Abstract
Technological advancements in the field of Artificial intelligence (AI) are being adopted by society at large since it has the potential to change the way we transact. Conventional methods are being disrupted, and it has an enabling impact in most cases. In the Energy sector, the Digitisation model is being adopted, driven by AI technology. From Generation to Transmission, from demand to supply, all are now managed automatically with the help of smart algorithms that are almost human-like. These software applications optimise operations and aid decision-making. However, AI is yet to sit in the chair to make decisions because AI is still a utopian concept that may conflict with the co-existence of man and machine. This path could lead to economic downfall and have an adverse impact on sustainability.
This study aims to examine recent advances in AI technology and its use in energy supply and demand management, especially in the context of SDG 7. This transition from a conventional system to newer technological advanced management will impact leadership, necessitating a certain kind of training and education. Thus, the business and energy industry need to focus on adopting AI technologies, while public policies should be in place to regulate developments and their implementation to protect customer privacy, information security, and customer safety. This article combines perspectives from the energy industry and public policy to analyse the impacts of AI on Sustainable Development in the Energy sector. In conclusion, the paper draws some inferences for management/leadership amid state-of-the-art technological and social change in the Energy sector.
Keywords: Artificial Intelligence (AI), Sustainable Development Goals (SDG), Internet of Things (IoT), energy supply and demand, big data, energy digitisation
1.Introduction
In 2017, Warren Buffet, a very successful stock market investor, was asked about the impact of AI. He said, "AI is here to disrupt." Now, Warren Buffet knows a lot about investing, but he's not an AI expert. So, should we be concerned about what he said? The answer is yes, because AI is indeed changing the way we live. We have things like Siri, Alexa, self-driving cars, and smart technology that suggests things to us. Companies like Yahoo, Twitter, Amazon, and Google also use AI to provide us with helpful tools. For example, Google saved a lot of money using AI to manage its devices better (Kaplan and Haenlein, 2019). So, AI is already here and is changing our society. It's up to us to think about what we need to do. And policymakers need to make plans for a future where AI plays a big role. Right now, the world is on the edge of a big change with technologies like AI, Quantum Computing, and 5G. These technologies will affect how we communicate, live, work, and more.
Advancements in AI are important, but they need rules to make sure they help sustainable development. If we don't have rules, AI might not be transparent or ethical, which could be unsafe. AI has gotten really good at things like recognizing images, understanding speech, and making decisions, often doing better than people. Using AI and automation costs a lot of money, and this is connected to how well it works. Money is becoming the most important thing for making things happen, which could mean less need for human work and productivity. This might make inequality worse and cause big changes in society and the economy, unlike anything we've seen in a long time. All of this can have serious effects on how people live and on global goals for equality and development.
Machine Intelligence vs. Human Intelligence
Artificial Intelligence (AI) is like making machines smart with technology, so they can do things that seem like human thinking (Marr, 2018). But AI and natural human intelligence (NI) are different. AI is faster and usually works without breaks, while NI can be more impartial but sometimes makes biased decisions. NI can handle really tricky tasks better than AI and is better at doing many things at once. NI can also move around better, but AI can adapt quicker because it doesn't take thousands of years to change like NI. AI used to be expensive, but it's getting cheaper fast. It's becoming so good that it's replacing some human jobs, but not all at once. In the future, humans might merge with AI, and robots might become a part of us (Harari, 2017).
2.Growth of AI
AI had its beginnings in 1950 when Alan Turing came up with a test called the Imitation Game. This test helped tell if a response came from a human or a machine. Then, in 1956, John McCarthy organized a workshop called the Dartmouth workshop. This is where the term "Artificial Intelligence" was first used, and people who were interested in AI discussed the problems they wanted to solve. In the 1970s and 80s, computers became much more powerful, but AI was mostly a thing in research labs. In 1996, IBM's computer program Deep Blue did something big – it beat the world chess champion, Gary Kasparov. This made many people think that AI had become so smart that it could outthink humans, at least in a game that was considered very hard for a machine.
