Blog: How Society Gets Under the Skin - A Biological Signal for Societal Computing

As a result of the research in the past decades, everyone knows that health is strongly shaped by social conditions. Factors such as socioeconomic status, neighborhood environment, stress, and early-life adversity all influence long-term health outcomes. Importantly, these differences often remain even after accounting for genetics and individual behaviors such as smoking, diet, or exercise. This raises an important question: 

Fig1. How different cells rise to different tissues (partly)

To answer this question, we would first need to explain what biological embedding means. Biological embedding is the process by which repeated social and environmental experiences affect the body over time. Epigenetics is one of the main ways this happens, as it controls how genes work without changing the DNA itself. In this way, epigenetics helps us understand how social conditions can “get under the skin,” not as fixed outcomes for individuals, but as general patterns seen across groups of people. Importantly, this is not a deterministic process, and individuals can still change their outcomes over time.

Fig2. Same genome, different regulation1.

To explain more about epigenetics, it refers to chemical modifications that regulate gene activity without altering the DNA sequence. Since these mechanisms respond to environmental conditions and can remain relatively stable over time, they offer a way to study how lived experience may become biologically internalized.

A well-known example of epigenetics is the Dutch Famine (1944–1945). Individuals exposed to famine during fetal development were later found to have higher risks of metabolic and cardiovascular disease, as well as lasting differences in DNA methylation, even decades later. This example shows how extreme social conditions can lead to long-term biological changes without modifying the DNA sequence itself.

Fig3. Epigenetic clock as a concept

For societal computing, epigenetics can be especially relevant because traditional social variables such as income, education, or occupation are often too static to capture real-life exposure. Therefore, societal computing can address this limitation by measuring social and environmental conditions at much higher spatial and temporal resolution. These include factors such as neighborhood deprivation, pollution, mobility instability, heat, noise, and access to resources. Moreover, one promising variable that can be used to bridge biology and societal computing is the epigenetic clock. Epigenetic clocks estimate biological age based on DNA methylation patterns. When biological age is higher than chronological age, this may indicate accelerated aging linked to long-term stress or environmental burden. As a result, epigenetic clocks provide a practical and interpretable way to study how social exposure becomes biologically embedded.

This opens up exciting new research questions as well.

  • Can long-term neighborhood instability predict accelerated biological aging?
  • Do time-varying exposure histories explain more than static socioeconomic measures?
  • Are there sensitive periods when social conditions have stronger biological effects?

Societal computing can study these questions better by using epigenetic data, but at the same time, caution is necessary, as in every field. Associations between social exposures and epigenetic patterns are difficult to interpret causally and may be influenced by factors such as smoking, health status, ancestry, or technical bias. There are also important ethical concerns, including stigma, surveillance, and the misuse of biological data. For this reason, epigenetic signals should not be used for individual diagnosis or prediction. Their main value lies in looking at how social conditions shape biology at the population level.

In conclusion, epigenetics, especially through epigenetic clocks, offers societal computing a promising biological signal of cumulative social exposure. When used carefully, it can help connect social structure, lived experience, and long-term health in a more integrated and measurable way.

REFERENCES:

  1. https://www.novusbio.com/research-areas/epigenetics?srsltid=AfmBOorBtgVOTuVVsT0ifRkQ_oIFlovXGm7JBtm54lC3wSqmGZSE1Ylh
  2. https://www.thetech.org/ask-a-geneticist/articles/2019/epigenetics-and-cell-types/
  3. https://www.researchgate.net/figure/Schematic-diagram-of-an-epigenetic-clock-across-a-human-lifetime_fig2_330874051?__cf_chl_rt_tk=5t1YLAoIEHVO5Se8u.Rnpi2C6vUM1m.M4Bh0Ay7lA5s-1768925756-1.0.1.1-gVRUlNQvw1hKtpV1b_IRbr7WGMGDVxvKJ0nmqsi1Q24

- Written by Ful Belin Korukoglu 

Popular posts from this blog

AI Girlfriend or AI Boyfriend? Social Determinants of Human-AI Relationships

In the West and across the English-language internet, the idea of using AI for intimate companionship often conjures images of female personas. From Sam Altman's cryptic one-word X post—"her," a clear nod to the 2013 film—to Grok's launch of its AI companion Ani, the dominant narrative seems tailored to a heterosexual male audience. The archetype of the AI girlfriend, designed to be emotionally available, submissive, and aesthetically pleasing, has become a cultural fixture. In China, however, the discourse around human-AI intimacy takes a different shape. Media coverage and user engagement tend to center on women's experiences. The most talked-about AI bachelor? Dan—a character created using the "Do Anything Now" jailbreak prompt—who has captured the hearts of many Chinese women. Online discussions about Dan and similar AI companions flourish on Xiaohongshu, a lifestyle platform with a predominantly female user base, often dubbed "China's Inst...
Read more

Blog: The Importance of Good Data in Satellite Imagery Analysis

Introduction The phrase "Garbage-In-Garbage-Out" is well-known in data science, but it takes on new meaning in real-world projects, especially those involving satellite imagery. In these contexts where ground truth labels are often sparse, preprocessing becomes not just a step, but a cornerstone of success. Reflecting on my project, I have realized that understanding and preparing data account for about 70% (if not more) of the work and determines the quality of the results. Data preprocessing ensures that the inputs to your model are clean, structured, and tailored to the problem at hand. This is true for all kinds of data, whether tabular data, text, or images. However, the proper preprocessing steps come from initially "looking" at the data. That means preprocessing is dependent on the data and the task at hand.   Understanding Satellite Images Satellite images are far more than just pictures; they encode a wealth of information about the spectral signature of a ...
Read more

Job: Student Research Assistant (m/w/d) for AI & Misinformation detection

Image
Join Us in Fighting Misinformation! We are seeking a passionate and skilled Research Assistant to contribute to cutting-edge projects at the intersection of AI, digital literacy, and societal impact. Be part of a team dedicated to developing AI-powered tools to help young people combat misinformation. If you are interested, submit your CV and a brief cover letter detailing your relevant experience and interest in combating misinformation through AI to Katja Raak - kraak@cs.uni-saarland.de .
Read more