Alexander Campolo
Dados Biográficos
| ID | 2744199 |
|---|---|
| NOME | Alexander Campolo |
| PRENOMES | Alexander |
| SOBRENOME | Campolo |
| ASSINATURA | CAMPOLO A |
| AFILIAÇÕES | Durham University |
| ORCID | 0000-0003-3159-4131 |
| VERIFICADO | Sim |
| TOTAL DE OBRAS | 9 |
| TOTAL DE CITAÇÕES | 22 |
| TOTAL COMO AUTOR | 9 |
| TOTAL COMO EDITOR | 0 |
| PRIMEIRO ANO DE PUBLICAÇÃO | 2020 |
| ANO MAIS RECENTE DE PUBLICAÇÃO | 2026 |
| ÍNDICE H | 3 |
Probabilistic spaces
Loss
This essay compares two statistical notions of error to draw out their distinctive epistemological and normative implications. The first sense crystallized in the nineteenth century as practical techniques for producing estimates from discrepant observations were interpreted as metaphysical laws of error. Historians have shown how these interpretations produced new forms of social knowledge and control over normal types. Although the metaphysical…
“Desired behaviors”
The concept of alignment has undergone a remarkable rise in recent years to take center stage in the ethics of artificial intelligence. There are now numerous philosophical studies of the values that should be used in this ethical framework as well as a technical literature operationalizing these values in machine learning models. This article takes a step back to address a more basic set of critical questions: Where has the ethical imperative of…
Politics of the prompt
A world model
The computational logics of large language models (LLMs) or generative AI – from the early models of CLIP and BERT to the explosion of text and image generation via ChatGPT and DALL-E − are increasingly penetrating the social and political world. Not merely in the direct sense that generative AI models are being deployed to govern difficult problems, whether decisions on the battlefield or responses to pandemic, but also because generative AI is …
Machine learning, meaning making
Computer science tends to foreclose the reading of its texts by social science and humanities scholars - via code and scale, mathematics, black box opacities, secret or proprietary models. Yet, when computer science papers are read in order to better understand what machine learning means for societies, a form of reading is brought to bear that is not primarily about excavating the hidden meaning of a text or exposing underlying truths about scie…
From rules to examples
This paper analyzes the effects of a perceived transition from a rule-based computer programming paradigm to an example-based paradigm associated with machine learning. While both paradigms coexist in practice, we critically discuss the distinctive epistemological and ethical implications of machine learning's "exemplary" type of authority. To capture its logic, we compare it to computer programming rules that date to the middle of the 20th centu…
Enchanted Determinism
Deep learning techniques are growing in popularity within the field of artificial intelligence (AI). These approaches identify patterns in large scale datasets, and make classifications and predictions, which have been celebrated as more accurate than those of humans. But for a number of reasons, including nonlinear path from inputs to outputs, there is a dearth of theory that can explain why deep learning techniques work so well at pattern detec…
Signs and Sight
February 01 2020 Signs and Sight: Jacques Bertin and the Visual Language of Structuralism Alexander Campolo Alexander Campolo Alexander Campolo is a postdoctoral researcher at the Stevanovich Institute on the Formation of Knowledge at the University of Chicago. He is working on a book project on the emergence of data visualization from epistemological problems in computing and human sciences during the second part of the twentieth century. Search…
A world model
The computational logics of large language models (LLMs) or generative AI – from the early models of CLIP and BERT to the explosion of text and image generation via ChatGPT and DALL-E − are increasingly penetrating the social and political world. Not merely in the direct sense that generative AI models are being deployed to govern difficult problems, whether decisions on the battlefield or responses to pandemic, but also because generative AI is …
Machine learning, meaning making
Computer science tends to foreclose the reading of its texts by social science and humanities scholars - via code and scale, mathematics, black box opacities, secret or proprietary models. Yet, when computer science papers are read in order to better understand what machine learning means for societies, a form of reading is brought to bear that is not primarily about excavating the hidden meaning of a text or exposing underlying truths about scie…
From rules to examples
This paper analyzes the effects of a perceived transition from a rule-based computer programming paradigm to an example-based paradigm associated with machine learning. While both paradigms coexist in practice, we critically discuss the distinctive epistemological and ethical implications of machine learning's "exemplary" type of authority. To capture its logic, we compare it to computer programming rules that date to the middle of the 20th centu…
Politics of the prompt
Enchanted Determinism
Deep learning techniques are growing in popularity within the field of artificial intelligence (AI). These approaches identify patterns in large scale datasets, and make classifications and predictions, which have been celebrated as more accurate than those of humans. But for a number of reasons, including nonlinear path from inputs to outputs, there is a dearth of theory that can explain why deep learning techniques work so well at pattern detec…
Signs and Sight
February 01 2020 Signs and Sight: Jacques Bertin and the Visual Language of Structuralism Alexander Campolo Alexander Campolo Alexander Campolo is a postdoctoral researcher at the Stevanovich Institute on the Formation of Knowledge at the University of Chicago. He is working on a book project on the emergence of data visualization from epistemological problems in computing and human sciences during the second part of the twentieth century. Search…
Machine learning, meaning making
Computer science tends to foreclose the reading of its texts by social science and humanities scholars - via code and scale, mathematics, black box opacities, secret or proprietary models. Yet, when computer science papers are read in order to better understand what machine learning means for societies, a form of reading is brought to bear that is not primarily about excavating the hidden meaning of a text or exposing underlying truths about scie…
From rules to examples
This paper analyzes the effects of a perceived transition from a rule-based computer programming paradigm to an example-based paradigm associated with machine learning. While both paradigms coexist in practice, we critically discuss the distinctive epistemological and ethical implications of machine learning's "exemplary" type of authority. To capture its logic, we compare it to computer programming rules that date to the middle of the 20th centu…
A world model
The computational logics of large language models (LLMs) or generative AI – from the early models of CLIP and BERT to the explosion of text and image generation via ChatGPT and DALL-E − are increasingly penetrating the social and political world. Not merely in the direct sense that generative AI models are being deployed to govern difficult problems, whether decisions on the battlefield or responses to pandemic, but also because generative AI is …
Loss
This essay compares two statistical notions of error to draw out their distinctive epistemological and normative implications. The first sense crystallized in the nineteenth century as practical techniques for producing estimates from discrepant observations were interpreted as metaphysical laws of error. Historians have shown how these interpretations produced new forms of social knowledge and control over normal types. Although the metaphysical…
“Desired behaviors”
The concept of alignment has undergone a remarkable rise in recent years to take center stage in the ethics of artificial intelligence. There are now numerous philosophical studies of the values that should be used in this ethical framework as well as a technical literature operationalizing these values in machine learning models. This article takes a step back to address a more basic set of critical questions: Where has the ethical imperative of…
Politics of the prompt
Probabilistic spaces
Ethics and Social Impacts of AI (8 obras) · Artificial Intelligence (5 obras) · Computer Science (5 obras) · Epistemology (4 obras) · Politics (4 obras) · Law (3 obras) · Philosophy (3 obras) · Political science (3 obras) · Psychology (3 obras) · Adversarial Robustness in Machine Learning (2 obras)