Figure 1: Growth of AI
The advent and subsequent rapid spread of the internet convinced computer scientists and researchers that computing and applications could be done in a distributed manner. In addition, advances in the field of big data, cloud computing, and neural networks have shaped AI into what it is today.
While AI can be categorised as Narrow, Strong, and Artificial General Intelligence (AGI), any machine capable of displaying or equipped with at least one human-like ability can be called artificially intelligent. In other words, humans are striving to make machines mimic natural intelligence. Thus, AI can be defined as the science that focuses on the development of functions similar to human intelligence, including cognition, reasoning, speech recognition, language skills, problem-solving, and the ability to respond to emergency situations. This multidisciplinary science calls for collaboration between various departments such as computer science, biology, psychology, linguistics, mathematics, and engineering, making AI unique and distinct from other technologies.
3.AI and Sustainable Development
Jeffery Sachs, Senior Advisor to the UN on SDGs and also the director of the UN Sustainable Development Solutions Network (USDSN), stated that the world is at an age where nations must collaborate and contribute to the eradication of poverty, social inclusion, economic justice, and environmental protection (Sachs, 2015).
He proposed a framework at the 2002 UN World Summit on Sustainable Development (WSSD) in Johannesburg, suggesting the four pillars of economic development, social development, environmental protection, and good governance as four components for analysing sustainable development (World Summit of Sustainable Development [WSSD], 2002, p. 2). However, Sachs did not take cognisance of newer technologies like AI. Thus, the impact of dynamic and evolving AI on Sustainable Development, which is emerging now, needs to be studied and utilised to its full potential.
Artificial General Intelligence (AGI), still a theoretical concept, has Human-Level Machine Intelligence (HLMI) (Artificial Intelligence, 2018), causing concerns that AGI will not only take away jobs but also replace humans as the superior species. Though the timelines are anyone's guess, jobs are being replaced through improved efficiencies in both production and supply chains. Such developments directly impact SDG #9 pertaining to Industry, Innovation, and Infrastructure and SDG #8 for Decent Work and Economic Growth favourably but have an adverse effect on SDG #10 and #1 because they do not reduce inequalities; rather, they bring in inequalities and poverty.
Some people believe that AI can help reduce inequality by sharing the benefits of increased production and efficiency, which aligns with SDG #10 (Reduced Inequalities). However, in the past, this hasn't happened because of a lack of awareness, people's efforts, and fair justice systems. While the future might be different, it's not realistic to think that those who create and own the next AI technology will give it away for free to everyone. Instead, they are more likely to use it to make themselves richer, which could widen the gap between those who have the technology and those who don't. This unequal distribution of wealth, knowledge, and power won't just be at the individual level but could also be concentrated in specific countries and cities. This would make global inequalities even worse and make it harder to achieve SDG #10 (Reduced Inequalities).
Instead, if nations rise above the goal of amassing wealth and keeping knowledge as their domain, as propounded by Jeffrey Sachs, AI can be harnessed in a wide range of economic sectors and situations to contribute to managing environmental impacts and climate change, which is humanly impossible. Some examples of applications include AI-infused clean distributed energy grids, precision agriculture, sustainable supply chains, environmental monitoring and enforcement, and enhanced weather and disaster prediction and response. Research by PwC UK, commissioned by Microsoft, models the economic impact of AI's application to manage the environment across four sectors—agriculture, water, energy, and transport. It estimates that using AI for environmental applications could contribute up to $5.2 trillion USD to the global economy in 2030, a 4.4% increase relative to business as usual. In parallel, the application of AI levers could reduce worldwide greenhouse gas (GHG) emissions by 4% in 2030, an amount equivalent to 2.4 Gt CO2e—equivalent to the 2030 annual emissions of Australia, Canada, and Japan combined.
At the same time as productivity improvements, AI could create 38.2 million net new jobs across the global economy, offering more skilled occupations as part of this transition. Recently, Stanford University launched an institute for Human-Centered Artificial Intelligence (HAI) that will bring together experts from various fields like economics, philosophy, ethics, psychology, and others (Marconi, 2019).
