The AI side of cognitive science is concerned with first world problems

I recently had the opportunity to attend a multidisciplinary conference where cognitive scientists, philosophers, psychologists, artificial intelligence (AI) researchers, neuroscientists and physicists came together to discuss the self. The conference was, generally speaking, well organized and most of the talks were interesting. The theme of the conference was on the openness of the self which means that contrary to the traditional essentialist view of self as fixed, fully autonomous and self-contained, the consensus, among the attendees, was that the self is not a static, discrete entity that exists independent of others but dynamic, changing, co-dependent, and intertwined with others. This intertwinement would furthermore extend to social and political forces that play crucial roles into constituting who we are. In this vein, any discussion of self and technology needs to acknowledge the entanglement of social and political factors and the necessity for diverse input and perspectives.

AI is a very broad field of enquiry which includes, to mention but a few, facial recognition technologies, search engines (such as Google), online assistants (such as Siri), and algorithms which are used in almost every sphere (medical, financial, judicial, and so on) of society. Unfortunately, the view of AI that seems to dominate public as well as academic discourses is a narrow and one-dimensional one where the concern revolves around the question of artificially intelligent “autonomous” entities. This view is unsurprisingly often promoted by a one-dimensional group of people; white, middle-class and male. Questions outside “the creation of artificial AI” rarely enter the equation. The social, political, and economical factors rarely feature in the cognitive science and interdisciplinary formulations of selfhood and technology — as if any technological development emerges in a social, political and economical vacuum. And the conference I attended was no different.

This was apparent during theme-based group discussions at this conference where one group discussed issues regarding self and technology. The discussion was led by researchers in embodied AI and robotics. The questions revolved around the possibility of creating an artificial self, robots, whether AI can be sentient and if so how might we know it. As usual, the preoccupation with abstract concerns and theoretical construction took centre stage, to  the detriment of the political and social issues. Attempts to direct some attention towards the social and political issues were dismissed as irrelevant.

It is easy to see the appeal of getting preoccupied in these abstract philosophical questions. After all, we immediately think of “I, Robot” type of robots when we think of AI and we think of “self-driving” cars when we think of ethical questions in AI.

game and gambling, gaming machines, chess playing Turk, design by Wolfgang von Kempelen (1734 - 1804), built by Christoph Mechel

A 1980s Turk reconstruction

The fascination and preoccupation for autonomous and discrete machines is not new to current pop-culture. The French philosopher René Descartes had a walking and talking clockwork named after his daughter Francine. The machine apparently simulated his daughter Francine, who died of scarlet fever at the age of five. The 18c Hungarian author and inventor Wolfgang von Kempelen created the Mechanical Turk, (a fake) chess-playing and speaking machine to impress the Empress Maria Theresa of Austria.

It is not surprising that our perception of AI is dominated by such issues given that our Sci-Fi pop culture plays an influential role towards our perception of AI. The same culture feeds on overhype and exaggeration of the state of AI. The researchers themselves are also often as responsible for miscommunication and misunderstanding about the state of the art of the filed. And the more hyped a piece of work is, the more attention it is given – look no further than the narrative surrounding Sophia – an excessively anthropomorphized and overhyped machine.

Having said that, the problem goes further than misleading coverage and overhype. The overhype, the narrow one-dimension view of AI as concerned with question of artificial self and “self-driving” cars, detracts from nuanced and most important and more pressing issues in AI that impact the very poor, disfranchised, socially, economically disadvantaged. For example, in the current data economy, insurance systems reward and offer discounts for those that are willing to be tracked and provide as much information about their activities and behaviours. Consumers who want to withhold all but the essential information from their insurers will pay a premium. Privacy, increasingly, will come at a premium cost only the privileged can afford.

An implicit assumption that AI is some sort of autonomous, discrete entity separate from humans, and not a disruptive force for society or the economy, underlies this narrow one-dimensional view of AI and the preoccupation with the creation of artificial self. Sure, if your idea of AI revolves around sentient robots, that might bear some truth. This implicit assumption seems, to me, a hangover from Cartesian dichotomous thinking that remains persistent even among scholars within the embodied and enactive tradition who think that their perspectives account for complex reality. This AI vs humans thinking is misleading and unhelpful, to say the least.

AI systems are ubiquitous and this fact is apparent if you abandon the narrow and one-dimensional view of AI. AI algorithms are inextricably intertwined with our social, legal, health and educational system and not some separate independent entities as we like to envision when we think of AI. The apps that power your smart phone, the automated systems, including those that contribute to the decision towards whether you get a loan or not, whether you are hired or not, or how much your car insurance premium will cost you all are AI. AI that have real impact, especially on society’s most vulnerable.

Yet, most people working on AI (both in academia and Silicon Valley) are unwilling to get their hands dirty with any aspect of the social, economic or political aspect and impact of AI. The field seems, to a great extent, to be constituted of those who are socially, economically and racially privileged where these issues bear no personal consequences. The AI side of cognitive science is no different with its concerns of first world problems.  Any discussion of a person or even society is devoid of gender, class, race, ability and so on. When scholars in these fields speak of “we”, they are barely inclusive of those that are outside the status quo which is mostly a white, male, Western, middle-class educated person. If your model of self is such, how could you and why would you be concerned about the class, economic, race and gender issues that emerge due to unethical application of AI, right? After all, you are unlikely to be affected.  Not only is the model of self unrepresentative of society, there barely is awareness of the issue as a problem in the first place. The problem is invisible due to privilege which renders diversity and inclusivity of perspectives as irrelevant.

This is not by any means a generalization of everyone within the AI scholarship. There are, of course, plenty of people who acknowledge the political and social forces as part of issues to be concerned about within the discussion of AI. Unsurprisingly, such important work in this regard is done by people of colour and women who unfortunately, remain a minority. And the field as a whole would do well to make sure that it is inclusive of such voices, and to value their input instead of dismissing them.

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Situating China’s Social Credit System in history and context

If you have been following the developments in the digital humanities, it is very likely that you’ve come across the news that China is implementing a Social Credit System, officially known as Social Credit Score (SCS). Although the SCS is portrayed as a single integrated system that quantifies all behaviour into credit scores, it is in fact an ecology of fragmented initiatives with many different stakeholders. Broadly speaking, it consists of scoring systems developed by private sectors and by governmental bodies. As far as the governmental perspective is concerned, the SCS is an attempt to promote “trustworthiness” and transparency in the economy which is expected to combat perceived lack of trust in the marketplace, and more generally to harmonize social conduct.

Citizens “trustworthiness” is rated based an individual’s social behaviour such as their crime records, what they say on social media, what they buy, the scores of their friends, and so on. This has possible positive or negative implications on individual’s job, visa, loan applications. As a commitment towards radical transparency is a central driving force behind the SCS, information on subjects’ trustworthiness is made publicly available, and in some circumstances even being actively broadcast. Individual citizens and businesses alike are publicly ranked where the records are publicly open.

SCS civilized families

Roncheng’s “civilized families” are displayed on public noticeboards like these. (Simina Mistreanu)

The SCS is to become mandatory by 2020 and is currently being implemented in some form or another across parts of China. Areas that are socioeconomically deprived seem prior targets. Rongcheng in the eastern province of Shandong, where the SCS has been rolled out for some time now, is, according to government officials, one of the best examples of the system working as intended, according to government officials.

From a general systems science perspective, the SCS is a self-organizing system that operates through incentive and punishment mechanisms. People with low ratings will, for example, have slower internet speeds, restricted access to restaurants, and the right to travel invoked.

“Higher scores have already become a status symbol, with almost 100,000 people bragging about their scores on Weibo (the Chinese equivalent of Twitter) within months of launch. A citizen’s score can even affect their odds of getting a date, or a marriage partner, because the higher their Sesame rating, the more prominent their dating profile is on Baihe.” (Creemers, 2018)

The SCS has been described as an insidious digital panopticon and a dystopian nightmare where individuals’ every move are monitored and ranked through data generated from all sorts of activity and interactions, online or otherwise through digital technologies (facial recognition tools and biometric information). Many draw parallels between the SCS and the dystopian science fiction Black Mirror episode “Nosedive” where people rate each other based on their interactions.

Black Mirror rating

Many ethical and human rights issues as well as the complete eradication of the idea of privacy have been raised and the negative consequences of such a dystopian nightmare system is indisputable.

With the realization that ‘digital reputations’ could limit opportunities comes the tendency to self-censor and the tendency to be risk-averse. We are unlikely to hit “like” on a Facebook post that protests some government policy knowing that it could impact our ‘digital reputations’. Consequently, people gradually change their behaviour to align with what the system requires, to get better scores. In the process those behaviours and norms defined as “acceptable” by the government are reinforced.

Nonetheless, among the misconceptions surrounding the SCS, there seems to be some consensus that using individual’s digital traces to directly or indirectly influence individual’s behaviour is something that only happens in non-Western totalitarian states. In fact, credit scoring practices are not unfamiliar in Western societies. Facebook, for instance, seems it is developing its own system of rating users trustworthiness.

It is also worth mentioning Facebook’s emotion tracking patent (where the aim is to monitor individuals’ typing speed in order to predict emotions and adapt messages in response), which was granted in May 2017 and the currently filed Socioeconomic classifier (which might enable Facebook to rank its users according to different social classes), among its series of patents. These developments in combination with others, such as Facebook’s ability to flag individuals through its facial recognition technology without the consent of the user, in some sense constitute a surveillance society. Facebook’s ability to rank and categorize people into a variety of socioeconomic categories has possible impacts on individuals’ opportunities depending on their class, gender, race and sexual orientation. Whether its the type of job ads one is excluded from viewing (due to their gender, class or age) or the exclusion from certain housing ads, Facebook’s ranking and categorizing systems often impact the under-privileged and those who fail to conform to the status quo.

Health insurance

Marshall Allen, July 2018, ProPublica

Along social media platforms, health insurers, and schools, can also be mentioned as examples that share features of the SCS. Like the SCS, these Western industries and institutes, track and surveil people through digital technologies including face recognition tools and biometric information.

We are rated, ranked and categorized using data extracted from us. Similar to the SCS, such ranking and rating often has possible “real” life consequences whether in the form of how much we pay for our insurance, what ads are pushed on us, or how we behave in school yards. The difference between the Chinese SCS and Western tech industry is, while the former is clear and upfront about it, the latter is much more invisible. In fact, such tech giants go out of their way to hide what they are doing.

Rating systems, those by the SCS or deployed through Western tech industry, create unwanted incentives and increase pressure on individuals to conform to the status quo. This creates and contributes to a society that is risk averse.

“When doctors in New York were given scores this had unexpected results. Doctors that tried to help advanced cancer patients had a higher mortality rate, which translated into a lower score. Doctors that didn’t try to help were rewarded with high scores, even though their patients died prematurely.” Tijmen Schep

Situating the SCS in history and context

The history and context which are crucial to the development of the current SCS are often missing from how the SCS is framed, at least within in Western media .

