place; an established system is disrupted by distinct absence. Just because some type of data doesn't exist doesn't mean it's missing, and the idea of missing data sets is inextricably tied to a more expansive climate of inevitable and routine data collection."
Renée: next session: what about allocating the first 20 mins to wrapping this text up. Adjacent: Agathe show + tell dataset ins and outs, and we watch something.
Chat:
Renée
4:13 PM
https://jubilee-art.org/?rd_news=2772&lang=en
mi
Michelle
4:15 PM
https://ethertoff.caveat.be/w/Eleni_Kamma::The_Corners_of_the_Mouth.md
so
Sonia
4:21 PM
Google deep dream as human-induced AI hallucinations? --> as a practice :D
si
Cristina
4:22 PM
Michelle, I think caveat is using ethertoff, which was developed around Etherpad :) it's a great tool by OSP
mi
really cool deep dream tool: https://colab.research.google.com/github/tensorflow/lucid/blob/master/notebooks/differentiable-parameterizations/appendix/infinite_patterns.ipynb#scrollTo=AZ9jgnMCRBB-
cr
Cristina
4:26 PM
https://aliciajuarrerodotcom1.files.wordpress.com/2012/02/dynamics-in-action-pdf1.pdf
mi
Michelle
https://asc-cybernetics.org/2008/HM-08WienerComments.pdf
mi
Michelle
4:51 PM
Transformation doesn’t happen in a linear way, at least not one we can always track. It happens in cycles, convergences, explosions. If we release the framework of failure, we can really that we are in iterative cycles, and we can keep asking ourselves—how do I learn from this?
Emotional growth is nonlinear. It feels really important to me to include pieces on grief and emotions in this book because, as people participating in movements, we are faced with so much loss, and because we have to learn to give each other more time to feel, to be in our humanity. Not to come to a standstill as a movement, but to take turns actually feeling what is happening to and around us, and letting our feeling help us understand what we much do. Because that is what we are creating, a world where we can feel ourselves and each other and do less harm and generate more freedom.
mi
Michelle
4:51 PM
adrienne maree brown - Emergent Strategy
mi
Michelle
4:52 PM
NONLINEAR AND ITERATIVE
The pace and pathways of change.
re
Renée
4:59 PM
btw: this is one of the most moving books I've read about breathing... Blackpentecostal Breath: The Aesthetics of Possibility
Book by Ashon T. Crawley
re
Renée
5:04 PM
robustness: The condition or quality of being robust (in various senses); sturdiness, hardiness; strength.
re
Renée
5:05 PM
robust adj: A. adj.
1.
a. Strong and hardy; strongly and solidly built, sturdy; healthy.
from Oxford
https://en.wikipedia.org/wiki/Ruth_Benedict
mi
Michelle
5:51 PM
The
Wink
and
the
Blink
re
Renée
5:56 PM
Agathe tries to think what machine learning would be in this context.
mi
Michelle
5:57 PM
Bring in the context
mi
Michelle
6:03 PM
Politics of Reticence
mi
Michelle
6:04 PM
I refuse to make my language palatable to your ears.
mi
Michelle
6:05 PM
What appears to be inaudible. What appears to be out sight.
mi
Michelle
6:05 PM
I am here, but I don't want to be included.
mi
Michelle
6:07 PM
Freedom in the silence
mi
Michelle
6:07 PM
The assumptions that you make when you think you are being inclusive.
mi
Michelle
6:09 PM
The freedom of not being nameable.
mi
Michelle
6:09 PM
And how does this work in an AI system?
cr
Cristina
6:10 PM
https://points.datasociety.net/the-point-of-collection-8ee44ad7c2fa#.y0xtfxi2p
cr
Cristina
6:11 PM
ah sorry, it's here
https://github.com/MimiOnuoha/missing-datasets
re
Renée
6:14 PM
https://www.youtube.com/watch?v=Dwr5ax3zek8
MARCH 16 MEETING NOTES (looking at COCO - Common Objects in Context (cocodataset.org) )
https://cocodataset.org/#home
(reading Microsoft COCO: Common Objects in Context)
http://arxiv.org/pdf/1405.0312.pdf
[Tsung-Yi Lin, Michael Maire, Serge Belongie, Lubomir Bourdev, Ross Girshick, James Hays, Pietro Perona, Deva Ramanan, C. Lawrence Zitnick, Piotr Dollár. Microsoft COCO: Common Objects in Context. arXiv:1405.0312. 2015]
(tour of code:
http://aif360.mybluemix.net/data#
)
(tour of code:
https://nbviewer.jupyter.org/github/Trusted-AI/AIF360/blob/master/examples/tutorial_medical_expenditure.ipynb
)
[A PROPOSAL FOR A PLAY]
Live Transcription - Michelle
Renee: We are reading through the data sets.
Reading through data sets quality assurance (equality and inequality) ISO quality assurance and how it is also used in education.
ISO verification language.
Thanks for show me that.
Sonia: ISO is the standard verification language. It is the the standard association that everybody guides themselves by in the technical world.
Renee: ISO Standards from pizza crusts to education to AI. It is quite something.
Sonia: reference ISO gym
Renee: We are doing a lot of reading. What about doing? Or look at the videos. We have been pretty text heavy in our previous exercises
Donna Summer: I would like to have opportunity to look at the actual code. The actual code and AI. It has a supernatural quality that I would like to incorporate. How does a system differentiate from one another. Example: Tesla car near a cemetary. The car was detecting shapes and energy but there was nothing there. Did AI detect a ghost?
I would like to see the code!
Agathe: I have code for how to detect objects.
DS: Information and context. How does that work as well?
Renee: HOw does the camera frame the recognition?
Sonia: Let's look through several introductions.
Michelle: I am doing live transcription and intend to write a play from this meeting. Would it be possible to have the screen share on so I can look at the code while I am writing?
[brings up Microsoft COCO: Common Objects in Context]
Agathe: Let's look through this link, then the pdf.
[opens dataset tab]
S: do you see it?
A: here is a summary of the data set s... persons, people, objects. They show what is annotated under the images. Pictures with computers is important to annotate.
[cats and computers, sinks, floors, cats in bottles, cats on a chair, cat on a sofa]
S: Our future is imagined through these flat surfaces instead of 3D spaces (with sounds)
R: COCO comes from the Gorilla, Like COCO wanta a banaan?
S: Perhaps happy coincidence.
S: Should I click on something else?
[brings up horses, in landscapes, hills, towns, etc]
A: These have been critized because of these connotations.
S: Of course it is going to be pretty safe. The scandal wit Google. Image recognition with people recognized as animals, and...
A: Pictures ... recently of a hand holding a thermomator .. Concentration camps as leisure parks
N: Interesting the cell phone, and the icon. How are the icons developed?
A: Interesting to see what they decide to annotate ... home images... subjective. The whole person, the face of the person. There isn't a lot of reasoning behind these piectures/ They seem quite random.
R: It is scraping any informatino from the url> ?? How much is being read. Whether that url is adding, framing the dataset. if you have the url there will be textual framing.
[guy with home cooking blog]
R: The circle is a cake.
A: Most datasets scrape images from the web. Generally they don't save any context information. They send the image on a cross reference platform. They ask precise questions to annotate what is in the dataset. Or precise segments. Either they force a certain set of annotations. Or let the workers annotate whatever is important in the image. There were pictures of people annotated with character traits. ... associate and full professor. You find a lot of hierarchical things in the dataset.
C: On the interface. They create a lot of interfaces. they are built for speed for speedy workers. Then another richer slower interaction interface. The level of communication between these interfaces was very interesting. Categories: the amount of sports are quite limited. But there are two for baseball and the baseball glove. Pizza, food, child's food. Reading the paper, the three sources for categories. Children 8-14 asked what is the most prominant feature in their environment.
A: They said they wanted to capture their whole world. And asked people to take a picture in their environment. So it is very telling.
Linda: Why children?
Christina: Assumption that children as the least bias. The difference between humans learning and machine learning.
A: To augment the data set they asked children to do it.
[showing pictures in front of computers, outside, on sidewalks, in diners]
A: Pictures of weddings. White long dress.
[Normative, Westernized images]
R: Mechanical Turks and where they might reside. There has to be a contradition.
[Army photos, people on phones, playing baseball, chopping onions, holding a cell phone, computer sccreen]
R: It raises the question who is being trained actually?
