The distinctions and the value of physician-scientists: a call for sustained support and nourishment

The rise of Artificial Intelligence (AI) in our society is becoming ubiquitous and undoubtedly holds much promise. However, AI has also been implicated in high profile breaches of trust or ethical standards, and concerns have been raised over the use of AI in initiatives and technologies that could be inimical to society. Public trust and perceptions of AI trustworthiness underpin AI systems’ social licence to operate, and a myriad of company, industry, governmental and intergovernmental reports have set out principles for ethical and trustworthy AI. To guide the responsible stewardship of AI into our society, a firm foundation of research on trust in AI to enable evidence-based policy and practice is required. However, in order to inform and guide future research, it is imperative to first take stock and understand what is already know about human trust in AI. As such, we undertake a review of 100 papers examining the relationship between trust and AI. We found a fragmented, disjointed and siloed literature with an empirical emphasis on experimentation and surveys relating to specific AI technologies. While findings suggest some convergence on the importance of explainability as a determinant of trust in AI technologies, there are still gaps between conceptual arguments and what has been examined empirically. We urge future research to take a more holistic approach and investigate how trust in different referents impacts on attitudinal and behavioural intentions. Doing so will facilitate a more nuanced understanding of what it means to develop trustworthy AI.

In today’s fast-moving, unpredictable world, the way organizations handle risk is being completely transformed by artificial intelligence (AI). With the rise of big data, global uncertainty, and increasing complexity in everything from finance to cybersecurity, traditional risk management tools are starting to fall short. That’s where AI comes in—not just as a tool, but as a game-changer. This article takes a close look at how AI is revolutionizing risk management. From analyzing massive amounts of data in real time to spotting threats before they happen, AI is helping companies make smarter, faster decisions. Machine learning models can detect patterns and anomalies that humans might miss, while natural language processing tools are scanning everything from news headlines to regulatory updates to flag potential issues. Routine tasks are being automated, saving time and reducing the risk of human error. In short, AI is making risk management more proactive, more precise, and more adaptive. But it’s not all upside. With great power comes real responsibility—and real concerns. Many AI systems are black boxes: they make decisions, but even the people who built them can’t always explain how. That lack of transparency can be risky, especially in high-stakes industries. There's also the issue of bias—AI learns from data, and if the data is flawed or biased, the results can be too. And as organizations depend more on AI, new vulnerabilities emerge, like cyberattacks specifically designed to fool these systems. This article explores both sides of the story. It highlights the exciting possibilities AI brings to risk management, while also being honest about the risks AI itself introduces. Through real-world examples and an eye on the latest research, we discuss how companies can strike the right balance—using AI to stay ahead of risks, while still keeping humans in the loop, ensuring transparency, and building systems that are ethical, fair, and resilient.

The rise of artificial intelligence (AI), particularly ChatGPT, has transformed educational landscapes globally. Moreover, the Beijing Consensus on Artificial Intelligence and Education and the ‘Pact for the Future’ propose that AI can support UNESCO in achieving development goals, especially focusing on SDG 4, which emphasizes quality education. Thus, this study investigates undergraduate students’ familiarity with and attitudes toward AI tools, as well as their perceived risks and benefits of using AI tools at a private university in China. An explanatory sequential mixed-method design was employed with an online survey of 167 students, followed by a qualitative analysis of open-ended responses. Data were analyzed using the one-sample Wilcoxon signed-rank test and thematic analysis, supported by SPSS and ATLAS.ti 25. The findings revealed that students demonstrated moderate familiarity with AI tools, particularly ChatGPT and willingness to use them in coursework. Positive attitudes toward AI’s value in education were evident, although concerns such as dependence and reduced independent thinking, algorithmic bias and ethical concerns, accuracy and information quality, data security, and privacy concerns were observed among students. Moreover, students generally viewed AI positively and perceived AI integration as inevitable and becoming common in academic settings. Students were concerned that the misuse of AI by their teachers was minimal and trusted their teachers to use AI effectively in teaching. Students also perceived AI’s benefits, such as personalized learning, efficiency and convenience, career and skill development, and support for independent learning. This study contributes to the discourse on AI integration in higher education by highlighting students’ nuanced perceptions and balancing their benefits with potential risks. The findings of this study were limited by the small sample size and institution. Future research should explore diverse contexts to develop comprehensive AI implementation frameworks for higher education.

