Hemachandran / Rodriguez / Rincon AI for Our Planet: How Artificial Intelligence can Solve Global Challenges

1. Auflage 2026
ISBN: 979-8-89881-369-7
Verlag: De Gruyter
Format: EPUB
Kopierschutz: 0 - No protection

E-Book, Englisch, 260 Seiten

AI for Our Planet: How Artificial Intelligence Can Solve Global Challenges brings together insights from leading scholars and industry experts to examine the responsible and strategic use of AI in addressing pressing global challenges, including climate change, resource scarcity, environmental degradation, ethical governance, and socio-economic inequality.
Across sixteen multidisciplinary chapters, the book positions AI not only as a transformative technological tool but also as a framework for building a sustainable and equitable future. Featuring real-world case studies on AI-driven governance, ethical and regulatory frameworks, climate diplomacy, circular economies, renewable energy, and sustainable resource management, the book offers forward-looking insights into AI's expanding global impact.
Key Features
Multidisciplinary perspectives integrating AI, sustainability, governance, and public policy
Evidence-based discussions supported by real-world case studies
Coverage of ethical, regulatory, and responsible AI deployment framework
Practical insights into AI applications for climate action, resource management, and circular economy models
Forward-looking analysis of AI's role in global development and environmental stewardship
AI for Our Planet: How Artificial Intelligence Can Solve Global Challenges brings together insights from leading scholars and industry experts to examine the responsible and strategic use of AI in addressing pressing global challenges, including climate change, resource scarcity, environmental degradation, ethical governance, and socio-economic inequality.
Across sixteen multidisciplinary chapters, the book positions AI not only as a transformative technological tool but also as a framework for building a sustainable and equitable future. Featuring real-world case studies on AI-driven governance, ethical and regulatory frameworks, climate diplomacy, circular economies, renewable energy, and sustainable resource management, the book offers forward-looking insights into AI's expanding global impact.
Key Features
Multidisciplinary perspectives integrating AI, sustainability, governance, and public policy
Evidence-based discussions supported by real-world case studies
Coverage of ethical, regulatory, and responsible AI deployment framework
Practical insights into AI applications for climate action, resource management, and circular economy models
Forward-looking analysis of AI'AI for Our Planet: How Artificial Intelligence Can Solve Global Challenges brings together insights from leading scholars and industry experts to examine the responsible and strategic use of AI in addressing pressing global challenges, including climate change, resource scarcity, environmental degradation, ethical governance, and socio-economic inequality. Across sixteen multidisciplinary chapters, the book positions AI not only as a transformative technological tool but also as a framework for building a sustainable and equitable future. Featuring real-world case studies on AI-driven governance, ethical and regulatory frameworks, climate diplomacy, circular economies, renewable energy, and sustainable resource management, the book offers forward-looking insights into AI's expanding global impact. Key Features
Multidisciplinary perspectives integrating AI, sustainability, governance, and public policy
Evidence-based discussions supported by real-world case studies
Coverage of ethical, regulatory, and responsible AI deployment framework
Practical insights into AI applications for climate action, resource management, and circular economy models
Forward-looking analysis of AI's role in global development and environmental stewardship

Autoren/Hrsg.

Hemachandran, K

Rodriguez, Raul Villamarin

Rincon, Manuel

Acereda, Alberto

Joshi, Himanshu

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz

Leseproben

AI and Governance: Criss-crossing the Innovation Valley

Rior Santos1, *

1 Department of Sociology and Behavioral Sciences, College of Liberal Arts, De La Salle University, Manila, Philippines

Abstract

This chapter explores the intersection of Artificial Intelligence (AI) and governance, emphasizing the public sector's dual role as an innovator and a regulator. It begins with a theoretical foundation on innovation, defining its dimensions and triggers, as articulated by thinkers such as Schumpeter and Christensen. The discussion highlights how innovation extends beyond economic motives, with the public sector playing a significant role in fostering societal advancement. The chapter addresses the perception of the public sector as resistant to innovation, showcasing examples of ICT advancements in Southeast Asia, including e-government initiatives in the Philippines. Despite bureaucratic and institutional challenges, these cases demonstrate how the public sector has successfully utilized technology to improve transparency, efficiency, and citizen engagement. The transformative potential of AI is categorized into three areas: streamlining bureaucracy, enhancing democratic accountability, and improving public service delivery. Applications include automated tax compliance, corruption-resistant procurement processes, citizen engagement platforms, and efficient resource allocation in sectors like healthcare and transportation. Challenges such as data bias, ethical concerns, and environmental impact are discussed alongside the need for a robust regulatory framework. The chapter advocates for ecological safeguards, human accountability in the use of AI, and equitable access to AI innovations. International cooperation is critical for establishing global norms and inclusive AI governance. Ultimately, the chapter affirms that the public sector, by balancing innovation with oversight, can harness AI to foster accountability, inclusiveness, and sustainable development.

Keywords: Artificial intelligence, Bureaucracy, Citizen engagement, Data bias, E-Government, Environmental safeguards, Ethical AI, Governance, ICT, Innovation, International cooperation.

