Juji, Inc.

Guiding Conversational AI Design with the Human Generalization Function A recent MIT News article by Adam Zewe discusses research by Keyon Vafa of Harvard University, Ashesh Rambachan of Massachusetts Institute of Technology, and Sendhil Mullainathan of University of Chicago, which reveals how our beliefs about large language models (LLMs) impact how we use them and their effectiveness. The researchers introduce a "human generalization function"—a model showing how people form beliefs about an AI's abilities based on interactions. When LLMs misalign with these beliefs, users may misjudge when to rely on them, leading to failures in high-stakes situations. https://lnkd.in/epkB2AWM This framework offers valuable insights for designing conversational AI agents, providing a controlled, purposeful approach to guiding AI behaviors in ways that align closely with user expectations. Here's how designers can leverage the framework to create and refine more effective conversational agents: 1. Using the Human Generalization Function to Guide Agentic Workflow Understanding how users form beliefs about AI capabilities can help designers establish workflows that intentionally guide agent behavior within clear boundaries. By tailoring responses based on anticipated human expectations, designers can ensure that conversational agents operate within well-defined parameters, reducing instances where AI actions fall outside user assumptions (Image 1) 2. Updating Design Based on Identified Misalignments When misalignments between user expectations and AI performance arise, the human generalization function can pinpoint where these gaps occur. Designers can use this feedback to adjust the AI's parameters, responses, or restrictions, updating the design iteratively to better meet user expectations and prevent misinterpretations of the AI's abilities (Image 2). 3. Continuous Monitoring Against Benchmarks To maintain alignment over time, conversational agents should be evaluated and continuously monitored against benchmarks derived from the human generalization function. This ongoing assessment ensures that the AI's behavior aligns with evolving user expectations and highlights any emerging discrepancies, allowing for timely adjustments (Image 3). By embedding the human generalization function into the design and evaluation of conversational AI agents, we can create agents that work predictably and effectively within the boundaries of user expectations, building trust and reliability into AI interactions. #ConversationalAI #HumanAIInteraction #AgenticAI #AIDesign #UserExpectations #MachineLearning #AIAlignment

How AI Chatbots Can Help Develop Effective Leaders In a recent Fast Company article, "Why Competent Workers Become Incompetent Managers," Dr Tomas Chamorro-Premuzic and Dr Sunny Lee discuss the Peter Principle: a common trend where individuals are promoted based on past performance rather than their leadership potential, often resulting in ineffective managers. https://lnkd.in/gJTvNNaP Addressing this gap in talent development is essential to foster more capable leaders who align with organizational goals and effectively support their teams. AI chatbots can help organizations identify and develop leadership potential in the following ways: 1. Skill-based Assessment for Solving Real-World Challenges AI chatbots can evaluate leadership potential by presenting users with real-world scenarios that managers face daily—such as navigating team conflicts, motivating employees, and handling complex projects. These practices allow AI to assess how individuals respond to situational challenges, providing insight into their readiness for managerial roles and ensuring promotions align with both skill and potential (Image 1). 2. Hyper-Personalized Leadership Development Not all leaders are the same. AI chatbots can tailor leadership training, such as people management, strategic decision-making, and effective communication, to each individual based on their situations and their personality. Through personalized, situation-based training, employees not only learn the methodologies, but also learn practical skills to handle situations they are likely to encounter in managerial roles, helping them build a foundational understanding of leadership dynamics even before they step into those roles (Image 2). 3. Practice Through Ongoing Scenario-Based Exercises AI chatbots can provide continuous, hands-on practice by offering scenario-based exercises tailored to employees' skill levels and roles. Practicing these real-world challenges allows employees to develop their leadership abilities over time, building confidence and competence in a low-stakes environment. This hands-on approach ensures employees are better prepared for the practical demands of management before they are promoted (Image 3). By using AI chatbots as tools for assessment, learning, and practice in real-world situations, organizations can address the pitfalls of the Peter Principle. Rather than relying on past performance alone, companies can create a talent pipeline that develops and promotes employees based on their true leadership potential. #LeadershipDevelopment #AIinLeadership #PeterPrinciple #TalentManagement #AIChatbots #LeadershipPotential #EmployeeGrowth #AITraining

