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  1.  34
    What does it mean to embed ethics in data science? An integrative approach based on the microethics and virtues.Louise Bezuidenhout & Emanuele Ratti - 2021 - AI and Society 36:939–953.
    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 science, in the sense of showing (...)
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  2.  86
    Big Data Biology: Between Eliminative Inferences and Exploratory Experiments.Emanuele Ratti - 2015 - Philosophy of Science 82 (2):198-218.
    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 into the traditional mechanistic approach in two respects. On the one hand, some studies provide eliminative inferential procedures to prioritize and develop mechanistic hypotheses. On the other, different studies play an exploratory role in providing useful (...)
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  3.  46
    What Kind of Novelties Can Machine Learning Possibly Generate? The Case of Genomics.Emanuele Ratti - 2020 - Studies in History and Philosophy of Science Part A 83:86-96.
    Machine learning (ML) has been praised as a tool that can advance science and knowledge in radical ways. However, it is not clear exactly how radical are the novelties that ML generates. In this article, I argue that this question can only be answered contextually, because outputs generated by ML have to be evaluated on the basis of the theory of the science to which ML is applied. In particular, I analyze the problem of novelty of ML outputs in the (...)
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  4.  51
    Data Science and Molecular Biology: Prediction and Mechanistic Explanation.Ezequiel López-Rubio & Emanuele Ratti - 2019 - Synthese (4):1-26.
    In the last few years, biologists and computer scientists have claimed that the introduction of data science techniques in molecular biology has changed the characteristics and the aims of typical outputs (i.e. models) of such a discipline. In this paper we will critically examine this claim. First, we identify the received view on models and their aims in molecular biology. Models in molecular biology are mechanistic and explanatory. Next, we identify the scope and aims of data science (machine learning in (...)
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  5.  65
    Junk or Functional DNA? ENCODE and the Function Controversy.Pierre-Luc Germain, Emanuele Ratti & Federico Boem - 2014 - Biology and Philosophy 29 (6):807-831.
    In its last round of publications in September 2012, the Encyclopedia Of DNA Elements (ENCODE) assigned a biochemical function to most of the human genome, which was taken up by the media as meaning the end of ‘Junk DNA’. This provoked a heated reaction from evolutionary biologists, who among other things claimed that ENCODE adopted a wrong and much too inclusive notion of function, making its dismissal of junk DNA merely rhetorical. We argue that this criticism rests on misunderstandings concerning (...)
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  6.  61
    ‘Models of’ and ‘Models For’: On the Relation Between Mechanistic Models and Experimental Strategies in Molecular Biology.Emanuele Ratti - 2018 - British Journal for the Philosophy of Science (2):773-797.
    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 manipulations and are important not because of their explanatory force, but because of the interventionist strategies they afford. This (...)
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  7.  58
    Mechanistic Models and the Explanatory Limits of Machine Learning.Emanuele Ratti & Ezequiel López-Rubio - unknown
    We argue that mechanistic models elaborated by machine learning cannot be explanatory by discussing the relation between mechanistic models, explanation and the notion of intelligibility of models. We show that the ability of biologists to understand the model that they work with severely constrains their capacity of turning the model into an explanatory model. The more a mechanistic model is complex, the less explanatory it will be. Since machine learning increases its performances when more components are added, then it generates (...)
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  8.  60
    Conceptual Challenges in the Theoretical Foundations of Systems Biology.Marta Bertolaso & Emanuele Ratti - 2018 - In Mariano Bizzarri (ed.), Systems Biology. New York: Springer, Humana Press. pp. 1-13.
    In the last decade, Systems Biology has emerged as a conceptual and explanatory alternative to reductionist-based approaches in molecular biology. However, the foundations of this new discipline need to be fleshed out more carefully. In this paper, we claim that a relational ontology is a necessary tool to ground both the conceptual and explanatory aspects of Systems Biology. A relational ontology holds that relations are prior—both conceptually and explanatory—to entities, and that in the biological realm entities are defined primarily by (...)
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  9.  17
    Docility as a Primary Virtue in Scientific Research.Louise Bezuidenhout, Emanuele Ratti, Nathaniel Warne & Dori Beeler - 2019 - Minerva 57 (1):67-84.
    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. Positioning scientific research as a distinct practice, virtue epistemologists strive to understand what virtues foster robust knowledge (...)
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  10. The End of 'Small Biology'? Some Thoughts About Biomedicine and Big Science.Emanuele Ratti - 2016 - Big Data and Society:1-6.
    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.
     
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  11.  51
    Phronesis and Automated Science: The Case of Machine Learning and Biology.Emanuele Ratti - 2019 - In Fabio Sterpetti & M. Bertolaso (eds.), Will Science Remain Human? Springer.