* Corresponding author Rior Santos: Department of Sociology and Behavioral Sciences, College of Liberal Arts, De La Salle University, Manila, Philippines; E-mails: [e-mail], [e-mail]

INTRODUCTION

Discussing Artificial Intelligence (AI) in the context of governance is impossible without first addressing the concept of innovation. This chapter argues that the public sector can serve both as an innovator and a regulator of AI. The structure begins by defining innovation and identifying its triggers, then explores its broader, public-oriented motives. Ultimately, it reflects on how AI intersects with governance as a form of innovation.

INNOVATION DEFINED

A key early figure in the study of innovation is Joseph Schumpeter. As defined by Joseph Schumpeter [1], innovation is the act of “doing things differently in the realm of economic life.” For Paul Sweezy [2], this is not solely attributed to an activity that instigates change or novelty but is associated with an individual or a set of individuals who “must be able to overcome the psychological and social resistances which stand in the way of doing new things; he must, in short, have the qualities of leadership.” Thus, Sweezy connotes that innovation is a mindset of initiating changes that challenge the status quo.

Another distinct viewpoint on defining innovation is provided by Clayton Christensen's concept of disruptive innovation. According to Christensen [3], disruptive innovations generate new value networks and markets, which in turn cause existing markets to become disrupted and established enterprises to be replaced. Targeting underserved client segments, disruptive innovations frequently begin at the lower end of the market and work their way upmarket, taking on more established rivals. Finally, in contrast to conventional ideas of closed, internal Research and Development (R&D), Henry Chesbrough established the concept of open innovation. The definition of open innovation, according to Chesbrough [4], is “a distributed innovation process based on purposively managed knowledge flows across organizational boundaries.” According to this paradigm, entities use internal and external ideas and technologies to enhance their innovation processes.

As a note, innovation differs from creativity as innovation focuses on the application of creative ideas within a social context. According to Amabile and Pratt [5], they claimed that based on existing literature, creativity involves the production of novel and valuable ideas by an individual or a small group of individuals working together.” On the one hand, Amabile and Pratt [5] defined innovation as “the successful implementation of creative ideas within an organization.”

Dimensions of Innovation

Apart from studying the definition of innovation, innovation can be analyzed in different dimensions. Each dimension offers unique perspectives on various facets of the innovation process and its results. There are three primary dimensions of innovation, to wit:

• Innovation in Process versus Product: Innovation is sometimes divided into two categories: process and product innovations. Process innovation pertains to advancements in production or delivery techniques, while product innovation is the creation of novel or markedly enhanced products or services [6]. One example of product innovation is the creation of the automobile, whereas a process innovation would be the application of lean manufacturing principles.
• Radical versus Gradual or Incremental Innovation: Radical innovation refers to important discoveries that open new markets or drastically change existing ones. This can be like the creation of the cellular phone or the first electric car. Conversely, incremental innovation refers to the methodical and slower-paced enhancement of current goods, services, or procedures. Long-term advancement is facilitated by incremental innovations, which are frequently less hazardous and easier to handle [7].
• Technological versus Non-Technological Innovation: Technological innovation refers to improvements in science and technology, whereas non-technological innovation includes adjustments to business models, marketing plans, and organizational procedures. Non-technological innovations, such as innovative business models or new approaches to customer service, can also play a significant role in propelling organizational success [8].

Determinants of Innovation

The previous section established the nature and dimensions of innovation. However, taken as a singular act, innovation has its own set of triggers. These triggers can be perceived to be primarily social.

Zaltman et al., [9] argue that a critical part of innovation is the cultural openness to innovation. Accordingly, innovation in an organization has a broad spectrum; depending on the intention of the innovation, it spans from the capacity to introduce a new product, service, or idea to the introduction of processes and systems that can lead to better business performance. In such a broad spectrum, cultural openness to innovation plays a crucial role in innovation. To assert this further, Van de Ven’s [10] study illustrates the connection between market orientation and innovation. Therefore, recognizing the need for innovation requi- res the organization’s cultural attention through cultural openness. This focus, in turn, determines whether initiatives for innovation are adopted or rejected.

Similar to Zaltman et al., [9], Tekin and Tekdogan [11] examined how cultural factors influence the innovation capacity of societies. Using the Hofstede Index, which measures cultural differences, the authors analyze the relationship between culture and innovation. They argue that cultural conditions, such as individualism, low power distance, and a positive attitude toward risk and change, significantly enhance a society's capacity for innovation. The paper also discusses the role of governments in fostering an innovative and entrepreneurial culture through education, business environments, and policies that encourage creativity and entrepreneurship. Ultimately, the authors conclude that cultural elements are crucial in determining a society's innovation potential and that deliberate efforts can create conditions conducive to innovation.

Another key factor to innovations is the capacity of organizations to define, instill, and reinforce innovation-supporting traits in their employees. Innovations flourish under certain circumstances, including the vision and mission, management processes, customer focus, leadership, support mechanisms, employee constituency, and others [12]. As Dobni [13] cites Hamel, the management needs to send necessary signals that facilitate change in how employees think and act. In such a way, employees respond to these changes and take up the challenges and other possibilities under new and orthodox...