What is Scientific Knowledge?

An Introduction to Contemporary Epistemology of Science

Kevin McCain, Kostas Kampourakis, Kevin McCain, Kostas Kampourakis

• Publisher: Routledge
• Year: 2019
• ISBN:
  9781351336604
• Edition: 1
• Topic: Philosophie
• Subtopic: Geschichte & Theorie der Philosophie

What Is Scientific Knowledge? is a much-needed collection of introductory-level chapters on the epistemology of science. Renowned historians, philosophers, science educators, and cognitive scientists have authored 19 original contributions specifically for this volume. The chapters, accessible for students in both philosophy and the sciences, serve as helpful introductions to the primary debates surrounding scientific knowledge. First-year undergraduates can readily understand the variety of discussions in the volume, and yet advanced students and scholars will encounter chapters rich enough to engage their many interests. The variety and coverage in this volume make it the perfect choice for the primary text in courses on scientific knowledge. It can also be used as a supplemental book in classes in epistemology, philosophy of science, and other related areas.

Key features:

* an accessible and comprehensive introduction to the epistemology of science for a wide variety of students (both undergraduate- and graduate-level) and researchers

* written by an international team of senior researchers and the most promising junior scholars

* addresses several questions that students and lay people interested in science may already have, including questions about how scientific knowledge is gained, its nature, and the challenges it faces.

Part I

How Is Scientific Knowledge Generated?

1

How Many Scientists Does It Take to Have Knowledge?

Jeroen de Ridder

Introduction

Contemporary scientific research, especially in most of the STEM disciplines and the social sciences, is massively collaborative. This is something you can easily observe for yourself when visiting your local university’s science labs. They will typically sport teams of researchers, technicians, and students involved in collaborative projects. These teams can be part of larger collaborations with people in other departments or at other universities. The collaborative nature of science also shows clearly in the official records of science: publications in peer-reviewed journals. A 2016 article in The Economist reports that the average number of authors on scientific papers rose from 3.2 to 4.4 between 1996 and 2015.¹ An earlier report from Thomson Reuters’ ScienceWatch newsletter notes that fewer than one in five papers in the sciences, social sciences, and humanities had a single author (the percentage goes down to 12% for the natural sciences alone), and that 2011 saw over 600 papers with more than 100 authors and 146 with more than 1,000 authors.² As I’m writing this, a 2015 paper in particle physics, produced by scientists from all over the world collaborating with the teams operating the Large Hadron Collider at CERN in Switzerland, holds the record for highest author count on a single paper, with a total of 5,154 authors.³ The list of authors takes up 24 of the paper’s 33 pages! In the same year, biologists broke the 1,000 authors barrier for the first time with a genomics paper on fruit-flies authored by 1,014 people, more than 900 of whom were undergrads.⁴

These numbers demonstrate that science has become increasingly collaborative over the past decades, but it should be noted at the outset that they also reflect one of the less edifying aspects of contemporary science. The amount and (perceived) quality of publications can make or break academic careers. Scientists have a strong incentive to rake in as many as they can. As a result, researchers frequently dish out authorships by very liberal criteria, engage in tit-for-tat exchanges of authorships on each other’s papers, and add honorary authors to increase the chances of getting published in prestigious venues.⁵ This leads to inflated author lists, which don’t always reflect genuine collaboration and substantive research contributions. In response, many scientific journals have started to implement stricter guidelines for authorships.⁶ These developments raise important questions, but for the purposes of this chapter, I will leave them aside.⁷

Instead, I want to explore some epistemological consequences of the fact that so much contemporary science is collaborative. That is, I want to investigate what collaboration means for the knowledge that is produced through it. What I will end up arguing is that there are a number of senses in which much contemporary scientific knowledge is collective knowledge. Often, groups, and not just individuals, have knowledge.

I start by surveying a number of salient features of scientific knowledge in collaborative settings. I then show how these features support the claim that scientific knowledge is collective knowledge in three different senses. I conclude with a short summary and some closing reflections.

Scientific Knowledge in Collaborative Contexts

Before we look at features of scientific knowledge specific to a collaborative context, we ought to get a better grip on scientific knowledge as such. Throughout this chapter, I rely on a characterization of knowledge that is widely endorsed in epistemology. According to it, knowledge is warranted true belief, where warrant is a general epistemically good-making property that makes the difference between a belief’s being merely true and its constituting knowledge (cf. Plantinga 1993 and Burge 2003 for two different accounts of warrant). If a belief is warranted, that might mean, among other things, that it’s not luckily true when it is true,⁸ that it is reliably produced, or that it is based on good grounds.

Why is scientific knowledge held in such high regard? What sets it apart from non-scientific knowledge? For one thing, it is knowledge produced through scientific research. That is certainly true, but it tells us little about what is supposed to be good about scientific knowledge. A better starting point is the thought that scientific knowledge is high-grade knowledge, that is, knowledge that satisfies demanding epistemic standards and that, as a result, is highly reliable, robust, or well-established. There are different ways of understanding this general idea (De Ridder 2018). One tempting but mistaken reading is to think that scientific knowledge is the most certain knowledge that we have. That is false, however. Quantum mechanics or the standard model of particle physics are among the most firmly established results of science, but my knowledge that there is coffee in the cup in front of me or that 2 + 2 = 4 is even more certain. That is because, unlike scientific knowledge, such humdrum beliefs are not based on complex inferences from observations mediated by instruments and technology. Hence, they do not suffer from the inevitable uncertainties that attach to such inferences.

