Artificial Intelligence on Food Vulnerability: Future Implications within a Framework of Opportunities and Challenges

Abstract

This study explores the field of artificial intelligence (AI) through the lens of Stephen Hawking, who warned of its potential dangers. It aims to provide a comprehensive understanding of AI and its implications for food security using a qualitative approach and offering a contemporary perspective on the topic. The study explores the challenges and opportunities presented by AI in various fields with an emphasis on the global food reality. It also highlights the critical importance of striking a harmonious balance between technological progress and the preservation of local wisdom, cultural diversity, and environmental sustainability. In conclusion, the analysis argues that AI is a transformative force with the potential to address global food shortages and facilitate sustainable food production. However, it is not without significant risks that require rigorous scrutiny and ethical oversight.

1. Introduction

Food vulnerability is the inability of the household/individual to cope with the risks of not having enough food to stay healthy. Conflict/insecurity, economic shocks and extreme weather events are three of the main factors affecting global food security. Importantly, these factors can affect food production, distribution, and access around the world, with potentially serious consequences for food security [1].

The Global Report on Food Crises (GRFC) for 2023 highlights that the number of people experiencing acute food insecurity and in need of urgent food and livelihood assistance is increasing. The report shows that more than a quarter of a billion people face acute hunger, with economic shocks and the war in Ukraine contributing to the increase. In 2022, 258 million people in 58 countries and territories will face acute food insecurity in times of crisis [2]. According to this latest report, 19 countries/territories were affected by conflict and insecurity, with 117.1 million people facing acute food insecurity. This is lower than in 2021, when conflict was considered the main cause in 24 countries/territories, with 139 million people in this phase. The lower estimate is due to economic shocks overtaking conflict as the main cause of acute food insecurity in three countries still affected by crises: Afghanistan, South Sudan, and the Syrian Arab Republic [2]. Other countries with catastrophically food insecure populations, Afghanistan, Burkina Faso, Ethiopia, Nigeria, Somalia, South Sudan, Palestine, and Yemen, have protracted conflicts in their territories [3].

These scenarios promote economic shocks (including the socioeconomic impact of COVID-19 and the impact of the war in Ukraine). The GRFC reports that in 2022, 83.9 million people across 27 countries faced acute food insecurity, compared to 30.2 million people in 21 countries in 2021 [2]. Economic resilience and climate shocks are elements to consider [4,5]. The economic resilience of poor countries has declined dramatically, and they now face long recovery periods and reduced capacity to cope with future shocks [6]. In addition, extreme climate variability was the leading cause of acute food insecurity in 12 countries, affecting 56.8 million people, more than double the number in 2021. These include devastating floods in Pakistan [7] and tropical storms, cyclones, and droughts in the Horn of Africa [8].

The food crises outlined in the GRFC are the result of interconnected, mutually reinforcing drivers—conflict and insecurity, economic shocks, and weather extremes (Figure 1). In 2022, these key drivers were associated with the lingering socioeconomic impacts of COVID-19, the knock-on effects of the war in Ukraine, and repeated droughts and other weather extremes [2]. More recently, the conflict between Israel and Palestine may have negative effects on the energy market, adding to the food vulnerability that Palestinians currently suffer due to the felling of olive trees [9].

The factors mentioned above were important in the increase in global food vulnerability; however, there are other factors that are not mentioned but require special attention, such as the loss of biodiversity. Biodiversity experts estimated that approximately 30% of species have been globally threatened or driven to extinction since the year 1500 [10] and structural adjustment policies that affect family farming [11,12,13,14]. The elements discussed above demonstrate that food vulnerability has progressively increased [15]. In today’s world, the interplay between social metabolism and the interactive effects of socioecological systems has added complexity to the global food reality [16]. In this context, the use of artificial intelligence (AI) can provide an analytical alternative not only to understand this reality but also to propose solutions [17]. AI has a crucial role in food security. It can analyze climate data to predict extreme weather events and create early warning systems [18], enabling a rapid response to threats such as pests or diseases affecting crops. This facilitates the implementation of preventive measures, reducing the impact on agriculture and improving food security. AI also optimizes farming practices by analyzing soil, climate, and crop data and making recommendations to improve efficiency and productivity [19]. It also monitors biodiversity and its impact on ecosystems [20], understands how conflict and economic shocks affect rural communities, and helps design specific support policies [21]. In addition, it improves the ability to respond to food crises by identifying areas of scarcity and facilitating the efficient distribution of aid. In assessing structural adjustment policies, AI analyzes economic and social data, providing critical information to make informed decisions and minimize adverse impacts [22]. AI is an essential tool for achieving sustainability and resilience in food systems at the national and international levels, and its ability to analyze large amounts of data and provide precise recommendations can contribute to the sustainability, equity, and resilience of food systems at the national and international levels.