A: The workers train themselves to have the same strategy.
[Who and where are the workers?]
A: A soup is generally in a bowl. Workers are flirting.
[laps, at a table, lawn chair]
R: To capture the whole world is almost an art project like Kenneth Goldsmith printing the internet.
A: Should we read the paper or look at something else?
A: The workers are mostly coming Amazon's Mechanical Turk.
Renée
3:23 PM
"For all crowdsourcing tasks we
used workers on Amazon’s Mechanical Turk (AMT). Our
user interfaces are described in detail in the appendix.
Note that, since the original version of this work [19],
we have taken a number of steps to further improve
the quality of the annotations. In particular, we have
increased the number of annotators for the category
labeling and instance spotting stages to eight. We also
added a stage to verify the instance segmentations. (Lin et al., 4)"
[Jeff Bezos refers to these workers as AI]
S: The more you work like machines the more you become one.
S: The background never matters. It is only about the object. But the context is makes the object. \
[Context matters]
S: Cars in the background. Even if tiny are still labelled as something to be presented.
Agathe Balayn
3:26 PM
https://unthinking.photography/articles/an-introduction-to-image-datasets
R: It is so interesting thinking about what context is. How much photography theory we had to read. What is happening inside and outside of the iamges. What happens in the web context where images can land in so many different contexts.
S: Segmentation. 2,500,000. 22 worker hours per 1,000 segmentations. I am trying to do the math. This is a lot of time! The need to do one task, super fast.
A: Having one person who has one task. And becomes super familiar with that task.
Sonia
3:31 PM
"On average our dataset contains 3.5 categories and 7.7 instances per image. In comparison ImageNet and PASCAL VOC both have less than 2 categories and 3 instances per image on average. Another interesting observation is only 10% of the images in MSCOCO have only one category per image, in comparison,over 60% of images contain a single object category inImageNet and PASCAL VOC. (Lin et al., 6)"
[scanning through several graphs]
[Fig 6: Samples of annotated images in COCO dataset]
[Person Bike Horse]
S: So COCO is better. Jesus 7,000 workers hours.
A: They evaluate training of datasets.
[Object& Scene Categories]
Donna Summer: I really like the captions on the categories.
Renée
3:34 PM
"Rather
than requiring workers to draw exact polygonal masks
around each object instance, we allow workers to “paint”
all pixels belonging to the category in question. Crowd
labeling is similar to semantic segmentation as object instance are not individually identified. We emphasize that
crowd labeling is only necessary for images containing
more than ten object instances of a given category. (Lin et al., 11)"
DS: A group of human judges evaluating whether the caption is right or wrong. There is something poetic about these captions. Woman in dress standing among them. Something literally. A person dressed in colourful clothes. \
R: Almost like Haiku
S: The situation of being in front of the computer. Recognizing an object as fast as possible. Is so alien of the situaiton of walking around on the street. The way to very forefully introduce this information into theis machines for events in the future is completely at odds of the experience of walking throught the city. Perhaps a person wearing Google glasses and annotating the experience of wlaking would be more interesting.
DS: Sounds like an over-estimation of reality. Most people don't walk thorugh the city that way. I mention the example of the captions becuase it reminded me of the expeirence of creative wriitng. Good stories are demonstrating something in an objective way. And it is you giving meaning. Chekov writing is not too different from the captions of COCO. We also always try to be purely descriptive, which is hard when today everybody is trying to giving opinions, and advancing their objectives. As researchers, we always try to spot the moment when the machine has the bias. We already know the answers, that machines are going to be racist and sexist, which are valid points. But it is not enough of this approach that finds something in this that can advance the arts, fine arts and scholarship of what these things can provide.
Renée
3:39 PM
So they are purely descriptive as opposed to interpretative.
Cristina
3:36 PM
"For COCO, the authors wanted, say, pictures of cats on couches, but not of cats posing in front of a white background for a feline studio shoot. To avoid images of single objects in isolation, the authors used combinations of object categories as search terms. This is how common objects are put in context: not primarily by any natural context in which they might appear, but explicitly by their appearance together with other COCO classes. It explains why the objects in COCO frequently seem neither common, nor in context."(Philipp Schmitt, https://humans-of.ai/editorial )
Cristina
3:37 PM
"What I am suggesting is that, as a result, COCO represents more than images of objects. It captures a logic of how things should be connected: In this world, umbrellas should be in toilets, and cats in sinks. Innocent, sure. The looming question is whether data or the artificially intelligent system that learn from them, in their far-reaching entrenchment within people’s lives, are ultimately able to instill their logic in the minds of people subjected to their algorithmic world views." (Philipp Schmitt, https://humans-of.ai/editorial )
Renée
3:44 PM
It is interesting to think about this text in relation to the other text, AI Fairness 360 ... under the header "Terminology" there is this point that somehow relates to what we are discussing with regards to "description" over interpretation:
"In this section, we briefly define specialized terminology from the field of fairness in machine learning. A favorable label is a label whose value corresponds to an outcome that provides an advantage to the recipient. Examples are receiving a loan, being hired for a job, and not being arrested. A protected attribute is an attribute that partitions a population into groups that have parity in terms of benefit received. Examples include race, gender, caste, and religion. Protected attributes are not universal, but are application specific. A privileged value of a protected attribute indicates a group that has historically been at a systematic advantage. Group fairness is the goal of groups defined by protected attributes receiving similar treatments or outcomes. Individual fairness is the goal of similar individuals receiving similar treatments or outcomes. Bias is a systematic error. In the context of fairness, we are concerned with unwanted bias that places privileged groups at a systematic advantage and unprivileged groups at a systematic disadvantage. A fairness metric is a quantification of unwanted bias in training data or models. A bias mitigation algorithm is a procedure for reducing unwanted bias in training data or models. " [AI Fairness 360: An Extensible Toolkit for Detecting, Understanding, and Mitigating Unwanted Algorithmic Bias (arxiv.org), https://arxiv.org/pdf/1810.01943.pdf ]
C: The glance vs the gaze. The workers of Imagenet. Doing it in person, writing the notes. One person gets three images. Then a group of three coming up with a common description. Glance: we only had a few seconds to look at the images. After we became more accustomed to looking at the images. Researchers did that to avoid bias. If you don't have time to register what you are looking at, then there is less bias. Going through this, and collectively was an amazing experience.
Strollology
Mi
Michelle
3:43 PM
Lucius Burckhardt
donna summer
3:44 PM
numerous tall flags and a colorfully dressed man standing among them
the person is stands in color as the surrounding flags are in black and white.
there is a person standing on the beach.
a person stands out amongst a black and white background
a person that is standing by a bunch of flags
Sieta
3:46 PM
https://experiments.runwayml.com/generative_engine/
Sonia
3:47 PM
http://moments.csail.mit.edu/
S: 3 seconds is how much time you need to recognize what is happening.
Agathe Balayn
3:47 PM
https://www.google.com/url?sa=i&url=https%3A%2F%2Fwww.groundai.com%2Fproject%2Fdo-imagenet-classifiers-generalize-to-imagenet%2F1&psig=AOvVaw1MKV_xTVY6u04H8kRsEfOc&ust=1615992357643000&source=images&cd=vfe&ved=0CAIQjRxqFwoTCPCYjeyGte8CFQAAAAAdAAAAABAJ this is what the ImageNet crowdsourcing task looks like
R: The glance and the gaze. The wink and the blink. We all blink. The wink is intentional. Funny to see that language echo.
R: On terminology. The desire to use more neutral language.
R: Interesting in that text, demonstration and not explanation. The cold eye, what would it do... 15 years ago I had a Polish student in PZI and was interested in political media images. He took super violent images and described them clinically. White and black drawing. No connotations. Violent images but absolutely neutral. And interesting in this case where bias is a computational error.
A: Lighter skin coloured people. So Twitter started to say that it was not a problem of fairness. That it didn't need to be systematic to talk about fairness.
R: And what if they were to say "bias is a sin".
[reading]
A: Defining a protective and non-protective group. Detecting bias. You should look at fairness by looking at attributes. But now that attributes are not universal...
R: And they are also trying to design themselves out of a problem. Designing out of bias.
A: The fairness matrix to determine whether something is fair or not. It is a bit of a design problem because you have to assign the attributes. But the matrix and methods have a lot of problems.
