Critical Studies in AI and Digitalisation Cluster (CSAID)

Artificial intelligence (AI) technologies are being used to manage, augment, or otherwise transform work. AI and algorithmic data driven systems are expected to help firms improve productivity and profitability, but they may also impact the world of work significantly.

The Essex AI Policy Observatory for the World of Work (E-AIPOWW) is the first Observatory highlighting how AI regulation, development and governance are occurring across the world, and what this is beginning to mean, and will mean for the world of work, and workers’ experiences.

This is an ongoing project developing an AI-based software solution for emotion research to help researchers from various areas, from design to neurorehabilitation. The first component of our innovative solution, an improved approach for measuring emotional arousal through pupillary response, is now under review.

Researchers have long recognised pupil response as a potential objective indicator of emotional arousal; however, confounding factors, particularly luminosity of stimuli and the ambient environment, have limited its usefulness in detecting emotions. This study presents a new approach to isolate and remove the effect of luminosity on pupil dilation, obtaining the component of pupil dilation due only to emotional arousal.

Our model predicts the pupil size due to luminosity only as a function of the screen luminosity and adapts to individual differences in pupil response to light, different types and configurations of monitors by using a calibration procedure. We demonstrate that our model can be used simply to calculate emotional arousal. We showed 32 video clips with different content and emotional intensity to 47 participants, who, after each video, reported their level of emotional arousal. We then calculated the pupil size due only to luminosity and subtracted it from the total recorded pupil size, obtaining the component due only to emotional arousal. From the latter, we predicted the arousal of each participant for each video. Our results highlight that separating the emotional and luminosity components from pupillary responses is critical to accurately and precisely predicting arousal.

• Pansara, Z., Navyte, G., Freitas-Mendes, T., Bottger, C., Franco, E., Citi, L., Jacobi, E.S., Poerio, G.L., Gillmeister, H., Cinel, C. and De Feo, V., 2025. Quantifying Emotional Arousal through Pupillary Response: A Novel Approach for Isolating the Luminosity Effect and Predicting Affective States. arXiv preprint arXiv:2504.13886.

The project aimed to understand how community businesses are co-developing and making better use of data, community technology, and AI. Its primary goal was to identify key gaps in how data is collected and used, with a particular focus on how this could inform the design, development, and application of community technology and AI (CTAI) to support the transition to sustainable and equitable futures. The findings provide a foundation for collaboratively developing new frameworks for local data collection and exploring practical uses of CTAI.

This report presents research conducted collaboratively by researchers from the University of Essex and Promising Trouble, funded by the Business and Local Government Data Research Centre. Carried out between May and September 2024, the study examines how community businesses engage with technology and artificial intelligence (AI) and explores their views on 'community technology' and 'community AI' approaches.

The research involved 28 community businesses across the UK and 13 in-depth interviews with a diverse range of organisations. The findings reveal a broad spectrum of technological engagement, with a strong interest in community tech and AI for social good. However, organisations face significant challenges, including issues with data management, ethical adoption, limited resources, and a need for more education, collaboration, and community-led governance. The report calls for investment in skills, ethical governance, funding, and collaboration to ensure that community tech and AI are inclusive, sustainable, and driven by the needs of communities. Achieving the potential of community technology and AI to support more equitable and sustainable futures will require ongoing collaboration and investment, alongside a shift away from market-driven models towards those that are community-led, ethically grounded, and environmentally responsible.

We deeply appreciate everyone who contributed to this research, especially the participants whose knowledge and insights made it possible.

• Funded by: Business and Local Government Data Research Centre
• Duration: May to September 2024
• Lead: Malu Villela
• Team: Peter Bloom, Anna Dent, Malu Villela

The Assemblage Brain unveils a major new concept of sense making, one that challenges conventional scientific and philosophical understandings of the brain.

Drawing on Deleuze and Guattari, the author calls for a radical critical theory that operates in the interferences between philosophy, science, art, and politics. From this novel perspective the book is structured around two questions: “What can be done to a brain?” and “What can a brain do?” Sampson examines the rise of neuroeconomics in informing significant developments in computer work, marketing, and the neuropharmaceutical control of inattentiveness in the classroom. Moving beyond the neurocapitalist framework, he then reestablishes a place for proto-subjectivity in which biological and cultural distinctions are reintegrated in an understanding of the brain as an assemblage.

The Assemblage Brain unravels the conventional image of thought that underpins many scientific and philosophical accounts of how sense is produced, providing a new view of our current time in which capitalism and the neurosciences endeavor to colonize the brain.

Tony has several related articles, chapters, and talks on this subject.

• Author: Tony D Sampson 2017, University of Minnesota Press

The project offers a toolkit for public sector organisations, especially social cash policymakers for leveraging a wide array of AI technologies under an organisational governance framework based on ethical principles.

