Understanding Human-Machine Interaction Trends

I had an epiphany while working on AI consulting engagement for a company that makes Robotic Toy companions. While I was working to fix "issues" with the AI System data and algorithms, and understand how the AI really works, it struck me - What if I could the AI understand where I am coming? What if explaining myself could help with better issue resolution? This article highlights key aspects of Human Nature that AI needs to comprehend, including emotional intelligence, cultural context, social dynamics, and ethical frameworks. It discusses the potential benefits of this approach, such as improved Human-AI collaboration, enhanced empathy in AI Systems, and more ethical decision-making. The article also addresses the challenges in implementing this concept, including the complexity of human behavior and the need for multidisciplinary collaboration. In the rapidly evolving landscape of Artificial Intelligence, a new paradigm is emerging: the importance of explaining humans to AI. While much focus has been on making AI Systems understandable to humans, this article explores the reverse – equipping AI with a deep understanding of human behavior, emotions, and contexts. This approach is crucial for developing AI Systems that can interact more effectively, ethically, and empathetically with humans in various domains, from healthcare to education. The impact of this paradigm shift could be profound, potentially leading to AI systems that not only mimic human intelligence but truly understand and respect human experiences. As we move towards an AI-driven future, ensuring that these powerful systems comprehend human nature may be one of the most critical tasks we face. This concept of 'Human Explainability' offers a promising path towards creating AI that is not just intelligent, but also aligned with human values and capable of fostering genuine collaborative intelligence. #ArtificialIntelligence #AIEthics #ExplainableAI #HumanCentricAI #CollaborativeIntelligence #EmotionalIntelligence #AIResearch #FutureOfAI #HumanAIInteraction #AIInnovation #TechEthics #AIandHumanity #AIBehavior #EthicalAI #AIinHealthcare

Love this analogy for the emerging chapter of UX: "We’ve moved from designing 'waterslides,' where we focused on minimizing friction and ensuring fluid flow — to 'wave pools,' where there is no clear path and every user engages in a unique way." That's Alex Klein in this article: https://lnkd.in/eRpmzUEd Over the past several years, the more that I’ve worked with AI and machine learning—with robot-generated content and robot-generated interaction—the more I’ve realized I’m not in control of that experience as a designer. And that’s new. Interaction designers have traditionally designed a fixed path through information and interactions that we control and define. Now, when we allow the humans and machines to interact directly, they create their own experience outside of tightly constrained paths. This has some implications that are worth exploring in both personal practice and as an industry. We’ve been working in all of these areas in our product work at Big Medium over the past few years SENTIENT DESIGN. This is the term I’ve been using for AI-mediated interfaces. When the robots take on the responsibility for responding to humans, what becomes possible? What AI-facilitated experiences lie beyond the current fascination with chatbots? How might the systems themselves morph and adapt to present interfaces and interaction based on the user’s immediate need and interest? This doesn’t mean that every interface becomes a fever dream of information and interaction, but it does mean moving away from fixed templates and set UI patterns. DEFENSIVE DESIGN. We’re used to designing for success and the happy path. When we let humans and robots interact directly, we have to shift to designing for failure and uncertainty. We have to consider what could go wrong, how to prevent those issues where we can, and provide a gentle landing when we fail. PERSONA-LESS DESIGN. As we get the very real ability to respond to users in a hyper-personalized way, do personas still matter? Is it relevant or useful to define broad categories of people or mindsets, when our systems are capable of addressing the individual and their mindset in the moment? UX tools like personas and journey maps may need a rethink. At the very least, we have to reconsider how we use them and in which contexts of our product design and strategy. These are exciting times, and we’re learning a ton. At Big Medium, we’ve been working for years with machine learning and AI, but we’re still discovering new interaction models every day—and fresh opportunities to collaborate with the robots. It’s definitely a moment to explore, think big, and splash in puddles—or as Klein might put it, leave the waterslide to take a swim in the wave pool.

NVIDIA's CEO has seen everything AI can do... And this is what actually gets him excited: Creating personalized digital assistants. Huang has a vision of the future. Where everyone has their own personalized AI agent This AI would be: Adaptive: → Learning and becoming smarter over time as it interacts with its user. ↳ This adaptability ensures that the AI stays relevant and useful. Understanding: → Developing a deep comprehension of the user's needs, preferences, and habits. ↳ This allows the AI to provide tailored assistance. Helpful: → Assisting in tasks and enhancing productivity. ↳ This help can range from managing schedules to providing insights. Lifelong AI Companions: The concept of having an AI companion throughout one's life is particularly intriguing. Huang suggests that: People growing up now will have AI assistants that accompany them throughout their lives. ↳ These companions will evolve with the user, becoming more in tune to their needs over time. These AI companions could exist in various forms, including digital, work-specific, and even physical. ↳ This versatility allows for seamless integration into different aspects of life. Excitement for Collaborative Intelligence What seems to excite Huang most is the idea of collaborative intelligence – humans working alongside increasingly capable AI systems. This collaboration could lead to: Enhanced problem-solving capabilities → The AI can provide insights and suggestions that humans might overlook. Increased efficiency in daily tasks → Routine tasks can be automated, freeing up time for more important activities. New forms of creativity and innovation → The AI can inspire new ideas and approaches. Potential Implications: While Huang's vision is optimistic, It also raises an important concern. Privacy and Data Security: → With AI agents becoming so intimately involved in our lives, ensuring data privacy and security will be crucial. ↳ Safeguarding personal information will be paramount. Human-AI Interaction: → Understanding and optimizing the dynamics of long-term human-AI relationships will be a new frontier in psychology and social sciences. ↳ This will require new research and insights. Societal Impact: → The widespread adoption of personal AI agents could significantly alter social structures, education systems, and workforce dynamics. ↳ These changes could bring both opportunities and challenges. This vision represents a significant shift in how we might interact with technology in the future. We'll move from tools to AI sidekicks. But I think we still have a few more years of humans. So follow Eitan to meet the humans behind AI. ♻️ Repost so your network can meet them too.

