Dan Mcquillan
Biographic Data
| ID | 297972 |
|---|---|
| NAME | Dan Mcquillan |
| GIVEN NAMES | Dan |
| FAMILY NAME | Mcquillan |
| SIGNATURE | MCQUILLAN D |
| AFFILIATIONS | Goldsmiths University of London |
| ORCID | 0000-0002-1975-1598 |
| VERIFIED | Yes |
| TOTAL WORKS | 11 |
| TOTAL CITATIONS | 30 |
| AUTHOR COUNT | 11 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 1984 |
| LATEST PUBLICATION YEAR | 2024 |
| H-INDEX | 3 |
We Are at an Extreme Point Where We Have to Go All in on What We Really Believe Education Should Be About
Predicted benefits, proven harms: How AI’s algorithmic violence emerged from our own social matrix
Artificial intelligence (AI) finally seems to be living up to the hype.We can chat with it, ask it to write an essay or use it to generate a photo-realistic image of anything we can imagine.At the same time, these capacities seem to confirm the dystopian potentials of machine intelligence.If AI can already "pass" law [https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4335905] and medical licence exams [https://www.medrxiv.org/content/10.1101/20…
Dan McQuillan in conversation: Big data, deep learning, and hold the apocalypse
Resisting AI: An Anti-fascist Approach to Artificial Intelligence
Resisting AI: An Anti-fascist Approach to Artificial Intelligence
This book is a call to resist AI. The operations of deep learning cause collateral damage in ways that can’t be fixed, and its take-up by institutions increases social precarity and structural violence. Instead of helping to address our current crises, AI produces states of exception that determine people’s life chances, becoming part of fascistic solutions to social problems. The book sets out an anti-fascist approach to AI that replaces computa…
Data Science as Machinic Neoplatonism
Data science is not simply a method but an organising idea. Commitment to the new paradigm overrides concerns caused by collateral damage, and only a counterculture can constitute an effective critique. Understanding data science requires an appreciation of what algorithms actually do; in particular, how machine learning learns. The resulting ‘insight through opacity’ drives the observable problems of algorithmic discrimination and the evasion of…
People's Councils for Ethical Machine Learning
Machine learning is a form of knowledge production native to the era of big data. It is at the core of social media platforms and everyday interactions. It is also being rapidly adopted for research and discovery across academia, business, and government. This article will explores the way the affordances of machine learning itself, and the forms of social apparatus that it becomes a part of, will potentially erode ethics and draw us in to a dron…
Algorithmic paranoia and the convivial alternative
In a time of big data, thinking about how we are seen and how that affects our lives means changing our idea about who does the seeing. Data produced by machines is most often 'seen' by other machines; the eye is in question is algorithmic. Algorithmic seeing does not produce a computational panopticon but a mechanism of prediction. The authority of its predictions rests on a slippage of the scientific method in to the world of data. Data science…
Algorithmic states of exception
In this article, I argue that pervasive tracking and data-mining are leading to shifts in governmentality that can be characterised as algorithmic states of exception. I also argue that the apparatus that performs this change owes as much to everyday business models as it does to mass surveillance. I look at technical changes at the level of data structures, such as the move to NoSQL databases, and how this combines with data-mining and machine l…
The Countercultural Potential of Citizen Science
What is the countercultural potential of citizen science? As a participant in the wider citizen science movement, I can attest that contemporary citizen science initiatives rarely characterise themselves as countercultural. Rather, the goal of most citizen science projects is to be seen as producing orthodox scientific knowledge: the ethos is respectability rather than rebellion (NERC). I will suggest instead that there are resonances with the co…
Urban upgrading and historic preservation
Algorithmic states of exception
In this article, I argue that pervasive tracking and data-mining are leading to shifts in governmentality that can be characterised as algorithmic states of exception. I also argue that the apparatus that performs this change owes as much to everyday business models as it does to mass surveillance. I look at technical changes at the level of data structures, such as the move to NoSQL databases, and how this combines with data-mining and machine l…
Algorithmic paranoia and the convivial alternative
In a time of big data, thinking about how we are seen and how that affects our lives means changing our idea about who does the seeing. Data produced by machines is most often 'seen' by other machines; the eye is in question is algorithmic. Algorithmic seeing does not produce a computational panopticon but a mechanism of prediction. The authority of its predictions rests on a slippage of the scientific method in to the world of data. Data science…
