Incorporating AI into the Inner Circle of Emotional Intelligence for Sustainability

Abstract

This paper delves into the fusion of artificial intelligence (AI) and emotional intelligence (EQ) by analyzing the frameworks of international sustainability agendas driven by UNESCO, WEF, and UNICEF. It explores the potential of AI integrated with EQ to effectively address the Sustainable Development Goals (SDGs), with a focus on education, healthcare, and environmental sustainability. The integration of EQ into AI use is pivotal in using AI to improve educational outcomes and health services, as emphasized by UNESCO and UNICEF’s significant initiatives. This paper highlights the evolving role of AI in understanding and managing human emotions, particularly in personalizing education and healthcare. It proposes that the ethical use of AI, combined with EQ principles, has the power to transform societal interactions and decision-making processes, leading to a more inclusive, sustainable, and healthier global community. Furthermore, this paper considers the ethical dimensions of AI deployment, guided by UNESCO’s recommendations on AI ethics, which advocate for transparency, accountability, and inclusivity in AI developments. It also examines the World Economic Forum’s insights into AI’s potential to revolutionize learning and healthcare in underserved populations, emphasizing the significance of fair AI advancements. By integrating perspectives from prominent global organizations, this paper offers a strategic approach to combining AI with EQ, enhancing the capacity of AI systems to meaningfully address global challenges. In conclusion, this paper advocates for the establishment of a new Sustainable Development Goal, SDG 18, focused on the ethical integration of AI and EQ across all sectors, ensuring that technology advances the well-being of humanity and global sustainability.

1. Introduction

In today’s fast-paced and constantly evolving world, the convergence of artificial intelligence (AI) with everyday human activities is reshaping the landscape of technological innovation and social interaction. As AI systems continue to advance in complexity and expand their capabilities to encompass a wide range of tasks, including routine automation and multifaceted decision making, their profound influence on personal and social dynamics becomes increasingly apparent.

The concept of emotional intelligence (EQ), traditionally focused on human-to-human interactions, now encounters an unprecedented challenge and opportunity—the assimilation of AI within its domain. This integration raises important questions about the impact of AI on human emotions and relationships and the potential for AI to augment or even replace certain aspects of emotional intelligence.

This integration unquestionably acknowledges the widespread use of AI in various sectors, such as healthcare, finance, education, and consumer electronics. It is important to note that technologies involving artificial intelligence capable of learning and recognizing human emotions date back to 1995, and these advancements have significantly impacted activities like marketing campaigns and healthcare. Considering the various aspects of the topics, this article is a conceptual paper with key insights and implications for integrating AI and EQ to enhance sustainability efforts. It includes numerous abbreviated terms and symbols commonly used within our organization or industry. Refer to

Table 1. List of abbreviations, acronyms and symbols.

AI	Artificial Intelligence	ML	Machine Learning
CPS	Cyber–Physical Systems	NGO	Non-Governmental Organisation
DL	Deep Learning	OECD	Organisation for Economic Co-operation and Development
EQ	Emotional Intelligence	SDG	Sustainable Development Goals
GPE	Global Partnership for Education	UN	United Nations
LLM	Large Language Model	WEF	World Economic Forum
MAIEI	Montreal AI Ethics Institute

for a list of abbreviations, acronyms, and symbols.

1.1. Purpose and Significance of Integrating AI with EQ

Renowned MIT Media Lab professor Rosalind Picard distinctly defines “Affective Computing” as computing that inherently involves or intentionally influences emotions. The development of new models for computer recognition of human emotion has both theoretical and practical applications in learning, human-computer interaction, perceptual information retrieval, creative arts and entertainment, human health, and machine intelligence.

In May 2024, OpenAI unveiled Chat-GPT-4o (omni) with remarkable emotional intelligence emulation skills, marking a significant release during Mental Health Awareness Week. Therefore, the omnipresence of AI tools—from chatbots providing customer service to algorithms determining creditworthiness—calls for an expanded definition of EQ that includes AI literacy and ethical interaction frameworks. This new paradigm suggests that our emotional intelligence must evolve, adapting to manage interactions not only with other humans but also with increasingly intelligent machines that mimic human behaviors.

