It is a high paced world. Nearly too rapidly. One day you are in a lecture on the old sociological theory. The following, you see AI composing papers, foreseeing election outcomes, and even reading emotions superior to some individuals. It’s strange. Exciting. A touch scary also. We nowadays live in a so-called post-AI world, where artificial intelligence is not only on the science shelves or board of directors. It is here. At home. In our cell phones. Oh, even in our own schools and in our own studies. and what do you think? Even social sciences, which we used to believe are absolutely human sciences are being drawn into this vortex. Now, what does that imply? How does a discipline such as sociology, psychology, political science or anthropology, which relies on the experience of human beings, exist when machines are becoming trained on human behavior with a scale greater than human beings? So there is the big question. In this blog I will bring you up to date on where we are, what is already changing and where we may be moving. there are no fixed forms. Nothing too unnecessarily technical. Only a semblance discussion on exactly how the use of AI is making the work of social sciences difficult, better, and with ability of changing its role. Since the future is not knocking at the door as it were. It already exists. and these social sciences? They either change. Or they are left alone.

Understanding the Post-AI World

What then is a post-AI world? It is no longer a far sci-fi thing. Nor is it about robot masters, or socialism based entirely on robots running the world (or at least not yet). It is about the world where artificial intelligence is no longer the tool that we operate, rather it is an environment that communicates, learns, and mold us in the way we live, learn, and behave. Every day. Quietly. Constantly. Here is an illustration. Just think about a young student of political science. She is conducting a research on trends of voting in her thesis. Ten years ago she would be dead in survey forms and dusty reports. Today? She feeds live Twitter data on a machine learning model. Seeing it splatter voter feeling analysis in a few seconds. Accurate? Maybe. Impressive? Definitely. That is just the start.  Artificial intelligence is getting to know how people behave. Millions of people. Every second. It monitors our clicks. What is forgotten. What we are afraid of. That which we almost, but not quite, dared to write. It can detect patterns where human beings cannot detect. Biases too. Sure, at times it goes wrong. But what is frightening is? It does not always. That is the world we now are in. Learning does not just happen in the tech companies. It is its algorithms shaking up political campaigns, affecting the development of policy, recommending who to hire or whether they should get bail. That’s real. It’s happening. And what about the social scientists? And here we are smack in the center of it. And that is the twist: post-AI is not only about people being pushed aside by a machine. It is about learning machines out of people. And next--changing them. We scroll. It learns. We act. It adjusts. The fringe between an observer and a participant? It’s blurring. Fast. It is not just a technological revolution. It is a social one. And when you are in the business of studying society; their behaviours, norms, cultures, you cannot pass on AI. It has become a landscape feature. Are you prepared or not. Therefore, when we talk of a post-AI world, what we actually refer about is as follows: A world where we are not having an AI which is merely having an impact on the systems. It is playing on souls. What about the social scientists? Then everything is different.

How AI Is Already Influencing Social Sciences

It is not just arriving. It's here. Already transforming things. It is very likely you did not recognize it even at first. That is how it goes the way with most of it. Quietly. You are reading a journal article in migration pattern. What of the data? It did not come by door-to-door interviews.

It was the result of Google searches, location detection and the use of predictive models powered by AI. The author? Perhaps it did not code the algorithm. They applied its results but they did not use it. Trusted them. and that confidence? That’s new. The social scientist today is using computers that can read thousands of tweets within a period of seconds.

Detect sentiment. Idenforce hate speech. Visualize real time conversational flows. What about ten years ago? That would have cost teams of researchers and weeks--if not months. Now? Click. Done. Suppose you are a sociologist who wants to undertake an examination of urban loneliness. Previously, you would most likely pamper yourself in coffee shops. Talk with the world. Write a questionnaire. Sensitive, cautious, homo.

Today? Analyzing Instagram captions and location tags that show up in pictures in time, AI would be able to determine who is single, who is lying to themselves, and, of course, who is... just acting in front of the camera. And no it is not always right. But it is too true very often to be frightening. The same thing is being observed by psychologists. Emotional analysis.

Detection of voice tones. Therapy apps. Artificial intelligence struggling with emotions. And other times doing better than the therapist. Ouch (ouch, a little bit). The AI is developed to write predictive models that will predict and forecast the behavior of voters in political science.

Not even by geography or party--but to the point of the mood-swings of individuals. It understands what you are passionate about ahead of you. On the basis of what you have liked. Shared. Skimmed. Paused on. Anthropologists? They are using machine learning to crack ancient languages. Fragmenting texts and feeding it to an AI model and receiving answers in a few seconds. Years of human-guesswork it would have cost.

Artificial intelligence does not tire. Doesn’t blink. That is not everything good, though. The tools do not always interpret correctly. They interpret sarcastic speech as sincerity. They perceive patterns that cannot be found. They bear the prejudice of man-kind, only quicker, chillier. Nevertheless we continue to use them. Since they are efficient. And because we do not want to lag behind. The thing is that AI is not only supplementing the research in social science.

It is remodeling it. A shift with which we approach questions. The way of how we collect data. Valid evidence is what we believe. The things we believe as true. That does not represent a minor transformation. It is a complete remodeling of the handbook of social science. And masses of us? As we are doing it, we are rewriting it. With opened eyes. Sometimes confused. But curious. Very curious.

Opportunities for Social Scientists

The world is evolving. Fast. What about the social scientists? They are the middle of the way of it, whether they want to or not. They used to study communities, behaviors, beliefs some time ago. Now? They study algorithms. Digital footprints. AI-generated opinions. It’s wild. But it is real. And it just gets worse.

 

To be frank. Social sciences were thought to be forgotten because of AI. Empathy is something that can supposedly be replaced by a machine. Replace culture. Human intuition. It seems that it is the reverse though. AI brought new windows. Hustled them open doors.

 

The profession of social scientist today is not merely to study a society it is also to be involved in the creation of the way AI perceives it. To give an example, when you are answered by a chat bot, someone under that system learnt language inflection, cultural gestures, tonal expression. A person like as… you.

The demand? It’s growing. Off tech companies to governments. They all are rushing to make AI more human. Less robotic. Who can help guide them better than a person who really knows how human beings behave?

Picture this: a group working at a startup in Silicon Valley to develop a biased-free AI hiring tool. They invite a sociologist. She is not a programmer. Does not do Python. She knows discrimination in institutions. Power structures. The mechanism of microaggressions. She prevents the product to be one more moral catastrophe. Simple as such or a digital anthropologist and urban developers. Applying AI to simulate the potential impact that a new metro line can have on neighborhood identity. Conservation and development. AI is the middleman.

The globe requires translators. Not only of wording--of scene, of morality, of experience. And there comes in social scientists. They are not expected to be tech savvy. However, they need to be inquisitive. Flexible. Prepared to change their millennium old inquiries to new instruments.

Of course the learning curve is steep. The questions are, what are the payoffs? Huge. Consulting roles. Policy influence. Soulful data analysis. Until even AIs design positions. The so-called human-centered AI that everyone is speaking about? Fine, that is your playground.

However, take this twist: it is not known to many social scientists. They feel left alone. He feels threatened by the geek speak. Understandable. But unnecessary. Machines know nothing about meaning because at the end of the day, that is what matters. Neither as you. They are not able to say, why does it matter? You can.

Don t stay out. The world is taking a new twist. The biggest opportunity of social impact may no longer be in dusty archives, or town halls survey. It may be camouflaged in data sets. In chatbots. By the fact that AI mediates truth. Enter. Influence it. The opportunities? They’re waiting. 

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