As Artificial Intelligence (AI) technologies continue to evolve, the gap between academic AI education and real-world industry challenges remains an important area of investigation. This study provides preliminary insights into challenges AI professionals encounter in both academia and industry, based on semi-structured interviews with 14 AI experts - eight from industry and six from academia. We identify key challenges related to data quality and availability, model scalability, practical constraints, user behavior, and explainability. While both groups experience data and model adaptation difficulties, industry professionals more frequently highlight deployment constraints, resource limitations, and external dependencies, whereas academics emphasize theoretical adaptation and standardization issues. These exploratory findings suggest that AI curricula could better integrate real-world complexities, software engineering principles, and interdisciplinary learning, while recognizing the broader educational goals of building foundational and ethical reasoning skills.

The increasing integration of Artificial Intelligence (AI) in digital ecosystems has reshaped privacy dynamics, particularly for young digital citizens navigating data-driven environments. This study explores evolving privacy concerns across three key stakeholder groups, digital citizens (ages 16-19), parents/educators, and AI professionals, and assesses differences in data ownership, trust, transparency, parental mediation, education, and risk-benefit perceptions. Employing a grounded theory methodology, this research synthesizes insights from 482 participants through structured surveys, qualitative interviews, and focus groups. The findings reveal distinct privacy expectations: Young users emphasize autonomy and digital freedom, while parents and educators advocate for regulatory oversight and AI literacy programs. AI professionals, in contrast, prioritize the balance between ethical system design and technological efficiency. The data further highlights gaps in AI literacy and transparency, emphasizing the need for comprehensive, stakeholder-driven privacy frameworks that accommodate diverse user needs. Using comparative thematic analysis, this study identifies key tensions in privacy governance and develops the novel Privacy-Ethics Alignment in AI (PEA-AI) model, which structures privacy decision-making as a dynamic negotiation between stakeholders. By systematically analyzing themes such as transparency, user control, risk perception, and parental mediation, this research provides a scalable, adaptive foundation for AI governance, ensuring that privacy protections evolve alongside emerging AI technologies and youth-centric digital interactions.

As Artificial Intelligence (AI) systems become increasingly integrated into various aspects of daily life, concerns about privacy and ethical accountability are gaining prominence. This study explores stakeholder perspectives on privacy in AI systems, focusing on educators, parents, and AI professionals. Using qualitative analysis of survey responses from 227 participants, the research identifies key privacy risks, including data breaches, ethical misuse, and excessive data collection, alongside perceived benefits such as personalized services, enhanced efficiency, and educational advancements. Stakeholders emphasized the need for transparency, privacy-by-design, user empowerment, and ethical oversight to address privacy concerns effectively. The findings provide actionable insights into balancing the benefits of AI with robust privacy protections, catering to the diverse needs of stakeholders. Recommendations include implementing selective data use, fostering transparency, promoting user autonomy, and integrating ethical principles into AI development. This study contributes to the ongoing discourse on ethical AI, offering guidance for designing privacy-centric systems that align with societal values and build trust among users. By addressing privacy challenges, this research underscores the importance of developing AI technologies that are not only innovative but also ethically sound and responsive to the concerns of all stakeholders.

When we think of artificial intelligence, we might think of robots like the ones in "Ex Machina," who are scarily smarter, closer to humans, and more perceptive than we think. The reality is that artificial intelligence is an innovative, growing field that offers creative opportunities for those who want to revolutionize the way we use technology. So, what is artificial intelligence, and what does a career in the field look like? Artificial intelligence (AI) is a branch of computer science concerning machines that can synthesize and process information to problem-solve. The concept first came into public view with Alan Turing's 1950 paper, "Computing Machinery and Intelligence," which explored whether we could train machines to think like humans.

Report says pattern seen in films such as Ex Machina risks contributing to lack of women in tech. A relentless stream of movies, from Iron Man to Ex Machina, has helped entrench systemic gender inequality in the artificial intelligence industry by portraying AI researchers almost exclusively as men, a study has found. The overwhelming predominance of men as leading AI researchers in movies has shaped public perceptions of the industry, the authors say, and risks contributing to a dramatic lack of women in the tech workforce. Beyond the impact on gender balance, the study raises concerns about the knock-on effects of products that favour male users because they are developed by what the former Microsoft employee Margaret Mitchell called "a sea of dudes". "Given that male engineers have repeatedly been shown to engineer products that are most suitable for and adapted to male users, employing more women is essential for addressing the encoding of bias and pejorative stereotypes into AI technologies," the report's authors write.