Agathe Balayn
3:56 PM
http://aif360.mybluemix.net/data#
A: I still cannot share my screen.
R: The language of 350 degrees. There is something inbuilt in that title because it says ... it is weirdly acclaimed to universal knowledge. Instead of how do you make bias transparent it is expunging. 360 degrees is an interesting starting point.
Renée
3:59 PM
expunge: verb
obliterate or remove completely (something unwanted or unpleasant).
R: Training models without biases. Is this where we are at?
A: Making a system to predict whether somebody will have to go to the hospital or not. To predict whether there will be expenses. There was a dataset on people who had been to the hospital for long periods of time to develop a dataset based on fairness.
A: This whole section. I am not sure how to go about looking at the code.
R: I love this prejudice remover. Glad they have an algorithm for that.
A: I have never read code with people. Not sure how to go about it.
[This is the starting point]
A: Now they have their data set and they are going to predict their model.
R: It is great to see 'privileged groups', and 'unprivileged groups' to get an idea of semantics.
A: Mostly they are picking and defining values based on race or gender or a combination of the two.
[scanning through code written in Python]
Protected attribute names
('RACE;)
Cannot do more than two groups at once (0 and 1) binary
Privileged and unprivileged protected attribute values
3.2.2. Validating LR model on original data
unprivileged groups=unprivileged groups,
privileged groups=privileged groups
print(explainer_orig_panel19_train.disparate_image))
from collections import defaultdict.
C: Do you think they developed it themselves?
def text(dataset, model, thresh_arr)
A: This validation model. Each is aligned to one fairness metric. I find it interesting to define the metric you have to define the protected group. So it simplifies the whole context.
R: Where things go array... the arc of the process is pattern recognition and extrapolating conclusions. Bias can come in at any of those junctures.
Renée
4:10 PM
So in terms of the arc... the process is:
Gathering
Categorizing
Searching/ Training
Pattern Recognition
Conclusions
A: There are historical biases in the data as well. Especially in the US.
Michelle
4:12 PM
Predpol
is an example
A: Categories are not often discussed. Crediting the committee.
Classificatoin Thresholds.
A: They don't just have a binary decision. Choosing between the threshold between 0 and 1 to determine whether a person should go to prison for example. The red line is the fairness. Practitioners need to make a choice between the threshold.
R: So this is almost a Mechanical Turk moment. Where a human says, a little tweak this way, a little tweak the other way.
[But what do these numbers mean and how do we apply them in practice]
[slowing down and having conversations about what do these numbers do, which is very different from computing science]
Renée
4:17 PM
So in other words, you're asking your students about the consequences of the calibration.
"Best: balance accuracy
L: It is interesting that you are trying to mitigate bias in the program but in the end you have to use bias to make a decisions.
L: Using the language of mathematics to describe an emotion. An inapproprateness of language.
[Technik and Magic]
A: Fairness based on their own metrics.
A: Issues of discrimination come from bias.
Threshold corresponding to Best balanced accuracy: 0.1900
Best balanced accuracy: 0.7759
Corresponding 1-min (DI, 1/DI) value: 0.5738
R: I dont' want to hold engineers to a higher moral standard than myself. Question: We are in an interdisciplinary moment where we need each other to think through the consequences. Looking through these documents, I need to see the logic. How to engage with the language with understanding the limits. (regarding education).
A: Re: Education. Mostly these conversations (discussion the socio-technical limitations) do not take place.
R: Arts have limits as well.
DS: This reminded of my classes on distance reading. In the humanities, many people use this methods to establish patterns between huge amounts of text. Critics of the methods of distance reading. In literature we are not interested in patterns, but exceptions. That is where the interesting story exists. Not trying to solve the bias of AI. It will exist nonetheless, but use this moment, these glitches of the code for a space of new knowledge, new art, new generation.
Renée
4:25 PM
distance reading
Renée
4:26 PM
patterns versus exceptions
DS: After years and activism, I am trying to use a new lens of fun to look at things.
L: Not trying to solve bias through code.
Renée
4:27 PM
rather than solve, perhaps it can become more transparent? Or use those biases as a source of debate and public engagement?
Sieta
4:28 PM
I like that very much, using the cracks of the old to rebuild the new
L: Playing cards. Playing the dataset. You can see algorithms as divination. Maybe bringing it out of the rationality. ['Algorithms as Cartomancy', Flavia Dzodan]
Renée
4:29 PM
algorithms as divination... taking them out of the "rational" language
Sieta
4:30 PM
my feelings exactly haha
Agathe Balayn
4:30 PM
an escape game to make people aware of AI bias https://www.tomokihara.com/en/escape-the-smart-city.html
L: We need to take it out into another type of field. Or looking at it differently.
[END]
Notes 23 March 2021
https://mynoise.net/NoiseMachines/dataCenterNoiseGenerator.php
Dates: 25, 26 May? or 26, 27 May?
Hotglue: https://v2.hotglue.me/the_slow_reading_group
Other site related things:
https://ethertoff.caveat.be/w/Eleni_Kamma::The_Corners_of_the_Mouth.md
__PUBLISH__ > https://etherpump.vvvvvvaria.org/p/slowreading.raw.html
Questions on Symposium: Re-imagining Black Youth-Led Technologies
Next session
Personal encounters with AI
https://app.mural.co/invitation/mural/v28710/1617120139614?sender=u812232d4b6c0c84d682d0139&key=7ecd6626-5e1b-4239-8cd2-af39e079a4f2
MARCH 30 MEETING NOTES: (screening of Ruja Benjamin talk about Race After Technology: The New Jim Code at Harvard Carr Center for Human Rights Policy
https://www.youtube.com/watch?v=bSK2ygnuXxE&t=82s
)
Shared notes:
*starts with Octavia Butler ref <3*
What brings you joy in this time?
What do "we" want to be "saved" from?
What kind of technologies do we want in the first place?
This is not about access as that works with something predefined – to be given entry.
How would we embed our highest values?
What is depth in the context of deep learning?
What is the role of social and cultural memory within the context of technology? What does it mean to recall and remember?
"Tool not visible unless it's broken" dictum (Heidegger, but also McLuhan in a different way, with the fish quote) -- reminds me of Susan Leigh Star's work on infrastructure --> also, yeah!
What are we forgetting today?
Is it possible to speak of "reconnection" at all? Aren't we disconnected, per definition?
(it's so cute that someone is agreeing in the background all the time)
(haha yes i thought it was one of us in the beginning)
Can technology help us to remember what we have forgotten?
What is consent in the context of data extraction?
How do you deal with the desire for social domination?!?!! (Age-old question, still not solved by things like democracy..)
(We were just talking about NFTs with Anna, something that has the same potential dangers as what she's talking about right now. Maybe something to chat about later)
What is the best way of framing a conversation around positive versus negative (or other forms) of exposure?
> predatory inclusion
> evitable technology
> "they tried to bury us, they didn't know we were seeds"
> subaltern pattern making
What kind of infrastructure is needed for subaltern pattern making?
Chat:
[16:08] Michelle : Undrowned
[16:08] Michelle : Black Feminist Lessons from Marine Mammals
[16:08] Michelle : Alexis Pauline Gumbs
[16:10] Cristina : hello sorry i am late, i was caught up in another meeting!
[16:11] Renée : I guess so
[16:11] Renée : So then we hit mute?
[16:11] Renée : or is it playing the same way for everyone
[16:12] Cristina : do we hit play?
[16:12] Renée : meaning is the timing similar
[16:13] Sieta : questions here
[16:14] Renée : We will do the questions here:
[16:14] Sieta : did you press play?
[16:14] Sieta : mine did not move
[16:14] Sonia : I pressed play to start it
[16:14] Agathe Balayn : mine either
[16:14] danae : same here
[16:15] Renée : press play yourself
[16:15] Cristina : mine either, i pressed play myself
[16:15] Sieta : haha oke
[16:15] Sieta : yes it starts!
[16:15] Cristina : it started again yes
[16:15] Renée : now we are synched
[16:19] Renée : What brings you joy in this time? (Remember to share that on the pad)
[16:21] Renée : What kind of technologies do we want in the first place?
This is not about access as that works with something predefined – to be given entry.
[16:21] Renée : How would we embed our highest values?
[16:21] Renée : What is depth in the context of deep learning?