A few remarkable works have outlined this paradigm shift in the field of EQ and AI integration, and these are listed as follows:

• Kaur, S. and Sharma, R. (2021). “Emotion AI: Integrating Emotional Intelligence with Artificial Intelligence in the Digital Workplace”. This paper discusses the integration of AI with emotional intelligence in business settings, emphasizing the necessity for two-way adaptation between humans and technology [1]. It can outline the evolving interaction between AI and EQ in various sectors, including workplaces.
• Assunção, G. et al. (2022). “An Overview of Emotion in Artificial Intelligence”. This paper provides a comprehensive view of the role of emotions in AI development and can be integrated into discussions about the need for AI to engage emotionally with users [2].
• Sharma, V. and Kumar, H. (2023). “Emotional Intelligence in the Era of Artificial Intelligence for Medical Professionals”. This study emphasizes the role of emotional intelligence for medical professionals interacting with AI [3].
• Li, X. and Cai, S. (2021). “Emotional Design for Intelligent Products Using Artificial Intelligence”. This paper explores how artificial intelligence (AI) can be integrated into the design of intelligent products to enhance user experience by incorporating emotional design principles. It discusses various methodologies and frameworks that enable AI to understand and respond to human emotions, making products more intuitive and user-friendly. The study highlights the importance of combining technical AI capabilities with emotional intelligence to create products that better meet users’ emotional and functional needs [4].

1.2. The Role of Deep Learning (DL) in Advancing Sustainability

Deep learning and LLMs (Large Language Models) have revolutionized organizational decision making by providing powerful data analysis and prediction tools. We can find various research studies on integrating deep learning in decision support systems across multiple industries. Some notable studies on the matter include the following areas:

• Deep learning models in decision making: ML and DL models enhance decision-making processes by augmenting data-driven decisions and refining decision frameworks [5].
• Business intelligence enhancement: Deep learning improves business intelligence through an automated analysis of complex data, leading to more accurate decision support systems [6].
• A comparative analysis of deep learning algorithms: Improved decision-making applications use deep learning models for sentiment analysis, disease prediction, and risk assessment, showcasing higher accuracy and efficiency than traditional methods [7].

The integration of deep learning technologies in agriculture aims to enhance productivity, sustainability, and address challenges related to climate change and resource shortages. Notable studies on this topic include the following areas:

• Current trends and innovations: Deep learning technologies are redefining agriculture by optimizing crop yields, mitigating ecological footprints, and ensuring global food security through precision agriculture and climate-smart methodologies [8].
• Climate change impact modeling: Deep learning models effectively capture the spatiotemporal dynamics of climate variables and their influence on agricultural production, providing valuable insights for adaptation strategies [9].
• Smart and sustainable agriculture: The automation and integration of deep learning, IoT, and cloud technologies lead to the development of smart agriculture systems, enhancing efficiency and sustainability [10].

1.3. Emotional Intelligence (EQ) and Its Relevance in Sustainability

By positioning AI awareness and connection at the center of EQ, we emphasize AI’s role as a central aspect of modern dynamics. This perspective suggests that understanding and managing our relationships with AI is as crucial as managing our relationships with people. This shift is not merely functional but philosophical, challenging us to redefine what it means to be intelligent in an emotionally and artificially interconnected world.

Furthermore, integrating AI with EQ sustainably aligns with the United Nations’ Sustainable Development Goals (SDGs), particularly those focusing on quality education, decent work, economic growth, and reduced inequalities. By fostering an inclusive approach to AI literacy and emotionally intelligent interactions with technology, we can create more equitable, inclusive, and sustainable communities that leverage AI for the betterment of all.

In 2024, the World Economic Forum [11] published a report showing how social innovation uses AI to achieve the SDGs. One of the most prevalent areas where social innovators are utilizing AI is healthcare. Specifically, 25% of social innovators are leveraging AI to advance SDG 3, which is focused on promoting good health and well-being. Beyond healthcare, approximately one in five social innovators are seeking to address climate change or environmental sustainability. The report highlights that over 70% of social innovators have incorporated various forms of machine learning into their operations. Out of this group, approximately 20% have utilized machine learning in conjunction with NLP, computer vision, or predictive analytics. Strikingly, it has been observed that sentiment analysis, recommendation systems, and deep learning have received minimal attention or have been deemed inconsequential by social innovators up to this point. That is the main dilemma or so-called bias because, as we discussed in our earlier paper [12], intrinsic motivation—in other words, connecting with and managing the emotions of the self and others—is vital for achieving the SDGs. When we use so-called “logical” or “strategical tools”, then we are losing the human side of innovations (Figure 1).

The integration of artificial intelligence (AI) into critical sectors such as healthcare and social innovation brings significant ethical considerations to the forefront that must be addressed to harness AI’s full potential responsibly. Carty and Bilodeau (2023) highlight the transformative role of AI in managing medical oxygen supply systems, emphasizing the need for ethical frameworks to ensure reliability and accessibility in critical medical infrastructure [13]. They illustrate how machine learning algorithms can predict oxygen demand, optimize supply chains, and monitor equipment usage to prevent shortages, thereby demonstrating the ethical imperative of ensuring continuous and equitable access to essential medical resources.