“[social systems] must be viewed whole cloth as open dynamical systems embedded in a physical, historical, and social fabric” (Juarrero, 1999, p. 201)

As far as China’s political tradition goes, morality and authority are inextricably linked. Enforcing moral standards, monitoring and disciplining the conduct of local officials and individual citizens is seen as the role of the state. “Governing the country by virtue” equals to “governing the country by the law”. Unlike the Western legal system where rights, responsibilities and entitlement of private actors and public sectors are relatively easily categorized, such categories are much more blurred within the Chinese legal system. Individual citizens, government officials, communities and business are all expected to contribute to the whole social and economic harmony and development.

“Chinese political tradition has, for centuries, conceived of society as an organic whole, where harmony can be achieved if all its members conduct themselves as appropriate to their position in public and civil structures. … Critical in this process were ideas about systems theory, derived from natural science and applied in the social context. Influenced by Western scholarship on cybernetics and systems theory, scholars such as Qian Xuesen and Song Jian worked closely with government to develop a conceptual framework for the adoption of systems engineering techniques in governance. Particular regard was given to the role of information flows, not just towards and within government, but also as part of cybernetic feedback loops to create self-correcting responses in society.” (Creemers, 2018, p. 7)

Historically the Chinese government has experimented with some forms of social control and controlling social order through self-policing and social controlling mechanisms go all the way back to the Song Dynasty.

“An 11th-century emperor instituted a grid system where groups of five to 25 households kept tabs on each other and were empowered to arrest delinquents” Mistreanu, 2018. The current SCS then is an extension of such historical traditions. The difference now is the addition of digital technologies.

From the Chinese authorities perspective the SCS epitomizes a self-correcting feedback loop where “trustworthiness” and social morality are fostered through incentives and punishments.

This by no means is to argue that the SCS is any less of a digital panopticon. However, by highlighting history and context, often missing from the SCS narrative, we can paint a somewhat complex and nuanced image of the system (as opposed to the often alarming pieces which are stripped of context and history). Furthermore, while we are preoccupied by the stories of how China is becoming one giant surveillance prison, we miss the indirect and evasive practices that are happening within our own “civilized” Western system.

 

Bibliography

Creemers, R. (2018). China’s Social Credit System: An Evolving Practice of Control.
Juarrero, A. (1999). Dynamics in action: Intentional behavior as a complex system (p. 127143). Cambridge, MA: MIT press.

 

 

The in(human) gaze and robotic carers

Google search “robot carers” and you’ll find extremely hyped up articles and think pieces on either how robot carers are just another way of dying even more miserably or how robot carers are saving the elderly from the lives of loneliness and nothing much in between. Not much nuance. Neither is right, of course. Robot carers shouldn’t be dismissed at first hand as the end of human connections and neither should they be overhyped as the flawless substitutes for human care.

I think they can be useful and practical and even preferable to a human carer in some cases while they cannot (and most likely never will) substitute human care and connection in other aspects. The human gaze is my reason for thinking that.

But first let me say a little about the Inhuman Gaze conference, which provoked me to think about robot care givers. The conference took place last week (6th – 9th June) in Paris. It was a diverse and multidisciplinary conference that brought together philosophers, neuroscientists, psychiatrists (scholars and practitioners alike) with the common theme of the inhuman gaze. Over the four days, speakers presented their philosophical arguments, empirical studies and clinical case studies, each from their own perspective, what the human/inhuman gaze is and its implication for the sense of self. I, myself, presented my argument for why other’s gaze (human or otherwise) is a crucial constituent to “self”. I looked at solitary confinement as an example. In solitary confinement (complete isolation or significantly reduced intersubjective contact), prisoners suffer from negative physical and psychological effects including confusion, hallucination and gradual loss of sense of self. The longer (and more intense) the solitary confinement goes, the more the pronounced the negative effects, leading to gradual loss of sense of self.

The reason for gradual loss of self in the absence of contact with others, Bakhtin would insist, is that the self is dependent on others for its existence. The self is never a self-contained and self-sustaining entity. It simply cannot exist outside the web of relations with others. Self-narrative requires not only having something to narrate but also having someone to narrate it to. To be able to conceptualize my self as a meaningful whole, which is fundamental to self-individuation and self-understanding, I need an additional, external perspective – an other.  The coherent self is put under threat in solitary confinement as it is deprived of the “other”, which is imperative for its existence. The gaze of another, even when uncaring, is an affirmation of my existence.

So, what is an inhuman gaze? A gaze from non-human objects: like the gaze of a wall in a solitary confinement? The gaze of a CCTV camera (although there often is a human at the other end of a CCTV camera)? or a gaze from a human but one that is objectifying and dehumanizing? For example, the gaze from a physician who’s performing an illegal organ harvesting where the physician treats the body that she’s operating on like an inanimate object? Let’s assume an inhuman gaze is the gaze of non-human objects for now. Because the distinctiveness of the human gaze (sympathizing, caring, objectifying or humanizing) is important to the point that I am trying to make. The human gaze, unlike the inhuman gaze, is crucial to self-affirmation.

channel-4s-new-sci-fi-robot-series-humans

From Channel 4’s sci-fi robot series Humans

Robot caregivers and the human gaze…

Neither the extreme alarmist nor the uncritical enthusiast help elucidate the pitfalls and potential benefits of robot caregiving. Whether robotic caregiving is a revelation or a doom depends on the type of care one needs. Roughly speaking, we can categorize care that robots can provide into two general categories. First one is physical or mechanical care – for example., fetching medicine or changing elderly patients into incontinence wear. The second one, on the other hand is companionship (to elderly people or children) where the aim might be to provide emotional support.

Now, robotic care might be well suited for the physical or mechanical type of care. In fact, some people might prefer a robot dealing with such physical task as incontinence care or any similar task that they are no longer able to perform themselves. Such care, when provided by a human, might be embarrassing and humiliating for some people. Not only is the human gaze capable of deep understanding and sympathy but also the potential to humiliate and intimidate. The robotic gaze, on the other hand, having no intrinsic values, is not judgemental. So, in the case of physical and mechanical care, the absence of the human gaze does not necessarily result in a significant negative effect. In fact, it might be desirable when we are in a vulnerable position where we feel we might be humiliated.

On the contrary, if companionship and emotional support are the types of care that we are looking for, the value and judgement free robotic gaze will simply not do. We are profoundly social, dynamic and embodied beings who continually strive to attribute meaning and value to the world. If we are to ascribe an ‘essence of the human condition’, it is that that our being in the world is thoroughly interdependent with the existence of others and context where we continually move and negotiate between different positions. True companionship and emotional connection requires intrinsic recognition of emotions, suffering, happiness, and the like. A proper emotional and ethical relation to the other (and the acceptance of genuine responsibility) requires the presence of a loving and value-positing consciousness, and not a value-free, objectifying gaze.

True human companionship and emotional support cannot be programmed into a robot no matter how advanced our technologies can become, for companionship and emotional connection require sense-making and a value-positing consciousness. Sense-making is an active, dynamic and partly open undertaking – and therefore a never-ending process – not a matter of producing and perceiving mappings of reality which can then be codified into a software.  The human gaze affords mutual understanding of what being a human is like. Recognition of emotions, suffering, etc., requires recognition of otherness based on mutual understanding. The human gaze recognizes an ‘other’ human gaze. As Hans Jonas has put it succinctly in ‘The Phenomenon of Life’, “only life can know life … only humans can know happiness and unhappiness.” 

 

 

A foetus is not a person

As the referendum on the Eighth Amendment of the Constitution of Ireland fast approaches, misinformation and misunderstanding (both deliberate and unintentional) continue to circulate on a massive scale, both on social media platforms and on the forest of posters that line every road and street. The rhetorical weapons used by the Vote No campaign are subtle and powerful. Consequently, it is becoming increasingly difficult to distinguish fact from mere propaganda, and sound argument from mere rhetoric.

Unsurprisingly, the stakes are high. For those seeking to remove the Eighth Amendment, the basic right to bodily autonomy for women and girls is at stake. For those seeking to maintain the status quo, the power to control, limit and punish women and girls – the basic aims of misogyny – seem to be slipping away. Emotions run high.

One clearly fallacious argumentative strategy used by the Vote No campaign is the use of various “slippery slope” arguments. For example, they argue that if abortion is legalized, then it will lead to terminations of all pregnancies with life limiting conditions; or that if abortion up to 12 weeks is legalized, then there is no guarantee that it won’t be extended to 20 weeks, or to 9 months, or indeed lead to the legalisation of infanticide.

There are a number of problems with these arguments. First, they are empirical, causal arguments: they tell us that if such-and-such state of affairs comes about, then a certain effect will follow. But we should only believe such arguments on the basis of empirical evidence: in particular, only if the relevant kind of state of affairs really has led to the relevant sort of effect in the past. And this evidence simply does not exist: there is no evidence that once the termination of pregnancy under certain circumstances is legalised in a jurisdiction, the effects claimed in the various slippery slope arguments come about.

Moreover, the first example above – that if abortion is legalized, then it will lead to terminations of all pregnancies with life limiting conditions – assumes that the only purpose of abortion is to terminate pregnancies with life limiting conditions. How does termination of pregnancies for reasons other than life limiting conditions fare based on this logic? A foetus’s life limiting conditions is not the sole reason for abortion, and prohibiting abortion in general in order to prevent termination of pregnancies with life limiting conditions makes no sense, since not all terminations are due to life limiting conditions of the foetus.

Furthermore – and this cannot be emphasised enough – abortion happens whether it is legal or not. So criminalizing abortion does not solve any problems – it simply creates more misery and suffering. Criminalizing abortion deprives women and girls of access to safe and legal abortion, and forces them to seek other unsafe means of terminating unwanted pregnancies.

This is an important point: the effect of legalising abortion is not to allow access to abortion where there was none, but rather to make abortion safe.

Finally, voting no to repeal the Eighth Amendment is actively deciding to take away a woman’s right to autonomy over her body. Since legalizing abortion is giving women the right to decide for themselves, neutrality is an expression of satisfaction with the status quo – which currently either forces women either to travel to seek termination, to go through the procedure illegally and unsafely, or forces (using the power of the State) women to carry pregnancy to full term.

Personhood: The Western Christian View vs dialogical views

Arguments about how Irish society’s most vulnerable (working class women, women of colour) are most affected by the lack of safe and legal abortion, or how the criminalizing of abortion in Ireland deprives women of their reproductive rights, are ongoing and familiar within the abortion debate.

What we want to address here is the (mis)conception (which is the basis of some anti-abortion arguments) that a foetus is a person with a right to life equivalent to that of a fully-fledged adult. This follows from the argument that life begins at conception, and that life guarantees personhood. It is a consequence of this line of thinking that as soon as conception occurs, there exist two independent lives (the foetus and the pregnant woman) with equal rights.

