Use of Generative AI by Small-scale Farmers in Nigeria: An Empirical Study

during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (see The Effect of Open Access).

This article presents a comprehensive study conducted during the spring semester of 2024, aimed at exploring undergraduate computer science students’ perceptions, awareness, and understanding of generative artificial intelligence (GAI) tools within the context of their Artificial Intelligence (AI) courses. The research methodology employed qualitative techniques, including human-subject research and focus groups, to delve into students’ insights on the evolution of AI as delineated in the seminal textbook by Russell and Norvig. The study-initiated discussions on the historical development of AI, prompting students to reflect on the aspects that intrigued them the most, and to identify which historical concepts and methodologies, perhaps even those not directly covered in their curriculum, piqued their interest. Furthermore, the dialogue encompassed the learning methodologies highlighted in the textbook, seeking students’ feedback on the strategies that have been most effective for mastering complex AI theories and their practical applications. Interdisciplinary applications of AI were also discussed, encouraging students to contemplate AI’s role beyond the realm of computer science and its potential to foster innovative solutions across various fields. Finally, the conversation shifted towards students’ personal goals and aspirations in AI, urging them to consider how their perspectives have evolved in light of technological advancements, societal needs, and ethical considerations. The findings underscore a notable gap in students’ awareness of AI’s history and its current capabilities, indicating a need for educational strategies that not only deepen understanding but also foster a broader appreciation of AI’s potential. This study contributes valuable insights into enhancing AI education and encouraging interdisciplinary innovation among the next generation of computer scientists.

(1) Background: Artificial intelligence (AI) has flourished in recent years. More specifically, generative AI has had broad applications in many disciplines. While mental illness is on the rise, AI has proven valuable in aiding the diagnosis and treatment of mental disorders. However, there is little to no research about precisely how much interest there is in AI technology. (2) Methods: We performed a Google Trends search for "AI and mental health" and compared relative search volume (RSV) indices of "AI", "AI and Depression", and "AI and anxiety". This time series study employed Box-Jenkins time series modeling to forecast long-term interest through the end of 2024. (3) Results: Within the United States, AI interest steadily increased throughout 2023, with some anomalies due to media reporting. Through predictive models, we found that this trend is predicted to increase 114% through the end of the year 2024, with public interest in AI applications being on the rise. (4) Conclusions: According to our study, we found that the awareness of AI has drastically increased throughout 2023, especially in mental health. This demonstrates increasing public awareness of mental health and AI, making advocacy and education about AI technology of paramount importance.

Response to M. Trengove & coll regarding "Attention is not all you need: the complicated case of ethically using large language models in healthcare and medicine".

How Can <i>IJDS</i> Authors, Reviewers, and Editors Use (and Misuse) Generative AI?

This study sought to identify significant barriers to market access and marketing connections for small-scale rural farmers, evaluating the impact of demographic factors (gender, education level) and operational factors (years in farming, distance from home, type of commodity) on these constraints. The research employed a cross-sectional descriptive and inferential quantitative approach to examine the barriers to market access and marketing connections among small-scale rural farmers in Ghana's Volta area. The conceptual framework is based on a multi-theory approach. The contingency theory elucidates the significance of farm size, resource availability, and geographic location; the human capital theory delineates the impact of education level and years of farming experience; and the logistics and spatial analysis framework examines how transportation infrastructure, geographic location, and commodity type affect market access and connections. The investigation indicated that inadequate road infrastructure and elevated transportation expenses were the primary obstacles for small-scale rural farmers in accessing markets, with notable disparities based on gender and educational attainment. The commodity kind, years of cultivation, and distance from home substantially influenced limitations. The study concentrated on the Volta region, however the results are probably relevant to other regions in Ghana because of comparable agro-ecological zones and rural socio-economic traits. The rigorous research design, data collection techniques, and comprehensive analysis guarantee dependable and valid outcomes. Notwithstanding possible constraints in generalisability, the research provides comprehensive insights into the distinct issues encountered by small-scale farmers. It emphasises socio-economic factors affecting market access, illustrates the impact of farm-level contingencies on market access and linkages, identifies both diversity and uniformity among small-scale farmers, and addresses a gap in the literature by offering empirical evidence on market access constraints specific to the Volta region that may have global relevance. These contributions are significant for both academic comprehension and practical initiatives aimed at assisting small-scale rural farmers in Ghana and analogous environments worldwide.

