Bridging Gaps: Harnessing Policies and Technology for Inclusive Development

 Bridging Gaps: Harnessing Policies and Technology for Inclusive Development

Rahul Ramya

26.01.2025

Patna, India

In this era of rapid automation and artificial intelligence, where human labor faces displacement, the insights of Acemoglu, Robinson, and Johnson—the 2024 Nobel laureates in Economics—offer a guiding light. Their groundbreaking research illustrates how policies have historically influenced technological progress over the last millennium. They demonstrate that the outcomes of technological advancements are not inherently determined by technology itself but by the policies that govern its development and deployment.

Their studies reveal a critical dichotomy: when policies foster inclusivity and prioritize broader societal benefits, technology catalyzes widespread prosperity, reducing inequality and fostering social harmony. On the other hand, when policies serve narrow interests, favoring elites or specific groups, the same technological growth exacerbates inequality, concentrating wealth and power in the hands of a few, leading to societal unrest.

This historical perspective underscores a vital lesson for today. The societal trajectory of automation and AI will depend on the policies we adopt. Inclusive policies that ensure equitable access to opportunities and benefits can transform these technological revolutions into engines of collective progress. Conversely, exclusionary policies risk deepening societal divides, destabilizing economies, and fostering discord.

The message is clear: technological progress is a double-edged sword. Its true impact lies in how we choose to wield it, through policies that can either empower societies or marginalize them.

While the arguments put forth by Acemoglu, Robinson, and Johnson may spark debate, the results of their studies are difficult to refute. Their conclusions are backed by robust data, compelling facts, and real-world examples that span centuries of economic and social development. These studies do not merely rest on theoretical models; they are anchored in the lived experiences of societies that have risen or faltered based on the inclusivity of their policies.

For instance, historical episodes like the Industrial Revolution in Britain, the rise of Silicon Valley, or the spread of digital technologies in Scandinavia demonstrate how inclusive policies can channel technological progress toward general prosperity. Conversely, examples such as colonial exploitation, where technological advancements served imperial powers while marginalizing local populations, illustrate the dangers of exclusionary policies.

What makes their findings resonate universally is the clarity with which they show that policy choices are decisive. Whether technology becomes a force for equality or inequality, progress or unrest, depends not on the technology itself but on the institutions and governance shaping its application. This makes their work an invaluable resource in understanding how to navigate the complex interplay of technology, economy, and society in today’s AI-driven era.

Thus, even amidst debates, the empirical strength and real-world relevance of their findings leave little room to deny their significance.

This makes it clear that it is not automation and AI that have threatened our society with mass-scale job loss. The truth is that, despite their potential to cause such drastic changes, it is our policies that enable these technologies to replace humans with machines. If we implement policies that empower individuals to enhance their knowledge and skills, these technologies can become trusted companions of human labor, augmenting its capabilities and productivity. In this way, we can transform an unproductive or less efficient labor force into a highly capable and significantly more productive workforce. Moreover, knowledge and skills are not sufficient on their own unless they are well integrated with supporting infrastructure and logistics.

Prompt 1: It is not automation and AI that have threatened society with mass-scale job loss, but our policies that enable these technologies to replace humans. Policies empowering individuals to enhance knowledge and skills can turn these technologies into companions of human labor, enhancing productivity and transforming an inefficient workforce.

Explanation with Real-World Examples:

 1. Germany’s Dual Education System

Germany has successfully mitigated the risks of automation by investing heavily in skill development through its dual education system, which combines vocational training with academic education. This approach ensures that workers acquire practical skills relevant to emerging technologies. As a result, automation in industries like manufacturing has enhanced productivity without significant job losses. Robots in German automotive factories, for instance, work alongside skilled workers, boosting both efficiency and employment in high-skilled roles.

 2. India’s AI in Healthcare

In India, AI-based diagnostic tools are being integrated into healthcare, particularly in rural areas. For example, tools like AI-powered tuberculosis detection systems allow healthcare workers to diagnose diseases quickly and accurately. However, the success of such initiatives depends on training healthcare workers to use these tools effectively. With supportive policies that promote skill development, these technologies augment human effort rather than replacing it, addressing labor shortages in critical sectors.

