Artificial Intelligence (AI) is transforming organizational dynamics, and revolutionizing corporate leadership practices. This research paper delves into the question of how AI influences corporate leadership, examini...Artificial Intelligence (AI) is transforming organizational dynamics, and revolutionizing corporate leadership practices. This research paper delves into the question of how AI influences corporate leadership, examining both its advantages and disadvantages. Positive impacts of AI are evident in communication, feedback systems, tracking mechanisms, and decision-making processes within organizations. AI-powered communication tools, as exemplified by Slack, facilitate seamless collaboration, transcending geographical barriers. Feedback systems, like Adobe’s Performance Management System, employ AI algorithms to provide personalized development opportunities, enhancing employee growth. AI-based tracking systems optimize resource allocation, as exemplified by studies like “AI-Based Tracking Systems: Enhancing Efficiency and Accountability.” Additionally, AI-powered decision support, demonstrated during the COVID-19 pandemic, showcases the capability to navigate complex challenges and maintain resilience. However, AI adoption poses challenges in human resources, potentially leading to job displacement and necessitating upskilling efforts. Managing AI errors becomes crucial, as illustrated by instances like Amazon’s biased recruiting tool. Data privacy concerns also arise, emphasizing the need for robust security measures. The proposed solution suggests leveraging Local Machine Learning Models (LLMs) to address data privacy issues. Approaches such as federated learning, on-device learning, differential privacy, and homomorphic encryption offer promising strategies. By exploring the evolving dynamics of AI and leadership, this research advocates for responsible AI adoption and proposes LLMs as a potential solution, fostering a balanced integration of AI benefits while mitigating associated risks in corporate settings.展开更多
A barrier-free wheelchair robot with a mechanism coupled by wheel and track is presen- ted in this paper. Using the wheelchair, the lower limb disabled persons could be more relaxed to take part in outdoor activities ...A barrier-free wheelchair robot with a mechanism coupled by wheel and track is presen- ted in this paper. Using the wheelchair, the lower limb disabled persons could be more relaxed to take part in outdoor activities whether on flat ground or stairs and obstacles in the city. The wheel- track coupling mechanism is designed and the stability of the bodywork of the wheelchair robot on the stairs is analyzed. In order to obtain the stability of wheelchair robot when it climbs obstacles, centroid projection method is applied to analyze the static stability, stability margin is proposed to provide the stability under some dynamic forces, and the push rod rotation angle in terms of the guaranteed stability margin is given. Finally, the dynamic model of the wheelchair robot based on Lagrange equation is established, which can be a theoretical foundation for the wheelchair control system design.展开更多
文摘Artificial Intelligence (AI) is transforming organizational dynamics, and revolutionizing corporate leadership practices. This research paper delves into the question of how AI influences corporate leadership, examining both its advantages and disadvantages. Positive impacts of AI are evident in communication, feedback systems, tracking mechanisms, and decision-making processes within organizations. AI-powered communication tools, as exemplified by Slack, facilitate seamless collaboration, transcending geographical barriers. Feedback systems, like Adobe’s Performance Management System, employ AI algorithms to provide personalized development opportunities, enhancing employee growth. AI-based tracking systems optimize resource allocation, as exemplified by studies like “AI-Based Tracking Systems: Enhancing Efficiency and Accountability.” Additionally, AI-powered decision support, demonstrated during the COVID-19 pandemic, showcases the capability to navigate complex challenges and maintain resilience. However, AI adoption poses challenges in human resources, potentially leading to job displacement and necessitating upskilling efforts. Managing AI errors becomes crucial, as illustrated by instances like Amazon’s biased recruiting tool. Data privacy concerns also arise, emphasizing the need for robust security measures. The proposed solution suggests leveraging Local Machine Learning Models (LLMs) to address data privacy issues. Approaches such as federated learning, on-device learning, differential privacy, and homomorphic encryption offer promising strategies. By exploring the evolving dynamics of AI and leadership, this research advocates for responsible AI adoption and proposes LLMs as a potential solution, fostering a balanced integration of AI benefits while mitigating associated risks in corporate settings.
基金Supported by State Key Laboratory of Robotics and Systems(HIT)(SKLRS-2010-ZD-04)Capital Medical Development Scientific Research Fund(20092098)
文摘A barrier-free wheelchair robot with a mechanism coupled by wheel and track is presen- ted in this paper. Using the wheelchair, the lower limb disabled persons could be more relaxed to take part in outdoor activities whether on flat ground or stairs and obstacles in the city. The wheel- track coupling mechanism is designed and the stability of the bodywork of the wheelchair robot on the stairs is analyzed. In order to obtain the stability of wheelchair robot when it climbs obstacles, centroid projection method is applied to analyze the static stability, stability margin is proposed to provide the stability under some dynamic forces, and the push rod rotation angle in terms of the guaranteed stability margin is given. Finally, the dynamic model of the wheelchair robot based on Lagrange equation is established, which can be a theoretical foundation for the wheelchair control system design.