In the context of pandemic response, Heino et al. (2023) discuss the ethical dimensions of using AI to build capacity for action during health crises [14]. Their work underscores the importance of leveraging AI for predictive analysis, resource allocation, and effective communication to enhance public health preparedness and responsiveness. The ethical considerations here include ensuring that AI-driven decisions are transparent and equitable and do not inadvertently exacerbate existing disparities in healthcare access.

Furthermore, the World Economic Forum’s (2024) white paper on AI for social innovation explores the ethical frameworks necessary for deploying AI in ways that drive positive social change [11]. The paper highlights AI’s potential to improve access to education and healthcare in underserved communities while emphasizing the need for inclusive and responsible implementation. Ethical considerations in this context involve ensuring that AI technologies do not perpetuate biases and are used to empower and uplift marginalized populations.

Together, these articles underscore the critical need for robust ethical guidelines and frameworks to govern the deployment of AI in healthcare and social innovation. They illustrate that while AI holds tremendous promise for improving efficiency and access, it is imperative to address ethical challenges to ensure these technologies benefit all segments of society equitably and justly. Thus, this leads to the need for the integration of EQ into AI use in every field, making it speak for human needs and challenges. As the UN’s Department of Economic and Social Affairs highlights AI’s potential to meaningfully enable 79% of the 169 SDG targets [15], the interplay between AI and emotional intelligence (EQ) has become critical. This review paper aims to explore the innovative concept of integrating EQ into AI applications, emphasizing AI and EQ synergy as a central aspect of sustainability—in particular, the SDGs. This approach recognizes the importance of managing our relationships with AI with human values, advocating for a balanced understanding of AI’s role in enhancing human capabilities and advocating the SDGs.

2. Theoretical Foundations:

2.1. The Necessity of AI Literacy for SDGs

Understanding AI—its capabilities, limitations, and workings—is imperative for technological professionals and the general populace. AI literacy empowers individuals to interact competently with AI systems, discerning their utility and mitigating risks. As AI technologies become ubiquitous, from personal assistants to more complex decision-making systems, a foundational knowledge of AI helps navigate these interactions more effectively and ethically.

AI literacy is becoming a fundamental skill akin to reading or writing in the digital age. As AI permeates various facets of life, understanding its mechanisms, strengths, and weaknesses is crucial. This literacy extends beyond technical prowess to include understanding AI’s decision-making processes and socioeconomic impacts. For instance, recognizing biases in AI outputs or understanding how AI can manipulate emotions and decisions in social media are essential skills.

Moreover, AI literacy allows individuals to participate more actively in discussions about AI policy and its societal implications. It encourages a well-informed populace that can advocate for responsible AI use and influence how these technologies are integrated into daily life. Therefore, enhancing AI literacy is about coping with a technology-infused environment and empowering citizens to shape the trajectory of AI development.

UNICEF places a strong emphasis on digital learning, which encompasses AI technologies, to provide assistance to children in emergency situations and those who are not part of the traditional school system [16]. At a global level, 222 million children face the repercussions of emergencies and prolonged crises; 244 million children do not have access to formal education, and a staggering 1 billion children—nearly half of the world’s youth—reside in countries classified as “extremely high-risk” in terms of the impacts of climate change [16,17]. Educational institutions in these regions often close due to natural disasters. AI holds the potential to deliver education to these children, thereby making significant contributions to Sustainable Development Goal 4 and, ultimately, SDGs 1 to 3 and 8.

Across the globe, a staggering 129 million girls are currently not attending school. The World Economic Forum (WEF) emphasizes the tremendous potential of artificial intelligence (AI) in transforming education through partnerships with governments, civil society, the private sector, and other stakeholders [18]. Furthermore, in developing countries, 45% of women and 60% of female caregivers are forced to halt or delay their education if they do not have access to online learning [19]. This underscores the critical importance of implementing ethically designed AI-based educational programs integrated with emotional intelligence (EQ). Such initiatives not only facilitate learning but also focus on nurturing and maximizing essential skill sets. Without girls and women having equal access to learning and growing initiatives as their counterparts in the modern world, achieving SDGs 3, 5, 10, and 8 is questionable, and that will have a direct impact on poverty and well-being, referring to SDG 1 and SDG 3.

On the other hand, there are calls for a human-centered perspective [20]. This aims to shift AI’s role in addressing current inequalities regarding access to knowledge, research, and the diversity of cultural expressions.

“If we want to hit our economic objectives for development, peace, and security, climate change—it can only be done if girls are in school and learning”, Ms. Gillard, Global Partnership for Education (GPE), stated.

Why is this so important for SDGs achievement?

