Seeing, Naming, Knowing

Curated on Posted on by Stefaan Verhulst

Essay by Nora N. Khan for Brooklyn Rail: “…. Throughout this essay, I use “machine eye” as a metaphor for the unmoored orb, a kind of truly omnidirectional camera (meaning, a camera that can look in every direction and vector that defines the dimensions of a sphere), and as a symbolic shorthand for the sum of four distinct realms in which automated vision is deployed as a service. (Vision as a Service, reads the selling tag for a new AI surveillance camera company).10 Those four general realms are: 

1. Massive AI systems fueled by the public’s flexible datasets of their personal images, creating a visual culture entirely out of digitized images. 

2. Facial recognition technologies and neural networks improving atop their databases. 

3. The advancement of predictive policing to sort people by types. 

4. The combination of location-based tracking, license plate-reading, and heat sensors to render skein-like, live, evolving maps of people moving, marked as likely to do X.

Though we live the results of its seeing, and its interpretation of its seeing, for now I would hold on blaming ourselves for this situation. We are, after all, the living instantiations of a few thousand years of such violent seeing globally, enacted through imperialism, colonialism, caste stratification, nationalist purges, internal class struggle, and all the evolving theory to support and galvanize the above. Technology simply recasts, concentrates, and amplifies these “tendencies.” They can be hard to see at first because the eye’s seeing seems innocuous, and is designed to seem so. It is a direct expression of the ideology of software, which reflects its makers’ desires. These makers are lauded as American pioneers, innovators, genius-heroes living in the Bay Area in the late 1970s, vibrating at a highly specific frequency, the generative nexus of failed communalism and an emerging Californian Ideology. That seductive ideology has been exported all over the world, and we are only now contending with its impact.

Because the workings of machine visual culture are so remote from our sense perception, and because it so acutely determines our material (economic, social), and affective futures, I invite you to see underneath the eye’s outer glass shell, its holder, beyond it, to the grid that organizes its “mind.” That mind simulates a strain of ideology about who exactly gets to gather data about those on that grid below, and how that data should be mobilized to predict the movements and desires of the grid dwellers. This mind, a vast computational regime we are embedded in, drives the machine eye. And this computational regime has specific values that determine what is seen, how it is seen, and what that seeing means….(More)”.

The Bad Pupil

Curated on Posted on by Stefaan Verhulst

CCCBLab: “In recent years we have been witnessing a constant trickle of news on artificial intelligence, machine learning and computer vision. We are told that machines learn, see, create… and all this builds up a discourse based on novelty, on a possible future and on a series of worries and hopes. It is difficult, sometimes, to figure out in this landscape which are real developments, and which are fantasies or warnings. And, undoubtedly, this fog that surrounds it forms part of the power that we grant, both in the present and on credit, to these tools, and of the negative and positive concerns that they arouse in us. Many of these discourses may fall into the field of false debates or, at least, of the return of old debates. Thus, in the classical artistic field, associated with the discourse on creation and authorship, there is discussion regarding the entity to be awarded to the images created with these tools. (Yet wasn’t the argument against photography in art that it was an image created automatically and without human participation? And wasn’t that also an argument in favour of taking it and using it to put an end to a certain idea of art?)

Metaphors are essential in the discourse on all digital tools and the power that they have. Are expressions such as “intelligence”, “vision”, “learning”, “neural” and the entire range of similar words the most adequate for defining these types of tools? Probably not, above all if their metaphorical nature is sidestepped. We would not understand them in the same way if we called them tools of probabilistic classification or if instead of saying that an artificial intelligence “has painted” a Rembrandt, we said that it has produced a statistical reproduction of his style (something which is still surprising, and to be celebrated, of course). These names construct an entity for these tools that endows them with a supposed autonomy and independence upon which their future authority is based.

Because that is what it’s about in many discourses: constructing a characterisation that legitimises an objective or non-human capacity in data analysis….

We now find ourselves in what is, probably, the point of the first cultural reception of these tools. Of their development in fields of research and applications that have already been derived, we are moving on to their presence in the public discourse. It is in this situation and context, where we do not fully know the breadth and characteristics of these technologies (meaning fears are more abstract and diffuse and, thus, more present and powerful), when it is especially important to understand what we are talking about, to appropriate the tools and to intervene in the discourses. Before their possibilities are restricted and solidified until they seem indisputable, it is necessary to experiment with them and reflect on them; taking advantage of the fact that we can still easily perceive them as in creation, malleable and open.

In our projects The Bad Pupil. Critical pedagogy for artificial intelligences and Latent Spaces. Machinic Imaginations we have tried to approach to these tools and their imaginary. In the statement of intentions of the former, we expressed our desire, in the face of the regulatory context and the metaphor of machine learning, to defend the bad pupil as one who escapes the norm. And also how, faced with an artificial intelligence that seeks to replicate the human on inhuman scales, it is necessary to defend and construct a non-mimetic one that produces unexpected relations and images.