Even if we grant that life begins at conception, the idea of equating of life with personhood is a wholly misguided one, which has its roots in the Western Christian notion of a soul. A person, according to this doctrine, is a totally autonomous, self-contained entity that exists independent of others. This view is generally known as “individualistic” and to a large extent attributed to the 17th-century French philosopher, René Descartes. This conception of selfhood is not only problematic but on a closer inspection fails to provide logical support for the argument that a foetus is a person. A foetus is clearly not a totally autonomous and self-sufficient entity, and therefore cannot be granted personhood.

Ubuntu-Empathy-the-New-Paradigm-for-Humanity.jpg

Alternatively, dialogical perspectives of selfhood provide a radically different view of personhood – one that views other people as imperative pillars of the self. According to dialogical perspectives, which stand in sharp contrast to the individualistic notion of personhood, we need and rely on others in order to construct and sustain our sense of self. We are inextricably inseparable from those around us, and continually develop and change through intersubjective interaction with others. Our self-knowledge comes from others and continually develops through our daily intersubjective interactions with others and our environment. As the Russian intellectual Mikhail Bakhtin put it:

“Within my own consciousness, my “I” has no beginning and no end. The only way I know of my birth is through accounts I have of it from others; and I shall never know my death, because my “self” will be alive only so long as I have consciousness – what is called my death will not be known by me, but once again by others. While the birth and death of others appear to be irreversibly real.”

Without others, the very core of our existence is threatened and solitary confinement is a grim and harrowing example of this. With the view of a person as a process (rather than an entity) continually developing and changing and interdependent with others, we might then grant a foetus some status of personhood but one that is not on a par with a fully-fledged adult and, furthermore, one that is entirely dependent on others (the pregnant woman or girl to be specific) for its existence and identity.

The idea of a continually changing self (which is dependent on others for its existence) can be troubling, especially since it seems to remove the apparent total autonomy that we typically take for granted, especially within individualistic cultures.

In non-individualistic cultures – where others are seen as pivotal constituents of the self, communal values are prior to individual ones, and we are before I am (or as the Kenyan-born philosopher John Mbiti put it ‘I am because we are, and since we are, therefore I am’) – the collective comes before the individual. Responsibility, for example, is distributed among every member of the community, and not something that is left up to individual parents.

In Ethiopia, for example, where I grew up, the manifestation of the sentiment ‘the collective before the individual’ can be seen in the values placed around abortion and child-rearing. While less emphasis is put on the status of the foetus (and the decision mainly left up to the grown adult – the pregnant woman or girl –  who is not equated with a foetus) more emphasis is put on the responsibility of each member of the community in raising a child. If, for example, an adult sees a school child skipping school, responsibility to advise that child and send them back to school is assumed. Members of that community are active participants in the upbringing of all children. This is in stark contrast to more individualistic cultures, where people make it their business to monitor pregnant bodies during pregnancy and (in the Irish case) force women or girls to carry pregnancy to full term, but take little or no responsibility for a baby when it has been born.

Coming back our point about abortion and the implication of the idea of personhood as a process that continually develops with complete dependence on others (gradually becoming less dependent) is that the foetus, being the early stage of the process, in not a person similar to that of a fully-fledged adult.

The response that is often raised by the anti-abortionists to this is that “when does a foetus become a person?”, “at what point does transformation from foetus to a person occur?”

This unfortunately is an ill-framed and irrelevant question, philosophically speaking. Personhood is a process that develops over time through intersubjective dialogical relationships with others. Not an all-or-nothing entity that either exists or doesn’t. Not something you have or don’t have. Looking for a specific time when a foetus becomes a person is therefore misguided.

The anti-abortion argument that a foetus has a right to life in the same sense that a pregnant woman or girl has then lies on philosophically erroneous conceptions of personhood. Given that personhood is a process of continual development that is sustained in interaction with others, it is a mistake to think that the foetus (which is considerably less developed and immensely dependent on the pregnant women) is a person in the same way – and to the same degree – that the pregnant woman or girl is.

This blogpost is co-written by Abeba Birhane, Cognitive Science PhD candidate at University College Dublin and Dr. Daniel Deasy, Lecturer in Philosophy at University College Dublin.

Resources – on automated systems and bias

Last updated: 09/11/2018

If you are a data scientist, a software developer, or in the social and human sciences with interest in digital humanities, then you’re no stranger to the ongoing discussions on how algorithms embed and perpetuate human biases. Ethical considerations and critical engagement are urgently needed.

I have keenly been following these discussions for a while and this post is an attempt to put together the articles, books, book reviews, videos, interviews, twitter threads and so on., that I’ve come across, in one place so they can be used as resources.

This list is by no means exhaustive and as we are becoming more and more aware of the catastrophic consequences of these technologies, more and more pieces/articles/journal papers are being written about it on a daily basis. I plan to update this site regularly. Also, if you think there are relevant material that I have not included, please leave them as a comment and I will add them.

Books

Weapons of math destruction: how big data increases inequality and threatens democracy by Cathy O’Neil. A great number of the article on the list below are written by O’Neil. She is also active on Twitter regularly posting links and interesting critical insights on everything to do with mathematical models and bias. Here is my own review of O’Neil’s book with plenty of relevant links itself and here for another excellent review of O’Neil’s book.

We Are DataWe Are Data: Algorithms and the Making of Our Digital Selves (2018) by John Cheney-Lippold. Below is the first few paragraph from a review by Daniel Zwi, a lawyer with an interest in human rights and technology. Here is also a link to my twitter thread where you can read excerpts from the book that I tweeted as I read the book.

In 2013, a 41-year-old man named Mark Hemmings dialled 999 from his home in Stoke-on-Trent. He pleaded with the operator for an ambulance, telling them that ‘my stomach is in agony’, that ‘I’ve got lumps in my stomach’, that he was vomiting and sweating and felt light-headed. The operator asked a series of questions — ‘have you any diarrhoea or vomiting?’; ‘have you passed a bowel motion that looks black or tarry or red or maroon?’ — before informing him that he did not require an ambulance. Two days later Mr Hemmings was found unconscious on the floor of his flat. He died of gallstones shortly after reaching hospital.

This episode serves as the affective fulcrum of We Are Data: Algorithms and the Making of Our Digital Selves, John Cheney-Lippold’s inquiry into the manner in which algorithms interpret and influence our behaviour. It represents the moment at which the gravity of algorithmic regulation is brought home to the reader. And while it may seem odd to anchor a book about online power dynamics in a home telephone call (that most quaint of communication technologies), the exchange betokens the algorithmic relation par excellence. Mr Hemmings’s answers were used as data inputs, fed into a sausage machine of opaque logical steps (namely, the triaging rules that the operator was bound to apply), on the basis of which he was categorised as undeserving of immediate assistance.

The dispassionate, automated classification of individuals into categories is ubiquitous online. We either divulge our information voluntarily — when we fill out our age and gender on Facebook, for example — or it is hoovered up surreptitiously via cookies (small text files which sit on our computer and transmit information about our browsing activity to advertising networks). Our media preferences, purchases and interlocutors are noted down and used as inputs according to which we are ‘profiled’ — sorted into what Cheney-Lippold calls ‘measureable types’ such as ‘gay conservative’ or ‘white hippy’ — and served with targeted advertisements accordingly.

Algorithms of oppressionAlgorithms of oppression: How search engines reinforce – below is an excerpt from Nobel’s book:

Run a Google search for “black girls”—what will you find? “Big Booty” and other sexually explicit terms are likely to come up as top search terms. But, if you type in “white girls,” the results are radically different. The suggested porn sites and un-moderated discussions about “why black women are so sassy” or “why black women are so angry” presents a disturbing portrait of black womanhood in modern society.
In Algorithms of Oppression, Safiya Umoja Noble challenges the idea that search engines like Google offer an equal playing field for all forms of ideas, identities, and activities. Data discrimination is a real social problem; Noble argues that the combination of private interests in promoting certain sites, along with the monopoly status of a relatively small number of Internet search engines, leads to a biased set of search algorithms that privilege whiteness and discriminate against people of color, specifically women of color.

Screenshot 2017-09-15 at 9.09.59 PM - Edited

Algorithms to Live By: The Computer Science of Human Decisions by Brian Christian and Tom Griffiths. This book is concerned with the workings of the human mind and how computer science can help human decision making.  Here is a post by Artem Kaznatcheev on Computational Kindness which might give you a glimpse of the some of the issues that book covers. Here is a long interview with Brian Christian and Tom Griffiths and a TED Talk with Tom Griffiths on The Computer Science of Human Decision Making.

The Black Box Society: The Secret Algorithms That Control Money and Information by Frank Pasquale. You can read the introduction and conclusion chapters of his book here And here is a good review of Pasquale’s book. You can follow his twitter stream here.

Technically Wrong: Sexist Apps, Biased Algorithms, and Other Threats of Toxic Tech by Sara Wachter-Boettcher

Technically wrongHere is a synopsis:  A revealing look at how tech industry bias and blind spots get baked into digital products—and harm us all.

Buying groceries, tracking our health, finding a date: whatever we want to do, odds are that we can now do it online. But few of us ask why all these digital products are designed the way they are. It’s time we change that. Many of the services we rely on are full of oversights, biases, and downright ethical nightmares: Chatbots that harass women. Signup forms that fail anyone who’s not straight. Social media sites that send peppy messages about dead relatives. Algorithms that put more black people behind bars.

Sara Wachter-Boettcher takes an unflinching look at the values, processes, and assumptions that lead to these and other problems. Technically Wrong demystifies the tech industry, leaving those of us on the other side of the screen better prepared to make informed choices about the services we use—and demand more from the companies behind them.

Paula Boddington, Oxford academic and author of Towards a Code of Ethics for Artificial Intelligence, recommends the five best books on Ethics for Artificial Intelligence. Here is the full interview with Nigel Warburton, published on December 1, 2017.

Automating inequality“Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor” by Virginia Eubanks is being published and will be released on January 23, 2018. Here is an excerpt from Danah Boyd’s blog:

“Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor” is a deeply researched accounting of how algorithmic tools are integrated into services for welfare, homelessness, and child protection. Eubanks goes deep with the people and families who are targets of these systems, telling their stories and experiences in rich detail. Further, drawing on interviews with social services clients and service providers alongside the information provided by technology vendors and government officials, Eubanks offers a clear portrait of just how algorithmic systems actually play out on the ground, despite all of the hope that goes into their implementation.

The Big Data AgendaThe Big Data Agenda: Data Ethics and Critical Data Studies by Annika Richterich PDF available through the link here.

“This book highlights that the capacity for gathering, analysing, and utilising vast amounts of digital (user) data raises significant ethical issues. Annika Richterich provides a systematic contemporary overview of the field of critical data studies that reflects on practices of digital data collection and analysis. The book assesses in detail one big data research area: biomedical studies, focused on epidemiological surveillance. Specific case studies explore how big data have been used in academic work.

