Before we prepare ourselves to answer this question, it is imperative to first familiarize ourselves with the terms used in the same. Science Science refers to the systematic and practical study of any aspect of the natural world, by means of observation and/or experiment. During the Renaissance movement, the scientific process evolved into a four-fold process that included observation, recording data, a theory explaining the observed phenomenon and the recorded data, and finally validation of the theory by further experiments.
Based on the subject matter it is concerned with, and also for the sake of this discussion, science can be broadly put into two categories, Natural Science and Social Science. Natural Science Wikipedia defines natural science as “Branch of science concerned with the description, prediction, and understanding of natural phenomena, based on empirical evidence from observation and experimentation.” For validation purpose, there are various methods employed by it. It includes peer review and repeatability of occurrences. It can be further divided into two branches, which are life sciences and physical sciences. But we would not be concerning ourselves with these, as they are out of the scope of this discussion. Social Sciences Social sciences are a field of study related to society and the relationships that individuals inside it share amongst each other. The term social science became popular in the late eighteenth century with knowledge of society being treated as a science as disciplined and systematic methods were applied to study individuals as well as society as a whole and various social institutions.
The methodology used by social scientists may vary. Positivist social scientists use methods that resemble those of natural sciences whereas interpretivist social scientists use social critique or symbolic representation instead of falsifiable theories. With the basic definitions at hand, let’s now look at some things which make the two aforementioned branches of science different. Quantitative vs Qualitative Natural sciences use formal scientific methods, like mathematics and logic, to make sense of the nature around us. It is done by quantifying the knowledge of our environment and the various phenomena through which it manifests itself. Social Sciences also make use of these methods, but they are oriented primarily towards the qualitative rather than the quantitative. This is the reason why the Social sciences are called soft science and the natural sciences, with their emphasis on quantifiable data, are called hard sciences.
Social Research Social research can be divided into two broad categories: quantitative and qualitative. Quantitative design sees social phenomena from statistical point of view and through quantifiable proof and then aims to make valid claims. Qualitative research understands social phenomena via direct observation , communication with subjects,analysis of text and may lay emphasis on subjectiveness instead of generality. It is sometimes referred to as method to get non-numerical data. Public Policy The policy-making process involves a sequence of steps to be followed before implementing the policy. It begins with identification of objectives and declaring the goal. Now, the next step is specification of alternatives, which requires use of both natural and social sciences. Both disciplines are taken into account before moving to evaluating policy alternatives and policy selection. What are facts? The Cambridge English Dictionary defines facts as: “Something that is known to have happened or to exist, especially something for which proof exists, or about which there is information” In simple words, a fact can be stated as something which is consistent with objective reality and evidently proved to be true.
They are the reality, situations, and relations that make some sentence to be true. For example, ‘Law of conservation of energy exists’ because there are facts that make it true. Likewise, statements as ‘5+7=12’ and ‘Visarg is happy’ are true only because there are facts to prove them true, and subsequently, they themselves can be called as facts. In philosophy, the concept of fact is considered in epistemology and ontology. Facts are backed by reality and truth and they provide the actuality to a statement or a sentence. Here, the facts and truth have close relations. In the natural sciences like physics and chemistry, when we refer to facts, we more often than not mean phenomena that are proven to happen repeatedly and predictably. That is, however many times you carry out a scientific experiment or observe some natural event, it is going to result in a known and predictable outcome, inside the bounds of some natural uncertainty. In other words, repeating a certain experiment or observation, while maintaining other factors unchanged gives a predictable, repeating outcome. This forms the basis of theories and concepts in natural sciences. Theories are induced from observing natural phenomena, and future events are subsequently deduced from the existing theories. This interplay of inductive and deductive reasoning forms the backbone of natural sciences.
With the social sciences, however, things get a bit more complicated. Social sciences deal with the study of human society and the existence of various forms of relationships and interactions within them. And human beings, in general, are not as simple as a molecule of benzene or a projectile hurled off a building. We are most frequently driven by our emotions and ideals, not unlike the following theory of notable psychologist Sigmund Freud: “All of a person’s actions are traceable to any of the following two sources: his will to assert dominance over another man, or his desire to command the romantic attention of the opposite sex.” A human may behave differently under the same observing conditions, depending on a multitude of other, uncontrollable factors. With such diverse and volatile subjects under consideration, obtaining results and ‘theories’ in social sciences tilts towards the probabilistic domain, as opposed to the deterministic outcomes in natural sciences. Facts in social science are probabilistic Having said this, we can directly establish a connection between facts and probability. Facts can be considered probabilistic. For natural sciences, where we can determine the exact variables that are the input to the functional model, a fact can correspond to a statement with a probability of one and thus one can exactly predict the outcome of a scientific experiment as it would be a “matter of fact”.