[16:23] Cristina : (side-question: did anyone read the Indigenous AI position paper? https://www.indigenous-ai.net/position-paper/ )
[16:23] Renée : What is the role of social and cultural memory within the context of technology? What does it mean to recall and remember?
[16:24] Renée : What are we forgetting today?
[16:24] Sieta : Can technology help us to remember what we have forgotten?
[16:25] Renée : What is consent in the context of data extraction?
[16:25] Cristina : ( https://en.wikipedia.org/wiki/IBM_and_the_Holocaust )
[16:27] Renée : What are the processes of alienation and detachment that take place within AI's ruse?
[16:28] Renée : How do race and technology shape one another?
[16:28] Renée : How are input, output and impact interrelated?
[16:31] Renée : How are algorithms, as proprietary black boxes, cloaking systemic racism while simultaneously executing (producing) (proliferating) it?
[16:35] Renée : How are we literally indebted to these technologies? Not in the sense of "grattitude" but in servitude.
[16:36] Renée : What is the responsibility with those with computational expertise?
[16:36] Renée : "of those"
[16:39] Sieta : what was the name of this movie?
[16:41] Cristina : did it also skip bacck to the beginning for you?
[16:42] Sieta : yes
[16:42] Renée : “Artifacts have politics” Langdon Winner
[16:43] Renée : now it's working
[16:46] Renée : What are the financial incentives behind racist and sexist patterning?
[16:48] Renée : How is fairness defined in this context?
[16:49] Renée : How do we interrogate what it means to be seen and grasp its consequences in terms of exposure, if not vulnerability?
[16:53] Renée : OMG.. the giant owl - oehoe is in the tree.. the gardeners are calling me to come and look.
[16:54] danae : <3!!!
[16:55] Renée : the zoo bird keeper is here
[16:55] Sieta : https://kikimager.com/input-output - Kiki made a artistic version of HireVue
[16:55] Cristina : is this adjacent video watching ?
[16:56] Renée : can you see him/
[16:57] danae : the zoo bird keeper? so i shouldn't be expecting owls in my balcony </3
[16:57] danae : i saw a blurry thing
[16:57] Renée : sorry I have to grab a ladder for him to go up the tree
[16:58] Sonia : So sorry, I have to go!!! :(
[16:58] Sonia : <3
[16:59] Sieta : No worries! :) <3
[16:59] Cristina : Nice to see you Sonia!! <3
[17:02] Cristina : resilient owl
[17:03] Cristina : the owl's bird view totally connects to ai perspectives i think
[17:18] Cristina : christine meinders https://vimeo.com/366495908
[17:21] Cristina : https://www.lorenbritton.com/media/pages/texts/abstracting-otherwise-in-search-for-a-common-strategy-for-arts-and-computing/369876103-1593078159/abstracting-otherwise-in-search-for-a-common-strategy-for-arts-and-computing-klumbyte-britton.pdf
[17:23] Agathe Balayn : https://web.br.de/interaktiv/ki-bewerbung/en/ some "demo" of biases in softwares like HireVue
[17:29] Renée : What is her name again?
[17:31] Cristina : @michelle, still thinking about your question... perhaps the sub- and infra- in subaltern and infrastructure can point towards grassroots infrastructures which can eventually federate?
[17:33] Renée : chapter in ?
[17:33] Agathe Balayn : the artist;s work ahttps://www.theguardian.com/technology/2020/feb/03/berlin-artist-uses-99-phones-trick-google-maps-traffic-jam-alert
[17:34] Renée : Thanks Agathe
[17:38] Cristina : https://ahprojects.com/vframe/
[17:39] Noemi : HI everyone! Sorry for joining late
[17:40] Cristina : hello :)
[17:42] Renée : When is being seen essential and when is exploitative?
[17:46] Renée : It is very contextual.
[17:51] Renée : https://www.eur.nl/en/people/antoinette-de-bont
[17:52] Michelle : What would my life be without AI?
[17:52] Renée : Is AI just convenience?
[17:52] Renée : Does AI help with more vitally with certain communities?
[17:53] Michelle : Is AI really necessary?
[17:53] Noemi : the why and the why not
[17:54] Michelle : What would happen if AI suddenly disappeared?
[17:54] Michelle : Is AI just an arms race and is the robot revolution imminent?
[17:59] Cristina : is AI only servitude?
[17:59] Renée : * not productivity
[17:59] Sieta : we could also use Mural, kind of same application as Miro (V2_ has a subscription)
[18:01] Cristina : i'm wondering if i actually come in contact with ai
[18:01] Renée : can we call it an encounter
[18:01] Agathe Balayn : i would say that any recommender system is ai, right? (e.g. twitter sorting posts on your wall?)
[18:01] Cristina : true but i use mastodon (just kidding)
[18:02] Renée : yes, I agree - these tailoring algorithms
[18:02] Linda : and email?
[18:02] Cristina : i use translation AI for my dutch class
[18:02] Agathe Balayn : gmail uses AI to predict next words, also to sort your emails. but you might not use gmail ^^
[18:02] Sieta : Personal encounters with AI
[18:03] Sieta : https://app.mural.co/invitation/mural/v28710/1617120139614?sender=u812232d4b6c0c84d682d0139&key=7ecd6626-5e1b-4239-8cd2-af39e079a4f2
[18:04] Linda : i can't open it yet but sure!
[18:05] Cristina : i added the link at the bottom of the pad
[18:06] Cristina : llet us know when you have a date for the hotglue, renee, just in case it's possible to join
APRIL 6 MEETING NOTES (Personal Encounters with AI)
We have been working here for the first hour:
https://app.mural.co/t/v28710/m/v28710/1617120139614/48a391880736b157a96c31e01eee941bde48a115
Sonia
5:08 PM
"AS THEY SAY IN AI
AI IS
WHATEVER AI CANT DO YET"
i love this one
--> I twisted it
Sonia
5:08 PM
But it's basically the saying, among AI researchers
Sonia
5:08 PM
AI is the horizon, as soon as something is accomplished it's no longer considered AI
Sonia
5:08 PM
(like DeepBlue chess, alphago, etc.)
Sonia
5:09 PM
"Pamela McCorduck calls it an 'odd paradox' that 'practical AI successes, computational programs that actually achieved intelligent behavior, were soon assimilated into whatever application domain they were found to be useful in, and became silent partners alongside other problem-solving approaches, which left AI researchers to deal only with the "failures", the tough nuts that couldn't yet be cracked.' "
(from https://en.wikipedia.org/wiki/AI_effect )
Agathe Balayn
5:11 PM
the book for which the first chapter tries to define AI: https://www.cin.ufpe.br/~tfl2/artificial-intelligence-modern-approach.9780131038059.25368.pdf
Sieta: intelligence is perhaps separate from consciousness
Sonia: Ned Block's China Brain
spatial intuintion/common sense is actually extremely difficult to replicate and to understand and not at all
Renee: what is care as intelligence?
Sonia
5:24 PM
(from a presentation by David Gunning):
John McCarthy (Stanford, circa 1960):
∃a. Name(a) = ANY-FOOL ∀𝑘𝑘.Knows(ANY-FOOL, k) ⟺∀𝑝𝑝∈Persons. Knows(p, k)∀𝑘𝑘.Commonsense(k) ⟺Knows(ANY-FOOL, k)
Agathe Balayn
5:24 PM
people really believe they can collect "common sense knowledge" objectively: http://conceptnet5.media.mit.edu/ (they made a database of common sense knowledge)
possible branches to be unravelled further:
what is intelligence, the artifice?
notions of refusal
curriculum of ai
APRIL 13 MEETING NOTES (reading "On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?")
[Emily M. Blender, Angelina McMillan-Major, Timnit Gebru, Shmargaret Shmitchell. "On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?". March 2021]
https://faculty.washington.edu/ebender/papers/Stochastic_Parrots.pdf
measured by leaderboards?
what are language models
Winograd schemas ("The man could not lift his son because he was too fat" --> who was too fat?! Not too easy to say).
benchmarks are now criticised for their ambiguity and claim to objectivity
baking ethics or a certain perspective into the luangage model
NLP has sought larger datasets with the larger LMs.
(https://searchengineland.com/welcome-bert-google-artificial-intelligence-for-understanding-search-queries-323976 - BERT used for Google search)
There are competing scales to be taken into consideration.