The Big Data Agenda concludes that the use of big data in research urgently needs to be considered from the vantage point of ethics and social justice. Drawing upon discourse ethics and critical data studies, Richterich argues that entanglements between big data research and technology/ internet corporations have emerged. In consequence, more opportunities for discussing and negotiating emerging research practices and their implications for societal values are needed.”

 

Re-Engineering HumanityRe-Engineering Humanity by professor Evan Selinger and Brett Frischmann

Every day, new warnings emerge about artificial intelligence rebelling against us. All the while, a more immediate dilemma flies under the radar. Have forces been unleashed that are thrusting humanity down an ill-advised path, one that’s increasingly making us behave like simple machines? In this wide-reaching, interdisciplinary book, Brett Frischmann and Evan Selinger examine what’s happening to our lives as society embraces big data, predictive analytics, and smart environments.

OutnumberedOutnumbered: From Facebook and Google to Fake News and Filter-bubbles – The Algorithms That Control Our Lives (featuring Cambridge Analytica) by David Sumpter.

A review from Financial Times, here.

 

 

 

 

TED Talks, podcasts, and interviews 

The era of blind faith in big data must end TED Talk by Cathy O’Neil, April, 2017

Machine intelligence makes human morals more important November 11, 2017. In this TED Talk, Zeynep Tufekci emphasizes the importance of human values and ethics in the age of machine intelligence and algorithmic decision making.

We’re building an artificial intelligence-powered dystopia, one click at a time, another thought provoking TED Talk from techno-sociologist Zeynep Tufekci.

How I’m fighting bias in algorthims TED Talk – MIT Researcher Joy Buolamwini, November 2016

AI, Ain’t I A Woman? Joy Buolamwini

Data is the new gold, who are the new thieves? TED Talk – Tijmen Schep 2016

O’Neil’s interview with Politics Weekly podcast (starts 30mins in) July 5, 2017. O’Neil calls for public awareness on how algorithms are used, often without our knowledge, in job interviews, for example., and explains why we should question and interrogate these algorithms which are often presented to us as authoritative.

A short interview with Frank Pasquale on his book Black Box Society May 12, 2016. Pasquale emphasizes the opaqueness of algorithms and argues on why we should demand transparency.

A 2 minutes video, a prototype example, of algorithms being used in recruitment. A working example of the kind of dangerous AI used for recruiting that experts such as O’Neil constantly warn against. This post provides a critical analysis of why such endeavors are futile and dangerous. Here’s another related video on how facial recognition technology will go mainstream in 2018. In fact, such technology has gone mainstream in China. Here is a short video where a BBC reporter experimented with the world’s largest surveillance system.

Tom Chatfield on Critical Thinking October 2, 2017 In this philosophically themed podcast, Chatfield discusses issues such as “how new digital realities interact with old human biases” with Dave Edmonds.

When algorithms discriminate: Robotics, AI and ethics November 18, 2017. Stephen Roberts, professor of computer science at the University of Oxford, discusses the threats and promises of artificial intelligence and machine learning with Al Jazeera.

Here is a series of talks, from the ABC Boyer Lectures, hosted by Professor Genevieve Bell. The series is called Fast, Smart and Connected: What is it to be Human, and Australian, in a Digital World? The issues discussed include “How to build our digital future.”

You and AI – Just An Engineer: The Politics of AI (July, 2018). Kate Crawford, Distinguished Research Professor at New York University, a Principal Researcher at Microsoft Research New York, and the co-founder and co-director the AI Now Institute, discusses the biases built into machine learning, and what that means for the social implications of AI.

Facebook: Last Week Tonight with John Oliver (HBO) an extremely funny and super critical look at Facebook.

Humans are biased, and our machines are learning from us — ergo our artificial intelligence and computer programming algorithms are biased too. Joanna Bryson explains how human bias is learned by taking a closer look at how AI bias is learned.

Websites

Social Cooling is a term that refers to a gradual long term negative side effects of living in an digital society where our digital activities are tracked and recorded. Such awareness of potentially being scored by algorithms leads to a gradual behaviour change: self-censorship and self-surveillance. Here is a piece on what looks like social cooling in action. The website itself has plenty of resources that can aid critical thinking and touches up on big philosophical, economical and societal questions in relation to data and privacy.

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www.socialcooling.com

For those interested in critical thinking, data and models Calling Bullshit offers various resources and tools for spotting and calling bullshit. This website, developed for a course entitled ‘Calling Bullshit’, is a great place to explore and learn about all things “data reasoning for the digital age”.

Another important website that is worth a mention here is Algorithmic Justice League where you can report algorithm bias, participate in testing software for inclusive training set, or where you can simply donate and contribute raising awareness about existing bias in coded systems. More on AI face misclassification and accountability by Joy Buolamwini here. With a somewhat similar aim is the Data Harm Record website – a running record of harms that have been caused by uses of big data.

fast.ai a project that aims to increase diversity in the field of deep learning and make deep learning accessible and inclusive to all. Critical Algorithm Studies: a Reading List – a great website with links to plenty of material on critical literature on algorithms as social concerns. Here is the Social Media Collective Reading List where you’ll find further material on Digital Divide/ Digital Inclusion and Metaphors of Data.

The AI Now Institute at New York University is an interdisciplinary research center dedicated to understanding the social implications of artificial intelligence. Data & Society is a research institute focused on the social and cultural issues arising from data-centric technological developments.  FAT/ML is a website on Fairness, Accountability, and Transparency in Machine Learning with plenty of resources and events, run by a community of researchers. Litigating Algorithms: Challenging Government Use of Algorithmic Decision Systems. An AI Now Institute Report.

ConceptNet Numberbatch 17.04: better, less-stereotyped word vectors This is not a website but a blogpost. I am putting it here with other websites as the author offers some solution to reducing biases when building algorithms for natural language understanding beyond simply stating that such algorithms are biased.

Auditing Algorithms – a useful website for those teaching/interested in accountability in automated systems. The site includes films festivals, videos, etc,.

The Ethics and Governance of Artificial Intelligence – a cross-disciplinary course that investigates the implications of emerging technologies, with an emphasis on the development and deployment of Artificial Intelligence. Here’s an Introduction to Data Ethics by Markkula Center for Applied Ethics.

Google launches a new course to teach people about fairness in machine learning.

 

Biology/genetics  – (Digital phrenology?) 

It is difficult to draw a line and put certain articles under the category of “social”, “biological”, “political”, or other as the boundaries between these categories are blurred and most of the themes are somehow all interlinked. Nonetheless, I think the following articles can loosely be described as dealing with biological/genetics/personality material. Furthermore, towards the end of this post, I have also thematized some articles under the category of “political”.

In a recent preprint paper “Deep Neural Networks Can Detect Sexual Orientation From Faces” (here are the Gurdian and the Economist reportings) Yilun Wang and Michal Kosinski calmed that their deep neural network can be trained to discern individuals’ sexual orientations from their photographs. The paper has attracted and continues to attract a massive attentions and has generated numerous responses, outrages and discussion. Here is an in-depth analysis from Calling Bullshit and here for a detailed technical assessment and here for a comprehensive and eloquent response from Greggor Mattson. Here is another response and another one here from a data scientist’s perspective and another recent response from O’Neil here. If you only want to read just one response, I highly recommend reading Mattson’s. There have been been plenty of discussions and threads on Twitter – here and here are a couple of examples. It is worth noting that Kosinski, one of the authors of the above paper, is listed as one of the the advisers for a company called Faception, an Israeli security firm that promises clients to deploy “facial personality profiling” to catch pedophiles and terrorists among others.

Do algorithms reveal sexual orientation or just expose our stereotypes? by @blaiseaguera et al., is the latest (January 11, 2018) response to the above Wang and Kosinski “gaydar” paper. In this critical analysis, @blaiseaguera et al., argue that much of the ensuing scrutiny of Wang and Kosinski work has focused on ethics, implicitly assuming that the science is valid. However, on a closer inspection, et al., find that the science doesn’t stand up to scrutiny either.

When advanced technologies in genetics and face recognition are applied with the assumption that “technology is neutral”, the consequences are often catastrophic and dangerous. These two pieces, Sci-fi crime drama with a strong black lead and Traces of Crime: How New York’s DNA Techniques Became Tainted provide some in-depth analysis of such.

Physiognomy’s New Clothes this is a comprehensive and eloquent piece and well worth your time. Physiognomy, the practice of using people’s outer appearance to infer inner character is a practice that is now discredited and discarded as phrenology. However, this piece illustrates how such practice is alive and well in the era of big data and machine learning. Here is more on the Wu and Zhang paper that the Physignomy’s New Clothes authors cover in the above piece. Further examples of digital phrenology can be found here and here here.

General articles on various automated systems and bias, discrimination, unfairness, ethical concerns, etc., listed in order of publication dates starting from the latest.

Frank Pasquale testifies (video, written testimony) Before the United States House of Representatives Committee on  Energy and Commerce Subcommittee on Digital Commerce and Consumer Protection in relation to “Algorithms: How Companies’ Decisions About Data and Content Impact Consumers”. Here for more written testimony on Algorithmic Transparency from the Electronic Privacy Information Center – November 29, 2017.
ProPublica

Image Courtesy of ProPublica

There’s software used across the country to predict future criminals. And it’s biased against blacks. May 23, 2016 The company that sells this program (Northpointe) has responded to the criticisms here. Northpointe asserts that a software program it sells that predicts the likelihood a person will commit future crimes is equally fair to black and white defendants. Following such response, Jeff Larson and Julia Angwin has written another response (Technical Response to Northpointe) re-examined the data. They argue that they have considered the company’s criticisms, and stand by their conclusions.

Politics

Algorithmic processes and politics might seem far removed from each other. However, if anything, the recent political climate is indicative of how algorithms can be computational tools for political agendas. Here and here are exemplar twitter threads that highlight particular Twitter accounts used as tools for political agenda. The articles below are, in some way or another, related to algorithms in the political arena.

Forum Q&A: Philip Howard on Computational Propaganda’s Challenge to Democracy July 25, 2017. “Computational propaganda, or the use of algorithms and automated social media accounts to influence politics and the flow of information, is an emerging challenge to democracy in the digital age. Using automated social media accounts called bots (or, when networked, botnets), a wide array of actors including authoritarian governments and terrorist organizations are able to manipulate public opinion by amplifying or repressing different forms of political content, disinformation, and hate speech.”