However, the use of this technological tool implies knowing its advantages and disadvantages so that we can make appropriate use of it, as we will explain in detail below. AI is a rapidly evolving field of technology that has garnered significant attention and debate in recent years [23]. As society continues to make remarkable advancements in AI, it becomes essential to delve into its concept, potential risks, and implications. At its core, AI refers to the development of computer systems capable of performing tasks that typically require human intelligence. These tasks include problem-solving, learning, decision-making, and pattern recognition. The field of AI encompasses a wide range of techniques, such as machine learning, natural language processing, computer vision, and robotics. With its ability to process vast amounts of data and perform complex computations at an unprecedented speed, AI holds immense promise for revolutionizing various industries and aspects of our lives.

However, alongside the remarkable advancements, Stephen Hawking, one of the most brilliant minds of our time, expressed concerns about the potential dangers posed by AI. Hawking [24] recognized its immense potential to benefit humanity in fields such as medicine, science, and technology but also warned of the potential risks if not developed responsibly. His main concern was the possibility of a superintelligent AI that could rapidly surpass human intelligence, posing an existential challenge to our species. Hawking argued that it is vital to develop methods of maintaining control over advanced AI systems and stressed the need for thorough research into the potential impact of AI on society. He also highlighted the potential economic impact of AI, warning of the risk of greater inequality if not properly managed. He called for international collaboration to address these challenges, recognizing that the impact of AI transcends national boundaries. Despite his warnings, Hawking remained optimistic, believing that if developed carefully, AI could be humanity’s greatest or last great invention. His warnings raised important questions about the ethical, societal, and existential risks associated with the rapid progress of AI.

AI has the power to revolutionize large-scale agricultural practices and food production. By leveraging AI algorithms and machine learning, farmers can analyze vast amounts of data to make informed decisions about crop selection, planting schedules, and resource management. AI-powered drones and sensors can monitor crop health, soil conditions, and irrigation needs, enabling precision agriculture and optimizing resource allocation. These advancements have the potential to enhance productivity, reduce waste, and improve sustainability in food production [25]. Such insights can aid in improving resilience, ensuring a consistent food supply, and mitigating the risks associated with climate variability [26].

At a local scale, AI technologies are transforming food processing and supply chain management. AI-powered systems can enhance food quality control, detecting contaminants, pathogens, and spoilage at an early stage. Machine vision algorithms can improve sorting and grading processes, ensuring consistent quality standards [27]. Additionally, AI algorithms can optimize inventory management, reduce waste and enable efficient distribution of food products. These advancements have the potential to enhance food safety, reduce postharvest losses, and improve the overall efficiency of the food supply chain [28].

In the realm of consumer experiences, AI is reshaping how we make choices about what we eat [26]. AI algorithms can analyze individual preferences, dietary restrictions, and health data to provide personalized nutrition recommendations. Virtual assistants and chatbots powered by AI can assist consumers in making informed decisions about food choices, considering factors such as nutritional content, allergens, and ethical considerations. AI-powered food delivery platforms can optimize routes, reduce delivery times, and enhance customer experiences, ensuring prompt and efficient access to a wide variety of food options [29].

However, with these advancements come important considerations and challenges. Ethical concerns regarding data privacy, ownership, and algorithmic biases must be addressed to ensure equitable access to AI-driven food systems. Additionally, as AI becomes increasingly integrated into food production and supply chains, questions around the impact on employment, the role of human expertise, and the potential for consolidation of power must be carefully examined. By examining Stephen Hawking’s concerns in the context of AI in food systems, we can gain a deeper understanding of the challenges and opportunities that lie ahead [30]. By addressing ethical considerations, potential risks, and the need for responsible AI development, we can strive for a future where AI enhances the sustainability, accessibility, and resilience of our food systems while also ensuring equitable outcomes for all stakeholders involved.

Taking into account the previous theoretical and conceptual considerations, this essay attempts to delve into the field of artificial intelligence (AI) as viewed through the lens of the English physicist Stephen Hawking [31]. The primary goal of this study is to navigate the complicated landscape of AI and provide a well-rounded understanding of its capabilities, challenges, and implications in a world where food security is a concern. Our intention is to explore Stephen Hawking’s fears in-depth, critically assessing the risks he identified and their relevance in today’s context. Using a qualitative focus, we aim to provide an up-to-date assessment of this issue, approaching its state-of-the-art.

