Economic and Social Council

✦ Topic A

Systems for Wealth Redistribution

1. Introduction & Background

Wealth and income inequality exist within and between countries, with differences influenced by wages, ownership of assets, education, taxation, employment opportunities, access to public services, and economic growth.

Governments use a variety of policies to redistribute economic resources. These can include progressive taxation, social transfers, pensions, unemployment benefits, public healthcare, education spending, and other social-protection measures.

Fiscal policy can reduce inequality through both taxation and government spending. The IMF describes fiscal policy as a major tool for addressing inequality, while research from the World Bank shows that taxes and transfers can reduce inequality but that their effects vary depending on their design.

However, redistribution remains controversial. Governments must consider questions of fairness, economic growth, incentives to work and invest, administrative capacity, and the financial sustainability of social programmes.

2. Key Issues & Challenges

A Progressive Taxation and Tax Burdens

Progressive taxation places a greater tax burden, relative to income, on higher-income individuals or households. Governments may use income taxes, capital-gains taxes, property taxes, inheritance taxes, or other measures.

The challenge is determining how progressive taxation should be without discouraging investment, entrepreneurship, or economic activity.

Countries also differ substantially in their tax capacity. A system that can be administered effectively in a high-income country may be more difficult to implement where informal employment or limited administrative resources are significant.

B Social Transfers and Public Services

Governments can redistribute resources through cash transfers, pensions, unemployment support, healthcare, education, housing assistance, and other social programmes.

Evidence from the World Bank indicates that taxes and transfers can reduce inequality, but their effects on poverty depend on how the programmes are structured. Indirect taxes, for example, can place proportionally greater burdens on lower-income households.

The key challenge is designing programmes that reach people who need them while maintaining sustainable government finances.

C Economic Growth vs. Redistribution

A major international debate concerns whether stronger redistribution supports or undermines economic growth.

Supporters of greater redistribution may emphasize reduced inequality, social stability, and improved access to education and healthcare. Others emphasize potential effects on investment, entrepreneurship, labour-market incentives, and government spending.

The IMF notes that equity and growth do not necessarily have to be opposing objectives, but outcomes depend heavily on policy design.

D Wealth vs. Income Inequality

Income refers mainly to money received over a period, while wealth includes accumulated assets such as property, financial holdings, and businesses.

This distinction creates different policy choices. Governments may focus on income taxes and transfers, while others consider property, inheritance, capital-gains, or wealth taxation.

The IMF's 2024 analysis discusses different approaches to taxing wealth and highlights debates surrounding capital-income, wealth, and inheritance taxation.

E International Differences in Redistribution

Countries have very different economic structures and fiscal capacities. OECD research shows that redistribution through taxes and transfers varies considerably between countries.

Developing countries may face additional difficulties such as large informal economies, limited tax collection capacity, and restricted public budgets.

This raises the question of whether international institutions should encourage common redistribution principles or allow countries to design systems according to their own economic circumstances.

3. International Perspectives & Stakeholders

High-income countries: Many have established tax-and-transfer systems but face debates over ageing populations, welfare costs, taxation, and long-term fiscal sustainability.

Developing countries: May prioritize expanding social protection while facing limitations in tax collection, public finances, and administrative capacity.

International financial institutions: Organizations such as the IMF and World Bank examine taxation, social spending, inequality, and economic development and provide policy analysis and technical assistance.

OECD countries: OECD research highlights differences in redistribution and examines how tax and benefit systems affect inequality and work incentives.

Businesses and investors: Businesses may be affected by changes to corporate taxation, capital taxation, wages, and social contributions.

Workers and lower-income households: These groups can be directly affected by social transfers, minimum-income policies, taxation, public services, and employment opportunities.

Civil society: Organizations concerned with poverty and inequality generally emphasize access to essential services and reducing economic disparities.

4. Previous International Action

International organizations have spent decades examining how taxation, social spending, and social-protection systems affect inequality.

The World Bank's Commitment to Equity work has analyzed the distributional effects of taxes and transfers across multiple developing countries. Its research found that taxes and transfers generally reduced inequality in the countries examined, although some combinations of taxes and transfers could have different effects on poverty.

The IMF has conducted extensive research on fiscal redistribution, including the effects of direct and indirect taxes and different types of transfers.

The OECD has also studied redistribution through taxes and transfers and differences in the effectiveness of these systems across countries.

Despite this work, there is no single international redistribution model. Major gaps remain concerning differences in national fiscal capacity, informal economies, tax avoidance, social-protection coverage, and the balance between redistribution and economic incentives.