The rise of artificial intelligence (AI) heralds a significant revolution in healthcare, particularly in mental health.AI's potential spans diagnostic algorithms, data analysis from diverse sources, and real-time patient monitoring. It is essential for clinicians to remain informed about AI's progress and limitations. The inherent complexity of mental disorders, limited objective data, and retrospective studies pose challenges to the application of AI. Privacy concerns, bias, and the risk of AI replacing human care also loom. Regulatory oversight and physician involvement are needed for equitable AI implementation. AI integration and use in psychotherapy and other services are on the horizon. Patient trust, feasibility, clinical efficacy, and clinician acceptance are prerequisites. In the future, governing bodies must decide on AI ownership, governance, and integration approaches. While AI can enhance clinical decision-making and efficiency, it might also exacerbate moral dilemmas, autonomy loss, and issues regarding the scope of practice. Striking a balance between AI's strengths and limitations involves utilizing AI as a validated clinical supplement under medical supervision, necessitating active clinician involvement in AI research, ethics, and regulation. AI's trajectory must align with optimizing mental health treatment and upholding compassionate care.

With the rise of artificial intelligence (AI), cultivating the AI abilities of the new generation of learners has become crucial. However, currently, there is a lack of tools in education found to effectively enhance students' AI abilities. To discover effective ways to foster students' understanding of AI concepts and skills, this research developed an Artificial Intelligence Image Recognition Robot unit, which was conducted through a series of AI courses in conjunction with educational robots. There are total of 41 undergraduates participating the instructional experiment. The first half of the experiment focused on introducing AI concepts and implementing image recognition models, while the second half involved robot programming and a robot board game competition. At the beginning and the end of the nit, students completed the AI Learning Achievement Test, the Programming-Oriented Computational Thinking scale and the Robot Self-Efficacy Scale to assess differences before and after the unit. The research found that by taking the AI Image Recognition Robot unit, students' AI learning achievements, programming-oriented computational thinking, and robot self-efficacy were significantly enhanced. This suggests that students will be better equipped to evaluate and understand the effectiveness of algorithms in programming and problem solving in the future. It is recommended that robots be incorporated as educational tools when engaging in AI learning.

Artificial Intelligence (AI) is rapidly entering the workplace, changing the way people work and affecting their careers. This integration raises critical questions about the capabilities employees need to maintain a positive outlook on the rise of AI and the future of their career. We explore how goal reengagement capacities shape the impact of human-AI interaction. In two experimental studies, we develop a moderated mediation model in which goal reengagement capacities moderate the path from AI interaction (vs. a control group) through perceived threat of AI to career-related optimism. Using two experimental studies with students ( N = 355) and full-time employees ( N = 186), we show that individuals' goal reengagement capacities moderate the indirect relationship between AI interaction and career-related optimism via perceived threat of AI, such that this indirect effect is negative for those with low goal reengagement capacities and positive for those with high goal reengagement capacities. Our findings underscore the value of letting go of previously held goals and embracing new ones as AI reshapes the world of work, and highlight goal reengagement capacities as critical for maintaining career optimism in an AI-transformed workplace. • Goal reengagement capacities shape the impact of interacting with artificial intelligence (AI) on perceived threat of AI. • Goal reengagement capacities moderate the effect of AI interaction on career optimism through perceived threat of AI. • Individuals interacting with AI perceive AI as more threatening when goal reengagement capacities are low. • Individuals interacting with AI are less optimistic about their careers when goal reengagement capacities are low.

Artificial Intelligence (AI) based applications have already made inroads into many aspects of our lives. The global consultancy firm PwC estimates that AI will contribute $15.7 trillion USD to the global economy by 2030.

The rise of artificial intelligence (AI) presents entrepreneurs with unique yet significant psychological challenges and opportunities that remain underexplored. This literature review examines the impact of AI adoption on entrepreneurs’ psychological well-being, performance, and work engagement, addressing the question: What are the psychological effects of AI adoption on entrepreneurs? It builds on existing psychological theories regarding entrepreneurship and the rise of new technologies,, such as technostress and burnout, while narrowing the focus to the emergent field of AI and its impact on founders. Given that scholars have expressed that negative founder mental health correlates with poor business performance, examining how AI affects the psychological states of entrepreneurs is essential for the flourishing of both individuals and their startups. Using a narrative synthesis of 39 studies, this paper categorizes findings into four key themes: Self-Efficacy, Mastery, and Confidence; AI Dependency and Automation Bias; Technostress, Burnout, and Anxiety; and Work Engagement. Findings indicate that AI tools can enhance entrepreneurs’ self-efficacy, confidence, and decision-making by lowering barriers to entry and reducing cognitive load (e.g., streamlining tasks and providing data-driven insights), particularly for diverse and underrepresented founders. At the same time, over-reliance on AI fosters dependency, automation bias, and diminished critical thinking, while both under- and over-use of AI correlate with heightened technostress, anxiety, and burnout. The relationship between AI adoption and work engagement appears two-fold: moderate use enhances productivity and focus, while excessive or minimal use undermines satisfaction and resilience. These findings underscore that entrepreneurs’ psychological outcomes depend on how they navigate AI’s capabilities and limitations, highlighting the need for balanced adoption strategies. Future research should examine longitudinal effects, individual differences, and targeted interventions to mitigate adverse outcomes and support founders’ well-being in an AI-driven entrepreneurial landscape.

