Is science neutral and impartial?

In a Nutshall: Science is never truly neutral as it is value laden - bias and values are embedded in the Scientific process. Introduction The ideal of scientific neutrality – the concept that research operates completely free from bias, social influences, or personal values – is a foundational principle. But can science truly live up to this expectation? Examining this question critically reveals how complex the relationship between science, values, and culture can be and its biased and value laden nature. A Thought Experiment: Race and Intelligence To illustrate the intertwining of science and values, let's consider a hypothetical study investigating whether Asians are intrinsically smarter than whites and blacks. In dissecting this scenario, we expose potential flaws in this study's approach: Flawed Constructs: Racial categories like "black," "white," and "Asian" are subjective social constructs. The diverse individuals grouped within each category, along with the arbitrariness of assigning individuals to these groups, calls the basis of this research into question. Problematic Variables: Measuring "intelligence" is problematic. Standardized IQ tests may reflect the dominant culture’s assumptions, potentially disadvantaging those from different backgrounds. They offer a narrow focus on analytical intelligence, not broader areas like emotional or creative intelligence. Unrealistic Conditions: Ensuring "ceteris paribus," or all other things being equal, is almost impossible in social research. Racial discrimination, socioeconomic inequalities, and varied life experiences render controlled comparisons unreliable. Questionable Analysis: What difference in IQ scores should be classified as "meaningful?" 5%? 25%? This is an inherently subjective judgment. Additionally, any statistical tests assume the study samples flawlessly represent their broader racial 'populations' –a deeply flawed assumption. Predetermined Conclusion Research often tends to confirm the investigator's existing biases. In this case, the flawed design and analysis will likely produce data misinterpreted as a confirmation of racial inequalities in intelligence. Analysis of Science's Alleged Neutrality and Impartiality I wish it were the case but it is not. Let's imagine we wanted to scientifically investigate whether Asians were smarter than whites and blacks to illustrate the point. Values, politics and culture will appear in five areas of the "scientific method" adopted - hypotheses, variables, conditions, testing and conclusion. Let's consider them one by one. 1. The hypotheses contains the terms "blacks," "whites," and "Asians" which are just constructs themselves, categories without any reality. For example, is an Indian man an "Asian" in the same way a Chinese is? Or a Nigerian "black" and an African-American is? What about someone who is half of either? Is "sharing" DNA the bar for belonging to a "group," when in fact the group itself is something we have constructed? If "sharing DNA" is the bar, then of course humans share more DNA with primates so our categories do mean much if anything. Assigning people to groups we are judging is a political and cultural act. 2. The second place values will intervene is in our choice of variables. How are we to operationalize "intelligence"? We could take the easy way out and reach for IQ as most researchers do. However IQ is not a value-free measure. It is loaded with assumptions. It measures one kind of analytical intelligence not creative, ethical or synthetic in a deterministic and rigid way: with "questions" for which there are right "answers." In life, most questions have no fixed sets of answers. Most obviously, IQ will test for "intelligence" in a socially-predetermined way - the kind of skills a society prizes and thus its most privileged will already tend to have. 3. How do we establish a ceterus paribus condition - to make all conditions equal if we wish to measure intellect. Can we find a black or asian child who has been brought up just the same as a white one? Can we subtract human life itself from our "experiment" where we find a population of children who have never suffered racism, trauma, bigotry, or mistreatment? But if we cannot find one, then we cannot really establish a ceteris paribus condition. The best we can assume is children who live in similar neighborhoods have had similar lives and set up proxy variables. Political and cultureal values have entered our assumption . 4. Now we come to the thorny question of hypothesis testing. We will take our IQ scores and use various kinds of statistical tests to see whether the differences among the groups are significant enough to count as meaningful. But all this is bound by values, politics and culture, too. Is a difference of "five percent" to count as "smarter"? Ten percent? Perhaps twenty five percent will count as very smart. Again, we are making cultural judgments. But there is a deeper problem still. These tests assume our samples represent their "populations." But those populations are social constructs in the purest sense: societies that human beings have built. There is no correspondence between sample and population - unless we say, white people build this kind of society and Asians that kind. But if we do that we have assumed our very own conclusion. So there is no truth to be inferred from our experiment. 