 3. Contrast: The U.S. Rust Belt

In contrast, the U.S. Rust Belt offers an example of what happens when policies fail to address the challenges posed by automation. The region experienced mass job losses as manufacturing industries automated processes without investing in reskilling displaced workers. This policy gap led to economic decline and social unrest, showcasing the crucial role of inclusive policies in adapting to technological change.

 4. Kenya’s M-Pesa and Mobile Banking

Kenya’s M-Pesa revolutionized financial access in rural areas, not just because of knowledge and digital literacy, but because the initiative was supported by robust infrastructure, including mobile network coverage and agent networks in remote locations. Without the logistical backbone to facilitate mobile transactions, the skills of individuals to use the system would have been ineffective.

 5. India’s Digital Literacy Mission and Lack of Connectivity

India’s Pradhan Mantri Gramin Digital Saksharta Abhiyan (PMGDISHA) aimed to make rural citizens digitally literate. While millions received training, the initiative faced hurdles in regions lacking internet connectivity and reliable electricity. This example highlights that knowledge and skills alone cannot yield results without adequate infrastructure to support their application.

 6. South Korea’s Smart Cities

South Korea’s development of smart cities, such as Songdo, exemplifies the seamless integration of knowledge, skills, infrastructure, and logistics. Advanced education programs train citizens to operate smart systems, while robust infrastructure, such as high-speed internet and IoT-enabled services, ensures that skills translate into productivity and improved quality of life.

These examples illustrate that the impact of technology and skills depends on a supportive environment that integrates infrastructure and logistics into the system effectively.

Fast forward to today’s India, where a significant portion of the workforce, despite being engaged in various economic activities, remains largely or entirely untrained. Due to a lack of knowledge and skill training, these workers are not only poorly productive and poorly paid but are also unable to fully benefit from the growing Indian economy. Their integration into the national economy, in terms of wages and earnings, remains minimal. Furthermore, their low productivity makes them vulnerable to being replaced by machines, as no economy in this highly competitive world can afford to sustain untrained and unproductive workers.

Explanation with Examples

 1. Unorganized Sector in India

A majority of India’s workforce is employed in the unorganized sector, including agriculture, construction, and small-scale industries. For example, agricultural workers often lack training in modern farming techniques and remain dependent on traditional methods. This not only limits productivity but also keeps their earnings low. Without access to skill development programs, they are unable to transition to more productive roles in emerging industries.

 2. Textile Industry

India’s textile and garment industry, a major employer, faces a dual challenge: global competition and low productivity due to an untrained workforce. Workers often rely on outdated methods, reducing their efficiency. Countries like Bangladesh, with a more skilled workforce, have surpassed India in textile exports. Initiatives like the Samarth Scheme for Capacity Building in the Textile Sector aim to address this issue by providing skill training to workers, but the coverage is still inadequate.

 3. Skill Development Mission and Gaps

While programs like the Skill India Mission and PM Kaushal Vikas Yojana (PMKVY) have been launched to train workers, their reach and impact are limited. For instance, a report by the Ministry of Skill Development and Entrepreneurship found that a large portion of those trained under PMKVY failed to secure meaningful employment due to a mismatch between training and market demands.

 4. Threat of Automation in Manufacturing

The rise of automation in sectors like automotive manufacturing poses a significant risk to untrained workers. For example, in Tamil Nadu, which is a hub for automobile production, factories are increasingly using robots for repetitive tasks. Without proper training, many workers in this sector may find themselves displaced as industries prioritize efficiency and cost-effectiveness.

Way Forward

To integrate this untrained workforce into the growing economy:

   •   Skill Development: Initiatives like PMKVY should be expanded with a focus on region-specific and industry-relevant skills.

   •   Infrastructure Support: Training must be complemented with infrastructure like digital connectivity, modern equipment, and affordable training centers.

   •   Linking Training with Employment: Programs should ensure a direct pipeline from skill training to employment opportunities in high-growth industries like renewable energy, IT, and healthcare.