The rise of Artificial Intelligence (AI) has brought a paradigm shift in Human Resource Management (HRM), especially in the sphere of employee development. AI-enabled tools support customized learning journeys, personalized career growth, and data-informed decision-making, ultimately boosting workforce efficiency and engagement. This study examines the transformative influence of AI on employee development, focusing on applications such as smart learning management systems, adaptive training programs, performance analytics, and AI-assisted coaching. Through machine learning models and predictive analytics, AI helps identify skill deficiencies, recommend targeted development initiatives, and ensure continuous upskilling in line with organizational objectives. Moreover, AI enriches the employee journey by enabling tailored career pathways and real-time performance feedback. The paper also addresses the challenges of adopting AI in HRM, including concerns about data security, ethical dilemmas, and algorithmic bias. It further outlines strategies for embedding AI into employee development frameworks while maintaining equilibrium between technological progress and people-centered practices. Case studies are highlighted where AI adoption has improved talent retention, strengthened learning outcomes, and driven organizational effectiveness. As businesses increasingly integrate AI-driven HR solutions, a clear understanding of its impact on workforce development becomes vital. This research offers practical insights for HR leaders, policymakers, and scholars, providing an in-depth analysis of AI’s contribution to shaping employee growth in the digital age. By harmonizing AI capabilities with human expertise, organizations can cultivate a flexible and future-ready workforce capable of adapting to evolving business landscapes. The paper concludes with recommendations for advancing AI-powered employee development models that uphold principles of ethics, fairness, and transparency.

The rise of Artificial Intelligence (AI) provides an exciting opportunity in many fields and aspects of life. In the field of design, one area to be explored, is how AI could be used to support a designer to develop more novel ideas at the idea generation stage of the product development journey. In this paper, we explore how AI can be utilised to support a traditional 6-3-5 creative design methods workshop, and whether it increases the novelty of the concepts. In our workshop, students were tasked with using the 6-3-5 method to generate ideas for a product which could make life easier for an arthritis sufferer when undertaking tasks in the kitchen. Some of the students were advised they could use Chat GPT to support idea creation; some of the students were advised they could use Google to support idea creation; and the remaining students were advised they would not be able to use any additional support for idea generation. This group was considered as the control group. A feedback survey was distributed among the participants to gather their thoughts on whether the use of AI/Google had assisted them in the application of the design method to generate more novel and creative concepts. Further analysis was then conducted, with a focus on novelty, on the outputs of the 6-3-5 to assess whether the novelty of the concepts in the AI/Google groups was greater than that of the control group. The results of the workshop indicated that the ideas generated with AI support were more novel than those without, and that students utilising AI became more relaxed in their approach to idea generation, relying on AI before fully exhausting their own ideas. Interestingly, the perceived helpfulness of AI was also not fully appreciated by the more novice designers in comparison to those more experienced designers. In this paper we discuss how AI could be used by educators to support teaching and application of more creative design methods such as 6-3-5.

AI assistants such as Siri and Alexa have historically been coded as female. Even ELIZA, the first chatbot and an early AI therapist, was coded as female. Interestingly, male- and female-sounding voice assistants respond differently to situations, according to gendered social expectations and stereotypes. This raises ethical concerns, as care work has historically been associated with women and has been the basis of oppression in the capitalism–patriarchy nexus. Simultaneously, the rise of artificial intelligence (AI) sex robots, chatbots and AI-generated pornographic content is leading to increased commodification of sex, higher rates of addiction and further reproduction of notions of non-consensual sexual activity. In this article, we aim to conduct an impact-oriented analysis of AI applications on cisgender women (as trans women face unique challenges due to AI, such as inaccurate facial recognition) through the process of othering and objectification. We demonstrate the negative impacts of AI technologies on women by studying their condition in the domains of sex and care work. We then place these trends in the larger context of ethics and political polarisation between the sexes, as seen by the recent gender ideology gap across nations. Lastly, we aim to predict the future of AI-regulated gender relations and the possibility of AI neutrality by undertaking a socio-technical approach to AI policy.