4.AI and Energy Management
The global economy is highly dependent on energy production and distribution (Jha et al., 2017). However, the current infrastructure in the energy sector, mainly the power grid infrastructure, is too old, inefficient, obsolete, prone to faults, and lacks inherent safety or protections under fault conditions. Furthermore, the conventional power grid infrastructure was not designed to accommodate the integration of Renewable Energy Sources (RES). The challenge to be addressed is the supply characteristics of RES in relation to the variable loads handled by the grid, and AI technology is seen as an effective and efficient solution. Since SDG #7 is about ensuring clean and affordable energy, it is imperative to adopt and deploy AI alongside traditional energy infrastructure because it is key to the development of agriculture, communications, healthcare, transportation, and, in other words, overall economic development. The lack of access to energy will hinder economic and human development.
The UN has established certain targets under SDG #7, which include ensuring universal access to affordable, reliable, and modern energy services, substantially increasing the share of renewable energy in the global energy mix, and doubling the global rate of improvement in energy efficiency by 2030. Sub-targets 7A and 7B also aim to enhance international cooperation to facilitate access to clean energy, research, and technology, and promote investment in energy infrastructure. This is intended to expand infrastructure and upgrade technology to provide modern and sustainable energy services for all in developing countries.
This is important because the United Nations' Sustainability Development Goals Report for 2022 shows that progress is being made towards sustainable energy goals. However, the rate of progress right now is not enough to reach Goal #7 by 2030. There are still significant differences in access to clean and sustainable energy. While the global access to electricity improved from 83% in 2010 to 91% in 2020, the number of people without electricity decreased from 1.2 billion to 733 million during that time.
From 2018 to 2020, the rate of electricity access increased by an average of 0.5% each year, which is slower compared to the 0.8% yearly increase from 2010 to 2018. At this current pace, only 92% of the world's population will have access to electricity by 2030, leaving 670 million people without it. The proportion of people using clean cooking fuels and technologies went up from 57% to 69% between 2010 and 2020. However, in 2020, 4 billion people still had to rely on inefficient and polluting cooking methods.
The share of renewables in total final energy consumption reached 17.7 per cent in 2019, which was 1.6 percentage points higher than in 2010. Lastly, the goals aim to address energy efficiency, where global primary energy intensity (energy efficiency) improved from 5.6 Mega Joules per US dollar in 2010 to 4.7 in 2019, with an average annual improvement rate of 1.9 per cent. To meet the energy efficiency target, the annual rate of improvement until 2030 will need to average 3.2 per cent a year. To achieve all the above-stated targets under SDG #7, it is essential for the global community to adopt AI technology to revolutionize the energy sector. From generation to control, forecasting, and efficient demand management, AI can handle these tasks with minimal human intervention. AI can manage efficient device control, such as transformers and inverters, and monitor power points. The role of AI in planning and forecasting load demand (Kong et al., 2018), forecasting solar energy (Rodríguez et al., 2018), forecasting wind energy (Ren et al., 2015), and forecasting hydro and geothermal energy (Debnath and Mourshed, 2018) has been well-established.
With the substantial increase in AI deployment and IoT in the energy industry and smart grid infrastructure control, cyberattacks have been studied, and solutions to prevent these attacks are increasing rapidly (Sani et al., 2019). These attacks can destroy infrastructure and exacerbate climate concerns (for example, if a cyber-attack destroys a nuclear power plant, it can be very harmful to the environment) and lead to significant economic losses. Can AI eliminate the possibility of cyberattacks? AI can help trace the suspects of attacks and determine what additional evidence is required to conclude automated investigative AI algorithms. The adoption and concept of AI and IoT will notably enhance the smart grid's security against cyberattacks (Sani et al., 2019). References (Minoli et al., 2017) and (Yang et al., 2017) provide solutions to prevent cyberattacks on smart grid infrastructure. AI's ability to handle large volumes of data is a significant benefit for power system protection. This is achieved by automating the development of security threat algorithms.