Fragment of De zeven werken van barmhartigheid, Meester van Alkmaar, 1504 (Rijksmuseum, Amsterdam) analysed with YOLO9000 | The Bad Pupil - Estampa

Fragment of De zeven werken van barmhartigheid, Meester van Alkmaar, 1504 (Rijksmuseum, Amsterdam) analysed with YOLO9000 | The Bad Pupil – Estampa

Both projects are also attempts to appropriate these tools, which means, first of all, escaping industrial barriers and their standards. In this field in which mass data are an asset within reach of big companies, employing quantitively poor datasets and non-industrial calculation potentials is not just a need but a demand….(More)”.

Privacy’s not dead. It’s just not evenly distributed

Curated on Posted on by Stefaan Verhulst

Alex Pasternack in Fast Company: “In the face of all the data abuse, many of us have, quite reasonably, thrown up our hands. But privacy didn’t die. It’s just been beaten up, sold, obscured, diffused unevenly across society. What privacy is and why it matters increasingly depends upon who you are, your age, your income, gender, ethnicity, where you’re from, and where you live. To borrow William Gibson’s famous quote about the future and its unevenness and inequalities, privacy is alive—it’s just not evenly distributed. And while we don’t all care about it the same way—we’re even divided on what exactly privacy is—its harms are still real. Even when our own privacy isn’t violated, privacy violations can still hurt us.

Privacy is personal, from the creepy feeling that our phones are literally listening to the endless parade of data breaches that test our ability to care anymore. It’s the unsettling feeling of giving “consent” without knowing what that means, “agreeing” to contracts we didn’t read with companies we don’t really trust. (Forget about understanding all the details; researchers have shown that most privacy policies surpass the reading level of the average person.)

It’s the data about us that’s harvested, bought, sold, and traded by an obscure army of data brokers without our knowledge, feeding marketers, landlords, employers, immigration officials, insurance companies, debt collectors, as well as stalkers and who knows who else. It’s the body camera or the sports arena or the social network capturing your face for who knows what kind of analysis. Don’t think of personal data as just “data.” As it gets more detailed and more correlated, increasingly, our data is us.

And “privacy” isn’t just privacy. It’s also tied up with security, freedom, social justice, free speech, and free thought. Privacy harms aren’t only personal, but societal. It’s not just the multibillion-dollar industry that aims to nab you and nudge you, but the multibillion-dollar spyware industry that helps governments nab dissidents and send them to prison or worse. It’s the supposedly fair and transparent algorithms that aren’t, turning our personal data into risk scores that can help perpetuate race, class, and gender divides, often without our knowing it.

Privacy is about dark ads bought with dark money and the micro-targeting of voters by overseas propagandists or by political campaigns at home. That kind of influence isn’t just the promise of a shadowy Cambridge Analytica or state-run misinformation campaigns, but also the premise of modern-day digital ad campaigns. (Note that Facebook’s research division later hired one of the researchers behind the Cambridge app.) And as the micro-targeting gets more micro, the tech giants that deal in ads are only getting more macro….(More)”

(This story is part of The Privacy Divide, a series that explores the fault lines and disparities–economic, cultural, philosophical–that have developed around digital privacy and its impact on society.)

A Skeptical View of Information Fiduciaries

Curated on Posted on by Stefaan Verhulst

Paper by Lina Khan and David Pozen: “The concept of “information fiduciaries” has surged to the forefront of debates on online platform regulation. Developed by Professor Jack Balkin, the concept is meant to rebalance the relationship between ordinary individuals and the digital companies that accumulate, analyze, and sell their personal data for profit. Just as the law imposes special duties of care, confidentiality, and loyalty on doctors, lawyers, and accountants vis-à-vis their patients and clients, Balkin argues, so too should it impose special duties on corporations such as Facebook, Google, and Twitter vis-à-vis their end users. Over the past several years, this argument has garnered remarkably broad support and essentially zero critical pushback.

This Essay seeks to disrupt the emerging consensus by identifying a number of lurking tensions and ambiguities in the theory of information fiduciaries, as well as a number of reasons to doubt the theory’s capacity to resolve them satisfactorily. Although we agree with Balkin that the harms stemming from dominant online platforms call for legal intervention, we question whether the concept of information fiduciaries is an adequate or apt response to the problems of information insecurity that he stresses, much less to more fundamental problems associated with outsized market share and business models built on pervasive surveillance. We also call attention to the potential costs of adopting an information-fiduciary framework—a framework that, we fear, invites an enervating complacency toward online platforms’ structural power and a premature abandonment of more robust visions of public regulation….(More)”.

Machine Ethics: The Design and Governance of Ethical AI and Autonomous Systems

Curated on Posted on by Stefaan Verhulst

Introduction by A.F. Winfield, K. Michael, J. Pitt, V. Evers of Special Issue of Proceedings of the IEEE: “…The primary focus of this special issue is machine ethics, that is the question of how autonomous systems can be imbued with ethical values. Ethical autonomous systems are needed because, inevitably, near future systems are moral agents; consider driverless cars, or medical diagnosis AIs, both of which will need to make choices with ethical consequences. This special issue includes papers that describe both implicit ethical agents, that is machines designed to avoid unethical outcomes, and explicit ethical agents: machines which either encode or learn ethics and determine actions based on those ethics. Of course ethical machines are socio-technical systems thus, as a secondary focus, this issue includes papers that explore the societal and regulatory implications of machine ethics, including the question of ethical governance. Ethical governance is needed in order to develop standards and processes that allow us to transparently and robustly assure the safety of ethical autonomous systems and hence build public trust and confidence….(More)?