For a more scholarly read

 

 

 

Afrofeminist epistemology and dialogism: a synthesis (work in progress)

Embodied, enactive and dialogical approaches to cognitive science radically depart from traditional Western thought in the manner with which they deal with life, mind and the person. The former can be characterised as emphasising interdependence, relationships, and connectedness with attempts to understanding organisms in their milieu. Acknowledgements of complexities and ambiguities of reality form the starting points for epistemological claims.  The latter, on the other hand, tends to strive for certainty and logical coherence in an attempt to establish stable and relatively fixed epistemological generalisations. Individuals, which often are perceived as independent discreet entities, are taken as the primary subjects of knowledge and the units of analysis.

Collins’s proposed black feminist epistemology, hereafter “Afrofeminist epistemology”, opposes the traditional Western approach to epistemology as well as the largely Positivist scientific view inherited from it.  As such, it is worth drawing attention to the similarities between Black feminist thought and dialogical approaches to the cognitive sciences. In what follows I seek to reveal a striking convergence of themes between these two schools of thought. In so doing, I intend to illustrate that the two traditions – cognitive sciences, especially the dialogical approach to epistemology, and Afrofeminist epistemology, particularly, the type proposed by Patricia Hill Collins (2002) – can inform one another through dialogue.

General characterization of classic Western approach to epistemology and the Cartesian inheritance

The classic Western approach to epistemology tends to be monological; meaning it tends to focus on individuals and their cognition and behaviour. When relationships and interactions enter the equation, individuals and their relations are often portrayed as distinct entities that can be neatly separated. Dichotomous thinking — subject versus object, emotion versus reason – persists within this tradition. Ethical and moral values and questions are often treated as clearly separable from “objective scientific work” and as something that the scientist need not contaminate her “objective” work with. In its desire for absolute rationality, Western thought wishes to cleave thought from emotion, cultural influence and ethical dimensions. Cognition, evaluation and emotions are treated as if they are entities that shouldn’t be contaminated. Abstract and intellectual thinking are regarded as the most trustworthy forms of understanding and rationality is fetishized.

In the classic Western epistemological tradition, abstract reasoning is taken to be the highest cognitive goal, and certainty as a necessary component for knowledge.  Since the ultimate goal is to arrive at timeless, universally applicable laws, establishing certainty is pivotal for laying the foundations. Although there are historical antecedents leading up to and contributing towards what is generally regarded as Western tradition – in particular, Plato in his dialogues Meno and Phaedo – Descartes represents the pinnacle of Western thought (Gardiner 1998, Toulmin 1992). The subject as autonomous and self-sustaining entity or a Cartesian cogito, which we have inherited from Cartesian thinking, remains prevalent in most current Western philosophy as well as in the background assumptions of the human sciences. The way the individual self is taken as the unquestioned origin of knowledge of the world and others is a legacy of this tradition (Linell 2009).

Black feminist criticism of dominant approach and the proposed alternative

Contrary to the classic Western epistemological tradition, in Afrofeminist epistemology ethical and moral values and questions are inseparable from our enquires into knowledge. Similarly, knowledge claims and knowledge validation processes are not independent of the interests and values of those who define what knowledge is, what is important and worthy of study, and what the criteria for epistemological justification are (Collins 2002). Such definitions and criteria are guarded fiercely by the institutions and individuals who act as the ‘gatekeepers’ of the classic Western epistemological tradition. This traditional Western epistemology, Collins points out, predominantly represents Western, elite, and white, male interests and values. In fact, a brief review of the history of Western philosophical canon reveals that knowledge production processes and the criteria for knowledge claims have predominantly been set by elite, white, Western men.

Scholars like Karen Warren (2009) have cogently argued that the history of classical Western philosophy has, for centuries, almost exclusively consisted of elite, white, Western European men giving the illusion that Western white men are the epitome of intellectual achievement. Women’s voices and perspectives were diminished, ignored, and systematically excluded from the canon. In her ‘recovery project’, Warren finds that women philosophers nonetheless have made important contributions throughout the history of philosophy and that you find them when you go looking for them. This, to a great extent, remains the case not only in philosophy, but also in much of the rest of the academic tradition. A brief look at any philosophy curricula would reveal that white European male philosophers and their views remain dominant and definitive.

Traditional approaches taken as the “normal” and “acceptable” ways to theorise and generalise about people’s lived experiences means that any other approaches to theorising about groups of people that are not aligned with canonical intellectual currents (often white European male) are dismissed as “anomalies”. For Collins, it is indisputable that different people experience reality differently and that all social thought somewhat reflects the realities and interests of its creators. Political criteria influence knowledge production and validation processes in one way or another.  Collins asserts, in studying Black women’s realities, the typical perspectives on offer have either identified black women with the oppressor, in which case Black women lack an independent interpretation of their own realities, or have characterised Black women as less human than the oppressor, in which case Black women lack the capacity to articulate their own standpoint. While in the first perspective independent Black women’s realities are seen as not their own, in the latter, it is seen as inferior. For that reason, the traditional epistemology is inadequate to capture and account for the lived experiences of black women – hence Collins’ proposal for an Afrocentric feminist epistemology which is grounded in black women’s values and lived experiences.

Black women’s lived experiences are different in important ways. The kind of relationships Black women have, and the kind of work they engage in are notable examples that demonstrate the differing realities and lived experiences. Intuitive knowledge, what Collins calls wisdom, is crucial to the everyday lives and survival of black women. While wisdom and intuitions, as opposed to abstract intellectualizing, might be excluded as irrelevant, and at best, less credible as far as the traditional epistemologies are concerned, they are highly valued within black communities:

“The distinction between knowledge and wisdom, and the use of experience as the cutting edge dividing them, has been key to Black women’s survival. … knowledge without wisdom is adequate for the powerful, but wisdom is essential to the survival of the subordinate.” (Collins 1989, p. 759)

The desire for complete objectivity and universally generalisable theories in the dominant Western tradition has led to a focus on abstract analysis of the nature of concepts like ‘knowledge’ and ‘justification’, with little to no grounding of complex lived experience. Its portrayal of reason and rationality in direct contrast with emotions – the former to arrive at pure, objective knowledge –  has led to dichotomous thinking, thus blinding us to continuities and complementarities. Consequently, “reason” has been privileged over emotions. This in turn has impeded emotional and bodily knowledge, what Foucault (1980) calls ‘subjugated knowledge’ often expressed through music, drama, etc., as less important. However, ‘subjugated knowledge’ is crucial and is part of a way of life and survival for black communities. Such knowledge, grounded in concrete experiences and recognised through connectedness, dialogues and relationships, is what is of real value for Black women.

That knowledge claims should be grounded in concrete, lived experience rather than abstract intellectualising is crucial to Collins’s Afrocentric feminist epistemology. Collins’s Afrocentric epistemology prioritizes wisdom over knowledge and has, at its core, black women’s experiences of race and gender oppression. Black women have shared experience of oppression, imperialism, colonialism, slavery, and apartheid as well as roots in the core African value system prior to colonization. The roots of Afrocentric epistemology can be traced back to African-based oral traditions. As such, dialogues occupy an important place. Dialogues, so far as the Afrocentric epistemology is concerned, are an essential method for assessing knowledge claims.

This Afrocentric epistemology, grounded in the lived experience of black women, that employs dialogues as a way of validating knowledge claims, stands in a stark contrast with that of the Eurocentric epistemology. Connectedness rather than separation is an essential component of the knowledge validation process. Individuals are not detached observers of stories or folktales, but rather active participants, listeners and speakers and part of the story. Dialogues explore and capture the fundamentally interactive connected nature of people and relationships.

Ethical claims lie at the heart of an Afrocentric feminist epistemology, in contrast to the classical Western epistemology that considers ethical issues as separate from and independent of ‘objective scientific investigations’. Afrocentric feminist epistemology is about employing emotions, wisdom, ethics and reason as interconnected and equally essential components in assessing knowledge claims with reference to a particular set of historical conditions.

Dialogical criticism to dominant approach and its alternative

The dialogical approach to cognitive science – inspired by Mikhail Mikhailovich Bakhtin’s (1895 – 1975) thinking and further developed by dialogists such as Per Linell (2009) – objects to the dominant Western epistemological approach. Dialogical theories which have roots in the Bakhtin Circle, a 20th century school of Russian thought, have had a massive influence on social theory, philosophy and psychology. At the centre of dialogical theories lies the view that linguistic production, the notion of self-hood, and knowledge are essentially dialogic. Dialogical approaches are concerned with conceptualizing and theorizing human-sense making and they do so based on a set of assumptions some of which stand in stark opposition to traditional Western philosophy and science. These assumptions include: individual selves cannot be assumed to exist as agents and thinkers before they begin to interact with others and the world; our sense-makings are not separable from our historical antecedents and current cultural and societal norms and value systems. The interrelation between self, others and the environment are there from the start in the infant’s life and the awareness of self and others co-develop over time; they are two sides of the same process. Classical Western philosophy and science has tried to reduce the world to rational individual subjects in attempt to establish stable universals. The origin of knowledge of the world and of others is the discreet individual person. So far as dialogical approaches go, most traditional Western epistemological approaches are rooted in Cartesian individualism and are monological – meaning, that they only encompass individuals and their cognition and environments. Groups and societies are nothing but ensembles of individuals:

“Individuals alone think, speak, carry responsibilities, and other individuals at most have a casual impact on their activities and stances.” (Linell 2009, p. 44)

Dialogism[1], in contrast, insists that interdependencies, co-dependencies, and relationships between the individual and the world are most fundamental components in understanding the nature of selves and furthermore, of knowledge. The term intersubjectivity captures this concept well:

“The term “intersubjectivity”—or what Hannah Arendt calls “the subjective in-between”—shifts our emphasis away from notions of the person, the self, or the subject as having a stable character and abiding essence, and invites us to explore the subtle negotiations and alterations of subjective experience as we interact with one another, intervocally or dialogically (in conversation or confrontation), intercorporeally (in dancing, moving, fighting, or competing), and introceptively (in getting what we call a sense of the other’s intentions, frame of mind, or worldview).”  (Jackson 2002, p. 5)

Cultures and societies are typically conceived as objective, stable structures so far as Western epistemologies go. Dialogism by contrast conceives cultures and societies as dynamic, living and partly open, with tensions, internal struggles and conflicts between majorities and minorities and different value systems. “Knowledge is necessarily constructed and continually negotiated (a) in situ and in sociocultural traditions, and (b) in dialogue with others; individuals are never completely autonomous1 as sense-makers.” (Linell 2009, p. 46) The individual is not a separate, discrete, fixed and stable entity that stands independent from others, but rather one that is always in dynamical interactions with and interdependent with others. Knowledge claims and knowledge validation processes need therefore to reflect these continual tensions and dynamic interactions.