AI's digital technologies will enable the renewable energy industry in several ways, including the maintenance and operation of renewable energy sources, improved monitoring of power infrastructure, more secure system operations, and new market designs (International Energy Agency, 2017). Key innovations and dimensions in AI applications can be categorised into key components, including energy market design, business models, system operations, and enabling technologies (International Energy Agency, 2017).
Countries worldwide began outlining their AI strategies from 2017 onwards. The timelines are outlined by Dutton and are shown in the figure.
Figure 2: Timelines of AI Strategy by Dutton
Enunciation of AI strategies has made neural networks, expert systems, pattern recognition, and fuzzy logic models the focus of energy research (Demirci et al., 2019). During the research, it became evident that there are bottlenecks for adopting AI in the energy sector. The quality and, in some cases, the lack of data itself are the biggest bottlenecks. While Quantum computing works in favour of AI, it also increases the probability of hacking. While AI and sustainability go hand-in-hand, an AI algorithm currently produces an enormous carbon footprint, which has a reverse effect on other SDGs (Nishant et al., 2020).
Another challenge is the lack of AI skills and domain knowledge among decision-makers in the energy sector. While there are professionals with significant technical depth, there are few who possess both AI knowledge and the requisite experience in the energy sector to develop AI-powered applications for the energy sector. The existing power system infrastructure is definitely outdated and is not compatible with the requirements of AI-enabled systems. This necessitates a significant amount of capital investment and leads to the development of economic pressure, which developing countries are not capable of absorbing (Fickling, 2019). AI, being a black box concept for an ordinary consumer, fails to earn trust and is therefore one of the biggest hurdles to its acceptance
5. AI Technology and Management Leadership
Accepting AI is not just a technical matter; it's a social and technical issue because it depends on various factors, and the most important group involved is society, meaning all of us. There are challenges when it comes to accepting AI as a helpful tool, including cultural differences, trust problems, judgments, and especially ethical concerns. AI isn't perfect and can have biases in its algorithms, which can lead to harmful outcomes (Barocas et al., 2017). While people are still studying these biases, AI has the potential to help with things like energy and achieving the Sustainable Development Goals.
However, it will only work well if future managers and business leaders are ready to deal with the opportunities and challenges that come with this new technology. Deciding whether to use a certain technology can make or break an organization. Sometimes, using new tech can give a big advantage and lead to success, while other times, it's necessary just to survive. There are cases where companies failed because they couldn't adapt to technological changes. AI is one of those technologies in today's rapidly changing world during the Fourth Industrial Revolution.
However, AI's promise of increased efficiency and production comes with some drawbacks. To achieve their production goals, organisations must not only find but also retain competent talent. At the same time, businesses must be cautious about putting safeguards in place to reduce the hazards associated with AI. According to the AI Index report 2021, the hiring rate in all sample nations increased in 2020. From 2016 to 2020, the countries with the highest increase in AI hiring include Brazil, India, Canada, Singapore, and South Africa. India has a hiring Index of 2.8, the USA 2.1, and Singapore 2.5.
Figure 3: AI Hiring Index by Country, 2020 (Source: LinkedIn, 2020| Chart: 2021 AI Index Report)
The disparity among countries in the adoption of AI is evident in various reports, and thus there will be a divide between nations in capturing the potential benefits. To reduce this gap, it is considered essential that future leaders be taught the micro and macro levels associated with AI technology. At the micro level, Science, Technology, Engineering, and Mathematics (STEM) will play a vital role, as emphasized by Galperin, 2010; Ogunsola & Okusaga, 2006; Schwab, 2018.
At the macro level, the adoption of AI applications can reap great benefits. This can involve studying and analysing a problem, arriving at probable solutions, finding the optimal solution, which can be evaluated for its effectiveness. If found suitable, the knowledge can be shared worldwide.