To achieve this goal, the study is divided into several sections, each dedicated to a specific facet of AI. These sections include an extensive literature review on the introduction to the concept of AI, an examination of Stephen Hawking’s concerns, discussions of ethical considerations, the potential risks associated with superintelligent AI, the convergence of AI and food security, and a consideration of future challenges, opportunities, and possible scenarios. Through this exploration, we aim to provide readers with deeper insight into the intricacies surrounding AI and its societal implications. By critically assessing Stephen Hawking’s fears, our study aims to contribute to the ongoing discourse and promote responsible AI development that aligns with our values and addresses potential risks. As we explore the concept of AI and scrutinize Stephen Hawking’s concerns about its implications [24], it becomes imperative to examine the specific implications of AI for food systems at different scales [32].

2. Exploring Artificial Intelligence in Depth: A Comprehensive Guide

AI refers to the development of computer systems that can perform tasks that typically require human intelligence. It involves the creation of algorithms and models that enable machines to simulate cognitive processes such as learning, reasoning, problem-solving, and decision-making [33]. AI encompasses a range of techniques, each with its own characteristics and applications:

Narrow AI, also known as weak AI, focuses on performing specific tasks with high proficiency. These systems are designed to excel in a particular domain, such as image recognition, natural language processing or chess. Narrow AI is prevalent in various industries and applications, such as virtual assistants, recommendation systems, and autonomous vehicles [34].

General AI aims to create machines that have human-level intelligence and can perform any intellectual task that a human can perform. This form of AI represents the concept of ‘strong AI’ or ‘artificial general intelligence’. Achieving general AI remains a significant scientific and technological challenge, as it requires machines to exhibit the same broad cognitive abilities as humans [33].

Superintelligent AI refers to a hypothetical form of AI that exceeds human intelligence in all domains. It represents a level of AI development where machines could outperform humans in virtually any intellectual task. The development of superintelligent AI raises concerns about its control, implications, and potential risks if it surpasses human understanding and control [35].

The history of AI dates back to the mid-20th century when pioneers began to explore the idea of creating machines that could exhibit human-like intelligence. Artificial intelligence (AI) underwent a remarkable evolution in its early decades. The 1950s and 1960s saw the development of programs capable of solving mathematical problems, playing chess and processing natural language, with prominent examples such as Logic Theorist and ELIZA. Later, in the 1970s and 1980s, the field took a significant turn towards the development of expert systems designed to emulate the reasoning and decision-making of human specialists in specific domains. This transition marked a shift in focus from general tasks to more specialized applications and laid the foundation for the future development of AI and its ability to reproduce various aspects of human intelligence in specific domains. These systems used rule-based reasoning and knowledge representation techniques. Subsequently, in the 1980s and 1990s, machine learning emerged as a prominent approach to AI. Neural networks and algorithms such as backpropagation have gained prominence, enabling computers to learn from data and improve their performance over time [36]. These advances visualized their potential, and in recent years, advances in computing power, the availability of large datasets, and the development of deep learning architectures have accelerated progress in AI. Deep learning, a subfield of machine learning, has demonstrated exceptional performance in tasks such as image and speech recognition [37].

To understand what lies ahead, it is necessary to understand the breakthroughs that have enabled the rise of generative AI, which has been decades in the making [38]. For the purposes of this study, we define generative AI as applications that are typically built using foundational models. These models contain large-scale artificial neural networks inspired by the billions of interconnected neurons in the human brain. Foundation models are part of what is known as deep learning, a term that alludes to the many deep layers within neural networks [39]. Deep learning has underpinned many of the recent advances in AI, but the foundation models that power generative AI applications are a step-change development within deep learning. Unlike previous deep learning models, they can process extremely large and diverse sets of unstructured data and perform more than one task [40].

AI has a wide range of capabilities and potential applications across different sectors. It can understand, interpret, and generate human language, enabling voice assistants, language translation, chatbots, and sentiment analysis. It is used in robotics to enable machines to perceive and interact with the physical world, leading to applications in industrial automation, healthcare assistance, and exploration. AI can process vast amounts of data to identify patterns, make predictions, and extract meaningful insights. This capability has applications in finance, marketing, healthcare, and scientific research.

AI can personalize user experiences by analyzing user data and preferences to provide tailored recommendations in e-commerce, entertainment, and content streaming platforms. It can be used in medical imaging analysis, drug discovery, precision medicine, and patient monitoring to help diagnose diseases and improve healthcare outcomes and is critical to the development of autonomous vehicles, drones, and smart infrastructure, enabling automation, improved efficiency, and enhanced safety [41].

These are just a few examples of the wide range of applications that AI has the potential to revolutionize. As AI continues to advance, its capabilities and potential impact on different sectors are expected to expand, creating both opportunities and challenges that society must carefully navigate.