"documentation debt" = when datasets are so large it is difficult/expensive to document them?
https://en.wikipedia.org/wiki/Claude_Shannon
n-grams
In the fields of computational linguistics and probability, an n-gram is a contiguous sequence of n items from a given sample of text or speech. The items can be phonemes, syllables, letters, words or base pairs according to the application. The n-grams typically are collected from a text or speech corpus. When the items are words, n-grams may also be called shingles.
word embeddings
word2vec, GloVe, context2vec, ELMo
Example of training NL on books of different genres and periods and they discovered that the systsem was trained with the bias of the period.
That was this paper https://www.pnas.org/content/115/16/E3635
Linda wonders about the use of literature because it is in fact highly edited and refined. Websites, tweets, reddit etc are more problematic because they are even more contextual. There is a temporal acceleration.
https://commoncrawl.org/
Renee: datasets as Rapuccini's daughter (?) https://en.wikipedia.org/wiki/Rappaccini%27s_Daughter
visible vs invisible biases
Sonia: bias is unavoidable, better embrace it, acknowledge it
(nicolas maleve's presentation on current trends in the bias discussion:
https://en.wikipedia.org/wiki/Grain_(textile)
The bias grain of a piece of woven fabric, usually referred to simply as "the bias", is any grain that falls between the straight and cross grains. When the grain is at 45 degrees to its warp and weft threads it is referred to as "true bias." Every piece of woven fabric has two biases, perpendicular to each other. A garment made of woven fabric is said to be "cut on the bias" when the fabric's warp and weft threads are on one of the bias grains.)
The very language used to name these datasets are manifest destiny
"the Colossal Clean Crawled Corpus" says it all
Either way, these models do not address the inclusion problems raised by [65], who note that over 90% of the world’s languages used by more than a billion people currently have little to no support in terms of language technology.
"I don't speak Spanish!"
Michelle: where is the funding concentrated? who is the audience of these papers? what use are these systems if someone is speaking urdu?
Agathe - only Google has the kind f power to process these large datasets which certainly raises questions.
Google open sources ALBERT (in 2020):
https://www.infoq.com/news/2020/01/google-albert-ai-nlp/
You can try some language models here (a demo) https://transformer.huggingface.co/
bag of words model
https://en.wikipedia.org/wiki/Bag-of-words_model
there is also a model called: https://camembert-model.fr/
and the dutch version is called BERTje https://arxiv.org/abs/1912.09582
this is a great text about bag of words:
https://www.mondotheque.be/wiki/index.php?title=A_bag_but_is_language_nothing_of_words
"In text indexing and other machine reading applications the term "bag of words" is frequently used to underscore how processing algorithms often represent text using a data structure (word histograms or weighted vectors) where the original order of the words in sentence form is stripped away. While "bag of words" might well serve as a cautionary reminder to programmers of the essential violence perpetrated to a text and a call to critically question the efficacy of methods based on subsequent transformations, the expression's use seems in practice more like a badge of pride or a schoolyard taunt that would go: Hey language: you're nothin' but a big BAG-OF-WORDS."
(different to the bags of words of ursula le guin)
carrier bag of fiction
"While the average human is responsible for an estimated 5t 퐶푂2푒 per year,2 the authors trained a Transformer (big) model [136] with neural architecture search and estimated that the training procedure emitted 284t of 퐶푂2. Training a single BERT base model (without hyperparameter tuning) on GPUs was estimated to require as much energy as a trans-American flight."
Can you imagine if a similar amount of energy was expended on educating a child?
Can you put that comment in the chat Agathe....
I'm not sure, but I believe that there is a tax to pay depending on the carbon emissions you create, and academic researchers probably don't have the financial resources to pay this tax directly, and so to do this research. https://arxiv.org/pdf/1906.02243.pdf
Look up: SustainNLP workshop
https://sites.google.com/view/sustainlp2020/home
This! "Among their recommendations are to run experiments in carbon friendly regions, consistently report energy and carbon metrics, and consider energyperformance trade-offs before deploying energy hungry models. In addition to these calls for documentation and technical fixes, Bietti and Vatanparast underscore the need for social and political engagement in shaping a future where data driven systems have minimal negative impact on the environment [16]." (p.3)
“Feeding AI systems on the world’s beauty, ugliness, and cruelty, but expecting it to reflect only the beauty is a fantasy.” (Ruha Benjamin)
"When we perform risk/benefit analyses of language technology, we must keep in mind how the risks and benefits are distributed, because they do not accrue to the same people."(p.3)
"Is it fair or just to ask, for example, that the residents of the Maldives (likely to be underwater by 2100) or the 800,000 people in Sudan affected by drastic floods pay the environmental price of training and deploying ever larger English LMs, when similar large-scale models aren’t being produced for Dhivehi or Sudanese Arabic?"
https://www.redpepper.org.uk/an-open-letter-to-extinction-rebellion/
"An open letter to Extinction Rebellion"The fight for climate justice is the fight of our lives, and we need to do it right." By grassroots collective Wretched of The Earth."
Our communities have been on fire for a long time and these flames are fanned by our exclusion and silencing. Without incorporating our experiences, any response to this disaster will fail to change the complex ways in which social, economic and political systems shape our lives – offering some an easy pass in life and making others pay the cost. In order to envision a future in which we will all be liberated from the root causes of the climate crisis – capitalism, extractivism, racism, sexism, classism, ableism and other systems of oppression – the climate movement must reflect the complex realities of everyone’s lives in their narrative.
parallels between deciding what to do with AI models and what to do with institutions; reforming institutions
ref to How Not To Teach (??) from a compedium of anarchist pedagogy texts
linda: how can you talk about refusal when you don't even have a base understanding? which feminism can actualise in data science? is it only liberal feminism? does the radical have space?
renee: what are the leaderboards/benchmarks for this text?
the meta elements (structure, refs) of the text are what are interesting maybe more so than the context
agathe: how do these topics become accepted through the peer review processes?
danae last week: the decline of american imperialism
the very last sentence of the article: "Thus what is also needed is scholarship on the benefits, harms, and risks of mimicking humans and thoughtful design of target tasks grounded in use cases sufficiently concrete to allow collaborative design with affected communities."
https://www.metamute.org/editorial/articles/californian-ideology
for next time:
https://www.apc.org/sites/default/files/sneak_peek2020_final.pdf (maybe rhizomatica? page 13)
cristina: a quote by Mariame Kaba that seems to fit our next reading:
"When something can't be fixed, then the question is what can we build instead?"
The Chat - April 20th
[16:14] Michelle: somebody is sending scratchy noises :)
[16:15] Renée: I'm seeing if it is me
[16:21] Welcome to Slow reading!For help on using BigBlueButton see these (short) tutorial videos.To join the audio bridge click the phone button. Use a headset to avoid causing background noise for others.To join this meeting by phone, dial: +31 15 201 0064Then enter 57941 as the conference PIN number.
[16:21] To invite someone to the meeting, send them this link: https://bbb.tbm.tudelft.nl/b/aga-9ab-8g7-tu1
[16:24] Renée: Agathe - do you feel like joining from the perspective of computer science
[16:25] Renée: So since I'm not doing well on the mic situation - shall I do the glossary
[16:25] Agathe Balayn: https://faculty.washington.edu/ebender/papers/Stochastic_Parrots.pdf
[16:27] Cristina: https://commoncrawl.org/
[16:27] Sonia: commoncrawl.org/
[16:27] Michelle: Common Crawl
[16:28] Cristina: The Internet is a large and diverse virtual space, and accordingly, it is easy to imagine that very large datasets, such as Common Crawl (“petabytes of data collected over 8 years of web crawling”,11 a
filtered version of which is included in the GPT-3 training data) must therefore be broadly representative of the ways in which different people view the world.
[16:29] Cristina: (under Size Doesn’t Guarantee Diversity)
[16:30] Cristina: https://twitter.com/Abebab/status/1309137018404958215
[16:41] Michelle: The Colossal Clean Crawled Corpus
[16:44] Michelle: We instead propose practices that actively seek to include communities underrepresented on the Internet. For instance, one can take inspiration from movements to decolonize education by moving towards oral histories due to the overrepresentation of colonial views in text [35, 76, 127], and curate training datasets through a thoughtful
process of deciding what to put in, rather than aiming solely for scale and trying haphazardly to weed out, post-hoc, flotsam deemed ‘dangerous’, ‘unintelligible’, or ‘otherwise bad’.