The “Empowering the Workforce of Tomorrow Report” by UNICEF predicts that by 2030, approximately 880 million children will lack the essential skills needed to thrive in the workforce [21]. This alarming statistic highlights a concerning trend, indicating that a significant number of children and young people need to receive the support and opportunities necessary to develop the skills essential for their future success. AI successfully blended with EQ can be the solution for these young people having access to training and personal skills development. As highlighted in the “AI in Education” report [22], multimodal AI-powered educational software can adapt to different learning styles to make learning processes more inclusive and effective. However, there is a need for an EQ blended design where AI not only speaks for the psychology of learning but also helps learners to improve their soft skills through EQ-enhanced interaction. This integration may raise the question of ethical AI. A study by Charisi V. et al. (2022) provides an extensive analysis of current ethical challenges and emerging trends in AI, making it a valuable resource for understanding the broader context of AI ethics [23]. Their report offers a comprehensive overview of the key developments in AI ethics from the second half of 2021. It covers various topics supporting AI literacy, including the Montreal AI Ethics Institute (MAIEI), privacy, bias, AI design and governance, social media and misinformation, and laws and regulations. The report also includes special features on gender specifics such as gender construction with AI-generated art. Charisi et al. (2022) also suggest limiting the use of AI to complete tasks that are considered essential and have valuable purposes. They open up the crucial question of what “valuable purposes” are. At this point, EQ will play a key role in identifying these (Figure 2).

2.2. Ethical Considerations in AI and Sustainability

Ethics plays a pivotal role in AI integration. As AI systems are designed and deployed, privacy, autonomy, and bias considerations are paramount. AI technologies must be developed with a strong ethical framework to prevent misuse and ensure they contribute positively to society. Emphasizing ethical considerations at the core of EQ when dealing with AI encourages a societal approach to AI that respects human dignity and values.

Integrating AI into society raises significant ethical questions that must be addressed to harness its full potential responsibly. Issues such as data privacy, surveillance, autonomy, and the ethical use of AI in decision-making processes are at the forefront of this discourse. The ethical deployment of AI systems is crucial to ensure they do not perpetuate existing inequalities or introduce new forms of discrimination.

Ethical AI frameworks must be robust and adaptable, guiding AI development while allowing for revisions as technological and societal contexts evolve. These frameworks should also promote transparency and accountability, ensuring that AI developers and users can explain and justify their use of AI systems. This focus on ethics within the AI–EQ nexus supports a broader societal goal of technology that serves humanity’s best interests, respects individual rights, and promotes justice.

Many studies have touched on this focus—notably, Yu, H. et al. (2018), “Building Ethics into Artificial Intelligence”. Their article offers a comprehensive overview of AI governance for ethical decision -making [24]. Piteira, M., Aparicio, M., and Costa, C. (2019) also explored similar questions in “Ethics of Artificial Intelligence: Challenges”. Their paper provides a bibliometric study on the guiding principles of ethics in AI, which would fit well in discussions about the ethics of integrating AI into different sectors [25]. With a more general approach, Jobin, A., Ienca, M., and Vayena, E. (2019) covered “The global landscape of AI ethics guidelines”. This analysis concerns global AI ethics and principles [26].

Balcombe, L. (2023) conducted a study pertinent to the matter due to its focus on the ethical implications of deploying AI in mental health services, emphasizing the importance of privacy and emotional authenticity [27]. This article reviews the role of AI chatbots in digital mental health services, examining their effectiveness in providing mental health support and counseling. It highlights the potential benefits of AI chatbots in improving the accessibility, affordability, and scalability of mental health services. The study also addresses the ethical and practical challenges associated with using AI in sensitive areas such as mental health, including privacy concerns, emotional authenticity, and the need for human oversight.

Recently, Shukla, A., Agnihotri, A., and Singh, B. (2023) concentrated on analyzing how AI and emotional intelligence affected Indian IT professionals’ decision-making abilities. This paper explores the ethical challenges and benefits of AI and emotional intelligence in decision making within Indian IT sectors [28]. Additionally, a technical report by Joerin, A., Rauws, M., Fulmer, R., and Black, V. (2020), titled “Ethical Artificial Intelligence for Digital Health Organizations”, provides a framework for ethical AI in digital health [29]. Huang et al. (2023) outlined how AI ethics is a crucial field that addresses ethical risks and concerns in AI systems, addressing privacy, discrimination, unemployment, and security risks while improving efficiency and benefits for individuals, organizations, and society [30].

Woodgate (2023) explores the ethical principles necessary for reasoning about value preferences in developing and deploying artificial intelligence [31]. This work, presented at the 2023 AAAI/ACM Conference on AI, Ethics, and Society, focuses on establishing a framework for integrating diverse human values into AI systems, ensuring that these technologies align with ethical standards and societal expectations.

