Embracing Value-Laden Science:
A New Paradigm for a Complex World
In an age of rapid scientific advancement, it has become increasingly important to reevaluate our approach to science and recognise the inherent value-laden nature of this pursuit. While the ideal of value-free, objective science has long been a guiding principle, it is time to acknowledge that science cannot escape its entanglement with societal values and perspectives. It’s time to learn to live with value-laden science and why this shift in mindset is crucial for addressing the complex challenges of our world.
Scientists often operate under the assumption that the weight of empirical evidence should exclusively determine our beliefs and theories. However, it’s time to confront a fundamental reality: what scientists accept is not solely determined by the evidence at hand; it is, in fact, underdetermined. Underdetermination is ‘the simple idea that the evidence available to us at a given time may be insufficient to determine what beliefs we should hold in response to it.’ This underdetermination arises from the inherent complexity of scientific inquiry, where multiple hypotheses and theories can be compatible with the available evidence without compelling us to adopt any particular standpoint.
Why does this underdetermination persist? The crux of the matter lies in the nature of scientific inquiry. To predict and explain observed phenomena, scientists must introduce a myriad of auxiliary assumptions into their frameworks. These assumptions, however, are often uncertain, creating room for choice and interpretation. This inherent uncertainty gives scientists the flexibility to accommodate evidence without outright rejecting their theories, even in cases where the evidence appears to clash with their preconceived notions. Conversely, when the evidence aligns with a given theory, scientists still retain the autonomy to opt for an alternative explanation.
we must decide which theories to accept, especially in practical contexts where we need to apply scientific knowledge.
In essence, what we accept within the realm of science is a delicate equilibrium between data and interpretation. While evidence provides the framework for our understanding, it is not the sole determinant of our scientific convictions. This nuanced interplay between data and interpretation creates a compelling paradox: we must decide which theories to accept, especially in practical contexts where we need to apply scientific knowledge. In this decision-making process, non-epistemic values come into play, filling the void left by the inherent underdetermination of scientific evidence. The question that remains is which values ought to enter.
History reveals that the concept of value neutrality in science is not as pure as we might believe. Rather, it was adopted, in part, as a means for academia to carve out its own territory, free from external interference, and also to serve the political agendas of governments. It emerged from a backdrop of value-laden ideals that promoted specific governance systems and perspectives on research priorities. This shift can perhaps be best epitomised by the value placed upon scientific objectivity during the cold war.
if we scrutinise science’s track record, it becomes evident that it has not been successful in adequately critiquing itself on crucial issues.
Additionally, the social landscape of science has evolved significantly since the post-World War Two era. Sandra Harding suggests that science is now more democratic, with diversified sources of funding that make the pursuit of a value-free ideal increasingly challenging. Moreover, if we scrutinise science’s track record, it becomes evident that it has not been successful in adequately critiquing itself on crucial issues. This has led to biases in research that have far-reaching consequences for society. I expand on these consequences in the context of mental illness below.
In response to these challenges, there is a growing consensus among philosophers of science for the adoption of a new, pluralistic set of values in science. This approach recognises that a value-free science carries political implications and acknowledges that science should be more inclusive and responsive to the problematic biases that have persisted throughout its history. Importantly, Harding recognises that terms like ‘pluralism’ are never value-free either.
According to Harding, we can maintain our commitment to empirical evidence and the willingness to respond to criticism while simultaneously fostering a more diversified scientific landscape. This diversification aims to enhance objectivity by embracing a broader range of perspectives, thereby moving science closer to its ideals of unbiased inquiry and equitable outcomes.
Consider the field of medical research, there has been a historical lack of diversity in clinical trials, particularly regarding the representation of minority populations. For example, studies investigating the efficacy and safety of certain medications or treatments have often been conducted primarily on white, male participants, leading to gaps in knowledge about how these interventions affect other demographic groups. Recognising this issue, researchers and policymakers have increasingly advocated for the diversification of clinical trial participants to ensure that findings are applicable to a broader range of individuals. Thus, reducing biases inherent in homogenous study populations.
Larry Laudon provides a counterpoint to the idea of underdetermination, suggesting that it may not be as substantial as it initially appears.
Larry Laudon provides a counterpoint to the idea of underdetermination, suggesting that it may not be as substantial as it initially appears. Underdetermination, he argues, essentially means that we have multiple hypotheses that are logically compatible with the available data. However, Loudon emphasises that the decision of which theory to accept extends beyond mere logic. It ventures into the realm of ampliative rules, which are rules that go beyond logic and offer a more substantive perspective.
To illustrate this, consider the hypothesis that suggests mental health issues stem primarily from unresolved conflicts rooted in childhood experiences (mommy issues). This hypothesis may seem superficially compelling, as childhood experiences often shape psychological patterns in adulthood. However, a more psychoanalytical perspective, grounded in the principles of Freudian theory, provides a much deeper understanding of mental health challenges. This conventional approach delves into factors such as unconscious drives, defense mechanisms, and the dynamics of the id, ego, and superego.