Deep learning techniques can be used to train the network or the AI application about the problem, which can learn, store, compare, and recommend at a much higher pace than humans can even think of. This very ability is suggested by this paper to be utilised for solving the problems identified by the SDGs. This new model can facilitate remote data collection at the individual level and aggregate the results, which is otherwise not possible. The application can be made open-source, where anybody can add to the pool of knowledge. This can make it an educational and learning tool that learns with time and a changing environment. Thus, the education system must innovate to teach today's students, who will be tomorrow's leaders, about AI and the tools available in various sectors for economic growth and sustainable development of the nation.
The fact that future leaders will encounter niche technologies like AI in their work environments demands that the government take steps now to change the curriculum in a way that introduces the concept of data science and emphasises that data is the future fuel on which economies will run. More accurate input data will lead to reliable output recommendations. Nations that want to take the lead, including India, have started conducting hackathons, collaborative computer programming, etc., to solve global problems.
Due to AI being a capital-intensive technology, it is essential to be financially prudent and consider the availability of funds when making decisions regarding the implementation of AI in the respective systems. If managed well, AI could lead to a virtuous cycle of higher productivity, income growth, and more socially inclusive and environmentally responsible practices. When mishandled, even well-intended AI applications can result in unintended consequences and a backlash against the new technology.
AI is mainly used for the Sustainable Development Goals (SDGs) in countries that are good at AI. To help less advanced countries, they need to understand their specific problems and get help with education, startups, entrepreneurship, and governance to catch up in AI. Governments should work with companies and communities to use AI for goals like Industry, Innovation, Infrastructure (SDG #9), Sustainable Cities and Communities (SDG #11), and Partnerships for the Goals (SDG #17).
As far as SDG #7 is concerned, AI will be a star performer and will be able to harness advances in AI techniques to improve the integration of renewable energy, optimise load and its distribution, create a balance between accuracy and reliability of power supply, and defend against and detect cyber-attacks, among other things. In this regard, management education that helps future leaders understand and embrace this new world of AI intervention in everyday life will be key to individual success as well as a nation's future growth trajectory.
6. Conclusion
AI is a very important technology in the energy sector, and it's helping make the world more sustainable. Many people and groups are involved in this. The energy industry is changing, moving towards cleaner and more efficient ways of doing things, and AI is helping a lot with that. Countries using AI are doing better in terms of efficiency, saving important resources, and sharing knowledge for the benefit of the planet. But not all countries are using AI yet, and that can be a problem. Some countries need to overcome issues like not caring enough, not wanting to change, not knowing about AI, or not having enough resources. Governments also play a big role in this. Countries should think more about the long-term benefits for their own country and the whole world when it comes to AI and sustainability.
AI brings new technology and skills that can help us achieve the Sustainable Development Goals (SDGs). It can provide data to help us reduce waste and improve how we make, use, and recycle things. In the energy industry, this means collecting data about how energy systems work and how we measure it. AI can make these systems work better and cost less. But, since AI is still new, there are some risks to watch out for. We need to be careful and minimize any bad things that might happen because of AI. In the energy sector, AI can help operators manage everything from routine tasks to fixing problems with equipment. It can even predict when things need maintenance.
Thus, when used wisely for projects that promote sustainability, AI will open up enormous opportunities across geographies, enable more effective and efficient public policy for sustainability, and, more specifically, improve access, connectivity, and efficiency in industries like that of Energy.
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Healthcare in rural India presents unique challenges and opportunities. While global health metrics emphasize indicators like life expectancy, mortality rates, and healthcare infrastructure, they often fail to capture the socio-cultural nuances of rural communities
The “Internet plus” government service reform in China has progressed through three stages, namely one-stop service, one-window service, and companion service. This reform has become a significant example of reshaping the relationship between the local government and the public.
This paper explores the evolution of Indian welfare philosophy from Gandhi's nonviolent resistance to contemporary governance. It traces how the sacrifices of Indian revolutionaries fostered Sarvodaya and Antyodaya ideals, examining the philosophical underpinnings of these concepts in Advaita and dualistic traditions.
Like most other countries around the world, after the emergence of the COVID-19 pandemic, Bangladesh's education system has undergone a radical change from the beginning of March 2020 onwards. The study attempts to analyse teachers’, students’ and parents’ perceptions and experiences about the online education in the COVID-19 pandemic at the school level.