When incorporating ethics into education or any direct association with human learning and growth, it is essential to involve a wide range of experts who actively contribute to its design and implementation. This includes experts in literacy and cognitive development, computer scientists specializing in natural language processing, machine learning, information retrieval, and child–computer interaction, as well as experts in privacy, law, and ethics, as suggested by the European Commission [32]. The Commission’s report emphasizes that the integration of AI should prioritize inclusive growth, sustainable development, and well-being. Additionally, the OECD recognizes children’s AI literacy as an essential component of their education and socio-emotional development [33].

On the other hand, the values and ethical principles for the integration of AI have already been published by UNESCO [34] in “Ethics of Artificial Intelligence”. One of the most striking points in that document is quoted as follows:

“Member States should promote the acquisition of “prerequisite skills” for AI education, such as basic literacy, numeracy, coding and digital skills, and media and information literacy, as well as critical and creative thinking, teamwork, communication, socio-emotional and AI ethics skills, especially in countries and in regions or areas within countries where there are notable gaps in the education of these skills”.

All of this leads us to integrating socio-emotional and AI ethics skills, which should be handled holistically for sustainability, referring to how EQ is critical. The capabilities of AI extend beyond just strategic and analytical skills; it also has the capacity to enhance EQ and communicate effectively with human emotions. This allows AI to better serve human learning and growth needs, ultimately contributing to sustainability (Figure 3).

2.3. Emotional Intelligence in Human–AI Interaction

The ability to manage emotions and relationships in the context of AI is crucial. AI can significantly influence our decisions, feelings, and interactions. For example, personalized AI in marketing exploits emotional responses to influence consumer behavior, necessitating a balanced EQ to manage and understand these influences. Also, while emotion plays a crucial role in AI advancement, benefiting reinforcement, social integration, and general development, Assuncao et al. (2022) outlined how it remains a stigmatized topic among engineers and computer scientists [2]. Firdaus, Chauhan, Ekbal, and Bhattacharyya (2022), when presenting EmoSen, their novel dialogue system designed to generate responses that are controlled by sentiment and emotion in a multimodal context, show how AI systems can be designed to recognize and appropriately respond to human emotions [35]. Their system exemplifies the integration of emotional intelligence in AI, highlighting its potential to make human–AI interactions more natural, empathetic, and effective. Integrating AI into EQ training can improve our ability to maintain objectivity and emotional intelligence in interactions influenced by AI.

As AI technologies increasingly mimic human traits, the ability to manage emotional interactions with AI becomes crucial. Emotional intelligence in the context of AI involves recognizing AI’s influence on our feelings and interactions and managing these emotions effectively. For example, AI-driven social media algorithms design interactions that can dramatically affect users’ moods and decisions; being emotionally intelligent in such contexts means maintaining a critical awareness of these influences.

Emotional intelligence and AI have been studied in recent years—notably, by Sharma, V. and Kumar, H. (2023) [3] in their study titled “Emotional Intelligence in the Era of Artificial Intelligence for Medical Professionals”. This study emphasizes the role of emotional intelligence for medical professionals interacting with AI, which is relevant to the discussion on ethical considerations in AI. Also, Li, Y. et al. (2019), in their paper, “AI-Enabled Emotion Communication”, explore AI’s role in enhancing emotional communication [36] Another article from Mamina, R., and Piraynen, E. (2023) discusses the potential of emotional AI to foster human–machine communication, making it relevant to the sections on emotional intelligence in human–AI interaction [37].

Similarly, a paper by Ranade, A. G., Patel, M., and Magare, A. (2018), titled “Emotion Model for Artificial Intelligence and their Applications” details AI systems incorporating emotional intelligence [38].

Furthermore, AI’s role in healthcare, education, customer service, and climate change interventions presents unique challenges for emotional management. For example, behavioral change is key to improving our environmental and climate predicaments [11]. This means that users need to navigate relationships where AI interfaces display empathetic behavior, requiring an adjusted approach to empathy and emotional responses. Cultivating an EQ encompassing AI interactions prepares individuals to maintain their emotional well-being and make informed decisions in increasingly complex social landscapes.

Overall, experts highlight AI contributions toward three goals, in particular, SDG 3 (Good Health and Well-Being), SDG 4 (Quality Education), and SDG 13 (Climate Action) Ref. [15], with the potential to contribute to other SDGs. In the following section, we highlight and comment on how emotional intelligence blended with AI can help to achieve SDGs in general.

3. Conceptual Framework

3.1. AI, Sustainable Development Goals, and EQ

AI is increasingly seen as a crucial tool for achieving the United Nations’ Sustainable Development Goals (SDGs), addressing a range of global challenges, including climate change, health, and infrastructure. This article discusses how AI can accelerate progress toward these goals by enhancing efficiency and providing innovative solutions.

