Technology and society is studied across at least seven disciplines, each asking different questions and using different methods. Sociologists examine social inequality and how technology shapes society. Cultural studies scholars examine meaning and representation. Political scientists examine power and governance. Economists examine markets and labour. Law scholars examine regulation. Communications researchers examine media and discourse. Engineers examine technical systems and design.

That disciplinary range is what makes "technology and society" dissertations either truly rich or incoherently scattered. The key is disciplinary grounding.

What This Field Covers

The social construction of technology: the idea that what technology does isn't determined purely by its technical features, but by how people design it, interpret it, and use it. A social media algorithm isn't a neutral system; it's built with choices about how to rank content, what to promote, what to suppress.

Digital inequality: the unequal distribution of internet access, digital skills, and the benefits of digital technologies. Not everyone has high-speed internet. Not everyone has learned to use digital tools. Not everyone benefits equally from the shift towards digital platforms.

Platform capitalism: the economic systems where value is extracted by platforms (Amazon, Google, Meta) that connect buyers and sellers or producers and consumers, taking a cut and controlling the terms.

Surveillance: the collection, analysis, and use of data about individuals and populations. The scope has expanded from state surveillance to corporate surveillance (companies tracking your behaviour online).

Automation and employment: how automation affects labour markets, whether people are displaced, whether new jobs emerge.

Digital governance: how technology is regulated, who makes decisions about technology policy, and what frameworks shape technology development.

Key Considerations and Best Practices

Media and democracy: how technology affects political information, polarisation, misinformation, and democratic participation.

Key Theoretical Frameworks

Langdon Winner's "politics of artifacts" argues that artefacts have politics: technological systems embody values and shape social life. The design of a technology reflects political choices. A highway built low enough to exclude buses (a real historical example) embodies a political choice to exclude poor people (who rely on public transit) from accessing places.

Shoshana Zuboff's surveillance capitalism framework examines how technology companies profit from data extraction. They collect data about your behaviour, predict your future behaviour, and sell predictions and persuasion. This's different from previous forms of commerce because it treats behaviour as a resource to extract and control.

Evgeny Morozov's "techno-solutionism" critique argues that technology is often presented as a solution to social problems, when the real issues are political or structural. Climate change won't be solved by a better app; it requires policy change. Education inequality won't be fixed by putting tablets in schools; it requires addressing poverty and inequality.

The Actor-Network Theory (ANT) of Bruno Latour and Michel Callon examines how human and non-human actors (people, technologies, institutions, algorithms) form networks that shape outcomes. Technology isn't simply used by passive humans; technology and humans co-produce effects.

Methodologies Used in Technology and Society

Qualitative approaches are dominant. Digital ethnography (participant observation online, studying how people use platforms and communities), interviews with technology workers or users, focus groups on technology attitudes, and case studies of specific technologies or their impacts.

Discourse analysis examines how technology is discussed in policy, media, and academic literature. A discourse analysis of "AI regulation" might ask: what metaphors are used, whose voices are centred, what assumptions underlie the discourse?

Critical platform analysis audits how platforms actually work (testing algorithmic recommendation, mapping data flows, examining moderation practices).

Secondary analysis uses existing datasets on digital inequality (internet access surveys, technology adoption data), or content analysis of digital platforms (analysing what content is promoted, how different groups are represented).

Expert Guidance for Academic Success

Quantitative approaches are used for specific questions: analysing digital inequality data (Ofcom surveys on internet access and digital skills), analysing employment impacts of automation (labour force surveys tracking skills and wages in sectors affected by automation), surveying attitudes towards technology regulation or privacy.

Key Data Sources

Ofcom's Connected Nations reports examine broadband coverage and adoption. The Online Nation report surveys people's internet use, skills, and attitudes. These are important for dissertations on digital inequality.

The ONS Internet Access Survey provides population-level data on broadband access and use.

Office for AI publications offer policy context on UK AI regulation. The DSIT (Department for Science, Innovation and Technology) digital strategy and AI safety work provide government perspective.

The Ada Lovelace Institute and Digital Poverty Alliance conduct research on digital inequality.

Published academic research provides theoretical frameworks and empirical findings.

UK and EU Regulatory Context

The UK Online Safety Act 2023 requires online platforms to take steps to protect users from harmful content. This's the primary UK law regulating tech platforms, though it's primarily focused on specific harms (child exploitation, terrorism, illegal content) rather than all harms.

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The EU Digital Services Act 2022 is more thorough: it requires transparency about recommendation algorithms, content moderation, and advertising. It's more prescriptive than the UK approach. Dissertations comparing UK and EU approaches to technology regulation are strong.

Practical Steps You Should Follow

GDPR (General Data Protection Regulation) still influences UK data protection (the UK's equivalent is the Data Protection Act 2018 and UK GDPR, which largely mirrors EU GDPR). This's relevant for dissertations on surveillance and data ethics.

Algorithmic accountability frameworks are emerging but not yet codified in law. Dissertations examining how to hold algorithms accountable are timely.

Dissertation Topics

1. Digital inequality in the UK: analysing Ofcom data to examine internet access and digital skills gaps by age, income, and location
2. How social media algorithms shape political information exposure: comparative analysis of recommendation systems on different platforms
3. Platform moderation in practise: interviews with content moderators about decision-making and labour conditions
4. The right to explanation under GDPR: do companies actually explain algorithmic decisions to users?
5. Surveillance capitalism and advertising: a critical discourse analysis of data privacy policies from major tech companies
6. Automation and employment: secondary analysis of labour force data examining job displacement in sectors affected by automation
7. Tech workers' ethics: interviews with software engineers about ethical conflicts and decision-making in tech companies
8. The "digital natives" myth: examining educational claims about young people and technology, 2000 to 2025
9. Online misinformation and political polarisation: a study of how algorithms contribute to filter bubbles during UK elections
10. Accessibility and technology design: interviews with disabled people about barriers to using digital platforms
11. The environmental cost of technology: analysing the carbon footprint of data centres and digital infrastructure
12. Governance of AI in the UK: comparing regulatory approaches (pro-innovation vs precautionary) in policy documents

Frequently Asked Questions

Q: What's the difference between technology and society dissertations and digital humanities dissertations? A: Technology and society dissertations study the social and political dimensions of technology, power, inequality, and governance. Digital humanities dissertations use digital tools and methods to study humanities questions (literature, history, culture). A digital humanities dissertation might use text analysis software to study patterns in historical documents. A technology and society dissertation would study the assumptions built into text analysis software and who benefits from its use. Disciplinary grounding shapes the approach.

Q: Can I write a dissertation on social media without understanding computer science? A: Yes. Sociology, cultural studies, political science, law, and communication studies dissertations on social media don't require technical knowledge of how platforms work. You need to understand the broad principles (platforms use algorithms to rank content, they collect data, they've commercial incentives), but you don't need to code or understand machine learning. Social science approaches to platform analysis are entirely valid and increasingly important.

Q: Is technology and society a real discipline? A: It's an interdisciplinary field without a single discipline. Technology studies, science and technology studies (STS), media and communication studies, digital sociology, law and technology, and technology ethics all overlap here. Most dissertations are grounded in a specific discipline (sociology, law, politics, media studies) but address technology as a topic. That disciplinary grounding matters; "technology and society" without disciplinary roots risks being unfocused.