By addressing these challenges, India can transform its unproductive labor force into a skilled and competitive workforce, enabling them to contribute effectively to the nation’s economic growth.

Besides all this, it is an undeniable fact that generating employment for such a large workforce is an extremely challenging task for any economy. Moreover, the time lag between acquiring training and becoming productively employed does not depend solely on the training itself. Establishing a well-structured system of production and services requires meticulous planning and the integration of various logistics and support systems. This includes creating infrastructure, ensuring market readiness, building demand for skilled labor, and fostering an environment where trained workers can thrive. Without these complementary measures, even the most robust training initiatives may fail to yield meaningful employment opportunities.

An alternative approach is to focus on equipping the working-age population, both male and female, with the necessary skills to become either productively self-employed or employed in private establishments at both local and national levels. This strategy involves fostering entrepreneurial capabilities, providing access to credit and resources, and ensuring skill training that aligns with market demands.

For example, encouraging women to engage in self-employment through initiatives like small-scale food processing units or tailoring businesses can boost local economies while also addressing gender gaps in employment. Similarly, men in rural areas can benefit from training in modern agricultural practices, carpentry, or digital services, enabling them to find work in private enterprises or start their own businesses.

At the national level, private establishments in high-growth sectors like IT, renewable energy, and e-commerce can absorb a significant portion of the trained workforce. However, this requires collaboration between governments, industries, and training institutions to ensure that skill development programs are demand-driven and regionally tailored. Additionally, measures such as microfinance support, ease of doing business reforms, and digital marketplaces can empower self-employed individuals and small entrepreneurs to scale their ventures and contribute meaningfully to the economy.

By focusing on both self-employment and private sector integration, this approach can provide sustainable livelihoods and reduce the strain on governments to generate direct employment opportunities.

This approach requires a synthesis of local and national perspectives. Achieving this involves area-specific skill training and creating employment opportunities tailored to regional needs. India, with its rich repository of traditional labor-intensive economic activities and indigenous knowledge, holds immense potential. However, in today’s era of advanced technology, traditional methods must be modernized, updated, and integrated with contemporary technologies and financial systems to remain relevant and effective.

This modernization can be achieved in several ways, as discussed in my essay Building Inclusive Economies: A Holistic Approach. One approach is to identify the specific needs of each local area and align skill training with other critical factors such as demographics, socioeconomic conditions, educational achievements, and existing skill levels. Simultaneously, geographical features and resources of the area should also be considered.

Key Steps in the Approach:

 1. Need-Based Training Programs:

Training programs should be tailored to the specific needs of the region. For example, in coastal areas, training in aquaculture and marine-related industries could be prioritized, while in agricultural zones, modern farming techniques and agro-processing could be the focus.

 2. Integration of Local Universities and Industries:

Local universities, industries, and manpower resources should be involved in designing customized training courses and curricula. For instance, universities in textile-rich regions like Gujarat and Tamil Nadu could collaborate with textile industries to modernize traditional skills, such as weaving, and integrate them with automation and AI technologies.

 3. Role of Premier Institutes and Local Trainers:

Leading institutes or industries in each region should be made primarily responsible for overseeing the entire training ecosystem. These entities should employ local trainers who have the expertise to impart relevant skills, ensuring the program remains rooted in the community’s cultural and economic context.

 4. Minimizing Bureaucratic Intervention:

To enhance efficiency and responsiveness, government bureaucracy should play a minimal role. Instead, existing training institutes, universities, and industries should take the lead in managing and delivering training programs, with minimal administrative hurdles.

 5. Focus on AI, Automation, and Digital Technologies:

Training programs must integrate traditional knowledge with cutting-edge technologies. For example, traditional artisans could be trained to use AI-powered design tools to enhance productivity and create globally competitive products. Similarly, farmers could learn precision farming techniques that utilize automation and IoT devices.

Real-World Applicability:

   •   Madhubani Art in Bihar: Traditional Madhubani artists could be trained in digital marketing and e-commerce to sell their art globally, while also integrating modern tools to innovate their designs.