[16:46] Cristina: https://www.ainarratives.com/ai-communism
[16:56] Michelle: geographies of datasets
[16:57] Renée: the provinces of datasets
[16:57] Renée: geographic specificity of datasets
[16:58] Agathe Balayn: this paper shows some kind of geography distribution for one dataset https://openaccess.thecvf.com/content_CVPRW_2019/papers/cv4gc/de_Vries_Does_Object_Recognition_Work_for_Everyone_CVPRW_2019_paper.pdf
[16:59] Michelle: While this was reportedly effective at filtering out documents that previous work characterized as “unintelligible”
[17:00] danae: Furthermore, the tendency of human interlocutors to impute meaning where there is none can mislead both NLP researchers and the general public into taking synthetic text as meaningful.
[17:01] Renée: that's super interesting
[17:02] danae: https://digitalwitchcraft.works/Autopoietic-Post-Doom
[17:02] Renée: what does synthetic text teach us
[17:02] Renée: meaning that's an interesting field of inquiry
[17:04] Michelle: A central aspect of social movement formation involves using language strategically to destabilize dominant narratives and call attention to underrepresented social perspectives.
[17:04] Renée: ‘value-lock’
[17:06] Renée: As a result, the data underpinning
LMs stands to misrepresent social movements and disproportionately
align with existing regimes of power.
[17:07] Renée: I so want to unpack "curation practices"
[17:08] Cristina: https://arxiv.org/abs/1803.09010
[17:08] Cristina: In the electronics industry, every component, no matter how simple or complex, is accompanied with a datasheet that describes its operating characteristics, test results, recommended uses, and other information. By analogy, we propose that every dataset be accompanied with a datasheet that documents its motivation, composition, collection process, recommended uses, and so on.
[17:11] Renée: data sheets for datasets
[17:11] Renée: that's great because it outs the gatekeepers in some sense
[17:11] Sieta: like a README?
[17:11] Renée: exactly
[17:11] Renée: dataset design
[17:12] Cristina: https://en.wikipedia.org/wiki/Appropriate_technology
[17:21] Renée: https://ethw.org/Oral-History:Karen_Sp%C3%A4rck_Jones#About_Karen_Sp.C3.A4rck_Jones
[17:25] Sieta: https://www.rijksoverheid.nl/onderwerpen/coronavirus-vaccinatie/vraag-en-antwoord/wanneer-krijg-ik-een-vaccinatie-tegen-het-coronavirus
[17:25] Cristina: https://book.affecting-technologies.org/introduction/
[17:26] Renée: Thank you Cristina
[17:27] Cristina: https://digilabour.com.br/2021/04/05/histories-of-ai-imaginaries-and-materialities-seminar-april-19-20/
[17:28] Michelle: As organizers, we prize these exchanges as productive collisions, as the signs of life of a new counterculture of computing that we hope to nourish. It’s a little world, and we hope just one of many. As the Zapatistas say, “The world we want is one where many worlds fit.”
[17:28] Cristina: I love that Zapatistas quote!
[17:29] Michelle: Of course, these proposed advocacy steps have to involve people from the affected geographies, who should be at the centre of strategising and in decision-making roles, in order to gain legitimacy and to not replicate the power imbalances of neocolonial realities.
[17:30] Cristina: Thus what is also needed is scholarship on
the benefits, harms, and risks of mimicking humans and thoughtful
design of target tasks grounded in use cases sufficiently concrete
to allow collaborative design with affected communities.
[17:30] Cristina: (Timnit agrees!)
[17:31] Michelle: Thus what is also needed is scholarship on
the benefits, harms, and risks of mimicking humans and thoughtful
design of target tasks grounded in use cases sufficiently concrete
to allow collaborative design with affected communities.
[17:32] Cristina: https://www.apc.org/sites/default/files/sneak_peek2020_final.pdf
[17:36] Renée: As organizers, we prize these exchanges as productive collisions, as the signs of life of a new counterculture of computing that we hope to nourish. It’s a little world, and we hope just one of many. As the Zapatistas say, “The world we want is one where many worlds fit.”
[17:37] Renée: who are the curators and what is their agenda - whether formulated forthrightly or through neglect?
[17:39] danae: caracoles :) https://freight.cargo.site/w/971/i/e8998287750263b2bf6b46b316c1dddb61ad72e0d74b4bc807e5c8e94acbb41d/caracolezln.png
[17:42] Sonia: Simon DeDeo
[17:43] Renée: It is who shows up and as a result who is showing up.
[17:48] Renée: using harm rather than bias
[17:48] Renée: some use "fairness"
[17:49] danae: now the infosec community uses "harm reduction" a lot
[17:49] Renée: systematic bias
[17:49] Michelle: how about a care brief?
[17:51] Renée: the word "harm" eliminates the mathematical response
[17:52] Michelle: Work on synthetic human behavior is a bright line in ethical
AI development, where downstream effects need to be understood
and modeled in order to block foreseeable harm to society and
different social groups.
[17:53] danae: i guess the text fails at computer science AND at politics :P
[17:53] Sonia: hahaa
[17:53] danae: tbh i was expecting more science
[18:03] Cristina: I’d like to suggest that machine learning is not new. It’s simply digital divination. Both the Ifá system and computers are trying to make a decision amidst great uncertainty. But then, with the case of machine learning, the computer seems to say: “Here you go, that’s your answer.” With Ifá divination there is no certain truth. There is no rational, logical, reasonable truth. Everyone has to bring their context to arrive at a conclusion, to arrive at a truth.
[18:03] Cristina: from https://book.affecting-technologies.org/overcoming-the-limits-of-rationality-in-humans-and-in-rational-machines-through-ubuntus-relational-personhood/
[18:03] Renée: I agree
[18:04] Sieta: O nice text Cristina
[18:04] Sieta: thanks for sharing
[18:05] Sonia: @Cristina, last line of my paper: This text explored several reasons why we can in fact understand the question of bias under a different light if we conceive of it as a fundamentally positive condition, and how we can understand the development of AI (and technology at large) under a different lens if we consider it as a technolinguistic feedbackloop whose very business is the endless negotiation of ambiguous concepts such as “intelligence,” “artificial,” or “human,” fueled by absolute uncertainty.
[18:06] Sonia: Amén!
[18:06] Cristina: Yessss! Great line Sonia! Also love that the last two words are "absolute uncertainty"
[18:06] Sonia: ;)
[18:07] Cristina: fleshyware
From: Introduction to Comparative Planetology by Lukas Likavcan (p. 73)
"[...] these infrastructures also display self-cannibalising tendencies, since computation is always a physical process involving the transformation of matter to energy, and energy to information. Seen through the optics of the future subsistence of the human species, as well as economic, social, and environmental injustices, this cannibalistic logic ought to be thoroughly criticised."
28/04/2021 - session 13
[15:08] Linda: p. 13
[15:09] Agathe Balayn: ahah, the train just arrived in Delft finally
[15:10] Cristina: Hello sorry I am late! A meeting before went on 10min longer
[15:19] Renée: does the line break occassionally?
[15:19] Renée: or is it my headphones
[15:19] Agathe Balayn: for me, yes
[15:25] danae: (i love linda's voice <3)
[15:25] Linda: <3
[15:26] Cristina: 40% of Romanian households have no access to the internet
[15:27] Sieta: https://cat.org.uk/
[15:27] Renée: thanks for that statistic Cristina and thanks for the link Sieta
[15:34] Cristina: in the ether :P
[15:34] Michelle: https://guifi.net/en
[15:36] Cristina: (we have a community networks working group if anyone wants to join :P https://pad.vvvvvvaria.org/wg.communitynetworks )
[15:36] Sieta: cool!!
[15:36] Renée: awesome!