Concluding remarks: drawing similarities between dialogical approaches and Afrofeminist epistemology

So, what are the implications, if any, of drawing these commonalities between Afrofeminist epistemology and dialogical approaches to epistemology, and their common refutation of traditional Western epistemology? Collins has described Afrofeminist and Western epistemological grounds as competing and at times irreconcilable:

“Those Black feminists who develop knowledge claims that both epistemologies can accommodate may have found a route to the elusive goal of generating so called objective generalizations that can stand as universal truths.”  (Collins 1989, p.773)  

The synthesis and incorporation of dialogism with Afrofeminist epistemology is, in a sense, not the discovery of that elusive finding into “objective generalization” or “universal truths” that satisfy both epistemologies. Rather such synthesis, I argue, is a means towards epistemological approaches that aspire to embed Afrofeminist values and dialogical epistemological underpinnings to our understandings of personhood and knowledge. Such epistemological approaches acknowledge that knowledge claims, knowledge validation processes and any scientific endeavours in general are value-laden and cannot be considered independent of underlying values and interests. A move towards epistemological approaches that acknowledge the role of the scientist/theorist which Barad (2007) captures concisely:

“A performative understanding of scientific practices, for example, takes account of the fact that knowing does not come from standing at a distance and representing but rather from a direct material engagement with the world.”   (Barad 2007, p. 49)

Connectedness and relationships rather than disinterested, disembodied, and detached Cartesian individuals form a central component of analysis. Great emphasis is placed on extensive dialogues and not to become a detached observer of stories. In so doing, individual expressiveness, emotions, the capacity for empathy and the fact that ideas cannot be divorced from those who create and share them need to be key factor for this epistemology. Such is an epistemological approach that aspires to embed Afrofeminist values and dialogical underpinnings.

Knowledge is specific to time and place and is not rooted in the individual person but in relationships between people. Individuals exist in a web of relations and co-dependently of one other, negotiating meanings and values through dialogues. As Bakhtin, pioneer of dialogism has emphasized, we are essentially dialogical beings, and it is only through dialogues with others that we come to realise and sustain a coherent – albeit continually changing –  sense of self. Reality is messy, ambiguous, and complex. Any epistemological approach that takes the person as fully autonomous, fixed, and a self-sufficient agent whose actions are guided by pure rationality fail to recognise the complexities and ambiguities of reality, time and context-bound nature of knowledge. At the core of this proposed Afrofeminist/dialogical approach to epistemology is an attempt to bring values as important constituent factor to the dialogical, intersubjective embodied, in a constant flux person and the epistemologies that drive from it.

[1] It is important to note that individuals do not disappear in dialogism, rather, the individual is a social being who is interdependent with others, “not an autonomous subject or a Cartesian cogito.” (Linell 2009)

Bibliography

Barad, K. (2007). Meeting the universe halfway: Quantum physics and the entanglement of matter and meaning. duke university Press.

Collins, P. H. (1989). The social construction of black feminist thought. Signs: Journal of Women in Culture and Society14(4), 745-773.

Collins, P. H. (2002). Black feminist thought: Knowledge, consciousness, and the politics of empowerment. Routledge.

Foucault, M. (1980). Language, counter-memory, practice: Selected essays and interviews. Cornell University Press.

Gardiner, M. (1998). The incomparable monster of solipsism: Bakhtin and Merleau-Ponty. Bakhtin and the human sciences. Sage, London, 128-144.

Jackson, M. (2012). Lifeworlds: Essays in existential anthropology. University of Chicago Press.

Linell, P. (2009). Rethinking language, mind, and world dialogically. IAP.

Toulmin, S. E., & Toulmin, S. (1992). Cosmopolis: The hidden agenda of modernity. University of Chicago Press.

Warren, K. (Ed.). (2009). An unconventional history of Western philosophy: conversations between men and women philosophers. Rowman & Littlefield.

 

The dark side of Big Data – how mathematical models increase inequality. My review of O’Neil’s book ‘WMD’

We live in the age of algorithms. Where the internet is, algorithms are. The Apps on our phones are results of algorithms. The GPS system can bring us from point A to point B thanks to algorithms. More and more decisions affecting our daily lives are handed over to automation. Whether we are applying for college, seeking jobs, or taking loans, mathematical models are increasingly involved with the decision makings. They pervade schools, the courts, the workplace, and even the voting process. We are continually ranked, categorized, and scored in hundreds of models, on the basis of our revealed preferences and patterns; as shoppers and couch potatoes, as patients and loan applicants, and very little of this do we see – even in applications that we happily sign up for.

More and more decisions being handed over to algorithms should in theory mean less human biases and prejudices. Algorithms are, after all, “neutral” and “objective”. They apply the same rules to everybody regardless of race, gender, ethnicity or ability. However, this couldn’t be far from the truth. In fact, mathematical models can be, and in some cases have been, tools that further inequality and unfairness. O’Neil calls these kinds of models Weapons of Math Destruction (WMD). WMDs are biased, unfair and ubiquitous. They encode poisonous prejudices from past records and work against society’s most vulnerable such as racial and ethnic minorities, low-wage workers, and women. It is as if these models were designed expressly to punish and to keep them down. As the world of data continues to expand, each of us producing ever-growing streams of updates about our lives, so do prejudice and unfairness.

Mathematical models have revolutionized the world and efficiency is their hallmark and sure, they aren’t just tools that create and distribute bias, unfairness and inequality. In fact, models, by their nature are neither good nor bad, neither fair nor unfair, neither moral nor immoral – they simply are tools. The sports domain is a good example where mathematical models are a force for good. For some of the world’s most competitive baseball teams today, competitive advantages and wins depend on mathematical models. Managers make decisions that sometimes involve moving players across the field based on analysis of historical data and current situation and calculate the positioning that is associated with the highest probability of success.

There are crucial differences, however, between models such as those used by baseball managers and WMDs.  While the former is transparent, and constantly updates its model with feedbacks, the latter by contrast are opaque and inscrutable black-boxes. Furthermore, while the baseball analytics engines manage individuals, each one potentially worth millions of dollars, companies hiring minimum wage workers, by contrast, are managing herds. Their objectives are optimizing profits so they slash their expenses by replacing human resources professionals with automated systems that filter large populations into manageable groups. Unlike the baseball models, these companies have little reason – say plummeting productivity – to tweak their filtering model.  O’Neil’s primary focus in the book are models that are opaque and inscrutable, those used within powerful institutions and industries, which create and perpetuate inequalities – WMDs – “The dark side of Big Data”! 

Weapons-of-math-destructionThe book contains crucial insights (or haunting warnings, depending on how you choose to approach it) to the catastrophic directions mathematical models used in the social sphere are heading. And it couldn’t come from a more credible and experienced expert than a Harvard mathematician who then went to work as quant for D. E. Shaw, a leading hedge fund, and an experienced data scientist, among other things.

One of the most persistent themes of O’Neil’s book is that the central objectives of a given model are crucial. In fact, objectives determine whether a model becomes a tool that helps the vulnerable or one that is used to punish them. WMDs objectives are often to optimize efficiency and profit, not justice. This, of course, is the nature of capitalism. And WMDs efficiency comes at the cost of fairness – they become biased, unfair, and dangerous. The destructive loop goes around and around and in the process, models become more and more unfair.

Legal traditions lean strongly towards fairness … WMDs, by contrast, tend to favour efficiency. By their very nature, they feed on data that can be measured and counted. But fairness is squishy and hard to quantify. It is a concept. And computers, for all their advances in language and logic, still struggle mightily with concepts. They “understand” beauty only as a word associated with the Grand Canyon, ocean sunsets, and grooming tips in Vogue magazine. They try in vain to measure “friendship” by counting likes and connections on Facebook. And the concept of fairness utterly escapes them. Programmers don’t know how to code for it, and few of their bosses ask them too. So fairness isn’t calculated into WMDs and the result is massive, industrial production of unfairness. If you think of a WMD as a factory, unfairness is the black stuff belching out of the smoke stacks. It’s an emission, a toxic one. [94-5]

The prison system is a startling example where WMDs are increasingly used to further reinforce structural inequalities and prejudicesIn the US, for example, those imprisoned are disproportionately poor and of colour. Being a black male in the US makes you nearly seven times more likely to be imprisoned than if you were a white male. Are such convictions fair? Many different lines of evidence suggest otherwise. Black people are arrested more often, judged guilty more often, treated more harshly by correctional officers, and serve longer sentences than white people who have committed the same crime. Black imprisonment rate for drug offenses, for example, is 5.8 times higher than it is for whites, despite a roughly comparable prevalence of drug use.

Prison systems which are awash in data hardly carry out important research such as why non-white prisoners from poor neighbourhoods are more likely to commit crimes or what the alternative ways of looking at the same data are. Instead, they use data to justify the workings of the system and further punish those that are already at a disadvantage. Questioning the workings of the system or enquiries on how the prison system could be improved are almost never considered. If, for example, building trust were the objective, an arrest may well become the last resort, not the first. Trust, like fairness, O’Neil explains, is hard to quantify and presents a great challenge to modellers even when the intentions are there to consider such concept as part of the objective.

Sadly, it’s far simpler to keep counting arrests, to build models that assume we’re birds of a feather and treat us such… Innocent people surrounded by criminals get treated badly. And criminals surrounded by law-abiding public get a pass. And because of the strong correlation between poverty and reported crime, the poor continue to get caught up in these digital dragnets. The rest of us barely have to think about them. [104]

Insofar as these models rely on barely tested insights, they are in a sense not that different to phrenology – digital phrenology. Phrenology, the practice of using outer appearance to infer inner character, which in the past justified slavery and genocide has been outlawed and is considered pseudoscience today. However, phrenology and scientific racism are entering a new era with the appearance of justified “objectivity” with machine-learned models. “Scientific” criminological approaches now claim to “produce evidence for the validity of automated face-induced inference on criminality. However, what these machine-learned “criminal judgements” pick up on, more than anything, is systematic unfairness and human bias embedded in historical data.  

model that profiles us by our circumstances helps create the environment that justifies its assumptions. The stream of data we produce serve as insights into our lives and behaviours. Instead of testing whether these insights stand up to scientific scrutiny, the data we produce are used to justify the modellers’ assumptions and to reinforce per-existing prejudice. And the feedback loop goes on.

When I consider the sloppy and self-serving ways that companies use data, I am often reminded of phrenology… Phrenology was a model that relied on pseudo-scientific nonsense to make authoritative pronouncements, and for decades it went untested. Big Data can fall into the same trap. [121-2]

Hoffman in 1896 published a 330-page report where he used exhaustive statistics to support a claim as pseudo-scientific and dangerous as phrenology. He made the case that the lives of black Americans were so precarious that the entire race was uninsurable. However, not only were Hoffman’s statistics erroneously flawed, like many of WMDs O’Neil discusses throughout the book, he also confused causation for correlation. The voluminous data he gathered served only to confirm his thesis: race is a powerful predictor of life expectancy. Furthermore, Hoffman failed to separate the “Black” population into different geographical, social or economic cohorts blindly assuming that the whole “Black” population is a homogeneous group. 