The Governance of Digital Technology, Big Data, and the Internet: New Roles and Responsibilities for Business

Curated on Posted on by Stefaan Verhulst

Introduction to Special Issue of Business and Society by Dirk Matten, Ronald Deibert & Mikkel Flyverbom: “The importance of digital technologies for social and economic developments and a growing focus on data collection and privacy concerns have made the Internet a salient and visible issue in global politics. Recent developments have increased the awareness that the current approach of governments and business to the governance of the Internet and the adjacent technological spaces raises a host of ethical issues. The significance and challenges of the digital age have been further accentuated by a string of highly exposed cases of surveillance and a growing concern about issues of privacy and the power of this new industry. This special issue explores what some have referred to as the “Internet-industrial complex”—the intersections between business, states, and other actors in the shaping, development, and governance of the Internet…(More)”.

Balancing information governance obligations when accessing social care data for collaborative research

Curated on Posted on by Stefaan Verhulst

Paper by Malkiat Thiarai, Sarunkorn Chotvijit and Stephen Jarvis: “There is significant national interest in tackling issues surrounding the needs of vulnerable children and adults. This paper aims to argue that much value can be gained from the application of new data-analytic approaches to assist with the care provided to vulnerable children. This paper highlights the ethical and information governance issues raised in the development of a research project that sought to access and analyse children’s social care data.


The paper documents the process involved in identifying, accessing and using data held in Birmingham City Council’s social care system for collaborative research with a partner organisation. This includes identifying the data, its structure and format; understanding the Data Protection Act 1998 and 2018 (DPA) exemptions that are relevant to ensure that legal obligations are met; data security and access management; the ethical and governance approval process.


The findings will include approaches to understanding the data, its structure and accessibility tasks involved in addressing ethical and legal obligations and requirements of the ethical and governance processes….(More)”.

Algorithmic fairness: A code-based primer for public-sector data scientists

Curated on Posted on by Stefaan Verhulst

Paper by Ken Steif and Sydney Goldstein: “As the number of government algorithms grow, so does the need to evaluate algorithmic fairness. This paper has three goals. First, we ground the notion of algorithmic fairness in the context of disparate impact, arguing that for an algorithm to be fair, its predictions must generalize across different protected groups. Next, two algorithmic use cases are presented with code examples for how to evaluate fairness. Finally, we promote the concept of an open source repository of government algorithmic “scorecards,” allowing stakeholders to compare across algorithms and use cases….(More)”.

Using Data Sharing Agreements as Tools of Indigenous Data Governance: Current Uses and Future Options

Curated on Posted on by Stefaan Verhulst

Paper by Martinez, A. and Rainie, S. C.: “Indigenous communities and scholars have been influencing a shift in participation and inclusion in academic and agency research over the past two decades. As a response, Indigenous peoples are increasingly asking research questions and developing their own studies rooted in their cultural values. They use the study results to rebuild their communities and to protect their lands. This process of Indigenous-driven research has led to partnering with academic institutions, establishing research review boards, and entering into data sharing agreements to protect environmental data, community information, and local and traditional knowledges.

Data sharing agreements provide insight into how Indigenous nations are addressing the key areas of data collection, ownership, application, storage, and the potential for data reuse in the future. By understanding this mainstream data governance mechanism, how they have been applied, and how they have been used in the past, we aim to describe how Indigenous nations and communities negotiate data protection and control with researchers.

The project described here reviewed publicly available data sharing agreements that focus on research with Indigenous nations and communities in the United States. We utilized qualitative analysis methods to identify specific areas of focus in the data sharing agreements, whether or not traditional or cultural values were included in the language of the data sharing agreements, and how the agreements defined data. The results detail how Indigenous peoples currently use data sharing agreements and potential areas of expansion for language to include in data sharing agreements as Indigenous peoples address the research needs of their communities and the protection of community and cultural data….(More)”.

Rescuing Human Rights: A Radically Moderate Approach

Curated on Posted on by Stefaan Verhulst

Book by Hurst Hannum: “The development of human rights norms is one of the most significant achievements in international relations and law since 1945, but the continuing influence of human rights is increasingly being questioned by authoritarian governments, nationalists, and pundits. Unfortunately, the proliferation of new rights, linking rights to other issues such as international crimes or the activities of business, and attempting to address every social problem from a human rights perspective risk undermining their credibility.

Rescuing Human Rights calls for understanding ‘human rights’ as international human rights law and maintaining the distinctions between binding legal obligations on governments and broader issues of ethics, politics, and social change. Resolving complex social problems requires more than simplistic appeals to rights, and adopting a ‘radically moderate’ approach that recognizes both the potential and the limits of international human rights law, offers the best hope of preserving the principle that we all have rights, simply because we are human….(More)”.