Climate Solutions: AI contributes to environmental sustainability by optimizing renewable energy systems, enhancing supply chain efficiencies, monitoring environmental conditions, and improving climate prediction models. These applications can help achieve SDGs such as affordable and clean energy (SDG 7), climate action (SDG 13), life below water (SDG 14), and life on land (SDG 15).

Health: In the medical field, AI technologies are advancing the quality and accessibility of healthcare. AI-driven diagnostics, for instance, offer significant improvements in detecting diseases like cancer more accurately and swiftly than human professionals, which aligns with good health and well-being (SDG 3). AI applications in health can bridge the gap in healthcare quality and access, especially in under-resourced areas.

Infrastructure: AI is also transforming infrastructure management through smart automation and data analysis, improving everything from traffic management to public transport efficiency. This contributes to building resilient infrastructure, promoting inclusive and sustainable industrialization, and fostering innovation (SDG 9). Additionally, AI can enhance the sustainability of cities and communities (SDG 11) by optimizing urban planning and resource management.

The European Commission’s document highlights the intersection of emotional intelligence (EQ) and AI in advancing the Sustainable Development Goals (SDGs) [32,39]. It emphasizes the need for AI to incorporate EQ principles to ensure that technology deployments are sensitive to human needs and emotions. By integrating EQ, AI can better address inequalities (SDG 10), promote inclusive societies (SDG 16), and enhance sustainable urban development (SDG 11). The ethical framework discussed advocates for AI systems that uphold human dignity and foster inclusivity, ensuring that AI benefits are equitably distributed without exacerbating existing disparities.

The document further elaborates on the integration of EQ into AI systems to enhance their contribution to the Sustainable Development Goals (SDGs). It suggests that AI equipped with EQ can more effectively address the complex social and emotional aspects of global challenges. This approach enables AI to contribute to goals like ensuring good health and well-being (SDG 3) and achieving gender equality (SDG 5) by adapting responses based on understanding and empathy. Examples in the document highlight how AI applications, sensitive to human emotions, can lead to more inclusive and effective solutions in fields such as education and healthcare. This integration is crucial for developing technologies that solve technical problems and address these global issues’ emotional and social dimensions.

Consequently, this highlights how empathetic AI can enhance interactions and solutions related to the SDGs. It suggests that AI designed with EQ can better understand and respond to human needs, fostering more effective and humane solutions. This is crucial in sectors such as healthcare and education, where understanding emotional contexts can significantly impact the effectiveness of interventions and support provided to individuals. Emphasizing empathy in AI designs ensures that technology solves technical issues and supports emotional and social well-being (Figure 4).

3.2. Next Steps: Harnessing AI Responsibly

To ensure that AI continues to enhance our capabilities and contribute positively to the Sustainable Development Goals, we need a proactive approach.

• Enhance AI Literacy: Promote comprehensive education about AI technologies and their ethical use across all levels of society to empower individuals with the knowledge to use AI effectively and responsibly.
• Develop Emotional Intelligence in AI Interactions: Integrate training programs that focus on managing relationships with AI systems, particularly in healthcare and education sectors where empathy and understanding are crucial.
• Strengthen Ethical Frameworks: Establish and enforce robust ethical standards for AI development and deployment, ensuring that AI systems uphold principles of fairness, accountability, and transparency.
• Foster Collaborative Innovations: Encourage partnerships between governments, private sectors, and NGOs to create inclusive AI solutions that address societal needs and drive sustainable development.
• Monitor and Evaluate AI Impacts: Regularly assess the social, economic, and environmental impacts of AI technologies to align them continually with human values and SDGs.

By following these steps, we can create a future where AI not only supports but enhances our collective efforts toward a sustainable and equitable world.

4. Application Areas

4.1. Transitioning into Adaptability to AI-Driven Change

As we build upon the foundation laid in our next steps, the focus shifts to adaptability—an essential quality in our rapidly evolving technological landscape. This adaptability is not just about technological agility but also encompasses emotional resilience in the face of AI-induced changes. As AI transforms employment landscapes and social interactions, our ability to adapt will determine how effectively we harness AI for positive outcomes. This section explores how individuals and organizations can prepare for and thrive amidst these shifts, emphasizing the role of enhanced AI literacy and emotional intelligence in fostering a balanced approach to emerging challenges.

The technology landscape is rapidly evolving, and adaptability is essential. Individuals must be equipped to adjust to these changes, effectively managing emotional and social impacts. This adaptability is particularly vital in sectors like employment, where AI’s role is growing, potentially displacing traditional jobs but also creating new opportunities. Preparing emotionally for these shifts can mitigate the adverse effects and harness the positive aspects of technological advancement.