This cruel industry has now been outlawed. Nonetheless, the unfair and discriminatory practices remain and are still practiced but in a far subtler form –  they are now coded into the latest generations of WMDs and obfuscated under complex mathematics. Like Hoffman, the creators of these new models confuse correlation with causation and they punish the struggling classes and racial and ethnic minorities. And they back up their analysis with realms of statistics, which give them the studied air of “objective science”. 

What is even more frightening is that as oceans of behavioural data continue to feed straight into artificial intelligence systems, this, to the most part will, unfortunately, remain a black box to the human eye. We will rarely learn about the classes that we have been categorized into or why we were put there, and, unfortunately, these opaque models are as much a black-box to those who design them. In any case, many companies would go out of their way to hide the results of their models, and even their existence.

In the era of machine intelligence, most of the variables will remain a mystery... automatic programs will increasingly determine how we are treated by other machines, the ones that choose the ads we see, set prices for us, line us up for a dermatologist appointment, or map our routes. They will be highly efficient, seemingly arbitrary, and utterly unaccountable. No one will understand their logic or be able to explain it. If we don’t wrest back a measure of control, these future WMDs will feel mysterious and powerful. They’ll have their way with us, and we’ll barely know it is happening. [173]

In the current insurance system, (at least as far as the US is concerned) the auto insurers’ tracking systems which provide insurers with more information enabling them to create more powerful predictions, are opt-in. Only those willing to be tracked have to turn on their black boxes. Those that do turn them on get rewarded with discounts where the rest subsidize those discounts with higher rates. Insurers who squeeze out the most intelligence from this information, turning it into profits, will come out on top. This, unfortunately, undermines the whole idea of collectivization of risk on which insurance systems are based. The more insurers benefit from such data, the more of it they demand, gradually making trackers the norm. Consumers who want to withhold all but the essential information from their insurers will pay a premium. Privacy, increasingly, will come at a premium cost. A recently approved US bill illustrates just that. This bill would expand the reach of “Wellness Programs” to include genetic screening of employees and their dependents and increase the financial penalties for those who choose not to participate.

Being poor in a world of WMDs is getting more and more dangerous and expensive. Even privacy is increasingly becoming a luxury that only the wealthy can afford. In a world which O’Neil calls a ‘data economy’, where artificial intelligence systems are hungry for our data, we are left with very few options but to produce and share as much data about our lives as possible. In the process, we are (implicitly or explicitly) coerced into self-monitoring and self-discipline. We are pressured into conforming to ideal bodies and “normal” health statuses as dictated by organizations and institutions that handle and manage our social relations, such as, our health insurances. Raley (2013) refers to this as dataveillance: a form of continuous surveillance through the use of (meta)data. Ever growing flow of data, including data pouring in from the Internet of Things – the Fitbits, Apple Watches, and other sensors that relay updates on how our bodies are functioning, continue to contribute towards this “dataveillance”.  

One might argue that helping people deal with their weight and health issues isn’t such a bad thing and that would be a reasonable argument. However, the key question here, as O’Neil points out, is whether this is an offer or a command. Using flawed statistics like the BMI, which O’Neil calls “mathematical snake oil”, corporates dictate what the ideal health and body looks like. They infringe on our freedom as they mould our health and body ideals. They punish those that they don’t like to look at and reward those that fit their ideals. Such exploitation are disguised as scientific and are legitimized through the use of seemingly scientific numerical scores such as the BMI. The BMI, kg/m2 (a person’s weight (kg) over height (m) squared), is only a crude numerical approximation for physical fitness. And since the “average” man underpins its statistical scores, it is more likely to conclude that women are “overweight” – after all, we are not “average” men. Even worse, black women, who often have higher BMIs, pay the heaviest penalties.  

The control of great amounts of data and the race to build powerful algorithms is a fight for political power. O’Neil’s breathtakingly critical look at corporations like Facebook, Apple, Google, and Amazon illustrates this. Although these powerful corporations are usually focused on making money, their profits are tightly linked to government policies which makes the issue essentially a political one.

These corporations have significant amounts of power and a great amount of information on humanity, and with that, the means to steer us in any way they choose. The activity of a single Facebook algorithm on Election Day could not only change the balance of Congress, but also potentially decide the presidency. When you scroll through your Facebook updates, what appears on your screen is anything but neutral – your newsfeed is censored. Facebook’s algorithms decided whether you see bombed Palestines or mourning Israelis, a policeman rescuing a baby or battling a protester. One might argue that television news has always done the same and this is nothing new. CNN, for example, chooses to cover a certain story from a certain perspective, in a certain way. However, the crucial difference is, with CNN, the editorial decision is clear on the record. We can pinpoint to individual people as responsible and accountable for any given decision and the public can debate whether that decision is the right one. Facebook on the other hand, O’Neil puts it, is more like the “Wizard of Oz” — we do not see the human beings involved. With its enormous power, Facebook can affect what we learn, how we feel, and whether we vote – and we are barely aware of any of it. What we know about Facebook, like other internet giants, comes mostly from the tiny proportion of their research that they choose to publish.

In a society where money buys influence, these WMD victims are nearly voiceless. Most are disenfranchised politically. The poor are hit the hardest and all too often blamed for their poverty, their bad schools, and the crime that afflicts their neighbourhoods. They, for the most part, lack economic power, access to lawyers, or well-funded political organizations to fight their battles. From bringing down minorities’ credit scores to sexism in the workplace, WMDs serve as tools. The result is widespread damage that all too often passes for inevitability.

Again, it is easy to point out that injustice, whether based on bias or greed, has been with us forever and WMDs are no worse than the human nastiness of the recent past. As with the above examples, the difference is transparency and accountability. Human decision making has one chief virtue. It can evolve. As we learn and adapt, we change. Automated systems, especially those O’Neil classifies as WMD, by contrast, stay stuck in the time until engineers dive in to change them.

If Big Data college application model had established itself in the early 1960s, we still wouldn’t have many women going to college, because it would have been trained largely on successful men. [204]

Rest assured, the book is not all doom and gloom or that all mathematical models are biased and unfair. In fact, O’Neil provides plenty of examples where models are used for good and models that have the potential to be great.

Whether a model becomes a tool to help the vulnerable or a weapon to inflict injustice, as O’Neil, time and time again emphasizes, comes down to its central objectives. Mathematical models can sift through data to locate people who are likely to face challenges, whether from crime, poverty, or education. The kinds of objectives adopted dictate whether such intelligence is used to reject or punish those that are already vulnerable or to reach out to them with the resources they need. So long as the objectives remain on maximizing profit, or excluding as many applicants as possible, or to locking up as many offenders as possible, these models serve as weapons that further inequalities and unfairness. Change that objective from leeching off people to reaching out to them, and a WMD is disarmed — and can even become a force of good. The process begins with the modellers themselves. Like doctors, data scientists should pledge a Hippocratic Oath, one that focuses on the possible misuse and misinterpretation of their models. Additionally, initiatives such as the Algorithmic Justice League, which aim to increase awareness of algorithmic bias, provide space for individuals to report such biases. 

Opaqueness is a common feature of WMDs. People have been dismissed from work, sent to prison, or denied loans due to their algorithmic credit scores with no explanation as to how or why. The more we are aware of their opaqueness, the better chance we have in demanding transparency and accountability and this begins by making ourselves aware of the works of experts like O’Neil. This is not a book only for those working in data science, machine learning or other related fields, but one that everyone needs to read. If you are a modeller, this book should encourage you to zoom out, think whether there are individuals behind the data points that your algorithms manipulate, and think about the big questions such as the objectives behind your code. Almost everyone, to a greater or lesser extent, is part of the growing world of ‘data economy’. The more awareness there is of the dark side of these machines, the better equipped we are to ask questions, to demand answers from those behind the machines that decide our fate.

ክርስትና እና እንስታዊነት ሆድና ጀርባ በሲራክ ተመስገን

የእንስታዊነት (Feminism) እንቅስቃሴ በመሰረታዊነት ሴቷን ከወንዱ እኩል በኢኮኖሚ፣ በማህበራዊ እና በፖለቲካው መስክ ተሳታፊ እንድትሆን ማስቻል ነው። ሴቷ በፆታዋ ብቻ የሚደርስባትን መገፋት ለማስቀረት መንቀሳቀስ ነው። የእዚህ መገፋት እና አባታዊ ስርዓት በአለም ላይ መዘርጋት ክርስትና ትልቅ አስተዋፅኦ አለው ብዬ አምናለሁ። ለእዚህም ነው ብዕሬን ያነሳሁት። እንግሊዛዊው የባይዎሎጅ ሊቅ ሪቻርድ ዳውኪንስ ብዙ በተነገረለት ‘The God Delusion’ በተባለው ድንቅ መጽሀፉ ላይ የብሉይ ኪዳኑን አምላክ እንዲህ ሲል በምሬት ይገልፀዋል፡

“The God of the Old Testament is arguably the most unpleasant character in all fiction: jealous and proud of it; a petty, unjust, unforgiving control-freak; a vindictive, bloodthirsty ethnic cleanser; a misogynistic, homophobic, racist, infanticidal, genocidal, filicidal, pestilential, megalomaniacal, sadomasochistic, capriciously malevolent bully”

ፕሮፌሰር ዳውኪንስ ይሄን ሲል ግን እንዲሁ በባዶው አይደለም፤ ለእያንዳንዱ ስያሜው ከብሉይ ኪዳን መጻህፍት ጥቅስ እያጣቀሰ እንጅ፡፡ እኔም ‹‹ይሄንን ኢ–ሰብዓዊ የሆነን አካል በአምላክነት የተቀበለ ሰው ስለ መብት ሊያወራ አይገባም ›› የምለውም በመጽሃፉ የተጠቀሰው ባህርይ እጅግ ከሰብዓዊነት የራቀ በመሆኑ ነው፡፡። በዚህ ርዕስ የማነሳው የሴቶች መብት እና የእንስታዊነት (Feminism) ጉዳይም የመጽሐፉ ዋነኛ ተጠቂ ናቸው፡፡ በመጽሐፍ ቅዱስ ሴቶች ከብሉይ ኪዳን እስከ አዲስ ኪዳን ድረስ ሴቶች ተጨቋኝ ሆነው የቀረቡበት ጥራዝ ነው። አብነት እየጠቃቀስኩ ላስረዳ፡፡

