Large Language Models (LLMs) have shown proficiency in generating persuasive dialogue, yet concerns about the fluency and sophistication of their outputs persist. This paper presents a multi-LLM communication framework designed to enhance the generation of persuasive data automatically. This framework facilitates the efficient production of high-quality, diverse linguistic content with minimal human oversight. Through extensive evaluations, we demonstrate that the generated data excels in naturalness, linguistic diversity, and the strategic use of persuasion, even in complex scenarios involving social taboos. The framework also proves adept at generalizing across novel contexts. Our results highlight the framework's potential to significantly advance research in both computational and social science domains concerning persuasive communication.

Customer Relationship Management (CRM) systems are vital for modern enterprises, providing a foundation for managing customer interactions and data. Integrating AI agents into CRM systems can automate routine processes and enhance personalized service. However, deploying and evaluating these agents is challenging due to the lack of realistic benchmarks that reflect the complexity of real-world CRM tasks. To address this issue, we introduce CRMArena, a novel benchmark designed to evaluate AI agents on realistic tasks grounded in professional work environments. Following guidance from CRM experts and industry best practices, we designed CRMArena with nine customer service tasks distributed across three personas: service agent, analyst, and manager. The benchmark includes 16 commonly used industrial objects (e.g., account, order, knowledge article, case) with high interconnectivity, along with latent variables (e.g., complaint habits, policy violations) to simulate realistic data distributions. Experimental results reveal that state-of-the-art LLM agents succeed in less than 40% of the tasks with ReAct prompting, and less than 55% even with function-calling abilities. Our findings highlight the need for enhanced agent capabilities in function-calling and rule-following to be deployed in real-world work environments. CRMArena is an open challenge to the community: systems that can reliably complete tasks showcase direct business value in a popular work environment.

Common narratives about automation often pit new technologies against workers. The introduction of advanced machine tools, industrial robots, and AI have all been met with concern that technological progress will mean fewer jobs. However, workers themselves offer a more optimistic, nuanced perspective. Drawing on a far-reaching 2024 survey of more than 9,000 workers across nine countries, this paper finds that more workers report potential benefits from new technologies like robots and AI for their safety and comfort at work, their pay, and their autonomy on the job than report potential costs. Workers with jobs that ask them to solve complex problems, workers who feel valued by their employers, and workers who are motivated to move up in their careers are all more likely to see new technologies as beneficial. In contrast to assumptions in previous research, more formal education is in some cases associated with more negative attitudes toward automation and its impact on work. In an experimental setting, the prospect of financial incentives for workers improve their perceptions of automation technologies, whereas the prospect of increased input about how new technologies are used does not have a significant effect on workers' attitudes toward automation.

An obstacle toward construction robotization is the lack of methods to plan robot operations within the entire construction planning process. Despite the strength in modeling construction site conditions, 4D BIM technologies cannot perform construction robot task planning considering the contexts of given work environments. To address this limitation, this study presents a framework that integrates 4D BIM and robot task planning, presents an information flow for the integration, and performs high-level robot task planning and detailed simulation. The framework uniquely incorporates a construction robot knowledge base that derives robotrelated modeling requirements to augment a 4D BIM model. Then, the 4D BIM model is converted into a robot simulation world where a robot performs a sequence of actions retrieving construction-related information. A case study focusing on the interior wall frame installation demonstrates the potential of systematic integration in achieving context-aware robot task planning and simulation in construction environments. Simulated a mobile robot's actions to install wall frames in a residential building 1. Introduction Rapid advancements in robotics technologies are making the utilization of robots for dangerous, tedious, and repetitive tasks more and more practical [1]. Unlike traditional industrial robots with fixed behaviors, modern robots with mobile platforms, sensors, and actuators can be programmed to perform given tasks intelligently adapting to changing work environments. Many sectors, including manufacturing [2], rescue [3], agriculture [4], and healthcare [5], are adopting robots to automate existing processes to achieve greater productivity and safety. Many construction tasks are repetitive and labor-intensive by nature [7,8], and thus robotization of these tasks can potentially address many chronic problems, such as stagnant productivity growth [9], labor shortage [10], and work-related diseases/fatalities [11]. A growing number of robotic solutions are introduced by academic studies [12,13] and industrial applications (excavation and leveling [14], marking of layout [15], rebar tying [16], and bricklaying [17,18]). With this trend, construction sites are expected to become crowded with robots and human workers in the near future exposing human workers to robot-related hazards, such as collisions, crushing, trapping, mechanical part accidents, etc. [19]. In order to utilize robots safely and effectively in congested construction environments, both high-level task planning and detailed simulation of construction robots should be performed as part of the entire construction planning. Despite the abundant studies on the coordination between human work crews [20,21], none of the prior studies incorporated robot operations into construction planning process.