The rapid pace of AI development demands a high level of adaptability. Individuals must be prepared not only technologically but also emotionally for the shifts AI brings to the workplace, home, and social settings. This adaptability involves understanding the changes AI can bring and being prepared to innovate and respond to these changes effectively.

An article by Kim, H. and Ben-Othman, J. (2020), titled “Toward Integrated Virtual Emotion System with AI Applicability for Secure CPS-Enabled Smart Cities”, discusses the integration of AI with emotional systems in smart cities [40].

For example, in the workplace, AI may automate tasks traditionally performed by humans, requiring workers to adapt by developing new skills or shifting to new roles. Emotionally intelligent responses to such transitions can reduce anxiety and improve the acceptance and integration of AI technologies. This adaptability extends to recognizing opportunities AI presents, such as enhanced data analysis and decision-making capabilities in business environments.

4.2. Focusing on Education and Leadership as Initial Areas for AI and EQ Integration

Building on the foundation of adaptability, education and leadership emerge as crucial fields where AI and EQ can be most effectively integrated. As we navigate the challenges and opportunities presented by AI, it is in these domains that our adaptive strategies can be applied to foster ethical reasoning, critical thinking, and emotional intelligence. This approach prepares future leaders to harness AI’s power and ensures they are equipped to manage its impact on human stakeholders with empathy and effectiveness. This section will delve deeper into how embedding AI into the core of educational and leadership frameworks can transform traditional paradigms and create more inclusive, adaptive, and forward-thinking environments.

Incorporating AI into the core of EQ education transforms traditional learning and leadership development paradigms. It promotes an integrated curriculum that prepares future leaders to harness AI’s power and manage its impact on human stakeholders effectively. This approach advocates for educational systems emphasizing ethical reasoning, critical thinking, emotional intelligence, and technical skills [25].

In leadership, the ability to merge AI understanding with emotional intelligence equips leaders to create more inclusive, empathetic, reflective, and effective management strategies. This integration helps in navigating the complexities of modern organizational environments, where decisions often involve balancing technological efficiency with human factors.

Touching on AI governance and the knowledge gaps, Birkstedt et al. (2023) outlined how AI governance research should focus on technical, stakeholder, and contextual aspects, with a focus on AI oversight units and collaborative governance approaches [41]. On the other hand, Yellapantula, K. and Ayachit, M. (2019), looking at the “Significance of Emotional Intelligence in the Era of Artificial Intelligence”, examined AI’s impact on emotional intelligence in the financial and educational sectors [42]. Fenster, K. et al. (2023), published a paper titled “Ethical Implications of AI in Healthcare”, which has pertinent applications in the fields of education and leadership, as it addresses the ethical challenges of AI in healthcare and offers guidelines for responsible AI implementation [39]. In addition, another study featuring a comprehensive review examines the ethical implications of using AI in healthcare, focusing on issues such as patient privacy, data security, and the potential for bias in AI algorithms [8]. It discusses how AI can both positively and negatively impact healthcare delivery, patient outcomes, and healthcare equity. This study outlines significant recommendations for developing ethical guidelines and robust frameworks to guarantee the responsible and effective implementation of AI technologies in healthcare settings.

5. Discussions

5.1. Challenges and Transformative Potential

Current research emphasizes the universal integration of AI literacy with emotional intelligence training to ensure that every individual is equipped to utilize AI technologies responsibly and empathetically. As the world rapidly advances in technology, particularly AI, there is a growing recognition of the need to integrate AI with EQ to maximize benefits and minimize risks. Given the transformative potential of AI and the critical role of EQ in its ethical application, establishing an 18th SDG has been proposed, with this specifically focused on AI and EQ. Four main areas could justify the determination of this goal, each playing a significant role.

1.

The Transformative Potential of AI

• AI has demonstrated immense potential to contribute to most of the existing SDGs, notably, the following:
  • Healthcare (SDG 3): AI enhances diagnostic accuracy and personalized treatment, improving patient outcomes and healthcare efficiency [39].
  • Education (SDG 4): AI-powered personalized learning platforms adapt to individual learning styles, promoting inclusive and equitable quality education [43].
  • Climate Action (SDG 13): AI aids in modeling and predicting climate patterns, optimizing resource use, and implementing sustainable practices.

2.

Addressing Ethical and Social Implications with EQ

• While AI offers numerous benefits, its deployment poses significant ethical and social challenges that require high EQ to address the following:
  • Bias and Fairness: AI systems can perpetuate existing biases if not properly managed. High EQ in AI developers and policymakers ensures these systems are designed and implemented ethically.
  • Privacy Concerns: EQ is essential in balancing technological advancements with the need to protect individual privacy rights.
  • Job Displacement: As AI automates more tasks, high EQ is crucial for managing social impacts, including workforce retraining and support.