Health is a fundamental human right and a critical indicator of development. The 2030 Agenda for Sustainable Development emphasizes the importance of ensuring health and well-being for all individuals. A key objective of this agenda is to guarantee favorable health outcomes, underscored by the endorsement of a new declaration during the Global Conference on Primary Health Care held in Astana,…
In this article, published reports have been used for analysing state-wise status of SDGs achievements and their correlations with attainments in areas of poverty-reduction and other developmental indicators. Also, progress made by GPs on various metrics related to SDGs has been corroborated with other relevant metrics
Loss of governance reform efficacy is an identified entrenched institutional problem in systems. Reform, anywhere, is a sticky material because holders of powers and their cronies have rarely shown altruistic intentions of relaxing their profiteering grips over resources.
On September 1, 2023, a committee headed by former President Ram Nath Kovind explored the possibility of something called One Nation, One Election in India and ever since this thing has come out in public, political parties all across the country have been fuming with anger.
This paper examines various initiatives taken by Government of India to promote collaborative governance in various sectors. With increasing needs and aspirations of the community for public services and the limited capacity of government to provide the same, the involvement of various stakeholders to deliver these services becomes important and necessity.
In the vast and diverse landscape of India, regional disparities in development have long posed significant challenges to achieving equitable growth and social justice. Recognizing the urgent need to address these disparities, the Government of India launched the Aspirational Districts Programme in January 2018.
A dynamic interaction between the recognition of human complexity in organizations and the pursuit of structural efficiency has shaped the evolution of administrative philosophy. The foundational works of Frederick W. Taylor, Max Weber, Mary Parker Follett, Elton Mayo, Chester Barnard, Rensis Likert, Chris Argyris, and Douglas McGregor are critically examined in this essay, which charts the shift from traditional administrative…
In India, National Training Policy was formed in 2012, replacing the old policy of 1996. This was needed two reasons, new areas of administration given in the reports of second administrative reforms commission setup in 2005 and changing environment in different spheres of governance and new challenges of administration being faced by the civil servants.
India's emergence as a global services powerhouse in the 21st century marks a profound and transformative shift. This evolution, far from a mere economic change, is a strategic leap driven by its demographic dividend, technological advancements, and the burgeoning global demand for specialized services.
Public administration, as the executive arm of the state, has tremendous responsibilities to match the needs and aspirations of the citizens of the state. The systems have evolved over the years in almost every country as the politico and socio-economic environment of the respective country have changed.
Public administration is the cornerstone of modern governance. It refers to the organization, management, and implementation of government policies and programs, carried out by public officials and institutions. As a vital mechanism of the state, public administration not only ensures the effective delivery of services to citizens but also upholds the principles of accountability, transparency, and rule of law.
Tribal Sustainable Development through Evidence-based Policy and Planning: A major issue in post-Independence India has been a misreading of demands of tribal communities. What they have been demanding pertains to choice upholding their traditions and customs and having ownership over natural resources
As the Idiom of technological advancement takes its toll. The paper highlights a few poignant and emerging factors in the International Relations theorization. It was conservatively maintained by the defense strategists and the political leadership across the Global polity that foreign policy and the Diplomacy are greatly determined by the “given” of Geography and terrain
With the deepening of democracy, increased decentralisation, increasing social and political awareness, digital penetration, shifts in demography, demand for quality services by common citizens has been accelerating at a faster pace. In such a scenario, the role of State is critical for promoting equity in access to services.
"Accelerating India's Development" holistically looks at India’s growth trajectory since gaining independence – it rounds up all where it has done well including unity, upholding the integrity of its constitution, retaining democratic values at its core. It also does not mince words to convey where all the nation has faltered such as falling short in delivery of public services including…
Income and Employment Intensive Growth Agenda for India: The paper examines income and employment status in the Indian labour force to identify policy attention and follow up. The macroeconomic policies taken during last one decade are yielding positive results leading to expansion of manufacturing and services and structural transformation in the economy.