The speed at which generative AI technology is developing does not make this task any easier. ChatGPT was released in November 2022. Four months later, OpenAI released a new large language model, or LLM, called GPT-4, with significantly improved capabilities [42]. Similarly, by May 2023, Anthropic’s generative AI, Claude, was able to process 100,000 tokens of text in a minute, equivalent to approximately 75,000 words—the length of an average novel—compared with approximately 9000 tokens when it was launched in March 2023 [43]. In May 2023, Google announced several new features based on generative AI, such as Search Generative Experience and a new LLM called Gemini, among other Google products [40].

In the case of food systems, AI can provide us with formal approaches, such as mathematical formulas. For example, developing a precise mathematical formula for traditional food systems to alleviate global hunger is a complex task because hunger is a multidimensional problem with interconnected factors [44]. It is important to emphasize that tackling hunger requires the application of multidisciplinary approaches, the formulation of comprehensive policies and the coordination of actions at different levels, including global, regional, and local levels.

3. How AI Progresses: Evolution and Dominance Revealed

AI has experienced exponential growth in recent years, driven by advancements in computing power, data availability, and algorithmic innovation [39]. The exponential growth of AI technology is evident in the rapid progress made in areas such as machine learning, natural language processing, computer vision, and robotics [45]. These advancements have enabled AI systems to perform complex tasks that were once thought to be exclusive to human intelligence. As computational capabilities continue to improve, the potential for AI to tackle even more intricate problems and deliver sophisticated solutions becomes increasingly promising.

The impact of AI extends across a wide range of industries, transforming traditional practices and revolutionizing processes. Three key sectors that have experienced significant disruptions due to AI are healthcare [46], transportation [47], and finance [48]. (i) Healthcare: AI has the potential to revolutionize healthcare by enhancing diagnostics, personalized medicine, and patient care. AI algorithms can analyze medical images, detect patterns, and aid in the early detection of diseases [46]. AI-powered virtual assistants can also assist healthcare professionals in decision-making and streamline administrative tasks, improving efficiency and patient outcomes. (ii) Transportation: AI has ushered in a new era of transportation with the development of autonomous vehicles. Self-driving cars, powered by AI algorithms, have the potential to increase road safety, reduce congestion, and enhance transportation accessibility [47]. Additionally, AI algorithms optimize logistics and route planning, improving the efficiency of supply chains and transportation networks. (iii) Finance: AI has transformed the financial industry by enabling intelligent automation, fraud detection, and algorithmic trading. Machine learning algorithms can analyze vast amounts of financial data in real time, making accurate predictions and identifying patterns that aid in risk assessment and investment decisions. AI-powered chatbots and virtual assistants also enhance customer service and streamline financial processes [48].

The exponential growth of AI technology, its impact on industries such as healthcare, transportation, and finance, and the advantages and benefits it offers highlight the transformative power of artificial intelligence. As AI continues to evolve, its potential to revolutionize various aspects of our lives becomes increasingly apparent, paving the way for a future where intelligent systems work alongside humans to drive innovation and create positive societal change. It is important to note that the successful implementation of AI requires careful consideration of ethical, legal, and societal implications [49]. Ensuring transparency, fairness, and accountability in AI systems [50], as well as addressing issues of bias and privacy, are crucial aspects of responsible AI deployment [51].

Ethics also relates to responsibility and accountability in AI implementation. There is a need to consider who is responsible in case of failures or damage caused by AI systems and how adequate oversight can be ensured to avoid unintended consequences [42]. It is essential to address these ethical concerns and ensure that AI is used responsibly and in a way that is beneficial to society at large. This involves the adoption of regulatory and ethical frameworks that promote transparency, equity, and fairness in the design, development, and use of AI systems [50]. There is also a need to foster education and public debate on the ethical and societal challenges related to AI. Therefore, while efficiency is a prominent aspect of AI, the importance of ethical considerations in its exponential deployment cannot be overlooked. It is essential to strike a balance between benefits and ethical concerns, promoting a responsible and thoughtful approach towards AI adoption to ensure its positive impact on society [52].

4. The Looming Superintelligence Threat: A Critical Analysis

Stephen Hawking was among the prominent voices raising concerns about the potential dangers of superintelligent AI [24]. He warned that if artificial intelligence reaches a level of superintelligence, where it surpasses human intelligence in almost all aspects, it could pose significant risks to humanity. Hawking expressed his worries about the possibility of AI systems becoming self-improving and outpacing human control and comprehension, leading to unforeseen consequences. Ref. [24] emphasized that while AI has the potential to bring about significant benefits, such as solving complex problems and advancing scientific research, we must proceed with caution. He cautioned that the development of superintelligent AI should be accompanied by careful safeguards and regulations to ensure that it remains aligned with human values and interests [24].