Several revolutions are currently taking place in the healthcare industry to provide accurate, reliable, and valid healthcare to patients. Among these is artificial intelligence (AI). This study aimed to assess the CP's awareness, perceptions, and opinions of AI in health care among community pharmacists. This cross-sectional survey-based study was conducted over 3 months in 2023 using structured prevalidated 34 items questionnaires. In this study, 94.5% (n= 258) of the CPs were aware of AI, yet 25.6% (n= 70) believed that AI would eventually replace healthcare professionals. However, 63.4% (n= 173) of the CPs concurred that AI is a technology that supports healthcare workers. 12.8% of the CPs believed that there is a risk of losing their jobs if AI is widely used in Saudi Arabia, but 68.9% (n= 188) of them considered that healthcare professionals will benefit from the extensive use of AI. Eighty-four percent of CPs (n= 232) agreed or strongly agreed that AI decreases drug mistakes in clinical practice. Similarly, 86% of the CPs (n= 235) concurred that AI makes it easier for patients to access the service. In contrast, almost 58% of the CPs (n= 232) agreed that AI makes it easier for healthcare professionals to acquire information, and 87.9% of the CPs (n= 240) said that AI helps them make better decisions. This study concluded that most of the CPs were aware of AI and agreed that AI is a tool that helps healthcare professionals. In addition, the majority of the CPs thought that AI adoption in healthcare practice will benefit healthcare practitioners.

Artificial intelligence (AI) is a rapidly developing technology with the potential to have a major impact on society. However, there is growing concern that Generative AI could be used in ways that exclude or harm certain groups of people. This raises the question of how Generative AI awareness can be used to promote inclusivity. This paper presents the findings of an exploratory study on the impact of Generative AI awareness on inclusivity. The study involved semi-structured interviews with participants from a variety of backgrounds, including the general public, specific stakeholder groups, and marginalized groups. The findings of the study suggest that Generative AI awareness can have a positive impact on inclusivity. Participants who were more aware of AI were more likely to be supportive of policies and practices that promote inclusivity in the development and use of AI. They were also more likely to take steps to mitigate the potential risks of Generative AI for marginalized groups. However, the study also found that AI awareness may be related negatively with inclusivity. Participants who were more aware of the potential for AI to be biased were more likely to avoid using AI-powered products and services. This could lead to marginalized groups being excluded from the benefits of AI. The findings of this study have several of implications for policymakers, businesses, and other organizations that are developing and using AI. It is important to be aware of the potential for Generative AI to exacerbate existing inequalities and to take steps to promote inclusivity in the development and use of AI.

Awareness of the Role of Artificial Intelligence in Health Care among Undergraduate Nursing Students: A Descriptive Cross-Ssectional Study.

Drawing on the conservation of resources theory (COR), the research aims to reveal the influence of artificial intelligence (AI) awareness on employees' mental health and behaviors, particularly examining whether and how employees' AI awareness impacts their counterproductive work behaviors (CWB) in human-intelligence collaborations. Data was collected from 327 Chinese employees who collaborated with AI in sales, manufacturing, logistics, and other industries. The measurement instruments included scales for AI awareness, psychological contract (PC), emotional exhaustion (EE), and counterproductive work behavior (CWB). We used Hayes's PROCESS macro to analyze the data. AI awareness had a significant positive impact on CWB (β = 0.448, p < 0.01). PC and EE play a role as partial mediators in the relationship between AI awareness and CWB. The mediating pathways consist of three sequences: "AI awareness → PC → CWB," "AI awareness → EE → CWB" and "AI awareness → PC → EE → CWB," with the respective contributions to the overall effect amounting to 8.04, 18.53, and 4.91%. Our research contributes to the study of AI in the management field by elucidating the relationship between AI awareness and CWB, as well as the mediating mechanisms of this relationship, which enriches the literature on CWB and expands the understanding of the associations between AI and CWB.