The Countercultural Potential of Citizen Science
What is the countercultural potential of citizen science? As a participant in the wider citizen science movement, I can attest that contemporary citizen science initiatives rarely characterise themselves as countercultural. Rather, the goal of most citizen science projects is to be seen as producing orthodox scientific knowledge: the ethos is respectability rather than rebellion (NERC). I will suggest instead that there are resonances with the co…
People's Councils for Ethical Machine Learning
Machine learning is a form of knowledge production native to the era of big data. It is at the core of social media platforms and everyday interactions. It is also being rapidly adopted for research and discovery across academia, business, and government. This article will explores the way the affordances of machine learning itself, and the forms of social apparatus that it becomes a part of, will potentially erode ethics and draw us in to a dron…
Urban upgrading and historic preservation
Urban upgrading and historic preservation
The Countercultural Potential of Citizen Science
What is the countercultural potential of citizen science? As a participant in the wider citizen science movement, I can attest that contemporary citizen science initiatives rarely characterise themselves as countercultural. Rather, the goal of most citizen science projects is to be seen as producing orthodox scientific knowledge: the ethos is respectability rather than rebellion (NERC). I will suggest instead that there are resonances with the co…
Algorithmic states of exception
In this article, I argue that pervasive tracking and data-mining are leading to shifts in governmentality that can be characterised as algorithmic states of exception. I also argue that the apparatus that performs this change owes as much to everyday business models as it does to mass surveillance. I look at technical changes at the level of data structures, such as the move to NoSQL databases, and how this combines with data-mining and machine l…
Algorithmic paranoia and the convivial alternative
In a time of big data, thinking about how we are seen and how that affects our lives means changing our idea about who does the seeing. Data produced by machines is most often 'seen' by other machines; the eye is in question is algorithmic. Algorithmic seeing does not produce a computational panopticon but a mechanism of prediction. The authority of its predictions rests on a slippage of the scientific method in to the world of data. Data science…
Data Science as Machinic Neoplatonism
Data science is not simply a method but an organising idea. Commitment to the new paradigm overrides concerns caused by collateral damage, and only a counterculture can constitute an effective critique. Understanding data science requires an appreciation of what algorithms actually do; in particular, how machine learning learns. The resulting ‘insight through opacity’ drives the observable problems of algorithmic discrimination and the evasion of…
People's Councils for Ethical Machine Learning
Machine learning is a form of knowledge production native to the era of big data. It is at the core of social media platforms and everyday interactions. It is also being rapidly adopted for research and discovery across academia, business, and government. This article will explores the way the affordances of machine learning itself, and the forms of social apparatus that it becomes a part of, will potentially erode ethics and draw us in to a dron…
Resisting AI: An Anti-fascist Approach to Artificial Intelligence
Resisting AI: An Anti-fascist Approach to Artificial Intelligence
This book is a call to resist AI. The operations of deep learning cause collateral damage in ways that can’t be fixed, and its take-up by institutions increases social precarity and structural violence. Instead of helping to address our current crises, AI produces states of exception that determine people’s life chances, becoming part of fascistic solutions to social problems. The book sets out an anti-fascist approach to AI that replaces computa…
Predicted benefits, proven harms: How AI’s algorithmic violence emerged from our own social matrix
Artificial intelligence (AI) finally seems to be living up to the hype.We can chat with it, ask it to write an essay or use it to generate a photo-realistic image of anything we can imagine.At the same time, these capacities seem to confirm the dystopian potentials of machine intelligence.If AI can already "pass" law [https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4335905] and medical licence exams [https://www.medrxiv.org/content/10.1101/20…
Dan McQuillan in conversation: Big data, deep learning, and hold the apocalypse
We Are at an Extreme Point Where We Have to Go All in on What We Really Believe Education Should Be About
Computer Science (7 works) · Ethics and Social Impacts of AI (7 works) · Sociology (7 works) · Epistemology (4 works) · Philosophy (4 works) · Psychology (4 works) · Artificial Intelligence (3 works) · Law (3 works) · Neuroethics, Human Enhancement, Biomedical Innovations (3 works) · Political science (3 works)