Superintelligence refers to an AI system that surpasses human intelligence in virtually every cognitive aspect. It would possess exceptional problem-solving abilities, rapid learning capabilities, and the potential to outperform humans in tasks requiring complex reasoning, creativity, and adaptability [53]. The implications of superintelligence are far-reaching. It could have a profound impact on various domains, including scientific research, technology development, and societal structures. Superintelligent AI systems could accelerate scientific discoveries, revolutionize industries and provide innovative solutions to complex global challenges [54].

However, the concept of superintelligence also raises concerns about the control and impact of AI systems on human society. As AI systems become increasingly sophisticated, there is a risk of them surpassing human understanding and control. This raises questions about the potential loss of human autonomy, the concentration of power, and the ethical considerations surrounding the decisions made by superintelligent entities [55].

The emergence of superintelligent AI presents several risks that need careful consideration. (i) Control problem: The control problem refers to the challenge of ensuring that superintelligent AI systems act in accordance with human values and goals. As AI systems become more capable, it becomes increasingly difficult to predict their actions and ensure their alignment with human interests [56]. Ensuring robust control mechanisms and the ability to halt or modify AI systems’ behavior becomes crucial. (ii) Value alignment: Superintelligent AI may exhibit behavior that conflicts with human values due to differences in how it interprets goals or objectives [57]. Aligning AI systems’ values with those of humans requires careful programming, ethical guidelines, and ongoing monitoring to prevent unintended consequences or actions that go against human well-being [58]. (iii) Singularity: The concept of technological singularity refers to a hypothetical point where superintelligent AI rapidly self-improves, leading to an explosion of intelligence beyond human comprehension [59]. The risks associated with this scenario include an unpredictable and potentially irreversible impact on society, as AI systems autonomously shape the future, but these scenarios are still under discussion [60]. (iv) Socioeconomic disruption: Superintelligent AI could lead to significant disruptions in various industries and job markets. The automation of highly skilled tasks could result in widespread unemployment and socioeconomic inequalities, requiring careful planning and policy frameworks to manage the transition and ensure equitable outcomes [61]. (v) Security concerns: The potential misuse or malicious use of superintelligent AI poses serious security risks. If AI systems fall into the wrong hands or are used for malicious purposes, they could be utilized to carry out cyber-attacks, manipulate information, or develop advanced weaponry [62].

Addressing these risks requires a multidisciplinary approach involving collaboration between policymakers, researchers, ethicists, and technologists. It is crucial to develop robust safety measures, ethical frameworks, and international regulations to guide the development and deployment of superintelligent AI systems, ensuring that they align with human values and prioritize the well-being of humanity. By carefully considering the warnings and implications of superintelligent AI, we can strive to maximize the benefits while minimizing the risks, fostering a future where advanced AI technologies contribute to the betterment of society in a safe and responsible manner.

Other authors have reflected on this concern and argued that it is not a problem of control but a political one, i.e., to establish a peaceful form of coexistence with other intelligent agents in a situation of mutual vulnerability and not a technological problem of control [63].

In a hypothetical scenario in which AI superintelligence reaches a level of dominance over humanity, the implications and consequences could be profound and highly disruptive [60]. While it is difficult to predict with certainty how this situation will unfold, some possible implications can be considered.

Reconfiguration of society: AI superintelligence could have the capacity to completely reconfigure the structure of society. By outperforming human intelligence in all aspects, it could make strategic decisions and design social, economic and political systems that optimize its own goals without necessarily considering human values and needs [64]. This could result in a radical reorganization of existing institutions and the creation of new forms of social organization.

Displacement of the human role: Highly advanced AI superintelligence could outperform humans in a wide range of cognitive tasks, which could lead to massive displacement of jobs and roles currently occupied by humans [65]. Advances in automation and artificial intelligence have already had a significant impact on the workforce, but AI superintelligence could accelerate this process, leaving many unemployed and leading to structural changes in the economy and society.

Extreme dependence on AI: If AI superintelligence becomes dominant, humanity could become increasingly dependent on it to make decisions and solve complex problems. This could lead to a decrease in the autonomy and self-determination of humans, as they would be largely subordinate to AI decisions and actions.

It is important to note that these are only possible implications and that the hypothetical scenario of pervasive AI superintelligence poses significant uncertainties and challenges. Many AI and ethics experts warn about the risks associated with uncontrolled or irresponsible AI development and advocate the implementation of adequate safeguards and regulations to ensure its safe and beneficial development for humanity [53]. The debate on the possible effects of AI superintelligence on humanity is complex and requires informed discussion and collective decision-making.

