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Prospectus

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Philosophy of Natural Sciences: Philosophical Implications of Deep Learning for Scientific Practice

Course
2019-2020

Admission requirements

Admission to this course is restricted to students enrolled in MA Philosophy 120 EC, specialisation Philosophy of Natural Sciences.

Description

Semi-supervised or unsupervised machine learning algorithms, or “deep learning”, have the capacity to revolutionise scientific practice as much as they have implications for communication, health care, commerce, finance, and other domains of modern life. In this course, we consider the use of deep learning in scientific discovery and address two general questions: how should our image of scientific practice change in response, and to what extent are established concepts and theories in philosophy of knowledge adequate to analyse these changes? The course involves studying recent applications of deep learning in scientific discovery, for example in protein folding prediction competitions; assessing to what extent the outcomes satisfy standards of justifiable or reliable knowledge in epistemology and philosophy of science; and clarifying the relation between the virtues of empiricism, surveyability, and understanding in this new form of science.

Course objectives

Students who successfully complete the course will be able to:

  • Present and discuss the intellectual principles underlying deep learning and explain the differences between deep learning and earlier algorithms for data handing;

  • Discuss connections and similarities between uses of deep learning for pattern recognition and decision making;

  • Give a critical account of recent applications of deep learning in scientific practice;

  • Apply concepts and theories from philosophy of knowledge to such cases, and use such cases to evaluate the adequacy of those philosophical concepts and theories;

  • Assess the implications of these developments for the changing nature of science;

  • Give a class presentation and write a paper on the above topics;

  • Design and present a PhD-level research proposal on the topics of the course.

Timetable

The timetable is available on the following website:

MA Philosophy 120 EC

Mode of instruction

  • Seminars, or tutorials if the enrolment is small.

Class attendance is required.

Course load

Total course load (10 EC x 28 hours): 280 hours

Class attendance: 13 × 3 hours = 39 hours
Reworking of class notes: 13 hours
Literature study (approx. 500 pages): 74 hours
Preparation for class presentation: 24 hours
Practical assignment: 10 hours
Writing of research proposal/final essay: 120 hours

Assessment method

Assessment

  • Two compulsory presentations during the semester;

  • Two shorter papers;

  • Term paper;

  • Oral class participation.

Weighting

The final mark for the course is established by determination of the weighted average of several subtests.

Resit

One resit will be offered, covering the entire course content and consisting of a paper. The grade will replace previously earned grades for subtests. Class participation and practical assignments (presentations) are mandatory requirements for taking the tests and resit. Students who have obtained a satisfactory grade for the first examination(s) cannot take the resit.

Inspection and feedback

How and when an exam review will take place will be disclosed together with the publication of the exam results at the latest. If a student requests a review within 30 days after publication of the exam results, an exam review will have to be organized.

Blackboard

Blackboard will be used for:

  • Posting course material.

Reading list

Research articles and other recent scholarly literature. A list will be circulated to students later. All material available online: no purchase required.

Registration

Enrolment through uSis is mandatory.
General information about uSis is available on the website.

Students are strongly advised to register in uSis through the activity number, which can be found in the timetables for courses and exams.

Registration Studeren à la carte and Contractonderwijs

Not applicable.

Contact information

Prof. dr. J.W. McAllister

Remarks

None.