Who are urban marginalized people

Photo Credit: https://humana-india.org/

In last 2-3 years, I have been part of several discussions to define and build a consensus on understanding of urban marginalised and vulnerable population (UMVP) in the context of India, and how this population group has been evolving and growing in numbers. India’s rapid urbanization over the past few decades has transformed its cities into economic powerhouses contributing 60% of India’s GDP. While in 2023 around 37% of India’s population lived in urban areas, it is estimated that by 2036, half of India’s population will live in cities. However, this growth has also led to the marginalization of a significant portion of the population. Cities Alliance estimated that 25% of the population living in urban areas are below the poverty line. By this estimate, a shocking 125+ million people are marginalised and vulnerable living in the urban areas. The urban marginalized and vulnerable groups comprising of slum dwellers, informal workers, migrant labourers, women, children, and the homeless face numerous challenges like access to basic citizens’ rights, services, and opportunities. As India continues its urban transition, addressing the vulnerabilities of these populations is critical to achieving inclusive development.

The UMVPs live in precarious conditions, often lacking access to basic services like clean water, housing, sanitation, healthcare, and education. Their vulnerabilities are shaped by socio-economic, cultural, political, and structural factors that leave them excluded from mainstream urban life. They often lack the necessary documentation to access government schemes and services, such as ration cards, Aadhaar cards, or voter identification. This exclusion prevents them from benefiting from welfare programs like the Public Distribution System (PDS), healthcare subsidies, or housing schemes. The UMVPs can broadly be classified in five sub-groups,

  1. Slum Dwellers: According to the 2011 Census, about 65 million people in India live in urban slums. Slums across India have poor housing, lack of sanitation, overcrowding, and a high risk of diseases, especially communicable. People living in the slums often have insecure tenure, making them vulnerable to eviction and displacement due to urban development projects. Displacement not only disrupts their livelihoods but also pushes them further into poverty. Poor living conditions contribute to health problems, including respiratory diseases (especially TB) and waterborne infections.
  • Homeless Population: India’s urban homeless population is particularly vulnerable, facing extreme marginalization. With no permanent shelter, the homeless are exposed to harsh weather conditions, violence, and health risks. They have limited access to government welfare schemes and often fall outside the purview of census data, making it difficult to design targeted interventions. HLRN estimates that there could be more than 3 million homeless individuals. Extreme poverty, unemployment, displacement due to natural disasters, mental illness, substance abuse, runaways, are often the causes of homelessness, and their numbers are continuously increasing in urban India.
  • Informal Workers: The informal sector accounts for nearly 80% of India’s urban workforce. This includes daily wage labourers, street vendors, domestic workers, and construction workers, among others. Informal workers lack job security, social protection, and access to formal financial systems, leaving them vulnerable to economic shocks. The COVID-19 pandemic exposed the extreme vulnerability of informal workers, who faced sudden job losses and had low-to-no access to financial aid. Informal workers often are slum dwellers, or live in low income housing colonies, or are even homeless.
  • Migrant Laborers: Migration to cities in search of employment and better life is common in India. However, migrant labourers, often from rural areas both intra- and inter-state, face significant challenges in urban settings. They often find employment in low-paying jobs with little to no benefits, live in temporary or inadequate housing, and struggle to access public services due to a lack of local identification documents. Temporary migratory population is also a sub-set of this group, who come to cities for seasonal work, migrate from one place to another, also migrate within the cities in search of work. Construction workers and artisanal nomadic groups can be good examples of migratory population.
  • Women and Children: Women and children within urban marginalized communities living in slums or informal settlements often work in low-paid informal jobs while managing household responsibilities. They are more likely to experience gender-based violence, discrimination and exploitation, limited access to healthcare, and lack of educational/skilling opportunities. Children in these settings suffer from malnutrition, poor schooling, and limited opportunities for social mobility. They often attend poorly equipped government schools or are forced to drop out to contribute to household income.

India’s urban marginalized and vulnerable populations represent a significant and often overlooked segment of society. Ensuring their inclusion in the country’s urban development is essential for sustainable and equitable growth, while bestowing opportunity and dignity for all citizens as their Right.

Data is Divine

In God we trust. All others must bring data.” This quote, made by W. Edwards Deming holds true (and may even supersede God for some as Divine).

I have been in love with data right from my school years and the mysteries of the world it holds. I have tried to develop data driven models on human relationships, the movement of animals, finding patterns in the ways of the world, and later designing programs of social impact for challenging poverty, and policy development. In the end, we all are data, from the moment we are an idea until long after we pass away.