This study investigates the patterns of artificial intelligence (AI) awareness among pre-service teachers at Mersin University, using both descriptive and inferential analyses to examine the levels of knowledge and attitudes towards AI. Understanding educators' AI awareness is essential as AI is increasingly integrated into education. A sample of 117 pre-service teachers completed the Artificial Intelligence Awareness Scale for Teachers, measuring Practical Knowledge, Beliefs and Attitudes, Attitude to Association, and Theoretical Knowledge. Statistical analysis were conducted to assess differences in AI awareness across demographic variables, including gender, academic department, and technology use. In addition, cluster analysis was performed, revealing three distinct clusters: (1) a moderate-awareness cluster, characterized by average levels of AI knowledge and attitudes across all dimensions; (2) a low-awareness cluster, characterized by limited AI knowledge and neutral-to-negative attitudes; and (3) a high-awareness cluster, characterized by strong AI knowledge and positive attitudes toward artificial intelligence. The findings that technology usage significantly influences pre-service teachers' AI awareness levels, whereas demographic factors such as gender and academic department do not. The results emphasize the need for differentiated AI training within teacher preparation programs, suggesting foundational AI literacy training for lower-awareness groups and more advanced content for those already possessing higher awareness.

Impact of membership in agricultural cooperatives on yield of smallholder tomato farmers in Nigeria

We may have to soon decide what kind of Artificial General Intelligence (AGI) computers we will build and how they will coexist with humans. Many predictions estimate that artificial intelligence will surpass human intelligence during this century. This poses a risk to humans: computers may cause harm to humans either intentionally or unintentionally. Here we outline a possible democratic society structure that will allow both humans and artificial general intelligence computers to participate peacefully in a common society.There is a potential for conflict between humans and AGIs. AGIs set their own goals which may or may not be compatible with the human society. In human societies conflicts can be avoided through negotiations: all humans have the about the same world view and there is an accepted set of human rights and a framework of international and national legislation. In the worst case, AGIs harm humans either intentionally or unintentionally, or they can deplete the human society of resources.So far, the discussion has been dominated by the view that the AGIs should contain fail-safe mechanisms which prevent conflicts with humans. However, even though this is a logical way of controlling AGIs we feel that the risks can also be handled by using the existing democratic structures in a way that will make it less appealing to AGIs (and humans) to create conflicts.The view of AGIs that we use in this article follows Kantian autonomy where a device sets goals for itself and has urges or drives like humans. These goals may conflict with other actors’ goals which leads to a competition for resources. The way of acting and reacting to other entities creates a personality which can differ from AGI to AGI. The personality may not be like a human personality but nevertheless, it is an individual way of behaviour.The Kantian view of autonomy can be criticized because it neglects the social aspect. The AGIs’ individual level of autonomy determines how strong is their society and how strongly integrated they would be with the human society. The critic of their Kantian autonomy is valid, and it is here that we wish to intervene.In Kantian tradition, conscious humans have free will which makes them morally responsible. Traditionally we think that computers, like animals lack free will or, perhaps, deep feelings. They do not share human values. They cannot express their internal world like humans. This affects the way that AGIs can be seen as moral actors. Often the problem of constraining AGIs has used a technical approach, placing different checks and designs that will reduce the likelihood of adverse behaviour towards humans. In this article we take another point of view. We will look at the way humans behave towards each other and try to find a way of using the same approaches with AGIs.

Getting AI Right: Introductory Notes on AI &amp; Society

Purpose The prevalence of artificial intelligence (AI) has considerably affected management and society. This paper aims to explore its potential impact on hospitality industry employees, bringing enlightenment to both employees and managers. Design/methodology/approach Data were collected from a survey of 432 employees who worked in full-service hotels in China. Structural equation modeling (SEM) was used to analyze the data. Findings Results presented a positive relationship between AI awareness and job burnout. No significant direct relationship was found between AI awareness and career competencies. Organizational commitment mediated the relationship between AI awareness and career competencies, as well as the relationship between AI awareness and job burnout. Research limitations/implications This study contributes to human resource management in the hospitality industry to theoretical and practical aspects. Theoretically, it enriched both career theory and fit theory. Practically, this study reminds managers to pay attention to the adverse effect of AI on human capital. It also enlightens the manager to think of the positive effects that AI may bring. Managers should provide proper support to overcome AI’s threat to human resources. Practical implications Practically, this study reminds managers to pay attention to the adverse effect of AI on human capital. It also enlightens the manager to think of the positive effects that AI may bring. Managers should provide proper support to overcome AI’s threat to human resources. Originality/value The study aims to analyze the impact of AI from a career perspective. It provided theoretical support and evidence for hotel managers for the effects of AI awareness on hotel employees. The study conveys a potential topic of concern that the hospitality industry may face in the future.