🌟 What’s Next for AI Design: Themes for 2025 🌟 As we enter 2025, the landscape of AI design is evolving rapidly, with emerging trends reshaping how we build and interact with technology. Here are some key trends I’m particularly excited about: 🔹 1. Interfaces That Adapt to User Needs We’re moving from static UIs to interfaces that dynamically adapt to context, personalization, and real-time inputs. This means simpler, cleaner, and more intuitive UX that delivers exactly what users need when they need it. 🛠️ Examples: Jordan Singer's work at Mainframe and Beam by @Toby Bream (https://beem.computer/) showcase the future of adaptive design. 🔹 2. Reimagining Data Organization Traditional data structuring feels ancient today. AI is helping us rethink how unstructured data is reorganized and delivered intuitively, in formats tailored to our needs. 💡 Check out @MatthewWsiu's explorations on this (https://lnkd.in/gFADJkXS) 🔹 3. Fluid Media AI is democratizing media creation - transforming text into videos, sketches into 3D models, and more. These capabilities open up a world of immersive, creative possibilities. 🎨 There are many advanced models out there, but here is a classic example I worked on a while back that transforms sketches into animated characters (https://lnkd.in/gPYA7xfP) 🔹 4. Multimodal Interactions Gone are the days of singular inputs. Multimodal AI systems combine voice, visuals, text, and beyond to create richer, more engaging user experiences. Claude artefacts are a good example! 🔹 5. Human-AI Connections AI isn’t just a tool - it’s becoming a partner for advice, journaling, task management, and more. Designing safe, meaningful interactions is key to ensuring this shift feels natural and intuitive. 🤖 e.g. I’ve been using apps like Rosebud (https://www.rosebud.app/) that probably know me better than some of my friends! 🔹 6. Immersive Experiences Adaptive interfaces, fluid media, and multimodal capabilities make immersive experiences more accessible than ever. 🌐 Rooms by Things, Inc. has recently launched some fun examples of this (https://lnkd.in/grcnyRcy) 🔹 7. Empowering Anyone to Build Anything The lines between designer, PM, and engineer are blurring. Tools like Cursor are empowering everyone to create AI apps, breaking down traditional silos. 🚀 Dreamcut.ai by Meng To is a great example of the creative potential unlocked by AI. 🔹 8. AI-First Interaction Patterns As AI capabilities grow, we must develop new design patterns to handle these challenges. For those interested in diving deeper, check out my course (https://lnkd.in/gcVgP3My). The next cohort starts in February, and we’ll explore these trends and more! As a reminder, these are just some themes I'm personally excited about and I'm sure I've missed many. Are there other themes you're excited about? Please share them in the comments!

The future of AI is not in the prompts but in the conversation. Prompt inversion is revolutionizing how humans interact with AI. Rather than relying on the user to input the perfect prompt, AI is now taking the lead by asking clarifying questions to guide the conversation. This shift is significant. It allows AI to better understand the user's intent and provide more accurate and relevant responses. Humans often struggle with articulating their thoughts and needs. Having AI prompt the user can help overcome these biases and lead to more effective communication. In classic, centralized search, Google and others make more money if they get you "close" to the answer - but not if they give you the answer. This is why going beyond "auto-complete" for these tools has never made (financial) sense. But with AI, soon, there will be no more staring at a blank box, hoping for the right query to lead you to an answer. The AI takes the lead, asking clarifying questions to guide the conversation. It's a dialogue, not a discrete game of search. We covered this in our last #Yext Insights program. In the Information Foraging theory developed by Peter Pirolli and Stuart Card, humans' search for information is likened to how animals forage for food. This theory could provide a compelling academic framework for understanding prompt inversion. It suggests that just as animals seek patches of rich food resources, humans are driven to find rich information patches. Prompt inversion could be seen as a method where AI helps humans navigate to these 'rich patches' more efficiently by actively guiding the search process. This shift promises to make AI interactions more intuitive and productive. It's a step towards truly conversational AI, adapting to individual needs and preferences. Try the ChatGPT premium version on your phone to preview this technique. Click the earphones icon and experience the difference. Prompt inversion is a glimpse into the future of human-AI interaction.