For social sciences, the determination of exact variables is not possible as it concerns itself with the human factor, which relies on emotion and feelings and thus these facts are believed to have a probability anywhere between zero and one, with variations for different kinds of observations obviously. The outcome of a social experiment cannot be exactly predicted, rather we can have a set of possible outcomes. Many experiments like ‘The Big Bell test’ (which was conducted in order to introduce human choices into the field of quantum mechanics) have been conducted to establish a relation between randomness and the volatile and ever-changing human factor. Can they be interrelated? Based on the above discussion, it appears as if experiments in the natural and social sciences are similar; it is only a matter of knowing what variables to input. For example, we earlier stated that a human may behave differently, unpredictably, under the same observing conditions, at different points of time. We can levy this uncertainty onto our lack of knowledge of the infinite variables that lead to this difference of decision. Variables like what kind of external stimuli the person received during that time frame, the action and concentration of different chemicals in his brain, what reaction these chemicals had to the aforementioned external stimuli, his intuition and ideals, etc. that would lead him to behave in the particular way as was observed. An analogy to the above discussion can be given in the natural science domain as well.
The well known French scholar Pierre-Simon Laplace envisioned a concept (known as Laplace's demon) in which he stated that if we know the exact position and momentum of each and every particle present in the universe at any given point of time, we can predict the values of all the variables at any given time in the future. This sounds absurd at first glance, but on deeper thought, comes out as quite a logical approach. The obvious loophole here is the fact that there do not exist any physical means by which to gather all this information. But, hypothetically, if a means like this existed (which Laplace thought of a Demon), we could predict anything and everything going on about the universe. There wouldn’t exist any uncertainties, any probabilities. Everything would be deterministic; in other words, every study and observation would converge towards the domain of natural sciences. This argument forms the crux of this whole discussion. Is it really the lack of information about variables that keeps us from proclaiming social sciences as definitive and deterministic?
Natural vs Social science Both natural and social sciences aren’t exactly definitive, since nothing can measured accurately. Some branches in science like health sciences provide their conclusions by taking majority of the signal collected. So it is safe to say that in natural sciences, the physical sciences are more definitive than life sciences.The argument though, that social science is not as definitive as natural science holds true when looked through proper definition. Simply put, in true definitive sense social sciences has only “facts” and “hypothesis” but not “laws” and “theories”. This is due to the fact that “Laws” and “Theories” take all the events into calculation whereas “Facts” and “Hypothesis” only take singular event into consideration.
The way both the sciences are approached are also different. In natural sciences only scientific method is used but in social along with scientific method social critique and interpretive methods are used which makes it harder for it to be definitive. Moreover in natural sciences no emotional linkage is attached between the researcher and study.
But, as it turns out, even if Laplace’s proverbial demon did exist, he would have a hard time carrying out his thought experiment. The reason for that lies in the ever-increasing entropy of the universe. But to understand what entropy is, we need to wrap our heads around the true meaning of random, something entropy is most commonly associated with. What is Random? When the outcome of an event is uncertain and contains no predictable patterns, we call it random. Now the usage of the word ’random’ itself is quite debatable. We often consider unplanned and unrelated events as random events. For example, consider the event of ‘randomly’ bumping into a friend at a restaurant. This event is, in its true meaning, is not random. It can be easily predicted given sufficient initial information, such as what their taste of food is, their budget, distance of the restaurant from their house, their willingness to go to a restaurant in the first place, etc. But first, what does information fundamentally mean? If we consider every letter of every word of this essay, it’s easy to assume that each of them carries some information. But is the amount of information carried by them the same? If it were to say so then the following image would make no sense whatsoever : (Image credits: SSed from the Veritasium video “What is not random?”) We can read this because we are used to certain patterns in the English language, like a ‘u’ after a ‘q’, an ‘e’ or ‘a’ after ‘th’, an ‘i’ before or after ‘e’, etc. Any random permutation of letters does not make a word.
A completely compressed and distilled piece of information (somewhat like the above picture), which makes no sense by itself, is true randomness. A non-repeating sequence of binary digits in no defined order is random; it is the CPU’s job to interpret it and make sense of the randomness, and thus decode the information it contains. Therefore, if we want to know how much information a system contains, we must calculate how random that system is, and vice versa. This is a theorem stated in the Information Theory given by Claude E. Shannon, that “ Information is directly proportional to randomness.” And, as we’re all well aware, randomness is scientifically referred to as entropy. Coming back to the point, The Second Law of Thermodynamics proclaims the entropy of the universe to be on a constantly increasing curve, as the universe is constantly expanding. This, from our previous discussion, implies that the information in the universe is constantly increasing as we would need more data and statistics to define the new state of universe. But where does this new entropy comes from? Now as per the above definition true randomness should mean nothing. So what is a system which is defined by nothing.
The best answer we have as a scientific community lies in quantum mechanics. The basic particles are defined as probabilities in the quantum theory. This means that one cannot predict the exact position of the electron rather we can only calculate the probability where it is likely to be. This is what we call ‘Heisenberg’s uncertainty principle’. So everytime a quantum measurement is made we have gained information. These quantum events cannot be discarded if we consider the butterfly effect which states “the sensitive dependence on initial conditions in which a small change in one state of a deterministic nonlinear system can result in large differences in a later state”. Now it is very tempting to consider second law as a bane but it is because of this law truly unexpected can occur. So this arguments justify the Human Free Will. (End of my part. Ab Kuch philosophy pel do yaha so it seems that we have approached the problem from both ends of the spectrum )