The science of you, the science of us

How to make sense of the human science, its avenues of learning, and its growing level of precision

Very often, the social science(s) get massively confusing and there isn’t much work done by means of introduction. As a result – most of us feel very lost. What are the social sciences? Is it even a science? Are they the same as the humanities? Where do we begin? What do these words “society”, “development”, “poverty” mean? Is it all just philosophy? Which philosophical view is most coherent and logical? … and so on. While philosophy (coming from its Greek roots “philosophia”, or the love of knowledge) is what all science emerged from, the social science’s intention is to be that – a science. To observe and record patterns and regularities. To determine background context faithfully and to extend human insight.

The complexity of social thought, our inability to frame a universal objective language to discuss human society (such as how mathematics is used in physics), and the biases generated by our lived experiences come together to create widespread confusion about the social sciences. In writing this article, I want to share with you my perspective. I will present a unified view of the social science, and how it works today.

Before continuing further, I do wish to share a caveat: theorizing (or even thinking for that matter) is an emotionally guided process, and emotional self-awareness is the key to accounting for our own feelings amidst our narratives. With that in mind, I want to let you know that I'm writing here with a sense of wonder...I feel that no matter how close we get to theorizing and encapsulating human experiences and social patterns in objective, measurable, and predictable terms, we will never be able to capture the unbridled essence of humanity. Each of us is fated to capture only a glimpse of our reality in this world.

The human unit

At its foundation lies the study of the individual. Disciplines like neuroscience and psychology attempt to solve the puzzle of how humans tick. How our memories work. What makes us happy or sad. How types of individuals vary in personality and behavior, and conversely how we are all so very similar in behavior. In what motivates us, and what causes us grief. These are a few of the sense-making concerns that the social science puzzles over. At this level of the human unit, we are trying to better observe and understand ourselves as singular human beings. But no human's a lone island. We live together, often playing our part in influencing and being influenced by the different communities we belong to, whether they be our families, schools, occupations, close friends, and other online and offline communities... how do we function among groups of people, and how do groups themselves function? To visualize these questions that are explosively complex, we now turn to the collective mesoscale.

The collective mesoscale

Collective behavior impacts individuals: I know how to use chopsticks now because of Hong Kong’s high table dinner rituals at my university, and I'll probably download WeChat soon due to peer pressure. After all, everyone in Hong Kong is using it. Likewise, individual(s) impact collective behavior. For instance, we are often moved by a rousing speech by a personality like Steve Jobs, or inspired by that one discerning friend to change our bubble tea preferences. The mesoscale is where human behavior gets wonderfully messy, and as greedy scientists, we want to make sense of it all. Whether the individual disciplines are called economics, social psychology, marketing, or anything else, the aim is usually similar: pick a context, and observe how networks of people behave and do different/similar things within that context. Yield generalizable insights. Refine the process during the next experiment, and so on...

As a marketer, I'm trying to sell you an iPhone by appealing to your desires as a high-income, aspirational consumer. As a social psychologist, I could be observing whether you are more/less accepting of minorities and why. As a sociologist, I could analyze how and why your workplace language and behavior changes around Chinese managers and executives, as opposed to British managers due to their differing cultural expectations. While disciplines within the social science often diverge, co-interact and/or use different concepts/terms, what is simple to notice is the scale they operate at. At the collective mesoscale, culture and networks of individuals all come together in different contexts, and the social science studies the "what", "why", and "how" of it all. A good social scientist can cut across subject disciplines. They find the explanation that harmonizes the most with the question posed to them. For instance, if I was asked "how rich/poor are people in India?", I would use Economics to figure out the quantum of India's national income per person and then factor in the population-level income inequality. This kind of resource-based analysis is what Economics is good at. I would then use techniques in Sociology to elaborate on how much those numbers reflect the cultural realities of living in India. Observing and analyzing sociocultural experiences is a task the discipline of Sociology is more attuned to performing. By using these two disciplines together, I gain a coherent answer to this research question. In the collective mesoscale, one is usually attempting to solve a particular question, often involving group(s) of people.