“Data is divine” highlights the growing understanding of data’s vital significance in modern society, in much the same way that religious or spiritual values have directed civilizations throughout history. In today’s digital age, data powers innovation, decision-making, and advancement in all fields, including governance, research, business, healthcare, and lifestyle.

1. Data as a source of truth: Data is frequently regarded as an impartial depiction of reality, providing information on trends and occurrences that may be imperceptible to anecdotal experience or intuition. In this way, data has a unique position as the basis for making well-informed decisions and uncovering hidden facts.

2. The power of data in innovation: Data is driving advancements in domains like healthcare, finance, and climate science and is revolutionizing industries as it powers AI/ML and sophisticated analytics. This emphasizes how data has the “divine” ability to spark significant change. The use of data for enhancing human welfare, from preventing pandemics through data-driven epidemiology to lowering inequality by studying societal trends has been in use. When applied sensibly and morally, it can aid in resolving some of the most pressing issues facing society.

3. Data as omnipresent: From the apps we use daily to the systems that manage our cities, data is present everywhere in the modern world. Its pervasiveness is comparable to a certain “divine” quality in that it affects almost every facet of contemporary life, whether we are conscious of it or not.

4. Data and ethics: Data carries a great deal of responsibility along with its power. Similar to supernatural knowledge, there are significant ethical ramifications to the way we collect, use, and safeguard data. Data misuse can result in inequality, manipulation, and privacy violations. As a result, it is crucial to handle data with dignity, openness, and ethics.

“Data is divine” also implies that we must treat it with deference and accountability while simultaneously appreciating its immense importance in shaping our future. We need to balance the power of data with ethical considerations as our world grows more and more data driven. The following are some crucial strategies to preserve this equilibrium,

1. Data privacy and informed consent: People ought to be in charge of how their information is gathered, kept, and utilized. It is not appropriate to force them to divulge information. Companies must be open and honest about their data practices so that users know what information is being gathered and why. Clear and informed consent should not be buried in complicated terms and conditions. Data literacy is essential among general population so that they are aware of the consequences of disclosing personal information, and the dangers of data misuse.

2. Data minimization: Only gather information that is absolutely required for the current job. This reduces the possibility of abuse and shields people from needless exposure. I’ve seen in recent years how social development initiatives gather and store vast amounts of data, with donors coercing their nonprofit partners to obtain it, yet this doesn’t address any societal issues. It is crucial to have a conscious grasp of what is needed.

3. Data bias and fairness: AI/ML systems may reinforce or increase biases found in the training data. Therefore, diversifying datasets, employing inclusive development techniques, and reviewing algorithms for bias are all necessary to ensure fairness.

4. Equitable data access: One way to lessen inequality is to make sure that data access and its advantages are shared equitably among all communities. This entails preventing the reinforcement of systemic disadvantages while ensuring that marginalized groups have access to data-driven insights.

5. Data governance and accountability: To ensure that data is utilized properly, organizations and governments must establish robust data governance policies and ethical frameworks. To stay up with the latest developments in technology, these policies must be revised regularly. It is imperative to establish unambiguous lines of accountability for the handling and utilization of data. Data practices can be kept moral and in line with social standards with the support of independent oversight organizations or ethics boards.

6. Regulation and legal safeguards: Strong data protection laws that impose restrictions on how businesses and organizations can gather, keep, and handle personal data must be enforced by governments. Laws that address issues like accountability for algorithmic judgments, eliminating discrimination, and safeguarding human rights in AI-driven systems are crucial for the ethical application of automation and artificial intelligence. Because technology is changing so quickly, regulatory models must be adaptable and flexible to support innovation and enable quick responses to emerging ethical dilemmas.

7. Data for social good: Data can and should also be used positive social impact including lowering inequality and poverty, combating climate change, and improving public health. Governments, corporations, and civil society organizations working together can help guarantee that data is used morally and for the good of society. These collaborations may result in common frameworks for the ethical use of data.

A multifaceted strategy including legislation, transparency, public education, and proactive governance is needed to strike a balance between the power of data and ethical issues. Prioritizing the defence of individual rights, maintaining equity, and advancing the common good while fostering innovation should be the main goals of ethical data use. Through cultivating a culture of accountability and responsibility, we can leverage data’s promise (and divinity) without sacrificing moral principles.

Disclaimer: The opinions expressed are those of the author and do not purport to reflect the views or opinions of any organization, foundation, CSR, non-profit or others

Cover Photo: This is an AI generated image.