How to prevent AI from making us dumber: 3 ways to use AI to enhance our cognitive abilities In a recent article, Paul Graham warns that relying on AI for writing could weaken our cognitive abilities, particularly our capacity for clear thinking. Since writing helps clarify our thoughts, outsourcing it to AI could lead to a future where fewer people possess strong reasoning and critical thinking skills. https://lnkd.in/egTt_A7s Instead of viewing AI as a threat to our cognitive development, we can flip this narrative: what if we use AI to enhance our cognitive abilities? Here are 3 ways AI can support and even strengthen our mental skills: 1. Improving Reasoning Skills AI can be a valuable partner in improving reasoning by providing real-time feedback on the clarity and logic of our writing. Through suggestions and critical questions, AI tools can highlight gaps in our arguments, suggest stronger connections, and challenge us to clarify vague statements. This feedback loop isn't just about polishing text; it’s about sharpening our reasoning skills, encouraging us to think more rigorously and logically about the ideas we express (Image 1). 2. Systematic Approach to Critical Thinking AI can guide individuals to practice and develop critical thinking skills through a structured, systematic training. With personalized feedback and adaptive learning, AI can identify areas where we need improvement and offer structured tasks—such as argument evaluation and problem-solving exercises—that push us to think more critically. By creating a space for repeated practice, AI can help us build the habit of approaching complex problems with clarity and structure (Image 2). 3. Encouraging Reflection and Developing Metacognitive Awareness Effective thinking isn’t just about finding answers; it’s also about understanding how we arrive at those answers. AI can help by tracking our learning patterns and offering insights into our thought processes, helping us develop metacognitive awareness—our ability to think about our thinking. Through reflective prompts and insights, AI encourages us to assess our assumptions, recognize cognitive biases, and refine our problem-solving approaches, ultimately making us more self-aware and reflective thinkers. Even better, AI can help us reflect based on what we are: our strengths and weaknesses and our personality (Image 3). Rather than reducing our cognitive abilities, AI has the potential to serve as a coach and mentor, guiding us to think more clearly, critically, and consciously. By using AI thoughtfully, we can transform it from a shortcut into a tool that challenges us, helping us become stronger, more capable thinkers. Let's harness AI as a force for cognitive growth rather than a crutch, so we create a future where technology and human intellect elevate each other. #CriticalThinking #AIinEducation #MetaCognition #AIEmpowerment #CognitiveSkills #AIforGood #LearningAndDevelopment

3 Ways Human-AI Symbiosis Can Revolutionize Education In his insightful article, The Human-AI Symbiosis: Embracing Collaboration For A Smarter Future, Austin Ambrozi, co-founder and COO of Doxci, discusses the power of AI-human collaboration across various industries, emphasizing that AI's true potential is realized when combined with human intelligence. This synergy leverages AI's ability to process vast amounts of data and humans' unique traits like creativity and emotional intelligence to drive innovation and productivity. With responsible deployment, AI can augment rather than replace human capabilities, creating a future where the two work hand-in-hand to achieve transformative outcomes. Applying this vision to the education sector, here are three ways human-AI collaboration can advance education: 1. From AI to Human: Personalized Learning for Students AI is a powerful ally in personalizing education for each student. By analyzing student data and learning behaviors, AI can tailor content, recommend resources, and adjust difficulty levels to suit individual needs. This helps students progress at their own pace, boosting engagement and knowledge retention (Image 1). https://lnkd.in/eh4Rajbv 2. From AI to Human: Empowering Educators with Smart Tools Teachers and coaches benefit from AI-driven insights, which help them understand student performance trends and identify areas where additional support is needed. In addition, by automating mundane and repetitive tasks, AI frees educators to focus on what they do best—teaching, mentoring, and inspiring students (Image 2). 3. From Human to AI: Enhancing AI through Human Feedback A true partnership between humans and AI means continuous improvement. Feedback from both students and educators allows AI systems to learn and adapt, becoming more effective and attuned to educational needs. This reciprocal relationship ensures that AI tools evolve based on real-world use and human insights. The fusion of human intelligence and AI's computational power opens up unparalleled opportunities in education, transforming how we teach, learn, and grow together. Let’s embrace this collaboration for a smarter, more adaptive future in education. For insights on the broader impact of human-AI collaboration, read Austin Ambrozi's full article in Forbes: https://lnkd.in/eSk_byC7 #HumanAISymbiosis #AIinEducation #EdTech #PersonalizedLearning #FutureOfEducation #AIEmpowerment #EducationInnovation #HumanAIcollaboration