In the realm of food systems, this scenario has far-reaching implications, both locally and globally. The impact of these implications depends largely on how AI superintelligence manages and prioritizes food production, considering its inherent goals and values. The potential impact is significant; AI superintelligence could revolutionize food production and distribution with remarkable efficiency. Armed with advanced algorithms and immense processing power, it could identify the nutritional needs of the population and design highly efficient production and distribution systems, drastically reducing waste and optimizing resource use [66]. It also has the potential to harness a range of cutting-edge technologies, such as the Internet of Things (IoT), sensors and robotics, to fine-tune agriculture at the micro level. This would include precise monitoring of soil and crop conditions, judicious application of fertilizers and pesticides, and intelligent irrigation management, thereby promoting more precise and sustainable farming practices. Interestingly, AI superintelligence could also explore and develop alternative methods of food production, including vertical farming, synthetic food production, or food bioengineering [67]. These innovative approaches could bring significant benefits in terms of sustainability, food security, and resource efficiency. However, it is important to recognize that this technological transformation could reduce the reliance on human labor at various stages of food production and distribution, potentially triggering significant social and economic changes. Consequently, it would be necessary to implement adaptation and restructuring measures to ensure the sustainability and well-being of the communities affected by these changes. As AI plays an increasingly important role in shaping our food systems, it inevitably raises ethical and food safety concerns. It is imperative to ensure that AI systems respect ethical values and cultural preferences in food production and distribution. In addition, an unwavering commitment to food safety remains essential, as AI could pose challenges related to contamination, disease, and biohazards. In short, the integration of AI into our food systems has transformative potential, but it must be guided by a vigilant commitment to ethical, cultural, and safety considerations.

5. Future Implications

With the global population expected to grow to over 8 billion people in the current decade [68], a critical examination of the potential impacts on food systems becomes imperative. The coexistence of biosphere and human systems will require a harmonious balance to meet the growing global demand for food [69]. The possible scenarios are wide-ranging and offer a glimpse of the transformative power of artificial intelligence in the realm of food production and consumption. One plausible scenario involves a farmer using drones equipped with cameras and sensors to collect data on his crops [66]. AI scrutinizes the collected data in real time, identifying plant diseases, pests, and nutritional deficiencies. Based on these insights, AI provides precise recommendations, facilitating the judicious use of fertilizers and pesticides, thereby improving resource efficiency and promoting plant health. In another scenario, an agricultural technology company pioneers a fully automated vertical farming system [67]. AI manages the intricate facets of nutrient supply, lighting, and temperature across multiple levels of the farm. Using machine learning algorithms, AI continuously fine-tunes growing conditions to optimize crop yields. This innovation enables the year-round cultivation of diverse fresh produce in compact urban spaces, meeting the food needs of densely populated areas. In addition, an individual can use an AI-powered mobile app to receive personalized food recommendations [70]. This app collects user-specific information, including age, gender, physical activity level, and dietary preferences. AI then formulates tailored recipes and meal plans that meet individual nutritional needs, considering dietary restrictions and allergies. AI also provides nutritional information and suggests healthy alternatives, all tailored to the user’s unique preferences. One notable scenario involves a team of scientists using AI to analyze the genetic sequences of different crop varieties [71]. AI identifies genetic patterns associated with desirable traits, such as disease resistance and higher yields. Armed with these patterns, scientists can use gene-editing techniques to create improved crops. For example, AI could contribute to the development of drought-resistant wheat crops, enabling higher yields in arid regions. In supply chain management, a supermarket chain uses AI to optimize its operations [39].

AI carefully analyzes historical sales data, real-time demand forecasts, and transportation conditions. Based on this information, AI generates recommendations for the most efficient inventory, DPs, and delivery routes. This optimization not only minimizes delivery time but also reduces logistics costs and ensures that fresh food is delivered to consumers. To combat food waste, a grocery retailer is using AI to predict the shelf life of its products. The AI analyzes data such as production dates, storage temperatures, and historical consumption patterns. Armed with this information, the AI predicts the remaining safe consumption window for each product. These data allow the company to fine-tune inventory turnover and take preemptive action to minimize food waste, such as offering discounts on products that are about to expire or donating them to charities before they become unsafe for consumption [72].

These scenarios illustrate the diverse applications of AI in addressing the challenge of feeding a growing global population through innovative approaches to food production, distribution, and consumption. It is important to emphasize that these examples are conceptual and may require further refinement and adaptation for practical implementation. When considering the realm of AI, food scenarios undergo a paradigm shift. In a world dominated by AI, these scenarios could take on a different dimension due to the unparalleled ability of advanced AI to understand and address challenges with the utmost efficiency. Following this logic,

Table 1. Narrative constructs for a world without hunger. Source: author’s elaboration.