✦ Topic B

Economic Effects of Algorithmic Decision-Making

1. Introduction & Background

Algorithmic decision-making refers to situations in which computer-based systems use data and predetermined rules, statistical models, or artificial intelligence to assist or make decisions.

These systems are increasingly used in areas such as employment, finance, logistics, healthcare, insurance, and online platforms. In workplaces, algorithmic management can involve systems assigning tasks, monitoring workers, evaluating performance, and organizing workflows. The ILO reports that algorithmic management is already used across several sectors and countries.

The growing use of these systems creates potential economic benefits. Algorithms can process large amounts of information quickly, improve efficiency, reduce certain administrative costs, and assist organizations in making decisions.

However, economic concerns also arise. These include biased outcomes, lack of transparency, worker surveillance, changes in job quality, unequal access to technology, and uncertainty about who is responsible when automated decisions cause harm.

The economic impact is therefore not limited to technology companies. It can affect workers, businesses, consumers, governments, and entire economies.

2. Key Issues & Challenges

A Productivity and Economic Efficiency

One potential benefit of algorithmic decision-making is improved efficiency. Algorithms can process information rapidly and help organizations allocate resources, manage workers, identify patterns, and automate repetitive tasks.

The ILO has found that algorithmic management can produce efficiency gains and improve service delivery in some contexts.

However, efficiency gains may not be distributed equally. The economic benefits may primarily reach companies or highly skilled workers, while other workers could face reduced job quality or displacement.

B Employment and Job Transformation

Automation can change the number and type of tasks performed by workers. Some occupations may become partially automated, while others may be transformed rather than eliminated.

ILO research on generative AI indicates that the effects differ significantly between occupations and countries, with some jobs more exposed to automation and others more likely to experience task transformation.

This creates challenges for education, retraining, labour protections, and social-security systems.

C Algorithmic Bias and Economic Discrimination

Algorithms can reproduce or amplify biases present in the data used to train or operate them.

If automated systems are used in hiring, lending, insurance, or other economic decisions, biased outcomes could affect people's access to jobs, credit, services, or other opportunities.

The challenge is particularly difficult because individuals may not understand how a decision was reached, while companies may be reluctant to reveal proprietary systems.

D Worker Surveillance and Job Quality

Algorithmic management can allow employers to monitor workers and track performance in ways that were previously difficult or impossible.

ILO research identifies worker surveillance and potential deterioration in job quality as important concerns associated with algorithmic management.

At the same time, employers may argue that monitoring systems can improve productivity, safety, and organizational efficiency.

E Unequal Access to Technology

The economic effects of algorithmic systems can vary depending on a country's technological infrastructure, education levels, digital skills, and access to investment.

ILO research on generative AI highlights differences between high-, middle-, and low-income countries in potential exposure and ability to benefit from new technologies.

This raises concerns about whether technological development could widen existing economic inequalities between countries and within societies.

3. International Perspectives & Stakeholders

Developed economies: Countries with strong digital infrastructure may benefit from increased productivity and investment but may also face significant labour-market disruption and regulatory challenges.

Developing economies: These countries may benefit from technological development and new economic opportunities while facing infrastructure, skills, and investment gaps that could limit their ability to capture the benefits.

Businesses and technology companies: Businesses may view algorithmic systems as tools for efficiency, innovation, cost reduction, and improved decision-making. They also face concerns about regulation, liability, and compliance costs.

Workers and trade unions: Workers may benefit from automation of repetitive tasks but can also face increased monitoring, changing job requirements, and reduced job security. The ILO emphasizes social dialogue and strong industrial relations as mechanisms for addressing these challenges.

Governments: Governments must balance innovation and economic competitiveness with consumer protection, labour rights, privacy, and accountability.

International organizations: Organizations including the ILO, OECD, and UN system examine how digital technologies affect employment, economic development, and inequality.

4. Previous International Action

International organizations have increasingly examined the economic and labour implications of algorithmic systems.

The ILO and European Commission's Joint Research Centre conducted research across France, Italy, India, and South Africa examining algorithmic management and its effects on work organization, job quality, and industrial relations. The research identified both efficiency benefits and concerns about surveillance and job quality.

The ILO has also studied the potential effects of generative AI on employment across more than 140 countries. Its research emphasizes that the impact varies according to occupation, income level, and the extent to which technology augments or automates tasks.

More broadly, international organizations have promoted discussion of responsible digital transformation, worker protections, skills development, and social dialogue.

However, major gaps remain. Countries differ considerably in their regulatory frameworks, technological capacity, labour protections, and ability to monitor algorithmic systems. There is therefore no single international approach to managing the economic consequences of algorithmic decision-making.