Study Validates the Reliability of Juji AI’s Personality Assessment A collaborative study led by researchers jinyan fan, Jiayi Liu, Teng Zhao, and Melissa Glorioso from Auburn University, Tianjun Sun, Bo Zhang, Zheng Chen from USF St. Petersburg, and Elissa Hack from United States Air Force Academy explored the effectiveness of the Juji AI chatbot in measuring personality traits through real human conversations. This groundbreaking study confirms that Juji's AI model achieves reliable personality assessments, offering accuracy across broad personality dimensions and detailed traits. Unlike LLM-based methods, which often fall short in delivering consistent personality insights, Juji's machine-learning-based approach successfully derives psychological traits from causal conversations. This approach represents a significant advance in AI-assisted personality assessment, opening up exciting opportunities for organizations and individuals to understand psychological attributes in real-time, seamlessly. Curious about your own personality insights? Visit Juji’s website and interact with our welcome chatbot to discover your unique strengths and gain valuable insights today. For more details on this study, access the full paper here: https://lnkd.in/e9K-_htR Missed our previous post on the limitations of LLM-based personality assessments? Read it here: https://lnkd.in/egXgkcVA #AIChatbot #PersonalityAssessment #JujiAI #PsychologicalInsights #PersonalityInsights

Enhancing Conversational AI with a Hybrid Approach A recent article by Dr. Laurence Lock Lee, Chief Scientist at SWOOP Analytics, highlights the power of hybrid AI chatbots that combine rule-based and generative AI approaches. As Dr. Lee explains, while generative AI, with its advanced large language models (LLMs), is transforming chatbot interactions by handling nuanced language, it still has limitations. Unlike traditional rule-based systems, which excel at precise, structured tasks, generative AI often struggles with complex logic or delivers responses that lack accuracy due to its probabilistic nature. Dr. Lee advocates for a balanced blend of both AI types, leveraging rule-based processing for reliable accuracy while utilizing generative AI for natural, adaptive engagement. This hybrid approach combines flexibility and control, setting a new standard for chatbot performance. https://lnkd.in/gUGJQvYT Since its inception, Juji Studio embodies this hybrid approach, bringing together the strengths of rule-based and generative AI to create highly adaptive, intuitive chatbots that also have precision for task execution and completion. Juji goes further with two unique features that power rapid AI chatbot creation as well as ensure engaging, accurate conversations: 1. Fine-Grained Task Control: Juji allows creators to leverage generative AI with precision based on specific application and task needs—whether acknowledging users, delivering tailored content, answering questions, or following up on requests—ensuring real-time adaptability that remains focused and context-aware (Screenshots 1-2). 2. Streamlined Creation with Generative AI Assistance: Juji also harnesses generative AI to simplify and speed up the chatbot creation process by automating tasks like drafting conversation flows, developing step-by-step tutorials, extracting Q&A from documents, summarizing conversations, and more—significantly reducing manual workload for creators (Screenshots 3-6). With Juji Studio, building an interactive AI chatbot with precise agentic flow controls has never been easier. Juji’s hybrid model provides the best of both AI worlds, giving creators a powerful tool for designing conversational agents that are adaptive, dependable, and engaging. Discover Juji Studio to experience how this innovative fusion of rule-based and generative AI is shaping the future of conversational AI. #HybridAI #JujiStudio #GenerativeAI #AIchatbots #ConversationalAI #AIInnovation