    The applications of machine learning and deep learning to the natural sciences has fostered the idea that the automated nature of algorithmic analysis will gradually dispense human beings from scientific work. In this paper, I will show that this view is problematic, at least when ML is applied to biology. In particular, I will claim that ML is not independent of human beings and cannot form the basis of automated science. Computer scientists conceive their work as being a case of (...)
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  12. Towards a Notion of Intervention in Big-Data Biology and Molecular Medicine.Emanuele Ratti & Federico Boem - 2016 - In Marco Nathan & Giovanni Boniolo (eds.), Philosophy of Molecular Medicine - Foundational Issues in Research and Practice. Routledge.
    We claim that in contemporary studies in molecular biology and biomedicine, the nature of ‘manipulation’ and ‘intervention’ has changed. Traditionally, molecular biology and molecular studies in medicine are considered experimental sciences, whereas experiments take the form of material manipulation and intervention. On the contrary “big science” projects in biology focus on the practice of data mining of biological databases. We argue that the practice of data mining is a form of intervention although it does not require material manipulation. We also (...)
     
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  13.  13
    Cultivating Moral Attention: a Virtue-Oriented Approach to Responsible Data Science in Healthcare.Emanuele Ratti & Mark Graves - 2021 - Philosophy and Technology 34 (4):1819-1846.
    In the past few years, the ethical ramifications of AI technologies 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 have highlighted the limitations of such a principled approach. Drawing from microethics and the virtue theory tradition, (...)
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  14.  15
    The Main Faces of Robustness.Giovanni Boniolo, Mattia Andreoletti, Federico Boem & Emanuele Ratti - 2017 - Dialogue and Universalism 27 (3):157-172.
    In the last decade, robustness has been extensively mentioned and discussed in biology as well as in the philosophy of the life sciences. Nevertheless, from both fields, someone has affirmed that this debate has resulted in more semantic confusion than in semantic clearness. Starting from this claim, we wish to offer a sort of prima facie map of the different usages of the term. In this manner we would intend to predispose a sort of “semantic platform” which could be exploited (...)
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  15.  4
    Science and Politics in a Time of Pandemic: Some Epistemological and Political Lessons From the Italian Story.Federico Boem & Emanuele Ratti - 2021 - Humana Mente 14 (40).
    Making public policy choices based on available scientific evidence is an ideal condition for any policy making. However, the mechanisms governing these scenarios are complex, non-linear, and, alongside the medical-health and epidemiological issues, involve socio-economic, political, communicative, informational, ethical and epistemological aspects. In this article we analyze the role of scientific evidence when implementing political decisions that strictly depend on it, as in the case of the COVID-19 pandemic. In carrying out this analysis, we will focus above all on the (...)
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  16.  31
    Levels of Abstraction, Emergentism and Artificial Life.Emanuele Ratti - 2014 - Journal of Experimental & Theoretical Artificial Intelligence:1-12.
    I diagnose the current debate between epistemological and ontological emergentism as a Kantian antinomy, which has reasonable but irreconcilable thesis and antithesis. Kantian antinomies have recently returned to contemporary philosophy in part through the work of Luciano Floridi, and the method of levels of abstraction. I use a thought experiment concerning a computer simulation to show how to resolve the epistemological/ontological antinomy about emergence. I also use emergentism and simulations in artificial life to illuminate both levels of abstraction and theoretical (...)
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  17.  62
    Diverse Perspectives on Ontology: A Joint Report on the First IAOA Interdisciplinary Summer School on Ontological Analysis.Emilio Sanfilippo, Emanuele Ratti, Francesca Quattri, Aleksandra Sojic, Federico Boem, Gaoussou Camara & Eric Chuk - 2013 - Applied Ontology 8 (1):59-71.
  18.  17
    Big Data in the Experimental Life Sciences: Bruno J. Strasser: Collecting Experiments: Making Big Data Biology. Chicago: The University of Chicago Press, 2019, 392 Pp, $45.00. [REVIEW]Emanuele Ratti - 2020 - Metascience 29 (3):403-408.
  19. Science, Technology & the Good Life: Perspectives on Virtue in Modern Science & Technology.Emanuele Ratti & Tom Stapleford (eds.) - forthcoming
  20.  7
    D enis N oble, Dance to the Tune of Life — Biological Relativity, Cambridge: Cambridge University Press, December 2016, 302 pp., £ 17.99. [REVIEW]Emanuele Ratti - 2018 - History and Philosophy of the Life Sciences 40 (3):54.
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  21.  2
    Unity of Science and Ethics of Belief.Emanuele Ratti - 2018 - Philosophy, Theology and the Sciences 5 (1):5.