   •   Tea Plantations in Assam: Local youth could be trained in value-added processes like packaging, branding, and quality control, integrating traditional tea cultivation methods with modern production techniques.

   •   IT Hubs in Karnataka: Programs that upskill individuals in AI, data analytics, and software development could be introduced, leveraging Karnataka’s strong IT ecosystem while incorporating local manpower.

By aligning training subjects with local geographical, demographic, and socioeconomic needs, and incorporating AI and digital technologies, this approach can create a sustainable model of development. It fosters inclusivity, enhances productivity, and ensures that the benefits of growth are shared across diverse regions and communities.

This strategy will play a crucial role in equipping a vast population with modern technological skills, enabling them to pursue self-employment or secure jobs in various industries and services. By enhancing the skill set of the workforce, this approach will significantly improve labor productivity, thereby boosting the employability and bargaining power of skilled workers.

Simultaneously, it will create opportunities for entrepreneurs to establish new businesses and industries, which, in turn, will generate more employment opportunities. Workers and other participants will find increased avenues to integrate into the economy with higher income levels, leading to a ripple effect of economic growth and prosperity.

Moreover, this initiative will foster integration at multiple levels—locally and nationally, as well as nationally and internationally. Such integration will not only address issues related to unemployment and income inequality but also encourage the emergence of new industries and facilitate upward social mobility. It will provide individuals with greater access to economic opportunities and educational advancement, ultimately contributing to a more inclusive and dynamic economy.

This type of policy choice—focusing on equipping the workforce with modern technological skills and fostering integration with economic systems—will demonstrate that automation and AI can act as allies rather than competitors to human labor.

How Policies Turn AI and Automation into Allies:

1. Enhancing Human Capabilities:

Automation and AI, when integrated with skill development programs, can complement human labor rather than replace it. For example, AI-powered tools in agriculture, such as precision farming technologies, can help farmers make better decisions, leading to higher yields. This does not eliminate the need for human farmers but enables them to be more productive and profitable.

2. Creating New Job Opportunities:

While automation can perform repetitive tasks, it creates new roles in fields such as AI development, maintenance, data analysis, and technology management. Policies that focus on reskilling and upskilling workers ensure that they can transition into these emerging roles. For instance, India’s IT industry has embraced AI and automation to create jobs in machine learning, cybersecurity, and cloud computing, demonstrating that technology can generate employment rather than reduce it.

3. Fostering Entrepreneurship:

By reducing production costs and improving efficiency, automation and AI can lower entry barriers for small businesses. Policies that encourage training in digital tools enable entrepreneurs to leverage technology for starting and scaling businesses. For instance, e-commerce platforms in India like Flipkart and Amazon have allowed small-scale artisans and manufacturers to reach national and international markets using AI-driven logistics and marketing tools.

4. Improving Workforce Productivity:

When workers are trained to work alongside AI and automation systems, their productivity increases. For example, in healthcare, AI diagnostic tools assist doctors in identifying diseases more accurately and quickly, enabling them to treat more patients in less time. Policies that integrate such technologies into the workforce create a synergistic relationship between humans and machines.

5. Mitigating Fear of Job Displacement:

Without appropriate policies, automation can displace unskilled labor, leading to unemployment and social unrest. However, when governments and industries implement skill-building initiatives, they empower workers to adapt to technological changes. For example, the Skill India Mission aims to train millions of workers in fields like AI, robotics, and data science, ensuring they can thrive in a tech-driven economy.

6. Facilitating Inclusive Growth:

Automation and AI can bridge gaps in accessibility and efficiency when deployed thoughtfully. For instance, AI-based tools are being used to provide remote education in rural India, ensuring that students in underprivileged areas can access quality learning resources. Policies that align technology deployment with societal needs turn AI into a tool for empowerment rather than exclusion.

Conclusion:

By adopting policies that prioritize skill development, workforce integration, and technological inclusivity, automation and AI can transform from perceived threats into essential allies of human labor. These technologies, guided by the right policies, enhance human capabilities, create new opportunities, and promote inclusive economic growth, proving that automation and AI are not competitors but trusted partners in progress.