First, the project critically examines the data and algorithmic-led targeting process for the disbursement of emergency cash relief to flood victims after the 2022 floods in Pakistan. After highlighting the limitations in programme design, especially pertaining to data/algorithmic targeting, the findings offer practical recommendations for the greater inclusion of beneficiaries. Second, the project proposes an organisational AI governance framework for the responsible adoption of AI technologies to guardrail the risks associated with AI and data-driven targeting decisions. The paper contributes to the emerging discourses around AI, data, governance, and social policy directives that can positively impact on digital public services and equitable outcomes in society.

The second stage of the project aims to critically analyse Pakistan’s AI Draft National Policy, and situate it within wider global AI discourses (in comparison to the Global North) to constructively inform national and public policy in the Global South – work-in-progress.

The role of different types of data and algorithmic technologies in adaptive social cash systems appears promising for emergency social cash disbursements in time of climate crisis, yet few governments have deployed artificial intelligence (AI) technologies to reap its benefits. Hence, public policymakers and practitioners face mounting pressures to rapidly exploit opportunities arising from AI solutions. While AI-led algorithmic targeting may play a significant role in increasing efficiencies for enrolling beneficiaries onto adaptive social cash systems, they may pose even serious challenges than automated (non AI) algorithms in targeting processes.

Through an empirical case study of the Benazir Income Support (BISP) Emergency Flood Cash Programme in Pakistan, the research critically examines the automated targeting process, and unveils the shortcomings pertaining to design, data and algorithmic decision-making that leads to bias and certain exclusionary outcomes for beneficiaries. Based on the findings, the study makes several contributions to the data, policy and governance literature. First, it offers a set of practical recommendations for the greater inclusion of beneficiaries. Second, it highlights novel prospects that AI technologies can provide, whilst cautiously evaluating its potential risks. Third, in order to mitigate the risks, the study designs an organisational AI governance framework to guide the development of responsible AI practices within a scaffold of ethical principles and practices. Thus, the research affords practical insights for social cash policymakers, practitioners, regulators and stakeholders, advocating the redesign of social and public policy that positively impacts on inclusive organisations and society.

• Duration of Project: October 2022 – ongoing
• Lead Author: Dr Atika Ahmad Kemal

Other related publications

• Kemal, A., & Shah, M. H. (2024). Digital Innovation in Social Cash Organizations – the Effects of the Institutional Interactions for Transforming Organizational Practices. Information Technology and People. Vol. 37 No. 5, pp. 2092-2126
• Kemal, A. A. (2019). Mobile banking in the government-to-person payment sector for financial inclusion in Pakistan. Information Technology for Development, 25(3), 475-502.
• Kemal, A. A., & Yan, L. (2015). Mobile banking adoption and diffusion: Enabling and constraining social or financial inclusion among poor women in Pakistan?. In ECIS 2015 Completed Research Papers. Association for Information Systems Electronic Library. 

As the two leading countries in the development of artificial intelligence (AI) systems, China and the United States largely rely on separate AI infrastructure and data annotation ecosystems. Studies have focussed almost exclusively on data annotation associated with American and European companies, limiting our understanding of how this contrasts with the Chinese development of AI.

This article provides a comparative analysis of the political economy of the Chinese and American/European AI data annotation ecosystems, focusing on the role of the state and the practice of outsourcing to data annotation institutions. It finds that while the US state plays a protectionist role concerning AI infrastructure such as semiconductors and data centres, it adopts a laissez-faire approach to data annotation. The Chinese state, however, understands it has a comparative advantage in data and invests heavily in its own data ecosystem while maintaining stringent regulations for Chinese tech companies. Secondly, many US companies outsource data annotation work to business process outsourcing centres and digital platforms, whereas Chinese companies maintain these activities in-house or, through a process of “inland-sourcing”, send this work to “third-tier” cities in Chinese provinces to data labelling bases, often jointly managed by local government and private companies.

• Dr Tongyu Wu
• Dr James Muldoon
• Dr Bingqing Xia

Published in Big Data & Society May 2025

Loneliness has emerged as a pervasive social issue, significantly impacting individuals' emotional well-being and overall quality of life. This research aims to explore the social psychological mechanisms behind lonely consumers' preferences for service robots over human interactions. Specifically, it will investigate how emotional loneliness influences these preferences and identify the features of service robots that can enhance satisfaction and well-being for lonely individuals.

By examining the interplay between emotional loneliness and service robot attributes, this research seeks to provide valuable insights into how service robots can be optimised to meet the emotional needs of lonely individuals. The findings will contribute to the existing literature on loneliness, technology, and consumer behaviour, offering practical implications for service industries aiming to foster emotional connections and improve customer experiences.

Ultimately, this study aims to advance understanding of how technology can serve as a supportive tool in addressing the loneliness epidemic and enhancing emotional well-being.

• Funded by: British Academy
• Duration: 1 May 2025 to 30 April 2027
• Lead author names: Dr Min Yan (University of Essex), and Dr Qionglei Yu (Newcastle University).