የብሉይ ሴቶች

በብሉይ በእግዚአብሔር ተወዳጅ ከሆኑ ነገስታት አንዱ ንጉስ ዳዊት ነው። ይህ ሰዉ ወሲብ በጣም ይወድ ነበረ። ብዙም ዕቁባቶች ነበሩት። ሴቶችንም እንደግል ንብረቱ ቆጥሮ በአንድ ቤት ዘግቶ፣ ከማንም ሳይገናኙ እንዲሞቱ የማድረግ ስልጣን ነበረው ዳዊት (2ኛ ሳሙኤል 20:3)፡፡ በአመት ሶስት ጊዜ በሚደረገው የቂጣ በዓል፣ የመኸር በዓል እና የመክተቻ በአል ወቅት በእግዝአብሔር ፊት ለዕይታ የሚቀርቡት ወንዶች ብቻም ነበሩ (ዘጸአት፣ 23:14–17)፡፡ በሙሴዎ ዓለም የተፈጥሮ ኡደቶች (ወሊድም ሆነ የወር አበባ) ለሴት ልጅ የመርከስ ምልክት ነው። እንደዚህም ሆኖ ወንድ ከወለደች 7 ቀን የረከሰች ነች። በአስገራሚ ሁኔታ ሴት ከወለደች ዕጥፍ ቀን የረከሰች ነች መባሏ ነው (ዘሌዋውያን 12: 1–5)፡፡እግዜሩ ለሰው ልጆች ዋጋ ማውጣቱ ሲገርም ሴቶች ከወንዶች ያነሰ ዋጋ ያለቸው መሆኑ ይበልጥ ያስቃል። በብሉዩ ዓለም ከአምስት አመት ሴት ልጅ ይልቅ የአንድ ወር ወንድ ህፃን በዋጋ ይበልጣል (ዘሌዋውያን 27: 1–7)፡፡ ይባስ ብሎም ሙሴ በአምላኩ ሕዝቡን እንዲቆጥር ሲታዘዝ ሴቶች እንደሰው አይቆጠሩም ነበረ (ዘኁልቆ 3:15)፡፡ በዚህ አያበቃም እግዚአብሔር ለሙሴ በሰጠው ህግ መሰረት አንድ ሰው ቢሞት ወንዶች ልጆቹ ብቻ የንብረት ወራሾች ይሆናሉ። ሴቶች ልጆች ወራሾች የሚሆኑት ሟች ወንድ ልጆች ከሌሉት ብቻ ነው (ዘኁልቆ 27:8–11)፡፡ ድንግልና ሳይኖራት ያገባች ሴት በድንጋይ ተወግራ እንድትሞት ‹የእግዚአብሔር ህግ› ያዛል (ዘዳግም22:13–21)። በተቃራኒው ወንድ ድንግልና ከሌለው ይቀጣ የሚል ህግ ግን የለም። በአጠቃላይ የብሉይ ኪዳን ዘመን ተብሎ በሚታወቀው ጊዜ ሴት እቃ ( ) ነች እንጅ ሰው አልነበረችም፡፡ አዲስ ኪዳኑስ ምን ይላል;

ሴቶች በአዲስ ኪዳን

ከብሉይ ኪዳኑ የጭካኔ ዘመን አንፃር እየሱስ ክርስቶስ አብዮተኛ ነበረ ማለት ይቻላል። በአይሁዳውያን ዘንድ ሴቶችን ዝቅዝቅ የማድረግ ባህልን ሲጠቀም አይታይም። ሴቶችንም ያስተምርም ነበረ። በተዘዋወረባቸው ቦታዎችም ሁሉ በቋሚነት አብረውት ይከተለት ነበረ። እንደ ወንዶቹ ይፈውሳቸውም ምሳሌ ያደርጋቸዋልም። ይልቁኑ የክርትና መሰረት ነው ተብሎ ከሚነገርለት ከቅዱስ ጳውሎስ አስተምህሮ ነው አዲስ ኪዳኑ በሴቶች ላይ ሲጨክን የሚታየው፡፡ ጳውሎስ በ1ኛ ቆሮንቶስ 11:3 ላይ «ነገር ግን የወንድ ሁሉ ራስ ክርስቶስ፣ የሴትም ራስ ወንድ፣ የክርስቶስም ራስ እግዚአብሔር እንደሆነ ልታውቁ እወዳለሁ» ብሎ ሴትን በደረጃ ከወንዱ አውርዶ ያስቀምጣታል፡፡ አልፎም ለሴት ልጅ የፀጉር አቆራረጥ ህግ ያፀድቃል። ሴትም ለወንድ ሲባል የተፈጠረች እንደሆነ በግልፅ እና በጉልህ ይናገራል። ሚስቶች የባሎቻቸው ባሪያ እንደሆኑ እና ያለምንም ማመንታት ለባሎቻቸው እንዲገዙ ደንግጓል (ኤፌሶን 5:22–23)፡፡ ሴቶች ህዝብ በተሰበሰበበት ቦታ መናገር አይፈቀድላቸውም። ማወቅ የፈለጉት ነገር እንኳን ቢኖር በቤታቸው ባሎቻቸውን እንዲጠይቁ ነው እግዜሩ የሚያዘውይመክራል ጳውሎስ (1ኛ ቆሮንቶስ 14:34–36)፡፡ ሴቶች እንዲያስተምሩ አይፈቀድላቸውም። በወንድ ላይም መሰልጠን አይችሉም (1ኛ ጢሞቴዎስ 2:11–15)፤ በማለትም ‹ወንድ ወደ ችሎት፤ ሴት ወደ ማጀትን›› ጳውሎስ ይሰብከናል፡፡ ሲያጠቃልልም ሴቶች ደካሞች መሆናቸው በ1ኛ ጴጥሮስ 3:7 ላይ ይነግረናል ቅዱስ ጳውሎስ፡፡ እዚህ ላይ ነው ጥያቄው፡፡ ይሄን የመሰለ ሴቶችን እንደሰው እንኳን ለመቁጥር የሚግደረደር የጭቆና መሳሪያ ተይዞ ስለ ሴቶች መብት ማውራት እንዴት ይቻላል? መብትስ ምንድን ነው? ራስን መቃረን ደሞ በሽታ ነው። ይህን የሃይማኖት የጭቆና ህግጋት እና ትዕዛዝ አውልቀው ሳይጥሉ ‹እንስታዊት ነኝ› ማለት ለእኔ ለእንቅስቃሴው ስድብ ነው። እነደጳውሎስ ምክር ስጥ ብባልም እንደዚህ የመጽሃፉ አማኒያን ራሳቸው ‹የሴት መብት ተከራካሪ› ብለው የሚጠሩ ሰዎች ከእንስታዊነት እንቅስቃሴ ላይ እጃቸውን ቢያነሱ ሸጋ ነው ብይ ነኝ፡፡ “You can’t have your cake and eat it” እንዲሉ፤ ወይ ሽልጦውን ወይ ሆዳችንን ነው ጥያቄው፡፡ ለነገሩ እንደ ኤልዛቤት ስታንተን ያሉ ሴቶች ‘The Woman’s Bible’ ብለው ማሻሻያ ለማድረግ መነሳታቸው፤ የዚሁ የመጽሃፉ ጨቋኝነት ቢያማራቸው አይደለምን?

 

The Scope of Existential Anthropology – Jackson

Such a beautifully written passage which compels you to reflect, wonder, and think …

Like other human sciences, anthropology has drawn inspiration from many disciplines and sought to build its identity through association with them. But the positivism that anthropology hoped to derive from the natural sciences proved to be as elusive as the authenticity it sought from the humanities. Moreover, though lip service was paid to the models and methods of biology, ecology, psychology, fluid mechanics, structural linguistics, topology, quantum mechanics, mathematics, economics, and general systems theory, anthropologists seldom deployed these analytically or systematically. Rather, they were adopted as images and metaphors. Thus, society was said to function like a living organism, regulate energy like a machine, to be structured like language, organized like a corporation, comparable to a person, or open to interpretation like a text.

Jackson. M (2013) Lifeworlds: Essays in Existential Anthropology. (Chapter 1, The Scope of Existential Anthropology, p.3) 

Western philosophy has historically seen only what its “illusions” permitted it to see

Warren“Philosophy’s attachment to its illusions of gender neutrality functioned like Narcissus’s self-perception of himself when he looked at his image in the lake: he saw only what he wanted to see. Analogously, canonical Western philosophy has historically seen only what its “illusions” permitted it to see.” Karen Warren, 2009. 

When the issue of the absence of women and underrepresented groups in philosophy, or any other male-dominated discipline in general, is brought to attention, the reason for women’s absence is often attributed to the individuals themselves. ‘There aren’t many women in philosophy because it is not a subject that most women are attracted to’ or that ‘the Western philosophical canon almost exclusively consists of white males because there simply weren’t other voices’ or that ‘women didn’t write or take part in the philosophical debates of their times’. This simply is not true. As far as Western philosophy  (I presume as well as other domains) is concerned, one would find that women’s voices were systematically excluded or ignored from the canon. This is evident as when you go looking for them, you find voices and perspectives that have been diminished in important ways. This is in fact what Warren did in her “recovery project”. She rediscovered names, lives, texts, and perspectives of women philosophers from the 16th B.C.E. on. She then went beyond recovery, to an “inclusion project”: a gender inclusive account of the history of Western philosophy. The result, an anthology (An Unconventional History of Western Philosophy: Conversation Between Men and Women Philosophers) of the history of Western philosophy that accounts works of both women and men philosophers.

In this distinctive work, the first book in any language to include women philosophers among their historical male counterparts, Warren pairs women philosophers with canonical male contemporaries. Primary texts of “philosopher pairs” address topics or positions that when taken together, constitute a conversation. This project dissolves the add-women-and-stir-philosophy problem – a pertinent problem that arises when attempts are made to add women philosophers whose claims, positions, and methodologies are in conflict to that of the canon, creating what might seem “more like an explosion than a mixture”. The common practice is to avoid this attempt to integrate the works of women philosophers into the canon all together and develop a distinct “women’s philosophy or philosophy by women”. Examples of such include, ecofeminist philosophy, feminist ethics, feminist epistemology, and feminist philosophy of science. Warren, in this exceptional anthology, successfully manages to integrate the works of women philosophers into the canon whilst avoiding the add-women-and-stir-philosophy problem.

Given that there are material that are inclusive of both women and men, any curricula that fails to include women philosophers is outdated and inaccurate. At least, that’s Warren’s position. Now, whether the availability of material that have recovered and included the works of excluded and ignored women has had any significant impact on any philosophy curricula is another question.

The absence of women and underrepresented groups is not news to many, especially to those in philosophy. The exclusion of women from mainstream collections is indisputable. Take a look at these three randomly selected common textbooks/anthologies used in (political) philosophy: 1) A History of Modern Political Thought by Ian Hampsher Monk, 2) Political Thinkers: From Socrates to the Present by David Boucher & Paul Kelly, and 3) Western Philosophy: An Anthology by John Cottingham. Of these three (~600 pages long) anthologies, you’d find only one women philosopher mentioned (in Cottingham) – Judith Jarvis Thomson. And the philosophical work included in this anthology, unsurprisingly, is one that deals with abortion and rights.

This is depressing indeed but nonetheless, a poignant indicator that “rediscovery” and “inclusion” projects carried by the likes of Warren are of crucial importance in the long and slow journey towards fair representations in philosophy.