Defense companies exploring artificial intelligence will help the U.S. military "keep up" with rivals like China, a former fighter pilot told Fox News. Did you know that your boss can watch what you're up to when you're working, especially if you're using the company's equipment or networks. That's their legal right, but they also have to play by some rules, be transparent, and tell you about it. This way, you can trust them and they can avoid legal issues. CLICK TO GET KURT'S FREE CYBERGUY NEWSLETTER WITH SECURITY ALERTS, QUICK VIDEO TIPS, TECH REVIEWS, AND EASY HOW-TO'S TO MAKE YOU SMARTER Is your boss spying on you? (Cyberguy.com)

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Employee wellness has become a crucial aspect of organizational success in today's fast-paced world. With mental health issues becoming increasingly prevalent in the workplace, innovative solutions are needed to address these challenges. One such solution lies in the realm of artificial intelligence (AI), a rapidly advancing technology that's transforming various industries. This begs the question: can AI truly positively impact employee mental health and wellness? To answer this, let's take a closer look at the potential of AI in this sphere.

In this Q&A for TechRepublic, they discussed the shift to remote and hybrid work and how we can best prepare for it. The following is an edited transcript of their conversation. James Maguire: We have seen a lot of shifts in the working world in the last few years -- hybrid work, remote work. What are the key trends you see driving remote work and today's shift? We've seen, you know, this combination of people having made the shift to remote work during the pandemic, which was a fundamental change in the way in which we did our everyday. But now, three years later, we're returning to the offices, and that really is creating this dynamic of hybrid work.

As the use of Augmented Reality (AR) to enhance interactions between human agents and robotic systems in a work environment continues to grow, robots must communicate their intents in informative yet straightforward ways. This improves the human agent's feeling of trust and safety in the work environment while also reducing task completion time. To this end, we discuss a set of guidelines for the systematic design of AR interfaces for Human-Robot Interaction (HRI) systems. Furthermore, we develop design frameworks that would ride on these guidelines and serve as a base for researchers seeking to explore this direction further. We develop a series of designs for visually representing the robot's planned path and reactions, which we evaluate by conducting a user survey involving 14 participants. Subjects were given different design representations to review and rate based on their intuitiveness and informativeness. The collated results showed that our design representations significantly improved the participants' ease of understanding the robot's intents over the baselines for the robot's proposed navigation path, planned arm trajectory, and reactions.

As businesses evolve at an ever-increasing pace, emerging technologies are set to change the way we think about, approach, and conduct business. Artificial intelligence (AI) is one such technology that has the potential to shape the work environment in a revolutionary way. AI has been widely tipped as a powerful potential asset in the field of human resources. According to the ‘Artificial Intelligence as a Service Market Growth & Trends 2022’ report by Grand View Research Inc., the global AI as a service market is expected to reach USD 96,064.7 million by 2030. Growing at a CAGR of 37.1% from 2022 to 2030, the role of AI has evolved with digital transformation across industries, including the HR domain. From talent acquisition to exit interviews, AI is instrumental in addressing common issues that emerge during an employee’s life cycle while simultaneously transforming HR departments.