The Role of Engineers and Big Data in Transforming Sociology and Psychology
At the turn of the 21st century, significant changes occurred in several scientific disciplines, particularly those that study human behavior and society. Sociology, one of the leading social sciences, had long developed methods to analyze social processes. However, it began to lose its standing. This shift was largely driven by the entry of professionals from other fields, such as engineering and data analysis, into the realm of social research. The advent of Big Data and new technologies led engineers and analysts to solve problems previously confined to the domain of sociology—often without realizing it.
Meanwhile, sociologists themselves struggled to adapt to these new conditions. Many remained loyal to outdated methodologies, which led to a decline in the discipline. As a result, a paradox emerged: sociological research could now advance through technology, but sociologists themselves were left on the sidelines. Sociology, focusing on niche topics such as "The Culture of Toilet Use in Rural Yugoslavia," significantly lost its influence.
Simultaneously, similar changes occurred in psychology. Academically trained psychologists face challenges in applying their knowledge in modern workplaces and organizations, while engineers increasingly leverage data analysis techniques to study behavior and emotions. This article explores how engineering methods are displacing traditional approaches in sociology and psychology and the implications of these shifts for both fields and for society.
Problems in Modern Sociology
History and Traditions of Sociology
Sociology, which emerged in the 19th century, established itself as a crucial discipline for analyzing society. Using empirical methods, sociologists sought to identify patterns in human behavior and the structure of social groups. However, in recent decades, sociology has faced new challenges: the world has become digitized, and new methods of data analysis, such as machine learning and Big Data, have surfaced. Most sociologists failed to adapt to these changes and continued relying on outdated methods.
Traditional sociologists often focused on narrow topics, such as "The Culture of Toilet Use in Rural Yugoslavia." While these studies may have scholarly value in certain contexts, they disconnected sociology from pressing social issues. In an era of globalization and digitization, such studies lose relevance compared to larger issues such as migration, voter behavior, and social media interactions.
The Crisis in Methods and Technology
Sociology has always utilized a variety of methods, including both qualitative (interviews, observations) and quantitative (statistics, mass surveys). However, traditional methods like paper-based surveys and telephone interviews have lost their effectiveness in the digital age. Today, data can be collected and analyzed in real time, enabling more precise conclusions and predictions.
The issue is not that sociology does not use quantitative methods; rather, it failed to integrate modern technologies. While new tools such as Big Data and automation could significantly improve sociological research, many sociologists continue to operate using outdated paradigms. This has led to a situation where engineers and data specialists are solving modern social problems while sociologists remain on the periphery.
Similar Trends in Psychology
Challenges for Classical Psychology
Psychology also has a rich history grounded in years of empirical research. Traditional methods, such as self-reports and personality tests, have long been used to assess emotional states and mental traits. However, these methods do not always capture real human behavior and often depend on the subjectivity of the respondents.
With the emergence of new technologies, it became possible to analyze human behavior and emotions in real time. For example, by using digital traces left in social networks and mobile applications, researchers can examine emotional states and cognitive processes, greatly expanding the scope of psychological research.
Engineers and New Tools in Psychology
Engineers and analysts, using machine learning algorithms and data analysis, offer more precise and faster methods for studying the human psyche. They collect data in real time, analyzing people’s behavior on social media and even physiological reactions through biometric sensors.
An example of this is emotion recognition technology based on facial expression analysis. These systems are already widely used in marketing and corporate environments to assess customer reactions or monitor employee moods. Psychologists relying on traditional tests and interviews can no longer compete with this level of accuracy and speed.
How Engineers Are Redefining Social and Human Sciences
Algorithmizing the Psyche and Modeling Behavior
One of the key advantages of engineering approaches is the ability to algorithmize psychological parameters using data collected through sensors and other devices. These technologies make it possible to gather information about physiological and behavioral reactions in real time, which significantly enhances the capacity for analysis.
Modern technologies allow us to digitize psychological parameters such as stress levels, emotional reactions, and cognitive functions. Sensors tracking physiological indicators—such as heart rate or stress hormone levels—collect data, which is then used to build accurate psychological models. This data enables the creation of algorithms that model human behavior in various conditions, predict responses to stress, and assess productivity.
Modeling Interpersonal Relationships and Customizing Environments by Personality Type
Algorithmization also opens new doors in optimizing social and work environments for individuals. Analyzing emotional reactions and behavior allows not only the prediction of how a person will interact with others but also the selection of ideal teams and even countries where they will thrive.
For example, analyzing digital footprints that track online behavior can be used to select the country or region where a person with a specific personality type will feel most comfortable. This can also apply to corporate environments: algorithms can predict how a person will interact with colleagues, optimizing team formation.
Example: Selecting Teams and Countries
There are already examples of companies using algorithms to form teams based on the personality traits of employees. This approach helps predict team dynamics, identify potential leaders, and determine who will perform best in a specific role.
In the future, digital traces and psychophysiological data could even be used to select a country of residence that aligns with one’s personal traits. For instance, extroverts might prefer life in bustling metropolitan areas with active social lives, while introverts might feel more comfortable in less densely populated regions.
Conclusion
The algorithmization of the psyche, the use of sensors, and new data analysis methods are radically transforming the study of humans and society. Both sociology and psychology face the challenge that traditional research methods are becoming outdated compared to the capabilities offered by modern technologies.
Integrating engineering methods into the social sciences opens up prospects for more accurate behavioral analysis, personalized solutions, and optimal living and working conditions. This marks a new phase in the evolution of human sciences, and those disciplines that successfully adapt will play a pivotal role in future research.