The critical distinction between these two hypotheses lies in the assumptions that accompany them. Ampliative rules come into play here. They serve as the extra principles that help us make informed decisions about which theory to accept. These rules guide us, indicating which theories are more reasonable, grounded, and likely to produce meaningful predictions.
In essence, Loudon contends that when these ampliative principles are considered, the realm of scientific inquiry narrows, leaving little room for non-epistemic values. The decision of which theory to accept becomes more reliant on objective, substantive principles rather than subjective values or arbitrary inclinations. This perspective calls for a more robust and methodical approach to theory selection in science, guided by principles that help us distinguish between mere compatibility with data and the genuine explanatory power of a theory.
In response to Loudon’s perspective, Harding and Longino might emphasise the presence of ampliative rules within scientific decision-making. These take the form of the auxiliary assumptions mentioned earlier, characterised by their inherent uncertainty and the potential for manipulation to align with desired outcomes. Harding and Longino would raise the central concern that using ampliative rules, although influential, may not provide an unequivocal solution. These rules introduce additional assumptions into the scientific decision-making process, leading to questions about their validity and potential for bias. As a result, a critical challenge emerges: Navigating the intricate balance between empirical objectivity and the subjective influence introduced by ampliative rules.
To exemplify this, consider the significant debate in the field of psychiatry regarding the causes of mental illness and how to treat it in the 19th century. On one side, there were proponents of a more mechanistic and deterministic view of mental illness. This view emphasised that mental disorders were primarily due to physical factors, such as imbalances in bodily humours or structural abnormalities in the brain. Treatments were often based on the idea of restoring physical balance, and asylums were designed to isolate and control patients. On the other side, there were advocates for a more holistic and psychologically informed understanding of mental illness. This view recognised that mental disorders could result from a complex interplay of psychological, social, and environmental factors. Early pioneers in psychiatry advocated for the moral treatment of patients, emphasising the importance of environmental conditions and compassionate care.
power is pivotal in determining which rules and assumptions gain prominence and acceptance in scientific debates and theory selection.
The choice between these two contrasting views on mental illness was not solely based on empirical data but was deeply influenced by ampliative assumptions, societal norms, and the prevailing medical paradigms of the time. This historical example highlights how not only discourse and social context but also the historically changeable conditions determine the possibility of understanding a body of knowledge (in our context, the treatment of mental illness) and further emphasises that scientific knowledge is permanently embedded in a social context. In other words, Loudon’s assertion of ampliative rules and the subsequent scientific decision-making process are inherently influenced by power dynamics. This is because power is pivotal in determining which rules and assumptions gain prominence and acceptance in scientific debates and theory selection.
Modern science, specifically psychology, is inherently value-laden, challenging the ideal of value-free objectivity. Underdetermination underscores that empirical evidence alone doesn’t dictate beliefs due to the interplay of data and interpretation. Historical context reveals the influence of societal values on scientific neutrality. Addressing biases in research calls for embracing pluralistic values. Larry Loudon’s ampliative rules offer a methodical approach but can’t eliminate the impact of power dynamics. Scientific knowledge remains embedded in social contexts, necessitating a balanced approach that combines empirical objectivity with the recognition of power’s role in shaping scientific decision-making.
References:
Harding, Sandra. “A Philosophy of Science for Us Today? A Response to Fellows and Richardson.” Philosophical studies 174, no. 7 (2017): 1829–38. https://doi.org/10.1007/s11098-016-0836-7.
— — — . “Précis of Objectivity and Diversity: Another Logic of Scientific Research.” Philosophical studies 174, no. 7 (2017): 1801–06. https://doi.org/10.1007/s11098-016-0835-8.
Laudan, Larry. “Demystifying Underdetermination.” Scientific Theories 14 (1990). https://conservancy.umn.edu/bitstream/handle/11299/185722/14_12Laudan.pdf?sequence=1&isAllowed=y.
Longino, Helen E. “How Can Values Be Good for Science?”. Chap. 7 In Science, Values, and Objectivity, edited by Peter K. Machamer and Gereon Wolters, 127–42. Pittsburgh: University of Pittsburgh Press, 2004.
McHoul, Alec. A Foucault Primer. 1 ed. United Kingdom: Routledge, 2015. doi:10.4324/9780203501122. https://ebookcentral.proquest.com/lib/uql/reader.action?docID=178405.
Peters, Rik. “The Episteme and the Historical a Priori: On Foucault’s Archaeological Method.” Journal of French and Francophone Philosophy 29, no. 1–2 (2021): 109–29. https://doi.org/10.5195/jffp.2021.963.
Stanford, Kyle. Underdetermination of Scientific Theory. The Stanford Encyclopedia of Philosophy. Edited by Edward N. Zalta and Uri Nodelman. Summer 2023 ed. Edited by Edward N. Zalta and Uri Nodelman. Stanford: Metaphysics Research Lab, Stanford University, 2023. https://plato.stanford.edu/entries/scientific-underdetermination/.
Harry Shakespeare-Davies is a final year PPE student, aspiring academic, and Statecraft VP.
Thanks to Daniel Quill and Luca Bisogni for editing this submission.