Reimagining Education with AI Chatbots: Beyond the AI Tutor AI chatbots are redefining learning in ways that go far beyond typical tutoring roles. Inspired by Ethan Mollick and Lilach M., the Stanford University Teaching Commons Autumn Symposium 2024 shared several innovative ways to incorporate chatbots in the classroom to enrich both teaching and learning: https://lnkd.in/eTRs84WF AI as a Mentor Frequent, constructive feedback is critical for student growth, but it's not always feasible to provide in real-time. Chatbots can bridge this gap, offering instant, adaptive feedback on assignments, highlighting areas for improvement in essays or coding exercises, and helping students refine their work. Think of it as a feedback loop that's always available. AI as a Coach Developing metacognitive skills—like reflection and learning strategies—strengthens academic growth. Chatbots can encourage these practices by guiding students to reflect on learning habits, plan study routines, and evaluate project experiences. It's like having a personal academic coach, available anytime, to support effective learning habits. AI as a Simulator Role-play scenarios developed by chatbots foster critical thinking and empathy. Whether simulating an ethical dilemma in healthcare or a client interaction in business, these exercises enable students to explore real-world situations and practice responses in a safe, controlled environment. AI as a Teammate Group projects are vital for collaborative learning but can be hard to manage. Here, chatbots act as team members, synthesizing ideas, creating timelines, or providing fresh perspectives and critiques. By supporting coordination and brainstorming, chatbots can help teams stay organized and innovative. AI as a Simulated Student Teaching reinforces learning, and with chatbots, students can experience this by “teaching” a simulated student. Students can answer questions from the chatbot, organize their knowledge, and practice explaining concepts—reinforcing understanding in a powerful way. These innovative applications empower educators to create an engaging, interactive learning experience that goes beyond traditional methods. With AI, we're not just teaching—we're inspiring, collaborating, and preparing learners for a dynamic future. #EdTech #AIInEducation #LearningInnovation #ChatbotsInLearning #DigitalLearning #StudentSuccess #FutureOfEducation

Reflecting with AI to Elevate Practical Wisdom and Human Intelligence In education, reflection is key to deep learning and personal growth. At Stanford University’s Hasso Plattner Institute of Design, Leticia Britos Cavagnaro, PhD has pioneered Riff, an AI-driven chatbot designed to foster this reflective process. Far from being just another chatbot, Riff dynamically supports users in developing critical thinking and introspective skills, guiding them to build practical wisdom through structured reflection. https://lnkd.in/gS7xHFU5 Unlike traditional tools, Riff engages learners by asking personalized questions to help them dive deeper. Imagine a learner sharing their thoughts on a hands-on activity: instead of offering canned responses, Riff might follow up with, “What was it about the hands-on nature of the activity that helped you dive into your ideas?” It then goes further, encouraging the user to contrast this experience with others or think about how they'd apply what they learned in the future. This conversational and tailored approach supports not only a richer reflection but also prompts learners to actively connect their current experiences with future applications. Riff doesn’t aim to replace human connection; rather, it amplifies it by inviting students to better understand their learning process and share those insights in a way that enhances their future decisions. By supporting reflection on past experiences and prompting learners to think about future actions, AI tools like Riff could act as partners in intellectual growth. AI in education isn’t just about automated answers; it’s about elevating the learning journey and fostering deeper, more meaningful reflection. The remaining question is how instructors and coaches can easily and rapidly create an AI learning assistant like Riff that can coach people on a specific topic or skill but without the help of AI/IT experts? If you are an instructor or coach, have you created an AI learning assistant like Riff? Love to hear your input and thoughts in the comment section. #AIEducation #ReflectiveLearning #EdTech #AIinLearning #PracticalWisdom #FutureOfLearning