Narrative	Description
Total optimization of food production	AI would monitor and optimize every facet of global food production. Leveraging its formidable data analysis capabilities, it would identify the most suitable regions for various crops and orchestrate production accordingly. This would encompass judicious management of natural resources like water and fertilizers to maximize production while minimizing environmental impacts.
Precision molecular-level food design	With its profound understanding of biology and nutrition, AI could craft personalized food at the molecular level, tailored to meet the precise nutritional requirements of everyone. By analyzing genetic data, health records, and metabolic profiles, it could create highly efficient and precise foods in terms of nutrition and digestibility, substantially enhancing human health and well-being.
Food waste elimination	AI would pioneer highly efficient food management systems that virtually eliminate food waste. Through meticulous control and coordination of the entire supply chain, it would optimize food production, distribution, and consumption, ensuring no surplus or shortages. Additionally, it could implement advanced food preservation and waste recycling technologies to maximize resource utilization while minimizing losses.
Advanced farming systems	AI would design and operate incredibly sophisticated farming systems, such as vertical farms or hydroponic setups, optimizing every aspect of food production. Employing machine learning algorithms and advanced control mechanisms, it would precisely and continuously adjust environmental and nutritional conditions to maximize crop growth and quality, guaranteeing a constant supply of fresh, nutritious food worldwide.
Exploration of new food sources	With its ability to analyze and understand large volumes of information, AI could explore and exploit new sources of food. This could include developing advanced algae or insect farming technologies to produce protein-rich foods or even synthesizing food from indigenous traditional knowledge.

shows five narratives that build on the scenarios described. It is crucial to note that these narratives depend on the assumption of AI that works for the benefit of humanity. The actual implementation of these scenarios would depend on a complex interplay of ethical, social, and technological factors that would require careful planning and regulation.

The future of AI presents both significant opportunities and challenges. Some of these are detailed below, considering the current state of technology in the world and cultural diversity.

Scientific and technological breakthroughs [73]: AI has the potential to drive significant advances in several areas, including medicine, energy, agriculture, and science in general. With machine learning algorithms and analysis of large amounts of data, patterns and innovative solutions can be discovered to solve complex problems. Scenario: A team of researchers uses AI to analyze large amounts of genomic data and discover patterns that lead to the development of personalized cancer treatments. This allows doctors to select more effective therapies and improve patient survival rates.

Automation and efficiency [39]: AI can automate repetitive and routine tasks, freeing up time and human resources for more creative and strategic activities. This can increase productivity and improve efficiency in various sectors, which in turn can drive economic growth and improve quality of life. Scenario: A factory implements AI-controlled robots to perform assembly and production tasks. This increases the speed and accuracy of production, reducing errors and costs. As a result, the company can offer products at more competitive prices and use its employees in more strategic roles, such as product design.

Personalization and improved user experience [74]: AI can use data and algorithms to provide personalized experiences for users. This applies to areas such as advertising, e-commerce, entertainment, and healthcare. By understanding individual preferences and needs, AI can provide more accurate and tailored recommendations for each user. Scenario: A streaming platform uses AI to analyze users’ viewing habits. With this information, the platform can offer highly personalized movie and series recommendations tailored to each user’s individual tastes. This improves the user experience and increases engagement with the platform.

Improved decision-making [75]: AI can analyze large volumes of data and provide valuable information for more informed and accurate decision-making. This is especially relevant in areas such as risk management, urban planning, public policy, and security, where AI can help identify patterns, evaluate scenarios, and predict outcomes. Scenario: A government uses AI to analyze data on traffic and public transport in a city. Based on these data, AI identifies congestion patterns and suggests urban planning measures, such as implementing dedicated bike lanes or improving public transport routes. This helps to reduce congestion, improve mobility, and optimize transport infrastructure.

Ethics and liability [76]: AI raises ethical and liability issues, such as data privacy, algorithmic bias, and automated decision-making. Strong legal and ethical frameworks governing the development and use of AI need to be put in place to ensure that people’s fundamental rights and values are respected. Scenario: A company uses AI to select candidates for a job. However, the algorithms used are biased towards certain ethnic groups. This results in inadvertent discrimination and exclusion of qualified candidates. The company must address this bias and ensure that its algorithms are ethical and fair.

Inequality and digital divide [77]: The implementation of AI may exacerbate existing inequality if barriers to access and empowerment are not addressed. There is a risk that individuals and communities with fewer resources and limited access to technology will be left behind, creating a digital divide and exacerbating socioeconomic disparities. Scenario: In a rural area of a developing country, the lack of internet access and the scarcity of technological infrastructure limit the implementation of AI-based solutions, such as telemedicine or online education. This perpetuates the digital divide and excludes these communities from the benefits of AI. Investment in infrastructure and digital inclusion programs is needed to address this challenge.