Have you noticed how we've started saying "please" and "thank you" to AI? Or even using “Can you do this" rather than just asking for a task? It's interesting how readily we “anthropomorphize” these powerful tools, even when we know they're not human. Yes, that’s the term gaining lots of traction, as bringing AI adoption is tough, and without building such a bond, it’ll be even harder to do it. This isn't entirely new. Remember Alexa, Google Assistant, Cortana, or many other products in the past that got a name? But the current wave of generative AI products feels different. It's not just about a name or a pre-programmed persona; it's about the genuine sense of conversation we experience. We ask AI to summarize articles, generate creative content, and offer assistance, and we often thank it for its help. This shift in interaction is more than just a trend; it's a fundamental change in how we relate to technology. This “anthropomorphic” tendency is undoubtedly driving AI adoption. When interacting with AI feels more natural, more conversational, the barriers to entry crumble. This connection is converting human-computer interaction (HCI) to human-computer integration. The more human-like the interaction becomes, the more comfortable we are incorporating AI into our lives. We're already seeing use cases emerge where AI acts as a true assistant, proactively learning about the user and providing insights when needed, not just when asked. This goes beyond personalization. But this evolving relationship raises some important questions. As we blur the lines between human and machine, how does this impact our understanding of both? How do we ensure that this technology doesn’t create an emotional bond that might have long-term implications? We're already grappling with the dopamine rush from social media; this could be another step in that direction #ExperienceFromTheField #WrittenByHuman

Artificiality Institute's first research whitepaper explores how people are forming psychological relationships with AI systems that feel unprecedented to them. Whether these experiences represent genuinely novel human-technology interaction or familiar patterns under new conditions remains an open question. Humans have always formed relationships with tools, absorbed ideas from cultural systems, and adapted to new technologies. However, AI systems combine characteristics in potentially unprecedented ways: compressed collective human knowledge rather than individual perspectives, apparent agency without consciousness, bidirectional influence at population scale, and constant availability without social obligations. Through workshop observations of over 1,000 people, informal interviews, and analysis of first-person online accounts, we observe humans developing three key psychological orientations toward AI: - How easily AI responses blend into their thinking (Cognitive Permeability) - How closely their identity becomes entangled with AI interaction (Identity Coupling) - Their capacity to revise fundamental categories when familiar frameworks break down (Symbolic Plasticity) People navigate five psychological states as they adapt: Recognition of AI capability, Integration into daily routines, Blurring of boundaries between self and system, Fracture when something breaks down, and Reconstruction of new frameworks for AI relationships. The key finding? Symbolic Plasticity—the ability to create new meaning frameworks—appears to moderate how people navigate AI relationships. Those who can reframe their understanding of thinking, creativity, and identity adapt more consciously. Those who can't often drift into dependency or crisis without frameworks to interpret what's happening. And a huge thank you to our advisors and reviewers. Barbara Tversky, Steven Sloman, Abigail Snodgrass, Peter Spear, Tobias Rees, John Pasmore, Beatriz Paniego Béjar, Don Norman, Mark Nitzberg, Chris Messina, Josh Lovejoy, Elise Keith, Karin Klinger, Jamer Hunt, Lukas N.P. Egger, Alan Eyzaguirre, and Adam Cutler. Link to the whitepaper in the comments. #thechronicle #ai #genAI #humancentered #humanfirst #stories #aiadaptation #resilience #humanexperience #chatGPT #claude #AIsummit #impactofai #futureofwork

One of our most anticipated reports each year is out—a comprehensive look at the most significant tech trends unfolding today, from agentic AI to the future of mobility to bioengineering. It provides CEOs with insights on how to embrace frontier technology that has the potential to transform industries and create new opportunities for growth.   Here’s my top-line take: —Equity investments rose in 10 out of 13 tech trends in 2024, with 7 of those trends recovering from declines in the previous year. This rebound signals growing confidence in emerging technologies. —We're witnessing a significant shift in autonomous systems going from pilots to practical applications. Systems like robots and digital agents, are not only executing tasks but also learning and adapting. Agentic AI saw a $1.1 billion equity investment in 2024 alone. —The interface between humans and machines is becoming more natural and intuitive. Advances in immersive training environments, haptic robotics, voice-driven copilots, and sensor-enabled wearables are making technology more responsive to human needs. —And, of course, the AI effect stands out as both a powerful trend in its own right and a foundational amplifier of others. AI is accelerating robotics training, advancing bioengineering discoveries, optimizing energy systems, and more. The sheer scale of investment in AI is staggering, with $124.3 billion in equity investment in 2024 alone.   Let's discuss: Which of these trends do you think will have the most significant impact on your industry? Share your thoughts in the comments below!   Big thanks to my colleagues Lareina Yee, Michael Chui, Roger Roberts, and Sven Smit.   #TechTrends #AI #Innovation #FutureOfWork #EmergingTech http://mck.co/techtrends