5. Never mind. We write up our conclusion. The "science" we have done has invalid hypotheses, variables, conditions and tests confirming our own biases. Asians are smarter than whites who are smarter than blacks. Our categories, variables, conditions and now our tests, are all loaded with values, politics, assumptions. We cannot escape culture. Culture is woven into every aspect of the scientific endeavour, from thought to inference to conclusion. Our experiment simply repeats our values. Given the extreme example, it does however show categories, variables, conditions and tests contain cultural assumptions, values and judgments - regardless of what we are investigating, our biases will intrude. The experiment proves nothing, as it was designed to. And that in itself proves that scientific "proof" is not what is often thought to be. It is not confirmation or even falsifiability. It is temporary disconfirmation of a possibility - but never absolutely and only with a given margin of error. But every step of that process is culturally bound - from what is tested, to how, to under what conditions it is disconfirmed, to what counts as a margin and what counts as an error. All that is ultimately defined as "proof." But proof of this sort is not a hard thing at best a temporary, uncertain thing otherwise further scientific progress itself would fail to be possible. Science is a human creation riddled with uncertainties, values and assumptions. The Limits of "Proof" This thought experiment reveals that every step of scientific inquiry – from the initial question to data collection, analysis, and interpretation – can be susceptible to bias. Scientific "proof" isn't absolute, often instead offering temporary disconfirmation within a specified margin of error, itself determined by cultural values. Without absolute proof, scientific progress depends on continually revisiting findings in light of emerging knowledge. Scholarly Perspectives: Historians, Philosophers, and the Question of Scientific Neutrality Your argument convincingly illustrates the potential for bias and cultural values to influence scientific inquiry. The question of whether science can ever be truly neutral or impartial is a longstanding debate within the philosophy of science, history of science, and science and technology studies. Here's a look at some contrasting perspectives: Perspectives Challenging Absolute Neutrality Thomas Kuhn (Historian and Philosopher of Science): Kuhn's influential work, The Structure of Scientific Revolutions, argued that science operates within paradigms - established frameworks for understanding phenomena. These paradigms can shape what questions get asked, what methods are deemed valid, and how data is interpreted. Paradigm shifts necessitate revising older models of 'truth'. "The scientist...cannot fully anticipate discoveries or inventions that will ultimately undermine the assumptions he relies on in order to practice his trade.” (Kuhn, Thomas. The Structure of Scientific Revolutions) Sandra Harding (Feminist Philosopher of Science): Harding contends that dominant social values inevitably infuse scientific endeavors. She explores how marginalized perspectives can offer valuable critiques of mainstream research methods, contributing to stronger objectivity (as a collective, corrective process) rather than pure, individual neutrality. "The task is not to get the objectivity question right so we can make bias go away; it is to use our knowledge of how scientific inquiry actually works ... to design better institutions and practices.” (Harding, Sandra. Objectivity and Diversity) Defending the Scientific Method Karl Popper (Philosopher of Science): Popper emphasized the importance of falsifiability. He argued that while truly 'proving' theories impossible, rigorous empirical testing designed to challenge hypotheses helps weed out incorrect explanations. In his view, this systematic skepticism is inherent to science. "We do not know: we can only guess. And our guesses are guided by the unscientific, the metaphysical....faith in laws, in regularities which we can uncover -- discover." (Popper, Karl. The Logic of Scientific Discovery) Steven Pinker (Cognitive Scientist): Pinker defends science as humanity's most reliable avenue for uncovering truths about the natural world. While acknowledging historical misuse of science, he advocates for appreciating the scientific method's potential in addressing social problems and promoting informed decision-making. "The moral worldview of any scientifically literate person...requires a radical break from traditional religious beliefs." (Pinker, Steven. Enlightenment Now) FAQs If science isn't neutral, is it useless? Absolutely not! While its results must be interpreted with an understanding of potential biases, science remains a powerful tool for gaining knowledge, provided we remain critical of methodologies and recognize limitations. How can we make science more objective? Diversity among scientists, transparency about research methods, acknowledging researchers' perspectives, and encouraging critical debate all promote fairer, less biased outcomes. Misconceptions Science and technology are purely objective endeavors. While aiming for objectivity, they're influenced by social values, the priorities of research funding, and personal motivations of those involved. Scientists themselves are always unbiased. Like anyone, scientists have worldviews that inevitably seep into their work. This must be addressed through peer review, and scrutiny. Conclusion Science exists within a broader human context. Recognizing possible biases isn't about denigrating science, but acknowledging its potential imperfections. Understanding this is crucial for responsibly interpreting scientific findings and making informed decisions based upon them. References: Kuhn, Thomas. The Structure of Scientific Revolutions. University of Chicago Press, 1962. Harding, Sandra. Objectivity and Diversity. University of Chicago Press, 2015. Popper, Karl. The Logic of Scientific Discovery. Routledge, 1959. Pinker, Steven. Enlightenment Now. Viking, 2018.