- Convenors:
-
Neha Hui
(University of Reading)
Uma Kambhampati (University of Reading)
Send message to Convenors
- Format:
- Paper panel
- Stream:
- Digital futures: AI, data & platform governance
Short Abstract
This session explores shifting aspirations in a world shaped by AI and digital change, focusing on how people re-skill to meet new demands. We invite papers on how gender, race, and caste shape opportunities, constrain skill development, and perpetuate inequalities in the face of new technologies.
Description
This session examines how aspirations and opportunities shift in a world reshaped by AI, automation, and digital technologies. Labour markets in developing countries are undergoing profound change, but as Acemoglu (2025) notes, the ability to adapt depends not only on technology but also on institutions, market structures, norms, and ideologies.
We invite papers exploring how aspirations, reskilling, and skill upgrading are constrained by social structures such as gender, race, and caste, which shape access to opportunities and reinforce inequalities.
Key questions include:
Work in the digital era – Are jobs disappearing before they even emerge in developing economies? Are capital constraints a problem and do they reinforce existing social divides in responses to new technology?
Norms and aspirations – How do societal expectations restrict goals? For example, do patriarchal norms prevent women from adjusting aspirations while fulfilling roles as “good” wives or mothers? Do caste, religion, race, or ethnicity curtail aspirations and limit adjustment to technological change by reinforcing expectations of discrimination?
Education, training, and policy – Will historical exclusions from education hinder upgrading? Are women and marginalised groups disproportionately disadvantaged in reskilling and adapting to new technologies?
Institutions and governance – How will labour market discrimination and weak governance shape mismatches between aspirations, skills, and opportunities?
We welcome perspectives from different regions, industries, and social groups. By connecting research on aspirations, skills, and inequality, this session seeks to deepen understanding of how technological change reshapes opportunity—and who is left behind.
Accepted papers
Paper short abstract
This study adopts an Inequality of Opportunity perspective to explore how capital constraints and normative expectations shape preparatory skill accumulation and aspirations, producing anticipatory inequality in AI-related skilling before labour market entry among female undergraduates in Pakistan.
Paper long abstract
Inequalities in opportunity are emerging even before individuals enter the labour market as artificial intelligence adoption accelerates. While much of the existing research focuses on up- and re-skilling as adaptation strategies in response to automation and job displacement, employability uncertainty is also reshaping aspirations and impacting preparatory skill accumulation. Before entering the workplace, universities are serving as sites of adaptation. However, the opportunities to prepare for an uncertain and dynamic world of work are not distributed evenly among students. This proposed paper examines how capital constraints and normative expectations influence student preparatory capacity and shift aspirations among female undergraduate students in Lahore, Pakistan. The Inequality of Opportunity framework (Roemer, 1998) shall underpin the analysis, wherein AI-related skilling opportunities are conceptualized as outcomes determined by circumstances beyond individual control that constrain agency. Taking perceived adequacy of the ongoing formal degree programmes as a point of departure, access to informal learning opportunities, such as self-learning micro-credentialing, shaped by economic means, information exposure, peer effects, gendered narratives and responsibilities shall be explored through qualitative analysis. Semi-structured, in-depth interviews will be conducted with 22-24 students from two different universities, one co-educational and one women only, to map opportunity sets associated aspirational shifts. This paper contributes to debates on skill gaps and aspirations in an AI-driven world by foregrounding anticipatory inequality formation in a developing country context. It further provides the foundation for further research on aspiration-opportunity alignment and higher education’s approach to employability skills pathways in Pakistan.
Paper short abstract
Using mixed methods in Patna, India, this study analyzes what factors determine individual's aspiration for “good” or “bad" jobs. FGDs, interviews, and a survey experiment show that beyond pay, autonomy, and flexibility, caste and gender norms strongly shape job preferences and aspirations.
Paper long abstract
This article examines both objective and culturally constructed notions that determine whether a job is considered “good” or “bad.” We employ a mixed-methods approach in Patna, India, drawing on data from two focus group discussions (FGDs), 20 qualitative interviews, and a conjoint experiment embedded in a survey of 788 workers across multiple industries. Qualitative findings show that while monetary returns, perceptions of power, social status, and autonomy are central to how individuals evaluate jobs, gender and caste norms and expectations also shape occupational preferences and aspirations. The conjoint experiment confirms the salience of caste and gender norms, alongside the importance of salary, flexibility, and autonomy. Overall, our results indicate that although “objective” criteria matter, social and gender norms significantly influence attitudes toward occupations.