In social science, more specific research questions are answered with greater clarity. But for some researchers, that specific clarity is not enough. These researchers are even more ambitious. They want the answers to “everything there is”. At the structural scale, the social science attempts just that.

The structural scale

The word "structure" implies we can't change the answer easily as it is foundational in essence. For instance, one pessimistic observation was pointed out by Stanford historian Walter Scheidel. According to his research, natural disasters and wars are the only things that have ever put a dent on human social and material inequality across all of recorded human history. This begs the question: does the world really resemble a huge game of ‘Monopoly’? The view that inequality is an inevitable function of human society has been lent a great deal of credence in recent years. Thomas Piketty for instance used Economics as his primary discipline: he showed in his book "Capital in the 21st century" how the two World Wars were the major factor in reducing material inequality in the 20th century. This material inequality in global society was otherwise a perpetually growing trend.

Structural answers are aggregated macroscopic pictures. The work of Peter Turchin for instance, attempts to use mathematical models to predict macro-patterns of social order and disorder across recorded human history. In a more contemplative writing style, political theorist Sean McFate predicts the decline of nation-states and the rise of a neomedieval world. It is a deep-rooted instinct of humans to attempt a prediction of the future. We often do this so we can manage the present and evade the worst of what could be.

Studies in biological evolution, mathematics, genetics, and history, and other newer disciplines like network science, are now assisted by large statistical databases and growing banks of data. These disciplines, along with the ones mentioned above, help us ask those questions that are deeply rooted in our intrinsic humanity. Can we ever end inequality and war? What will humanity's evolution look like? What will our possible future be as a species? Thanks to the wealth of aggregated data we now have on the past and the present, we are now able to make headway into these questions. These humanist questions used to be confined to the realm of philosophical speculation as we had no way of testing/devising studies to tackle them. But with the proliferation of big databanks and the sophistication of social scientific creativity, we can study them better now.

However, large timescale predictions have not much relevance to one's daily use. Can we also predict individual and collective behaviour in the here and now?

Solving for “x” when it comes to people

The complexity of social life means it is very difficult to predict human behaviour over shorter timescales. I don't know whether you will buy the latest IPhone or not. That being said, it doesn't take much data to make a rudimentary judgment - if you're an Apple user, you're very likely to stick with them due to your pleasant experiences with Apple's quality and service. This is how Apple users tend to behave. But this might not be a simple stereotypical fact for you, and there might be room still for a different scenario.

How would I know? From your personal information, your Google searches, and by tracking your browsing activity, I'd be able to model you as a customer, and target you with a bespoke advertisement that exaggerates any pains you face. This increases my chances of selling to you the moment you are ready to buy a new phone. I just have to make sure I understand what you desire, and communicate that I have that in abundance in my advertisements. A politician could use the same principles in their campaign advertisements - targeting their opponents’ negatives and framing themselves in accord with their audiences’ desires. Using social insight in an applicative sense is more of an art than a science due to human complexity. But it is an art aided by science, nonetheless. The reason behind why some communications strategists run successful political campaigns consistently (APCO Worldwide, Blue State Digital, etc.) is because they understand this aspect of the social science and are experienced in their craft.

It is often difficult to translate social theory into practice; theories themselves are refined and updated over time and implementing and applying theory is often imperfect (since it is us biased humans that are applying them). But artistic practitioners are often both able and willing to study an environment – testing, tweaking, creating knowledge and solving problems by applying social ideas. These practitioners don’t need to have an academic background, for (almost) every human being is born with an innate social sense and the curiosity to learn. Moreover, academic theorists are often willing to engage and discuss and revise their imperfect findings with a wider audience. The book “Influence” (1984) by psychologist Robert Cialdini is an example of an early book theorizing on psychosocial influence – which became a go-to book for marketing professionals worldwide. His newer book “Pre-suasion” (2016) reads like an updated field manual, building on previous work. Cialdini was one of a team of behavioural consultants who advised on Barack Obama’s 2012 US Presidential Campaign.