<p>Technologies have long influenced elections, both positively and negatively, shaping their outcomes and the quality of public debate surrounding them. For example, the Internet enables citizens to organize more effectively than ever, empowering them to advocate for specific ideas and causes, but it is also a formidable channel for disinformation. The rise of artificial intelligence (AI) presents significant new threats, including the multiplication of deepfakes, heightened cybersecurity risks, the emergence of manipulative persuasive agents, and the proliferation of synthetic data and fake accounts. At the same time, AI offers political actors a powerful tool to connect with voters, influence public opinion, and shape the flow of information. By tapping into existing trends in elections, AI has the potential to profoundly reshape the democratic process and influence election outcomes. Without proactive measures, however, AI could exacerbate worrisome trends such as political polarization and declining trust in democracy. Governments must take decisive action regarding AI, particularly at a time when democracies around the world are facing increasing challenges and attacks on their elections. By acting on various fronts, they will shore up democratic systems, improve trust in society, and ensure that AI is leveraged responsibly to enhance the integrity of elections.</p>

Introduction. Artificial intelligence (AI) has profoundly impacted various aspects of human life, including text generation, software development, and art creation. Many sport and business news articles available online have been authored by AI. Under the current legal frameworks in many jurisdictions, AI-generated works have generally been regarded as tools. However, the evolution of advanced AI technologies has significantly challenged this traditional perspective.Problem Statement. The rise of AI has introduced significant challenges to intellectual property law, particularly copyright. In the context of copyright, AI-generated works have sparked legal disputes regarding whether AI can be recognized as the author of creative works, how such works should be protected, and who holds the rights to them.Purpose. This study aims to critically analyze copyright issues related to AI-generated works, identify the legal regulations governing such works in developed countries, and propose recommendations to enhance Kazakhstani copyright law for AI-generated outputs.Materials and Methods. The research has employed comparative legal analysis, general scientific methods, and specific scientific approaches.Results. Drawing on foreign practices, the study has concluded that the individual who has made the necessary arrangements for the creation of AI-generated works should be recognized as the author.Conclusions. The paper provides practical recommendations for improving Kazakhstani legislation on copyright protection for AI-generated works. The findings may serve as a valuable resource for future legal research on regulating copyright for AI-generated outputs.

Artificial intelligence (AI) technology, as one of the most sophisticated science and technology in today's world, is increasingly being used to production and life, particularly in the manufacturing business. it demonstrates how artificial intelligence technology is used in mechanical manufacturing, namely in defect detection, quality inspection, enhancing workplace safety, and other areas. Artificial intelligence technology is becoming increasingly important in people's lives as it becomes more widely used in people's daily lives, such as the widespread use of smart dishwashers and smart sweepers, which are the products of the fusion of artificial intelligence and the mechanical manufacturing industry. Indeed, artificial intelligence technology has been widely utilized in the mechanical manufacturing business, which not only ensures production precision, but also enhances job productivity and workplace safety. The rise of artificial intelligence has caused significant changes in the manufacturing industry as a whole. Without exception, the manufacturing industry must rely on AI technology to accomplish automation and intelligent development, as well as to improve productivity. Using artificial intelligence to categorize mechanical components, we may propose parts from a based solely on an image or CAD model. To find a necessary component in a machines we must currently browse through a catalogue and be able to discern which part you want based on the available possibilities and your understanding of the catalogue. There are serial numbers to memorize since a single digit or character change might indicate a different sort of part. The algorithm will choose which sections are the best and will significantly facilitate our search.

Artificial intelligence (AI) technology is becoming increasingly prevalent in society, offering a range of benefits and opportunities. However, with the rise of AI comes new challenges, particularly in hate speech. Hate speech, a type of expression that incites hatred or violence against individuals or groups based on ethnicity, religion, or other characteristics, has become a growing concern in Malaysia, with social media and online platforms becoming a breeding ground for such speech. In this context, AI technology has emerged as a potential solution for monitoring and regulating hate speech, but it also presents legal and ethical challenges that must be addressed. In view of double edge sword roles played by the development of AI, this article analyses the legal recourse available in Malaysia for disruptive AI technology and hate speech. The authors claim that AI systems are prone to errors and biases and that there is a risk of relying too much on such plans at the expense of human judgement. There are also concerns regarding the impact of AI on free expression and privacy rights. In addition, the author suggests that artificial intelligence be appropriately regulated to ensure that it is consistent with international human rights standards and national laws.