Study finds that just 8% of all depictions of AI professionals from 100 years of film are women – and half of these are shown as subordinate to men. Researchers from the University of Cambridge argue that such cultural tropes and a lack of female representation affects career aspirations and sector recruitment. Without enough women building AI there is a high risk of gender bias seeping into the algorithms set to define the future, they say. The team from the University's Leverhulme Centre for the Future of Intelligence (LCFI) whittled down over 1,400 films to the 142 most influential cinematic works featuring AI between 1920 and 2020, and identified 116 characters they classed as "AI professionals". Of these, 92% of all AI scientists and engineers on screen were men, with representations of women consisting of a total of eight scientists and one CEO.

Male dominance in big-screen depictions of tech is putting women off careers in Artificial Intelligence (AI) where they are massively under-represented, warns new research. Women make up just eight percent of workers in films depicting Artificial Intelligence - and half of them are subordinate to men, according to the findings. University of Cambridge researchers claimed this "dangerous cultural stereotype" is emulated in the real-world shortage of women in the industry. Across the globe, just 22 percent of real-world AI professionals are women, versus 39 percent across all STEM fields (Science, Technology, Engineering and Medicine.) Researchers argue the gender chasm is exacerbated by films such as Iron Man and Ex Machina promoting cultural perceptions of AI as "the product of lone male geniuses."

A relentless stream of movies, from Iron Man to Ex Machina, has helped entrench systemic gender inequality in the artificial intelligence industry by portraying AI researchers almost exclusively as men, a study has found. The overwhelming predominance of men as leading AI researchers in movies has shaped public perceptions of the industry, the authors say, and risks contributing to a dramatic lack of women in the tech workforce. Beyond the impact on gender balance, the study raises concerns about the knock-on effects of products that favour male users because they are developed by what the former Microsoft employee Margaret Mitchell called "a sea of dudes". "Given that male engineers have repeatedly been shown to engineer products that are most suitable for and adapted to male users, employing more women is essential for addressing the encoding of bias and pejorative stereotypes into AI technologies," the report's authors write. Researchers at the University of Cambridge reviewed more than 1,400 films released between 1920 and 2020 and whittled them down to the 142 most influential movies featuring artificial intelligence.

Working in the field of AI can be both relaxing and stressful, depending on the specific role and responsibilities. Some roles, such as AI research or development, may involve significant intellectual challenges and the need to stay up-to-date with rapidly evolving technologies, which can be stressful. On the other hand, other roles, such as using AI tools to solve specific business problems, may be less stressful. It's important to find ways to manage stress in a healthy way and to make sure you have a good work-life balance. It depends on the context in which you use an AI writer.

On August 9, 2022, President Biden signed the CHIPS Act of 2022 (the "Act"), legislation to fund domestic semiconductor manufacturing and boost federal scientific research and development (see our previous alert for additional background). As part of its science-backed provisions, the Act includes many of the U.S. Innovation and Competition Act's (USICA) original priorities, such as promoting standards and research and development in the field of artificial intelligence (AI) and supporting existing AI initiatives. The Act directs the National Institute of Standards and Technology (NIST) Director to continue supporting the development of AI and data science and to carry out the National AI Initiative Act of 2020 (previous alert for additional background), which created a coordinated program across the federal government to accelerate AI research and application to support economic prosperity, national security, and advance AI leadership in the United States. Furthermore, the Act provides that the Director may establish testbeds, including in virtual environments, in collaboration with other federal agencies, the private sector and colleges and universities, to support the development of robust and trustworthy AI and machine learning systems. A new National Science Foundation (NSF) Directorate for Technology, Innovation and Partnerships (the "Directorate") is established under the Act to address societal, national and geostrategic challenges for the betterment of all Americans through research and development, technology development and related solutions.