But if I succeed in persuading you to buy into my brand, have I predicted your behavior. Or have I influenced it and changed its course? We’ll get to the answer soon. At present, social science is synergizing with data science. More data means more trends to analyze and more patterns to record. It also increases the nuance with how companies/politicians/institutions understand different customer audiences which helps them create better products/services/social campaigns/political advertisements, etc. These end-products are tailored to harmonize with the audiences’ values and psychosocial backgrounds.

To give an example, it's strange to me how YouTube's algorithm knows me so well: it knows which song to play next on an auto-generated playlist. The song doesn't have to be the perfect match for my mood. It just needs to be good enough to keep me from switching to another website. I am browsing food recipe videos, and I immediately get a Gordon Ramsay ‘Masterclass’ advert which wonderfully holds my attention throughout the ninety seconds. If I was slightly wealthier and staying in my own apartment with a kitchen, I’d have signed up.

While the social science hasn't reached the natural sciences in its level of precision, it's getting scarily close. The marriage of big data with social science insight has increased human predictability. On one hand, it makes our lives far more comfortable as we stay ensconced within a social-virtual ecosystem that harmonizes with our worldview. On the other, this comfort numbs the capacity of our human agency. This cognitive comfort dulls our ability to think critically over time. To answer the question I posed a while ago: when we apply social science insights, the boundary between prediction and influence ceases to exist. This is because the very instant we applied our insight, we also became a factor in influencing the outcome. If I, as a company like APCO Worldwide, predict that a US presidential candidate projected with the labels “tough on China”, “political outsider”, “pragmatic and calm” is likely to be received well by voters, by acting on this insight and running the political campaign, I have also played my part in influencing the outcome. My success or failure would depend on my holistic understanding of the social reality we are living in, right from the language, accent, intonation and body language favored by different political audiences, down to how the audiences favour the dresses the candidates wear in different states of the US. And there are so many more other factors I could test and control for.

Living in human society, we co-create our realities, and the stimulus and the response are married together in our social behaviour. By being observant, we only tease the strands apart to make sense of the patterns in a causal sense, and this pattern-awareness helps us creatively select alternative behaviors. Three years ago, I was addicted to Facebook because the news feed was full of depressing and anxiety-inducing political news. Addicted to anxiety? Yes, I became comfortable with receiving and believing that news due to it being so readily available and familiar to me. I was also contributing to the problem (in my miniscule way) by becoming a part of Facebook’s addictive feedback loop. After all, I was viewing, sharing, and liking anxiety-driven content. Facebook had successfully co-opted me into its ecosystem. After reading Ryan Holiday’s “Trust me I’m lying confessions of a media manipulator”, I understood the nature of the new media landscape better, and promptly quit Facebook. I rejoined two years later, but thankfully I am now more mindful of how each social platform and its content influences my emotional state. This way I am able to engage with the social platform in my own alternative fashion, selecting an alternate set of behavioral patterns. I set a particular timeframe and browse on the site with a set of goals in mind. An example: I tell myself, “You have five minutes: you will search for the Slate article on CV design templates and skim through it, you will wish Yash a happy birthday, and then you will log off.” This time Facebook keeps me as a user within its ecosystem, but the engagement looks different and is atypical to the default lackadaisical way users browse Facebook.

Almost everything we do (liking friends’ and companies’ posts, uploading pictures with location-tags, ordering movie tickets online, etc.) leaves a virtual data-footprint, and this will only become truer as time passes. Our behaviour will become easier and easier to solve for. We therefore need to understand ourselves as much as large social institutions (companies, governments, etc.) understand us. That way, we can save our agency, and create a more vibrant, meaningful life through concerted effort. This isn’t just about critical thinking and self-discipline, because those concepts by themselves won’t work. We need to integrate those concepts with an empathy for the dynamics of the social world. This way we can start solving for “x” for ourselves. To be curious about the social science could be the key that unlocks our true human potential – and creates a mindful and self-reflective future.