Paper short abstract
This paper examines how digitalisation and platformization are reshaping women’s work in India. It shows how digital labour in feminized sectors reproduces intersectional inequalities shaped by societal norms, caste, community, religion, language, and institutional arrangements.
Paper long abstract
Domestic work burden, care-giving responsibilities, and prevailing gendered social norms are common bottlenecks to female labour force participation in India. Increasing digitization and the booming platform economy are reshaping opportunities in the feminised care sector, raising questions about whether digital transformation enables skill upgrading, aspiration formation, and economic inclusion. Using primary survey data on 56 workers, this study compares working conditions of effects of digitization on 28 Accredited Social Health Activists (ASHAs) in rural sectors and 28 platform-based domestic workers in urban centres.
The paper shows that digitisation does not uniformly expand opportunities for women but interacts with existing social structures to reproduce inequality. Platform-based domestic work attracts relatively more educated women and is often associated with aspirations of flexibility and income mobility. In contrast, ASHAs operate within a state-led digitalised system that relies on task-based incentives, digital monitoring, and performance targets, while continuing to classify workers as “volunteers.” Despite accumulating significant experiential and digital skills, ASHAs face limited pathways for skill recognition, career progression, or formal employment.
Across both sectors, gendered norms, caste and regional hierarchies, and institutional arrangements shape aspirations and adaptation to digital work. Rather than facilitating reskilling or upward mobility, digitisation often intensifies work without addressing structural barriers to decent employment. The findings highlight how unequal access to skills recognition, labour protections, and social security constrains women’s ability to benefit from technological change.
The paper underscores the need for labour regulation, public policy, and platform accountability to ensure that digital transformation supports inclusive and equitable employment.
Paper short abstract
In this paper we document persistent differences across socioreligious groups in acquiring tertiary education in India. Using the most recent employment survey data (PLFS), we calculate differences in returns to tertiary education that shows widening gap across the socioreligious groups.
Paper long abstract
In this paper, we document persistent differences in completion of tertiary education and calculate returns to education across in India. We deploy unit level data from the Periodic Labour Force Survey for the year 2023-24. For calculating/estimating returns to education, we use Mincerian Wage Equation and correct for sample selection bias using Heckman’s model. We find that returns to education is positive and increases with every additional level of education for entire sample of those employed. However, when we estimate the returns to education by employment type, for regular wage/salaried employment, returns increase monotonically and to a lesser extent for self-employment. We also find that that there is no significant relation between wages and education for the casual workers. The socio-economic factors like socioreligious groups, gender and place of residence etc appear to play an important role in determining income and employment probabilities. Our analysis suggests that at the higher levels of education, i.e. graduate and above, returns are significantly higher than those for below the graduate levels with prominent variation across socioreligious. We suspect that differences in the quality of tertiary education might explain the socioreligious group differences. It implies, therefore, that additional years of education, specially technical degrees and diploma/certificate (both below and above graduation) yield better returns.
Paper short abstract
AI is often seen as a threat to jobs, but its main impact may be widening skill and income inequalities. This paper examines how AI reshapes work, who (given intersectionality of personal characteristics) benefits, and the policy conditions under which AI could reduce rather than deepen inequality.
Paper long abstract
Artificial intelligence (AI) is frequently framed as both a productivity-enhancing tool and a major threat to employment. McKinsey (2025) forecasts 30% of jobs losses in USA by 2030. However, such projections, albeit varied across countries, often assume that the proportion of tasks AI (and robotic) can perform directly translates into job losses. This overlooks how occupations adapt and evolve in response to technological change. Past predictions of occupational displacement—e.g. radiology—illustrate that AI more often reshapes work, augmenting productivity rather than eliminating jobs outright.
This paper argues that the central development challenge posed by AI lies less in aggregate job loss and more in the distributional consequences of AI adoption. AI is more likely to complement workers with higher levels of education, digital skills, and income, while disadvantaging those with fewer opportunities to acquire such skills. Through intersectionality between different personal and household's characteristics, inequalities linked to gender, ethnicity, and socioeconomic status could be worsened. AI risks widening gaps in wages, employment opportunity and job security, with a stronger effects within each country rather than between high-, middle-, and low-income contexts.
We propose a framework grounded in firms and labour market incentives to explain how AI adoption interacts with skill formation and task/job reallocation. The framework highlights conditions under which AI could narrow skill gaps rather than deepen inequality. Using cross-country survey data on AI accessibility and usage, we assess whether these equalising conditions are emerging and identify policy priorities for leveraging AI as a tool for inclusive and equitable development.
