Emanuele Ratti
Biographic Data
| ID | 297975 |
|---|---|
| NAME | Emanuele Ratti |
| GIVEN NAMES | Emanuele |
| FAMILY NAME | Ratti |
| SIGNATURE | RATTI E |
| AFFILIATIONS | University of Notre Dame |
| ORCID | 0000-0003-1409-8240 |
| VERIFIED | Yes |
| TOTAL WORKS | 16 |
| TOTAL CITATIONS | 19 |
| WORKS AS AUTHOR | 15 |
| WORKS AS EDITOR | 1 |
| FIRST PUBLICATION YEAR | 2015 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 2 |
What can Artificial Intelligence learn from medicine? Generative analogies and reliable machine learning systems
In the past few years, machine learning (ML) has been widely (and to an extent, successfully) implemented in medicine. However, uncertainties surrounding ML have made it difficult to establish the bases of its epistemic and methodological warrants. In the literature, a parallel has been drawn between medicine and ML, suggesting that we should model epistemic and methodological standards for ML on the standards of clinical translation. By developi…
What Do We Teach to Engineering Students
In the past few years, calls for integrating ethics modules in engineering curricula have multiplied. Despite this positive trend, a number of issues with these ‘embedded’ programs remains. First, learning goals are underspecified. A second limitation is the conflation of different dimensions under the same banner, in particular confusion between ethics curricula geared towards addressing the ethics of individual conduct and curricula geared towa…
Integrating Artificial Intelligence in Scientific Practice
A recent article by Herzog provides a much-needed integration of ethical and epistemological arguments in favor of explicable AI (XAI) in medicine. In this short piece, I suggest a way in which its epistemological intuition of XAI as “explanatory interface” can be further developed to delineate the relation between AI tools and scientific research
Who Is a Good Data Scientist? A Reply to Curzer and Epstein
A central distinction in This can open up discussions about the relationship between ethics and epistemology in the practice of science. Focusing on the disadvantaged to the exclusion of good scientific practices, Curzer and Epstein argue, can harm everyone impacted by medical science, including the disadvantaged. For this reason, they propose that "ethical data scientists should strive for accurate data and scientifically sound data analysis" (2…
Philipp Fischer, Gabriele Gramelsberger, Christoph Hoffmann, Hans Hofmann, Hans-Jorg Rheinberger, Hannes Rickli, Natures of Data
Science, Technology, and Virtues
What does it mean to embed ethics in data science? An integrative approach based on microethics and virtues
In the past few years, scholars have been questioning whether the current approach in data ethics based on the higher level case studies and general principles is effective. In particular, some have been complaining that such an approach to ethics is difficult to be applied and to be taught in the context of data science. In response to these concerns, there have been discussions about how ethics should be “embedded” in the practice of data scien…
Cultivating Moral Attention
In the past few years, the ethical ramifications of AI technologies (in particular data science) have been at the center of intense debates. Considerable attention has been devoted to understanding how a morally responsible practice of data science can be promoted and which values have to shape it. In this context, ethics and moral responsibility have been mainly conceptualized as compliance to widely shared principles. However, several scholars …
Data science and molecular biology
What kind of novelties can machine learning possibly generate? The case of genomics
Models of’ and ‘Models for’
Molecular biologists exploit information conveyed by mechanistic models for experimental purposes. In this article, I make sense of this aspect of biological practice by developing Keller’s idea of the distinction between ‘models of’ and ‘models for’. ‘Models of (phenomena)’ should be understood as models representing phenomena and are valuable if they explain phenomena. ‘Models for (manipulating phenomena)’ are new types of material manipulation…
Unity of Science and Ethics of Belief
In this paper, I develop van Fraassen’s views about empiricism, science, and the empirical stance to make sense of the unity of the sciences. My claim will be that sciences are unified neither by their products nor by their objects, but rather by scientists’ attitudes towards knowledge. In particular, these attitudes take the form of an ethics of beliefs, namely a set of norms that constrain the ways knowledge is conceived and gathered.