[15:36] Noemi: the mentioned visualzier app: http://www.architectureofradio.com/
[15:36] Renée: thanks
[15:37] Cristina: https://www.wired.co.uk/article/google-project-loon-balloon-facebook-aquila-internet-africa
[15:37] Renée: it's like the star
[15:41] Linda: Lesbians are gonna save the world
[15:41] Renée: Information Activism\
[15:41] Cristina: by Cait McKinney
[15:42] Michelle: https://anarchy.translocal.jp/radio/micro/howtotx.html
[15:43] Michelle: http://www.tacticalmediafiles.net/videos/4556/Telestreet_-The-Italian-Media-Jacking-Movement;jsessionid=059CF4D59F1C46374B8215623418BD50
[15:43] Cristina: amazing ref, thanks for sharing
[15:43] Renée: OMG, there are so many good references
[15:43] Linda: coooool
[15:43] Michelle: https://criticalengineering.org/projects/deep-sweep/
[15:46] Michelle: https://mazizone.eu/
[15:47] danae: i think lesbianism becomes super central in mega patriarchal societies such as those in latin america, in the past they became nuns to avoid marrying men, now they're driving cars across the desert installing antennas <3
[15:57] Cristina: Wireless Leiden (NL) : https://wirelessleiden.nl/en
[15:57] Michelle: https://berlin.freifunk.net/
[15:57] danae: https://calyxinstitute.org/
[15:58] Cristina: https://buildyourowninter.net/index.html
[16:00] Renée: These approaches are somewhat designed for working on the fly
[16:02] Renée: rapid deployment of networks
[16:02] Michelle: Some of the critical concerns in the region are loss of traditional knowledge on agro-biodiversity and indigenous crop cultivation, and the impact of climatic change and weather patterns on crop yields and biodiversity. The open source platform allows farmers to share information and co-create knowledge on indigenous crop varieties, cultural art forms like paintings, craft, music, etc. This is collected by the community and stored as a repository on a locally accessible server.
[16:03] Renée: These are also archival practices
[16:03] Renée: setting up a repository of local and situated knowledge
[16:06] Renée: time, duration, volunteerism, and how these approaches can be sustained in the long run
[16:09] Renée: outside of a monetary incentive, another knowledge is liberated, possible and allowed to flourish
[16:11] Renée: I suck at working in the terminal
[16:15] Sieta: is there somewhere a website for rhizomatica?
[16:15] Noemi: https://www.rhizomatica.org/
[16:15] Sieta: thanks you
[16:17] Renée: This is useful - not just the links but the links: https://www.rhizomatica.org/resources/
[16:17] Michelle: Sustainable livelihoods are facilitated by this system using an e-commerce platform, ensuring direct connection between the farmer and the clientele for selling and purchasing of goods. In the Pathardi community network in Maharashtra, women played a lead role in collecting information of the various biodiversity available in the village. This information was collected in the form of audio recordings played on a community radio, and photographs and videos of different plant and crop varieties. Women also collected information on the various methods adopted by the community to preserve seeds. Other methods of biodiversity conservation that women contributed to were through tribal wild food festivals where women followed traditional recipes.
[16:18] Michelle: https://canal3lavictoria.cl/
[16:20] Sieta: haha sooo nice to hear the capitalist mindset of ever more and 'better' is completely dismissed in this regards Danae ;)
[16:21] danae: YES <3
[16:21] Linda: ugh! wish I could stay. Super interesting. See you all after the break!
[16:22] danae: good luck!
[16:22] Renée: take care Linda
[16:23] Renée: This is definitely a continuation of those traditions
[16:28] Renée: And if we speak about datasets, what does it mean and what will the impact be if some datasets dominate over others and shape particular futures...
[16:28] Renée: at the exclusion of others?
[16:32] danae: https://foundation.mozilla.org/en/blog/isolated-communities-connect-amid-pandemic/
[16:32] Renée: thanks for the link Danae
[16:33] Michelle: https://www.jacobinmag.com/2015/04/allende-chile-beer-medina-cybersyn/
[16:34] Agathe Balayn: natural language processing for Africa https://www.masakhane.io/
[16:34] Renée: Thank you Agathe
[16:35] Cristina: thanks agathe!
[16:36] Renée: Our Values
Umuntu Ngumuntu Ngabantu - loosely translated from isiZulu means “a person is a person through another person” or “I am because you are”. This philosophy calls for collaboration and participation and community. It proposes relationality, over individualism for stronger social cohesions towards sustainable communities. It believes we share our successes and one’s personhood is evaluated based on their contributions to the community.
African-centricity. We centralize the narratives of Africans as a remedy to the effects of Euro-centricism on our beliefs. This way we reassert a new way of looking at information from a African perspective and shun any attempts to devalue our knowledge and stories
Ownership - We believe that Africans should be in charge of owning, driving and participating in the NLP research process, rather than as observers or data providers.
Openness - We believe in sharing our ideas and progress openly, especially on the African continent, for Africans. We’re against research that takes African contributions or data and puts them behind a paywall that is infeasible for Africans to access.
Multidisciplinarity - We truly believe that participation from all fields and experience and that multidisciplinarity leads to a more robust and more inclusive society
Everyone has valuable knowledge - We believe that each person’s individual experiences have value and each person is worth listening too and has something to contribute.
Kindness - We believe that being considerate, friendly and generous within our community is the best way to support it and encourage more inclusivity
Responsibility - We believe that each person in the technology process has an ethical responsibility to what they produce in the world. For this reason, we actively wreckon with the ethical impacts of our work
Data sovereignty - We believe Africans should be able to decide what data represents our communities globally, retain ultimate ownership of that data, and know how it is used
Reproducibility - We believe in reproducible research. As a result, we publish our code and data from our research so that others can reproduce and build upon it.
Sustainability - We believe that sustainability is necessary for societal change - that small daily efforts, over a long time are what truly change the world. To that, we aim for sustainability of our work, by being fully integrated with technological stakeholders to ensure the community continues to thrive into the future
[16:38] Agathe Balayn: data for Black lives https://d4bl.org/
[16:40] Cristina: Abolish Big Data is a call to action to reject the concentration of Big Data in the hands of a few, to challenge the structures that allow data to be wielded as a weapon of immense political influence. To abolish Big Data would mean to put data in the hands of people who need it the most.
[16:42] Cristina: transgressive potatoes
[16:43] Cristina: While this digital divide must be addressed,
information and communications technologies
(ICTs) can and must be employed and deployed
differently. Community networks offer an example
of how. One way to understand this is through the
lens of “appropriate technology”, defined as being
small-scale, affordable by locals, decentralised,
labour-intensive, energy-efficient, environmentally
sound, and locally autonomous.6
In this definition
we find similar dynamics in land stewardship and
small-scale agriculture insofar as the appropriate
technology movement grew out of the energy crisis
of the 1970s, similar to land-based approaches that
promote environmental conservation by seeking to
“close the cycle”, such as permaculture.
[16:44] Sieta: a really nice book about permaculture and society is Cultural Emergence by Looby Macnamara
[16:45] Cristina: the phrase "appropriate data" from Timnit Gebru still haunts me
[16:46] Welcome to Slow reading!For help on using BigBlueButton see these (short) tutorial videos.To join the audio bridge click the phone button. Use a headset to avoid causing background noise for others.To join this meeting by phone, dial: +31 15 201 0064Then enter 21282 as the conference PIN number.
[16:46] To invite someone to the meeting, send them this link: https://bbb.tbm.tudelft.nl/b/aga-9ab-8g7-tu1
[16:46] Renée: I know, it's freaky
[16:47] Renée: permaculture as an overarching structure where you understand things within a loop
[16:50] Noemi: Thank you for sharing!
[16:54] Michelle: https://www.youtube.com/watch?v=JOgzQLnQcHI
[16:54] Michelle: you can't hear me
[16:54] Michelle: don't know
[16:54] Michelle: okay
[16:55] Michelle: I was wondering if we could have a look at her work together
[16:55] Michelle: and maybe watch this youtube video together
[16:56] Cristina: next time you mean or in between?
[16:59] Cristina: @michelle: this one is also great text by her http://schemasofuncertainty.com/algorithms-as-cartomancy
[16:59] Michelle: when?
[17:00] Sieta: Ok!
[17:00] Michelle: at 4?
[17:01] Michelle: I have a meeting from 14-16
[17:01] Michelle: sure I can come after that
[17:01] Sieta: I can be there until 15:30
[17:01] danae: psa: this friday i'm at this SEX TECH TALKSHOW in case you want to join <3 https://twitter.com/touchyfeelytech/status/1385551389368127492
[17:01] Cristina: I can join too
[17:02] Cristina: @danae: when is the talk with you and timnit?
[17:02] danae: was yesterday!
[17:02] danae: five people went haha
[17:02] Cristina: recorded?
[17:02] danae: idk
[17:02] Cristina: 5 very lucky people
Word Frequency Counter
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Questions scraped
Can machines think?
