Articles for tag: AI Regulation, BEACON project, Behnam Mohammadi, explainable AI, human-AI interaction, large language models, programming language

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Exploring Human-AI Interaction: Behnam Mohammadi’s Innovative Research on LLMs at Tepper School of Business

Behnam Mohammadi, a PhD student at the Tepper School of Business, focuses on human-AI interaction, large language models (LLMs), and AI regulation. His research includes developing LLM tools for businesses, like Pel, a programming language for coordinating AI agents, aimed at helping small businesses leverage AI. Mohammadi has published significant studies on AI transparency and ...

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AI vs. Humans: Who Excels in Customer Service and Journalism Listening Skills?

Artificial intelligence is rapidly evolving beyond simple chatbots, now capable of making calls, conducting research, and even simulating human personalities. This shift is particularly noticeable in customer service, where AI agents are demonstrating high levels of patience and knowledge, often matching or exceeding human performance. Klarna’s CEO noted equal customer satisfaction between AI and human ...

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Global Variations in Human Cooperation with Artificial Agents Across Countries: Insights and Implications for Future Interaction

The Trust game study involved 397 participants from Japan and compared their choices with 403 participants from the United States. Participants played either as the first or second player, interacting with either humans or AI agents. Results showed that while cooperation rates were slightly lower in Japan, they were not statistically significant when compared to ...

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Transform Your Team Collaboration and Workflows for Enhanced Productivity and Success

Dr. Rebecca Hinds, head of Asana’s Work Innovation Lab, emphasizes that AI is transforming teamwork and reshaping workflows. Her lab focuses on bridging research and business, helping leaders embrace the future of work through AI technologies. With a background in AI and hybrid work, Hinds highlights the potential of AI agents—intelligent digital assistants that can ...

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The Importance of Speed in AI Agents: Key Benchmarks, Metrics, and Their Real-World Impact Explained

In conversations, humans typically respond in about 200 milliseconds, but modern AI can process questions and give answers even faster, often under 100 milliseconds. This rapid response is essential for smooth human-AI interactions, whether in chatbots or self-driving cars. Quick replies not only enhance functionality but also build user trust. As AI can understand speech ...

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