Docility as a Primary Virtue in Scientific Research
Scientific epistemology is a topic that has sparked centuries of philosophical discourse. In particular, understanding the role that scientists play in the creation and perpetuation of scientific knowledge is a subject that continues to be hotly debated. A relative new-comer to scientific epistemology is the field of virtue epistemology, which positions knowledge creation as integrally linked to specific character traits held by the scientist. Po…
Why genes are like lemons
The end of 'small biology'? Some thoughts about biomedicine and big science
In biology-as in other scientific fields-there is a lively opposition between big and small science projects. In this commentary, I try to contextualize this opposition in the field of biomedicine, and I argue that, at least in this context, big science projects should come first
Big Data Biology
Recently, biologists have argued that data-driven biology fosters a new scientific methodology, namely, one that is irreducible to traditional methodologies of molecular biology defined as the discovery strategies elucidated by mechanistic philosophy. Here I show how data-driven studies can be included in the traditional mechanistic approach in two respects. On the one hand, some studies provide eliminative inferential procedures to prioritize an…
Big Data Biology
Recently, biologists have argued that data-driven biology fosters a new scientific methodology, namely, one that is irreducible to traditional methodologies of molecular biology defined as the discovery strategies elucidated by mechanistic philosophy. Here I show how data-driven studies can be included in the traditional mechanistic approach in two respects. On the one hand, some studies provide eliminative inferential procedures to prioritize an…
Data science and molecular biology
What kind of novelties can machine learning possibly generate? The case of genomics
Models of’ and ‘Models for’
Molecular biologists exploit information conveyed by mechanistic models for experimental purposes. In this article, I make sense of this aspect of biological practice by developing Keller’s idea of the distinction between ‘models of’ and ‘models for’. ‘Models of (phenomena)’ should be understood as models representing phenomena and are valuable if they explain phenomena. ‘Models for (manipulating phenomena)’ are new types of material manipulation…
Docility as a Primary Virtue in Scientific Research
Scientific epistemology is a topic that has sparked centuries of philosophical discourse. In particular, understanding the role that scientists play in the creation and perpetuation of scientific knowledge is a subject that continues to be hotly debated. A relative new-comer to scientific epistemology is the field of virtue epistemology, which positions knowledge creation as integrally linked to specific character traits held by the scientist. Po…
The end of 'small biology'? Some thoughts about biomedicine and big science
In biology-as in other scientific fields-there is a lively opposition between big and small science projects. In this commentary, I try to contextualize this opposition in the field of biomedicine, and I argue that, at least in this context, big science projects should come first
Big Data Biology
Recently, biologists have argued that data-driven biology fosters a new scientific methodology, namely, one that is irreducible to traditional methodologies of molecular biology defined as the discovery strategies elucidated by mechanistic philosophy. Here I show how data-driven studies can be included in the traditional mechanistic approach in two respects. On the one hand, some studies provide eliminative inferential procedures to prioritize an…
Why genes are like lemons
The end of 'small biology'? Some thoughts about biomedicine and big science
In biology-as in other scientific fields-there is a lively opposition between big and small science projects. In this commentary, I try to contextualize this opposition in the field of biomedicine, and I argue that, at least in this context, big science projects should come first
Unity of Science and Ethics of Belief
In this paper, I develop van Fraassen’s views about empiricism, science, and the empirical stance to make sense of the unity of the sciences. My claim will be that sciences are unified neither by their products nor by their objects, but rather by scientists’ attitudes towards knowledge. In particular, these attitudes take the form of an ethics of beliefs, namely a set of norms that constrain the ways knowledge is conceived and gathered.
Docility as a Primary Virtue in Scientific Research
Scientific epistemology is a topic that has sparked centuries of philosophical discourse. In particular, understanding the role that scientists play in the creation and perpetuation of scientific knowledge is a subject that continues to be hotly debated. A relative new-comer to scientific epistemology is the field of virtue epistemology, which positions knowledge creation as integrally linked to specific character traits held by the scientist. Po…
What kind of novelties can machine learning possibly generate? The case of genomics
Models of’ and ‘Models for’
Molecular biologists exploit information conveyed by mechanistic models for experimental purposes. In this article, I make sense of this aspect of biological practice by developing Keller’s idea of the distinction between ‘models of’ and ‘models for’. ‘Models of (phenomena)’ should be understood as models representing phenomena and are valuable if they explain phenomena. ‘Models for (manipulating phenomena)’ are new types of material manipulation…
Science, Technology, and Virtues
What does it mean to embed ethics in data science? An integrative approach based on microethics and virtues
In the past few years, scholars have been questioning whether the current approach in data ethics based on the higher level case studies and general principles is effective. In particular, some have been complaining that such an approach to ethics is difficult to be applied and to be taught in the context of data science. In response to these concerns, there have been discussions about how ethics should be “embedded” in the practice of data scien…
Cultivating Moral Attention
In the past few years, the ethical ramifications of AI technologies (in particular data science) have been at the center of intense debates. Considerable attention has been devoted to understanding how a morally responsible practice of data science can be promoted and which values have to shape it. In this context, ethics and moral responsibility have been mainly conceptualized as compliance to widely shared principles. However, several scholars …
Data science and molecular biology
Integrating Artificial Intelligence in Scientific Practice
A recent article by Herzog provides a much-needed integration of ethical and epistemological arguments in favor of explicable AI (XAI) in medicine. In this short piece, I suggest a way in which its epistemological intuition of XAI as “explanatory interface” can be further developed to delineate the relation between AI tools and scientific research
Who Is a Good Data Scientist? A Reply to Curzer and Epstein
A central distinction in This can open up discussions about the relationship between ethics and epistemology in the practice of science. Focusing on the disadvantaged to the exclusion of good scientific practices, Curzer and Epstein argue, can harm everyone impacted by medical science, including the disadvantaged. For this reason, they propose that "ethical data scientists should strive for accurate data and scientifically sound data analysis" (2…
Philipp Fischer, Gabriele Gramelsberger, Christoph Hoffmann, Hans Hofmann, Hans-Jorg Rheinberger, Hannes Rickli, Natures of Data
What Do We Teach to Engineering Students
In the past few years, calls for integrating ethics modules in engineering curricula have multiplied. Despite this positive trend, a number of issues with these ‘embedded’ programs remains. First, learning goals are underspecified. A second limitation is the conflation of different dimensions under the same banner, in particular confusion between ethics curricula geared towards addressing the ethics of individual conduct and curricula geared towa…
What can Artificial Intelligence learn from medicine? Generative analogies and reliable machine learning systems
In the past few years, machine learning (ML) has been widely (and to an extent, successfully) implemented in medicine. However, uncertainties surrounding ML have made it difficult to establish the bases of its epistemic and methodological warrants. In the literature, a parallel has been drawn between medicine and ML, suggesting that we should model epistemic and methodological standards for ML on the standards of clinical translation. By developi…
Epistemology (14 works) · Philosophy (14 works) · Computer Science (8 works) · Philosophy of science (7 works) · Biology (6 works) · Engineering (6 works) · Engineering ethics (6 works) · Sociology (6 works) · Ethics and Social Impacts of AI (5 works) · Political science (5 works)