How to Leverage Practical Wisdom When Building AI Chatbots In our previous post, we explored how practical wisdom—rooted in Aristotelian philosophy—can help both humans and AI make better decisions, behave more effectively, and contribute meaningfully. Today, we dive deeper into how practical wisdom can empower interactive AI agents, such as AI chatbots, to better guide human-AI interactions. When we talk about AI chatbots, we're looking at systems that interact directly with users—whether answering queries, providing guidance, or assisting with complex tasks. These interactions demand not just technical accuracy, but a nuanced understanding of human behavior and communication. Research by Brett Karlan, and Colin Allen from University of Pittsburgh emphasizes that practical wisdom is crucial at all levels of human-AI interactions. https://lnkd.in/eTW-C9wW Here we focus on two areas where practical wisdom is essential: 1️. Developing Conversational AI Platforms Creating a platform that allows non-technical domain experts to build effective AI agents is no small feat. Developers must have the practical wisdom to understand both the capabilities and limitations of AI. They should be able to anticipate the unpredictable ways users might interact with the AI—whether it's digressions from the main topic, misunderstandings, or unexpected challenges. To ensure the robustness of AI systems, developers need to integrate built-in safety features: • Using human-curated content for high-risk scenarios to avoid AI-generated hallucinations (Image 1). • Providing tools to manage diverse user behaviors, ensuring a reliable and effective user experience (Image 2). • Allowing AI agent builders to seamlessly handle complex use cases with minimal technical intervention (Image 3). 2️. Building AI Agents Using Conversational AI Platforms For those who use these platforms to create AI chatbots or conversational AI agents, having practical wisdom is equally crucial. AI agent builders must know how to construct a natural and effective conversation flow that not only achieves the desired task but also keeps the user satisfied. This requires an understanding of: • User psychology: Anticipating user needs and diverse user behaviors, and knowing how to gracefully handle unexpected digressions (Image 4). • Task goals: Ensuring that the conversation stays focused while feeling fluid and responsive (Image 5). • Leveraging the platform’s built-in support—from curated content options to advanced features for conversation design—to create AI agents with the reliability and resilience needed for diverse real-world scenarios (Image 6-7). By fostering practical wisdom across both platform developers and AI agent builders, we can design AI systems that are trustworthy and adaptable, capable of handling the complexities of real-world interactions. #AI #ConversationalAI #PracticalWisdom #AIdevelopment #HumanAIInteraction #AIPlatforms

Powering AI Agents with Practical Wisdom: What Is It and Why It Matters? Practical wisdom, or "phronesis," as Aristotle called it, goes beyond theoretical knowledge. It’s the art of blending what you know with how to act in complex, real-world situations. According to recent research by Dr. Peter Massingham of University of Wollongong, practical wisdom involves a nuanced balance between knowledge and judgment, helping professionals make better decisions, act maturely, and stay motivated by a higher purpose. https://lnkd.in/ePCnjxvD Why Should AI Agents Be Powered with Practical Wisdom? To be truly effective, AI agents need more than just domain-specific data (traditional “knowledge”) and language skills (often powered by #LLMs). They must also leverage #practicalwisdom to better assist humans in completing their tasks, including decision-making tasks. AI agents powered with practical wisdom can: • Make Better Decisions: Practical wisdom helps humans make more informed and balanced decisions, weighing both ethical and practical considerations. It's about making choices that not only solve problems but do so ethically and effectively. Just as practical wisdom improves human decision-making, it can enhance AI's ability to make choices that are not only technically sound but contextually appropriate (Image 1). • Exhibit Mature Behavior: Practical wisdom shapes behavior, leading to a more refined and appropriate response in varied contexts. With practical wisdom, AI agents can navigate human interactions with sensitivity, adaptability, and ethical consideration (Image 2). • Drive Meaningful Contributions: Practical wisdom gives people a deeper sense of purpose. AI with practical wisdom can focus on delivering societal benefits, supporting human needs and well-being, just as wise professionals aim to make a difference (Image 3). What’s Next? Building AI agents with Practical Wisdom How do we bring phronesis to AI? Stay tuned for upcoming discussions on integrating practical wisdom into AI development for a future where AI not only "knows" but truly understands and acts wisely. #AI #PracticalWisdom #HumanAIInteraction #AIFuture #AIDevelopment #WisdomInTech #EthicalAI #AIInnovation