What about spirituality?
What about Shinto?
Why should man be considered 'superior'?
(Michelle) Yes, this goes to the question of what is it to be human?
What does it mean to be alive/part of a society?
- 1st chapter is about how life is organasised when does the organism end and the envirohnment begins, are they part of tha same systems?
- (Michelle) where is the direction of the text going?
- (Sonia) Aristotle in relation to causes: humans choose their own causes (?
- (Michelle) how much of this concept of contingency is taken into the research process?
com/watch?
When is something called intelligence?
Renee: difference between wink and blink?
and how would that be worrying?
Danae: containeristation requires an amount of new skills, so we are in the midst of this problem, sustaining a more conservative system or embrace a new one?
Sieta: but an intentional trajectory would be within the context of the environment that also constraints, does that allow for less or more freedom?
Why do people become who they are?
If we release the framework of failure, we can really that we are in iterative cycles, and we can keep asking ourselves—how do I learn from this?
Which one is top down & which one is bottop up?
Linda: so the freedom we are talking about then, is it the freedom to be a finger while knowing that you are attached to a body?
What is the truth of freedom in this?
" (Juarrero P?
(Sieta can add note later?
At which stage do you introduce the ethics and that frameworks?
Is it too late to introduce them now?
Do they have to be introduced in the beginning or can they be encoded later?
Anna: Is ethics the potential of making an unbiased system?
Eg: what is a cancerous cell?
Sonia: yes, but how many people do you include?
Do you include nonhumans?
Agathe: how to relate machine learning to this complex system theory?
Question: How does this notion of bias relate to machine pedagogies (also relating to Linda's question about when to introduce these 'ethics' into AI), could a machine also be learning over time and space?
Renee: Renee talked about the video with Maya Indira Ganesh in conversation with Nishant Shah on: do datasets just grow?
Are they responsive or inclusive?
com/watch?
Renee: what does that mean in terms of datasets?
org/?
Google deep dream as human-induced AI hallucinations?
If we release the framework of failure, we can really that we are in iterative cycles, and we can keep asking ourselves—how do I learn from this?
And how does this work in an AI system?
com/watch?
What about doing?
Did AI detect a ghost?
How does that work as well?
Renee: HOw does the camera frame the recognition?
Would it be possible to have the screen share on so I can look at the code while I am writing?
S: do you see it?
R: COCO comes from the Gorilla, Like COCO wanta a banaan?
S: Should I click on something else?
How are the icons developed?
R: It is scraping any informatino from the url> ?
Linda: Why children?
R: It raises the question who is being trained actually?
[Who and where are the workers?
A: Should we read the paper or look at something else?
com/url?
Is this where we are at?
C: Do you think they developed it themselves?
rather than solve, perhaps it can become more transparent?
Or use those biases as a source of debate and public engagement?
Is this a Luddite arguement?
What is the scope of the objection - is it about simply limitations or more profound?
Rather than a problem of the mathematical capabilities of the machine, it can instead (missed this part) (be a problem of the receiver?
If Turing was to re-write this text in the present, how would he re-write it?
What is it to be human?
What would be the questions you would ask him if he were here?
But if he were in the room, what would be the questions we would ask him?
For example, what would he think of drones?
|||STOP||||Where does the organism begin or end?
What is necessary is to have clear ideas about what life is?
|||STOP||||How is this system relational?
|||STOP||||Are dualities gradients?
How is contingency defined within the models presented in the text?
Dates: 25, 26 March?
or 26, 27 March?
co/invitation/mural/v28710/1617120139614?
What brings you joy in this time?
What do "we" want to be "saved" from?
What kind of technologies do we want in the first place?
How would we embed our highest values?
What is depth in the context of deep learning?
What is the role of social and cultural memory within the context of technology?
What does it mean to recall and remember?
What are we forgetting today?
Is it possible to speak of "reconnection" at all?
Aren't we disconnected, per definition?
Can technology help us to remember what we have forgotten?
What is consent in the context of data extraction?
How do you deal with the desire for social domination?
What is the best way of framing a conversation around positive versus negative (or other forms) of exposure?
What kind of infrastructure is needed for subaltern pattern making?
[16:11] Renée : So then we hit mute?
[16:12] Cristina : do we hit play?
[16:14] Sieta : did you press play?
[16:19] Renée : What brings you joy in this time?
[16:21] Renée : What kind of technologies do we want in the first place?
[16:21] Renée : How would we embed our highest values?
[16:21] Renée : What is depth in the context of deep learning?
[16:23] Cristina : (side-question: did anyone read the Indigenous AI position paper?
[16:23] Renée : What is the role of social and cultural memory within the context of technology?
What does it mean to recall and remember?
[16:24] Renée : What are we forgetting today?
[16:24] Sieta : Can technology help us to remember what we have forgotten?
[16:25] Renée : What is consent in the context of data extraction?
[16:27] Renée : What are the processes of alienation and detachment that take place within AI's ruse?
[16:28] Renée : How do race and technology shape one another?
[16:28] Renée : How are input, output and impact interrelated?
[16:31] Renée : How are algorithms, as proprietary black boxes, cloaking systemic racism while simultaneously executing (producing) (proliferating) it?
[16:35] Renée : How are we literally indebted to these technologies?
[16:36] Renée : What is the responsibility with those with computational expertise?
[16:39] Sieta : what was the name of this movie?
[16:41] Cristina : did it also skip bacck to the beginning for you?
[16:46] Renée : What are the financial incentives behind racist and sexist patterning?
[16:48] Renée : How is fairness defined in this context?
[16:49] Renée : How do we interrogate what it means to be seen and grasp its consequences in terms of exposure, if not vulnerability?
[16:55] Cristina : is this adjacent video watching ?
[16:57] danae : the zoo bird keeper?
[17:29] Renée : What is her name again?
perhaps the sub- and infra- in subaltern and infrastructure can point towards grassroots infrastructures which can eventually federate?
[17:33] Renée : chapter in ?
[17:42] Renée : When is being seen essential and when is exploitative?
[17:52] Michelle : What would my life be without AI?
[17:52] Renée : Is AI just convenience?
[17:52] Renée : Does AI help with more vitally with certain communities?
[17:53] Michelle : Is AI really necessary?
[17:54] Michelle : What would happen if AI suddenly disappeared?
[17:54] Michelle : Is AI just an arms race and is the robot revolution imminent?
[17:59] Cristina : is AI only servitude?
[18:01] Agathe Balayn : i would say that any recommender system is ai, right?
twitter sorting posts on your wall?
[18:02] Linda : and email?
co/invitation/mural/v28710/1617120139614?
Renee: what is care as intelligence?
what is intelligence, the artifice?
measured by leaderboards?
Winograd schemas ("The man could not lift his son because he was too fat" --> who was too fat?
"documentation debt" = when datasets are so large it is difficult/expensive to document them?
Renee: datasets as Rapuccini's daughter (?
Michelle: where is the funding concentrated?
who is the audience of these papers?
what use are these systems if someone is speaking urdu?
php?
Can you imagine if a similar amount of energy was expended on educating a child?
xample, that the residents of the Maldives (likely to be underwater by 2100) or the 800,000 people in Sudan affected by drastic floods pay the environmental price of training and deploying ever larger English LMs, when similar large-scale models aren’t being produced for Dhivehi or Sudanese Arabic?
ref to How Not To Teach (?
linda: how can you talk about refusal when you don't even have a base understanding?
which feminism can actualise in data science?
is it only liberal feminism?
does the radical have space?
renee: what are the leaderboards/benchmarks for this text?
agathe: how do these topics become accepted through the peer review processes?
pdf (maybe rhizomatica?
"When something can't be fixed, then the question is what can we build instead?
[17:11] Sieta: like a README?
[17:37] Renée: who are the curators and what is their agenda - whether formulated forthrightly or through neglect?
[17:49] Michelle: how about a care brief?
[15:19] Renée: does the line break occassionally?
[16:15] Sieta: is there somewhere a website for rhizomatica?
[16:28] Renée: at the exclusion of others?
com/watch?
[16:56] Cristina: next time you mean or in between?
[16:59] Michelle: when?
[17:00] Michelle: at 4?
[17:02] Cristina: @danae: when is the talk with you and timnit?
[17:02] Cristina: recorded?
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