An Analysis of India's Social Welfare Programs: In a democracy, the state's role is to promote societal welfare. According to Aristotle, the state should not only ensure its survival but also improve the quality of life for its citizens. The state has a moral responsibility to its citizens. Modern views agree that the state should provide essential services like education,…
Digital Innovations in Social Protection: Trends, Challenges, and Solutions: The integration of digital technologies into social protection systems represents a transformative shift with profound implications for the delivery of welfare services. This chapter explores the evolving landscape of digital innovations in social protection, contextualising these developments within the broader framework of universal social protection and a systemic approach to welfare.
One of the most crucial aspects of our society is law enforcement, which deals with issues of law and order nationwide. It is an essential component of the state's legal system. The British government introduced a Police Act in 1861, which is still very relevant and based on policing.
India’s Vision for 2047 aims to transform the nation into a developed country, with healthcare being pivotal for this progress. Achieving universal health coverage and modernising healthcare infrastructure are essential for fostering a healthy productive population, which in turn drives economic growth and reduces poverty.
Several challenges linger in the Indian education system, like rote learning, the non-existence of practical skills among students, and disparities in access to quality education. To deal with the criticism for excessive curriculum and unreasonable focus on rote learning, this chapter examines the strategies comprising the building blocks to reform Indian schools.
Social development is expected to promote holistic improvement of individuals, institutions and their surrounding environments. Looking at the pace of development in India, the economy of most states requires strategic prioritization to accelerate improved well-being of the people. Accessibility to health, school education and public security are critical to the edifice of social development.
India is the largest democracy in the world inhabited by about 1.36 billion people over an area of 3287 thousand square kilometers according to an estimate for 2021 based on Census 2011. The Indian economy is characterised as a middle-income emerging market economy. In the last three decades the economy has faced three major crises, i.e., balance of payment crisis…
Neoliberal policies pursued by India since 1990s have created a space for private enterprises hitherto occupied by the state entities, unshackled the existing enterprises and introduced reforms to facilitate private initiative. This chapter looks into the ecosystem of the private sector in general and the developments in three specific sectors- urban mobility, water supply and housing, to draw lessons for…
This Chapter highlights the gradual transformation from Personnel Administration to Strategic Human Resource Management over the years in Government of India. However, there is still a long way to go. In this Chapter an attempt has been made to delineate the criticality to move towards Strategic HRM in Government of India to achieve India’s developmental goals.
Robust statistical data forms the cornerstone of an informed governance system. This paper studies the statistical system and data dissemination in the Centre and State governments in India, and the measures put in action to accelerate the data dissemination process. Arguing that the availability of high-frequency statistical data is a necessary condition for good governance, the first section of the…
In the Amrit Kaal (golden period) of independent India, the ‘citizen first’ approach guides public governance by deepening the outreach of service delivery mechanism so that international standards could be achieved in India@100. The goal can only be achieved by all inclusive governance involving stronger and effective local self-governments both panchayats and municipalities.
In modern societies, with the increasing role of the state in social and economic fields, emphasis on the quality of its governance is of prime concern to all. Indian bureaucratic system of governance is founded on the principle of rule of law, as the state power is divided amongst three chief organs, each has the its own quality under a…
This paper discusses the concept of good governance and its relations with the electoral politics in Indian context. It highlights the various strategies employed by the government and related agencies for the growth and development of the country. Major reforms pertaining to the country’s infrastructure, IT, administration, economy and public services are a few areas that have been explored in…
With the Indian government’s vision to transform India into a developed nation by 2047, marking hundred years of independence, it has become of highest importance to learn from the past, tenaciously work in the present and step towards the future with complete efficiency. In its 77 years of becoming a democracy, India has soared high with continuous transformations marked by both…
The vision of Viksit Bharat can be realised through Viksit States, and that the aspiration of Viksit Bharat should reach the grassroot level i.e. to each district, block, and village. For this, each State and District should create a vision for 2047 so as to realise Viksit Bharat @ 2047.