Paper short abstract
This study examines how gendered skill gaps and unmet aspirations shape economic inequality in urban transformation, focusing on how women food vendors in peri-urban zone within Mumbai, India. It explores the intersection of spatial marginality and digital exclusion.
Paper long abstract
In the 'brave new world' of digitally expanding cities, systemic inequalities are often reproduced rather than resolved. This study examines how gendered skill gaps and unmet aspirations shape economic inequality in urban transformation. Focusing on women food vendors in peri-urban zone within the 'Mumbai 3.0' expansion, it explores the intersection of spatial marginality and digital exclusion.
Employing a mixed-methods approach of in-depth interviews and spatial mapping (QGIS), the research documents the lived experiences of vendors navigating a transforming landscape. Findings reveal a critical duality: while these women possess resilient entrepreneurial aspirations, they face an extreme skill gap in accessing digital marketplaces. Their physical peripherality is compounded by digital marginalization, forcing reliance on invisible informal networks. This highlights how the digital transition, without intentional intervention, exacerbates existing gendered and spatial inequalities.
The study concludes that bridging the aspirational divide in cities requires moving beyond technical infrastructure. It argues for a framework where inclusive development is predicated on co-designed interventions that pair digital integration with community-led skill-building. Ultimately, equitable urban futures depend on recognizing and strengthening the informal care and support networks that already sustain marginalized workers.
Paper short abstract
The study (Ecuador, 2009–2019) finds that higher education and STEM jobs raise inequality through a “composition effect,” while no “structural effect” reduces it, especially from 2014–2019. STEM fields show no equalizing impact due to economic and institutional constraints.
Paper long abstract
This study examines the relationship between labor income inequality, higher education, and STEM occupations in Ecuador from 2009 to 2013 and from 2014 to 2019, considering techniques, degrees, and postgraduate education. It analyzes the “composition effect” and the “structural effect” using the Recentered Influence Function (RIF). The “composition effect” measures how much inequality increases due to the influx of more workers with higher salaries. Conversely, the “structural effect” measures the extent to which inequality is reduced by increasing the total resources allocated to the wage bill and how these resources are redistributed. The results show no evidence of a structural effect of higher education from 2014 to 2019. The “structural effect” does not occur in STEM fields. The inability to reduce inequality in STEM occupations in Ecuador is linked to the economy's structural limitations and the institutional framework of the Andean country.
Paper short abstract
Youth un- and underemployment remains one of the most pressing challenges, particularly in Sub-Saharan Africa. This research explores the factors that shape young people'ability to choose own career paths, despite challenging circumstances and to adapt to structural changes in the labour market.
Paper long abstract
Youth un- and underemployment remains one of the most pressing challenges, particularly in Sub-Saharan Africa, the world’s youngest region. The rapid rise of digital technologies and AI adds new complexity to our discussion on youth labour market participation. While there is an extensive body of literature examining the economic and social factors contributing to youth un- and underemployment in the region, less is known about how young people in Sub-Saharan Africa perceive their employment opportunities and their “work volition” - ability to choose own career paths, despite challenging circumstances. At the same time, studies from other regions suggest that these perceptions are crucial for understanding of young people´s career adaptability and their ability to navigate shifting labour markets.
This study seeks to address this research gap by examining work volition among young people living in urban centres of Sierra Leone. It employs a mixed-methods approach, combining 33 qualitative interviews with a structured survey (n=1502), conducted between September 2024 and April 2025. This research explores the factors that shape young people's work volition and their ability to adapt to structural changes in the labour market. It highlights the importance of both individual and socio-economic factors, providing a critical analysis of the structural inequalities that persist within the labour market. The study explores how age, ethnicity, educational background, gender, and employment status intersect, shaping young people's experiences in the changing labour markets.
Paper short abstract
About 10 -12 million young Africans enter the labour market each year where only 3 million formal jobs are available. The presentation seeks to address the question; are African countries preparing their youths for the jobs of the future?
Paper long abstract
Over 75 per cent of the population of Africa is under the age of 35. More decisive actions are needed to turn this demographic asset into an economic dividend,
Many of Africa’s young people remain trapped in poverty that is reflected in multiple dimensions, education, access to quality health care, infrastructure, and lack of job opportunities.
Far too many youths across sub-Saharan Africa emerge from school without the basic skills to advance in their lives
Without jobs after many years of trying, many young Africans are forced to take menial jobs. The pressure is too much when youth have education but no jobs.