A better way to think about this issue is that scientific knowledge is the most reliable knowledge we have about certain subject matters – to wit, the underlying nature of reality and human beings. Science is our most reliable means for discovering non-obvious or non-superficial factual truths about the universe and ourselves.⁹ Non-scientific methods for forming beliefs about such matters tend to be unreliable. Just consider the many false beliefs that people have had throughout the ages about the origin and age of the universe, about the ultimate constituents of reality, human nature, and so forth. Although not infallible, science is significantly more reliable in the long run when it comes to such matters. At the same time, we shouldn’t overestimate how reliable science is. There is, by now, solid evidence that more than half of published scientific results in the biomedical sciences, psychology, neuroscience, and the social sciences are false (Ioannidis 2005; Harris 2017). Such unreliable published results are not scientific knowledge in the sense in which I am using that phrase here, because they lack appropriate warrant or are false.¹⁰

That scientific knowledge is high-grade knowledge also means that scientific knowers ought to be able to justify knowledge claims (Gerken 2015). Having scientific knowledge requires not only that scientific beliefs are produced by reliable methods, scientists should also understand these methods and be able to explain them, providing reasons for thinking that their knowledge claims are true. If a biologist claims to know what the key drivers of random genetic mutation are, she ought to be able to explain herself, provide evidence, or point to literature where evidence is presented. Having scientific knowledge thus requires having access to and grasping the reasons why your beliefs are likely to be true.¹¹ This is why consulting an oracle that reports true claims with perfect reliability would never produce scientific knowledge.

Let’s shift our attention to features of collaborative scientific knowledge next. First, most scientific knowledge claims nowadays are credited to groups rather than individuals. Multi-authored publications have become the default. When you trace the original source of a scientific knowledge claim, it will often be a group. You could try to downplay the significance of this by pointing out that publications typically have a single designated corresponding author and that this individual is the real knowing subject, while the others are merely auxiliary. That’s simply false, however. Corresponding authorships don’t imply anything about credit or contribution; the choice for who fills that role can be purely pragmatic. Alternatively, you might suggest that the principal investigator (PI) for a research project or team bears ultimate responsibility for the knowledge produced and should thus be credited as the primary knower. But this, too, is wrong. While PIs bear certain sorts of ultimate responsibility – financial, managerial, intellectual ownership of a project’s key ideas – it’s not the case that the PIs have an exclusive responsibility to keep track of all the epistemic commitments and outputs in projects. Doing so is often impossible for any single agent, especially in large or multi-disciplinary projects. Hence, the point that many scientific knowledge claims are credited to groups stands.

Second, the reality behind multi-authored papers is collaborative work. Scientists work together on research projects in smaller or larger teams; sometimes with teams in other departments or institutions. They divide up the work amongst each other, according to expertise, skills, and availability. To take a toy example, scientist A might be responsible for finding and reviewing relevant literature; B for designing the survey and making sure it uses validated instruments; C for recruiting a sufficiently large and representative sample of test subjects; D for the online survey system; E for processing the results when they come in and getting them in the right data format; and F for carrying out appropriate statistical analyses. One or more of these people might write a first draft of a paper, others might contribute specific sections and paragraphs, or revise the first draft. Progress will be discussed so that everyone stays abreast of the project as a whole, tasks might be reassigned if needed, and sometimes new people are added to the team or team members leave. All of these tasks are necessary and make real and significant contributions to the project as a whole. It’s not as if some of these activities are easily dispensable or unimportant; they are all necessary and must be carried out well if the project is to produce scientific knowledge. Even though specific team members might be more involved, bear greater responsibility, or grasp the intellectual underpinnings of the project better than others, much research is a genuine team effort. The earlier example is relatively simple, but, to the extent that projects become larger and multi-disciplinary or interdisciplinary, mutual dependence will only become greater and the involvement of multiple researchers even more inevitable.

Third, teamwork is not just an accidental feature of contemporary science, which could easily be reversed.¹² Many questions that scientists are working on are so large and complex that answering them necessitates teamwork. There are two dimensions in which this is true: practical and cognitive.

Teamwork is practically necessary because the work needed to complete a research project is simply too much for any one person to complete on their own. Consider, for example, the Human Genome Project, the purpose of which was to identify and sequence the more than 3 billion (!) chemical units (nucleotides) in human DNA. This massively collaborative project took about 15 years from inception to completion (1985–2000) and involved research teams from twenty universities in the United States, Europe, and Asia. The sheer amount of work required to complete it necessitated the collaborative set-up. Even if one individual had possessed all the relevant expertise and skills, it would have been impossible for her to complete all this work within one lifetime. This project is an extreme example, but many projects are too big for individuals to carry out on their own.¹³

Next, teamwork is often cognitively necessary. Many research projects require expertise, skills, and background knowledge from different disciplines or sub-disciplines. Individuals usually don’t have formal training and experience in all the relevant disciplines or sub-disciplines and it is impossible for them to make up for this on the fly. Interdisciplinary projects are natural examples of this, but monodisciplinary projects c...