What do AI in Society researchers work on?

Artificial Intelligence (AI) in society has increasingly become a sexy term in social science, given the popularisation of generative AI. For Oxford Intersections — a newly launched academic publication run by Oxford University Press — for example, Racism by Context, Social Media in Society and Culture, and AI in Society are the three highlighted sections. This informs how valuable the discussion about AI in society has become (and is going to be in the long run) to enrich academic and public dialogue.

Beyond academia, Microsoft Research has been running its AI in Society Fellowship programme. Social scientists from academia are recruited to work alongside industry experts to analyse AI-inflicted societal issues and how AI can be applied to realise positive societal changes. These all suggest how world-leading academic institutions and industry organisations have been prioritising research and in-depth writing on AI in society topics. Below are three major intellectual topics on AI in society that are trending, as of writing this blog post in mid-2025. As time goes on, it is very likely that more social scientists will be invited to work on these areas of study to address societal issues surrounding AI.

1. Inequality and Social Stratification

One area social science researchers in academia and industry prioritise conducting research on is addressing inequality and social stratification. Inequality and social stratification have often been known as a dominant field of sociological investigation. Since the rise of generative AI, many social scientists are interested in unpacking how generative AI is designed and/or deployed under the influence of existing social hierarchies, which are likely to reinforce or create new forms of inequality.

For example, some researchers focus on investigating algorithmic bias. This refers to how AI systems perpetuate and amplify existing biases related to race, gender, class, age, and disability. Given my partial research interests in decolonisation and addressing inequality in the Global South, I am most interested in understanding how AI is marginalising voices and perspectives from the Global South while amplifying the dominating social, cultural, and political values within the Global North.

Moreover, I am interested in whether and how AI-influenced systems discriminate against women, ethnic minorities, and those living with disabilities. These areas of study all address the perpetuation of inequality and social stratification. As our world continues to champion the buzzwords of “societal equity”, it is very likely that more universities and industry organisations will be financially supported and incentivised to fund social science research projects on identifying and addressing inequality and social stratification inflicted by AI.

2. Power, Governance, and Surveillance

Another dominant area of study is power and governance. Power imbalance is always a leading research field in social science, especially in sociology. We study how inequality and, for example, poor governance result in unequal power relations in our societies. Such an underlying power imbalance, in turn, deepens existing inequality, contributing to a vicious cycle of injustice.

In AI in society research, social scientists are hired to analyse how AI is used as an instrument of social control and governance by both states and corporations. Broadly speaking, we investigate how governments and corporations use AI for surveillance, law enforcement, and social administration. If properly arranged, we study how AI can facilitate our social process of population control and management through debates on social norms, ethics, and laws for AI.

If not properly arranged, we study how poor governance would deepen existing power imbalance and institutional impotence, perpetuating existing inequality. Social scientists are increasingly encouraged to work on applied research projects (those that are policy-oriented) to evaluate existing policies and suggest how governments and corporations can respond to better regulate their AI-powered societal system of population control and surveillance.

3. Transformation of Social Institutions

At the community level, we also examine how core social institutions (such as family, education and healthcare) are being fundamentally restructured by the integration of AI. Within the family, we explore how smart home devices that are AI-powered can be incorporated in cities, especially in top-tier cities, to undertake caregiving responsibilities and support family dynamics. In 2022, I interned at the Asian Development Bank to evaluate smart elderly care policies for positive social and pro-ageing development. With the popularisation of AI, it is likely that more social science research, especially in the fields of futures studies, will analyse the role of AI in supporting existing family dynamics and caregiving responsibilities.

In education, for example, we study how AI tools can be used to personalise learning, automate grading, and monitor students’ performance. In healthcare, furthermore, researching the social dynamics of integrating AI into medical diagnostics and treatment would be prioritised. Also, how we can provide equitable access to high-tech care, such as by allowing established surgeons to perform surgeries remotely for patients in remote and impoverished areas, would continue to be studied by social scientists, medical experts, and policymakers.

Conclusions

AI in society will continue to be a sexy and mainstream term in the foreseeable future. This is an area of study where social scientists, both in academia and industry, are given opportunities to apply their expertise to conduct AI research. With the popularisation of AI, the ways in which social scientists conduct their research and their focus expand. This is an interesting transition, making the sub-fields of sociology — namely (1) society and technology and (2) information and society — gain more traction and influence in the long term.

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