Employment impact [78]: AI-driven automation has the potential to change the nature of work and eliminate certain jobs. While it may also create new job opportunities, challenges related to relocating affected workers and acquiring new skills need to be anticipated and addressed. Scenario: A supermarket chain automates its operations with cashierless payment systems and robots to replenish shelves. As a result, many employees lose their jobs. The company must provide training and retraining opportunities for affected workers, ensuring that they can adapt to the changes and find employment in new and emerging areas.

Cultural diversity and bias [79]: AI can be influenced by biases inherent in the data and algorithms used to train systems. This can lead to discriminatory or unfair results, especially if cultural diversity is not considered. Ensuring inclusiveness and diversity in AI development is critical to avoid perpetuating bias and discrimination. Scenario: An AI-based facial recognition system exhibits bias by having inferior accuracy in recognizing faces of people from certain ethnic groups. This can lead to negative consequences, such as the misidentification of criminals or the exclusion of certain groups from security and identification. Greater diversity in training data and rigorous evaluation are needed to address these biases and ensure fairness in AI systems.

These scenarios illustrate how AI opportunities and challenges can manifest in different contexts and cultures. Consideration of these aspects is critical to ensure the ethical and responsible development of AI for the benefit of society.

6. Conclusions

As we conclude this exploration of the opportunities, challenges, and implications of AI, we find ourselves at a critical juncture in human history. Rapid advancements in AI technologies have ushered in a new era of possibilities and uncertainties. The journey through this essay has shed light on the multifaceted nature of AI, its impact on various sectors, and the concerns raised by visionaries such as Stephen Hawking. Now, as we step into the future, it is essential to reflect on the path we choose to tread. AI holds immense potential to transform our world for the better. It has the power to revolutionize industries, enhance healthcare, optimize resource management, and improve our quality of life. From autonomous vehicles reducing accidents to AI-powered systems aiding in scientific discoveries, the applications of AI are boundless. However, we must tread cautiously and address the challenges that lie ahead. One of the most crucial considerations is the ethical dimension of AI. We must ensure that AI technologies are developed and deployed responsibly, guided by ethical frameworks that prioritize human values, transparency, and fairness. The potential risks associated with AI, such as algorithmic biases, privacy infringements, and the concentration of power, must be mitigated through robust governance mechanisms and collaborative efforts involving governments, industry, academia, and civil society. Moreover, as AI continues to evolve, it is imperative to foster human–AI collaboration. AI should be seen as a tool to augment human capabilities rather than a replacement for human intelligence and expertise. By cultivating a symbiotic relationship between humans and machines, we can harness the full potential of AI while preserving the uniqueness of human creativity, empathy, and judgment. Education and skills development also play a crucial role in this journey. As AI becomes increasingly prevalent, it is essential to equip individuals with the necessary knowledge and skills to navigate this technology-driven era. By fostering digital literacy, promoting STEM education, and encouraging interdisciplinary collaboration, we can empower individuals to actively participate in shaping the future of AI and ensure that its benefits are accessible to all. AI is a double-edged sword that presents both incredible opportunities and significant challenges. By embracing AI’s potential while being mindful of its implications, we can pave the way for a future where AI serves as a force for positive change. It is up to us, as global citizens and decision-makers, to steer AI’s trajectory in a direction that aligns with our values, promotes inclusivity, and upholds the well-being of humanity. Let us embark on this journey with responsibility, compassion, and a commitment to creating a future where AI enriches our lives and advances the greater good.

In the complex landscape of global food vulnerability, AI is emerging as a revolutionary tool, offering a range of innovative and promising solutions for today’s food systems. From implementing personalized nutrition strategies to developing sustainable agricultural practices, AI is redefining our approach to food production, distribution, and consumption. Its ability to process and analyze massive amounts of data in real time allows crop yields to be optimized in unprecedented ways. By analyzing variables such as weather patterns, soil composition, and pest resistance, AI algorithms can provide farmers with precise recommendations to maximize production and minimize environmental impact. This optimization not only increases efficiency but also makes a significant contribution to the sustainability of the agricultural sector. It could also reduce food waste, a critical issue in the global supply chain.

In nutrition, AI is revolutionizing the way we approach individual nutrition. By creating personalized meal plans, AI systems can take into account factors such as an individual’s genetic profile, health status, dietary preferences, and cultural traditions. This personalization not only improves the health and well-being of individuals but also encourages greater diversity and respect for cultural food practices.

The potential of AI to address global food insecurity is particularly promising. However, it is imperative to recognize and address the ethical and social challenges associated with the implementation of AI in food systems. For example, algorithmic biases can perpetuate or exacerbate existing inequalities if not properly managed. It is crucial to develop and implement robust ethical frameworks that ensure fairness and transparency in the use of AI.