While 10-12 million more young people in Africa join the labour market every year, only 3 million formal jobs are created annually. With little to no social protection, young people in Africa cannot afford to not work, thus, under-employment in the informal sector is the norm.
However, there has often been limited government support for innovation and young entrepreneurs, and a lack of government stimulus, especially for often vulnerable groups, including youth, women, and people living with disabilities or HIV/AIDS.
The presentation re-emphasizes youth empowerment and employment to unlock the potential of Africa’s young people.
In particular, there is need for education that can propel young Africans towards their career aspirations. Strong education systems in Africa need transformation. Also, young Africans with the requisite skills are the ones to drive development on the continent.
Paper short abstract
A multi-method causal analysis reflecting on how female-focused skilling expands women’s entry into work, yet pushes them into lower valued roles feminized occupations with widening wage penalties. Market-oriented training while empowering can unintentionally reproduce deeper gendered inequalities.
Paper long abstract
Using detailed occupational classification, rich covariates and multi-stage empirical approach this study investigates the heterogeneous evolution and implication of occupational gender typicality on wages and wage inequality in India. To mitigate biases arising from imperfect matching and model misspecification we employ doubly robust multivalued treatment model based on Augmented Inverse Probability Weighting Regression Adjustment. This is followed by Multinomial Endogenous Switching Regression (MESR) to account for endogenous occupational choices. Exogenous variation in occupational sorting is identified through a leave-one-out Bartik instrument, constructed by interacting district level exposure to female vocational training shocks with national skilling trends. The MESR results reveal significant wage penalties in feminized occupations, particularly for women, consistent with occupational devaluation and crowding hypotheses. At the macro level the micro-level mechanisms are validated using panel instrumental variables estimation and sequential IV 2SLS to reflect increased female participation in vocational training is causally associated with a rise in female employment and patterns of occupational feminization. This multi-level causal findings thus underscore a paradox inherent in market-oriented skilling interventions, facilitating women’s entry into the labor force, but inadvertently reproducing and exacerbating existing gender hierarchies in occupational sorting and wages. This study contributes to feminist political economy by critically engaging with the structural limitations of supply-side labor market interventions in contexts of persistent gendered stratification.
Paper long abstract
Gender disparity in time allocation to paid and unpaid work is an observed phenomenon globally, and India is not an exception. The problem of gender disparity in time use is important, as it could influence the economic opportunities, social well-being, and overall empowerment of women. This study examines the extent of disparity that exists in time allocation in paid and unpaid activity among men and women in households across Indian states/UTs. Specifically, it investigates whether the time allocation pattern in unpaid activity is different from the general trend if both male and female are employed in similar broad statuses of employment across the geographical regions of India. Furthermore, the study examines whether there is any significant difference in the mean time allocated to unpaid activities between employed and unemployed women. The analysis also tries to determine the factors influencing the gender differences in time allocation to unpaid activity across the states/UTs of India.
The study further explores how the time male and female spend on unpaid labor influences the female labour force participation rate (FLPR), controlling for the socio-economic and geographic factors. The findings reveal that even if males and females are employed in comparable types of work, there exists a huge disparity in time allocation to unpaid activity, particularly among regular salaried employees.
Paper short abstract
This study delivers the first nationwide evidence on who in India is being left behind in cybersecurity literacy. Using nearly one million survey responses, it shows that digital progress has not translated into digital safety for most citizens and that marginalised groups remain at greatest risk.
Paper long abstract
Cybersecurity literacy is defined as the ability to identify digital risks, protect personal data, and navigate online environments safely. It has become an essential yet insufficiently examined dimension of digital inclusion in India. As technology adoption accelerates and incidents of cyber fraud surge, the absence of cybersecurity literacy risks undermining the broader goals of digital governance and citizen empowerment. Drawing on nationally representative data from the National Sample Survey (79th round, 2022–23; N = 970,934), this study provides the first large-scale assessment of the distribution of cybersecurity literacy across socio-demographic groups in India. The results reveal that only 15.7% of individuals possess even basic cybersecurity competencies, with pronounced disparities across caste, gender, education, and age. Rural Scheduled Caste and Scheduled Tribe women emerge as the most digitally vulnerable group. Utilizing the Capability Approach as an analytical framework, the study argues that cybersecurity literacy is not merely a technical skill but a foundational capability for meaningful digital participation. Without targeted interventions to expand this capability, India’s digital transformation risks reinforcing structural inequalities and exposing marginalized populations to heightened digital insecurity.