Open 4-year Assistant Professorship of Artificial Intelligence and Causal Inference in Life Course Studies: Copenhagen

An open 4-year Assistant Professorship of Artificial Intelligence and Causal Inference in Life Course Studies is being advertised at the University of Copenhagen. The position is shared between Section of Epidemiology and Section of Biostatistics and it is part of a larger initiative to build capacity within this area:.


DOCTORAL OPPORTUNITY: Increasing Complexity – the First Rule of Evolution?

An opportunity for funded doctoral study exists on a grant titled ‘Increasing Complexity: the First Rule of Evolution?” (Templeton, $973,000). The project is in evolutionary biology, but has a philosophical component, to which the doctoral project will contribute. The PI is Matthew Wills in Bath, UK, and Alex Broadbent at the University of Johannesburg is responsible for the philosophical component of the grant, and will supervise this doctoral student. The exact topic is up to the student, but will relate to the topic of the grant. For example, a project might ask about the significance of driven complexity for notions such as biological law, teleology in evolutionary biology, and/or quantum evolution. The student must be registered at the University of Johannesburg but may engage in distance study. The opportunity comes with a stipend of ZAR 140,000 plus fees, renewable annually subject to satisfactory performance and availability of funds. Start date in October 2019, but may be pushed back to February 2020. The non-negotiable deadline for completion is 31 October 2022 (i.e. the doctorate must be completed within 3 years). Support and guidance will be given towards meeting this deadline, as part of the larger project. The opportunity is open to anyone with a philosophical background, not confined to philosophy of biology. Interdisciplinary engagement will be integral to the project. A Masters degree is required by the time of first registration. Deadline is open until further notice is posted on, with earlier applications having an advantage.

Applicants should send CV, covering letter, and a sample of written work to Alex Broadbent

Health as a secondary property – print version finally out

Health as a Secondary Property 

The British Journal for the Philosophy of Science, Volume 70, Issue 2, June 2019, Pages 609–627,

In the literature on health, naturalism and normativism are typically characterized as espousing and rejecting, respectively, the view that health is objective and value-free. This article points out that there are two distinct dimensions of disagreement, regarding objectivity and value-ladenness, and thus arranges naturalism and normativism as diagonal opposites on a two-by-two matrix of possible positions. One of the remaining quadrants is occupied by value-dependent realism, holding that health facts are value-laden and objective. The remaining quadrant, which holds that they are non-objective but value-free, is unexplored. The article endorses a view in the latter quadrant, namely, the view that health is a secondary property. The article argues that a secondary property framework provides the resources to respond to the deepest objections to a broadly Boorsean account of natural function, and so preserves the spirit, though not the letter, of that account. Treating health as a secondary property permits a naturalistic explanation—specifically, an evolutionary explanation—of the health concept, in terms of the assistance such a concept might have provided to the survival and reproduction of those organisms that had it. (This approach is completely distinct from evolutionary and aetiological accounts of natural functions.) This provides the explanation, missing from Boorse’s account, for the fact that function is determined with reference to the contribution to the goals of survival and reproduction, relative to the age of the sex of the species, rather than some other equally natural goals or reference classes.

  • 1 Introduction
  • 2 Two Ways to Disagree about Health
  • 3 Secondary Properties
  • 4 Health as a Secondary Property
  • 5 Conclusion

Why the fourth industrial revolution won’t happen: public lecture, 29 April


There is excellent scientific evidence that most human predictions are wrong, beyond our immediate physical and social environment. Bold, confident claims attract the most attention, yet these are the most likely to be wrong. For this reason, much of what you have probably heard about what the world will be like in or after 4IR is false. But in addition, there is good reason to doubt that counterfactual reasoning can be implemented on any computational platform. This means that machines will not be able to reason causally, to understand, or to predict, and thus that Strong AI is not possible. Without Strong AI, 4IR will not happen.


  • Prof Babu Paul, Director of Institute for Intelligent Systems, UJ
  • Dr Faeeza Ballim, Senior Lecturer in History, UJ
  • Prof Brendon Barnes, Head of Psychology, UJ

DATE 29 April 2019
TIME 17:00 for 17:30
VENUE Chinua Achebe Auditorium (6th Floor), APK Library

University of Johannesburg (corner Kingsway and University Road, Auckland Park)

RSVP By Friday 26 April 2019 to Theodorah Modise on / 011 559 2264



Paper: The C-word, the P-word, and realism in epidemiology

My paper ‘The C-word, the P-word and realism in epidemiology‘ is now available online.


Broadbent, A. The C-word, the P-word and realism in epidemiology. Synthese (2019).


This paper considers an important recent (May 2018) contribution by Miguel Hernán to the ongoing debate about causal inference in epidemiology. Hernán rejects the idea that there is an in-principle epistemic distinction between the results of randomized controlled trials and observational studies: both produce associations which we may be more or less confident interpreting as causal. However, Hernán maintains that trials have a semantic advantage. Observational studies that seek to estimate causal effect risk issuing meaningless statements instead. The POA proposes a solution to this problem: improved restrictions on the meaningful use of causal language, in particular “causal effect”. This paper argues that new restrictions in fact fail their own standards of meaningfulness. The paper portrays the desire for a restrictive definition of causal language as positivistic, and argues that contemporary epidemiology should be more realistic in its approach to causation. In a realist context, restrictions on meaningfulness based on precision of definition are neither helpful nor necessary. Hernán’s favoured approach to causal language is saved from meaninglessness, along with the approaches he rejects.