3.

Enhancing Human–AI Collaboration

• Creating an 18th SDG focused on AI and EQ would foster the following:
  • Ethical AI Development: Ensuring AI systems are designed with a human-centered approach that prioritizes ethical considerations and social impact.
  • Effective Communication: Promoting clear and empathetic communication about AI’s capabilities and limitations to build public trust and collaboration.
  • Adaptive Leadership: Encouraging leaders to develop high EQ to navigate the complex landscape of AI integration, addressing both technological and human factors.

4.

Strategic Importance for Sustainable Development

• An SDG dedicated to AI and EQ aligns with the strategic goals of sustainable development by striving for the following:
  • Ensuring Inclusive Growth: Leveraging AI to promote inclusive and equitable economic growth, supported by policies informed by high EQ.
  • Fostering Innovation and Infrastructure: Encouraging innovation that is responsible and aligned with sustainable development principles, guided by leaders with high EQ.
  • Strengthening Global Partnerships: Enhancing international collaboration on AI ethics and governance, facilitated by high EQ to ensure mutual understanding and cooperation.

5.2. Future Directions

Integrating AI with high EQ is essential for maximizing the benefits of technological advancements while mitigating associated risks. Establishing an 18th SDG focused on AI and EQ would provide a dedicated framework to ensure that AI technologies are developed and deployed ethically, sustainably, and inclusively. This new SDG would complement and enhance the existing goals, driving global progress toward a more equitable and sustainable future. By harmonizing AI competence with emotional intelligence, SDG 18 also would not only improve global efforts towards equality, diversity, inclusion, and equitable education but also enhance global efforts towards equality, diversity, inclusion, and equitable education, as well as promote economic growth, a peaceful future, and proactive climate action. Importantly, it is a powerful bridge to embracing all the SDGs, paving the way for a sustainable future in every dimension.

As a conclusive suggestion, we propose establishing a Sustainable Development Goal referring to AI and EQ. We might even go further and constructively advocate for the establishment of an 18th SDG: general AI competence blended with emotional intelligence. This goal underscores the importance of integrating AI literacy with emotional intelligence training on a global scale, ensuring that individuals are equipped to responsibly and empathetically harness AI technologies. By harmonizing AI competence with emotional intelligence, SDG 18 will not only advance global initiatives for equality, diversity, inclusion, and fair education but also drive economic growth, foster a peaceful future, and promote proactive climate action. Importantly, it will serve as a powerful enabler for embracing all the SDGs, laying the groundwork for a sustainable future across all aspects of society (Figure 5).

6. Conclusions

In summary, the integration of AI into the heart of EQ carries profound implications for education and leadership development. It facilitates a curriculum that harmonizes technical expertise with emotional intelligence, equipping individuals not only to wield technology but also to lead with integrity and compassion. In the realm of leadership, grasping AI and navigating its effects on teams and business strategies confers a competitive edge, nurturing a technologically sophisticated workplace centered around human values. Integrating AI awareness into the central framework of EQ for sustainability represents a forward-thinking approach to the interplay between technology and human emotion. As we venture further into an AI-integrated future, the necessity of this integration becomes more pronounced, ensuring that our societal progression is balanced with emotional intelligence. By fostering AI literacy, considering ethical dimensions, enhancing adaptability, and applying these principles in educational and leadership frameworks, we can prepare for a future where AI enhances rather than diminishes the human experience.

Considering sustainable AI–EQ integration methods also offers a pathway to achieving the Sustainable Development Goals (SDGs), particularly in promoting inclusive and equitable quality education (SDG 4), fostering innovation and resilient infrastructure (SDG 9), and ensuring public participation in decision making (SDG 16). By aligning AI development with these goals, we not only enhance our collective emotional intelligence but also support global efforts toward sustainable development. This approach underscores the importance of creating AI systems that are not only technically proficient and emotionally intelligent but also globally conscious and ethically grounded.

Looking forward, the integration of AI into the realm of EQ for sustainability presents both challenges and opportunities. This paper has explored the necessity of evolving our emotional intelligence to include AI literacy, ethical considerations, adaptability, and applications in education and leadership. As we advance, it is crucial to continue researching and developing strategies that enhance our ability to interact with AI in emotionally intelligent ways.

Future research should focus on empirical studies that evaluate the effectiveness of integrated AI–EQ training programs, the long-term impacts of AI on emotional health, and the development of ethical guidelines tailored to new AI advancements. Additionally, interdisciplinary approaches that bring together psychologists, ethicists, technologists, and policymakers will be vital in crafting frameworks that guide the symbiotic growth of AI and human emotional capabilities.