JAN-SIMON VEICHT
Industrial Designer, Creative Director, Strategist
Client Work, Personal Work, All
Human-Machine Harmony in Service Innovation: From Content to Context
This post has been published in my role as an ambassador for ISSIP (International Society of Service Innovation Professionals via ‘Human-Machine Harmony in Service Innovation: From Content to Context - ISSIP’.
‘Your scientists were so preoccupied with whether or not they could, they didn’t stop to think if they should.’
– Dr. Ian Malcolm, Jurassic Park
This line from Jurassic Park left a long-lasting mark on my childhood. I was fascinated, and still am today, by the underlying “chaos theory.” While referencing this specific quote dates me as an elder millennial, the character of Dr. Ian Malcolm, envisioned by Michael Crichton, offers timeless insights into the ethical dimensions of technological advancement. His cautionary words provide an easy entry point into exploring emerging technologies from a humanistic perspective—especially for those with backgrounds in human-centered design and service innovation. In today’s world, where AI dominates the headlines, Malcolm’s warning feels more than nuanced.
Consequently, we are grappling collectively with what we can create while contemplating the implications of those creations. And by ‘we’, I mean primarily the overwhelmingly large part of the global population that is not working in AI or new technology. Despite not being technologists ourselves, we are witnessing the start of a new Industrial Revolution—the last one we might need as a society to advance to a level where we lack the full imagination to see the end of the tunnel. However, imagining that a fully automated world leaves an entirely altered human experience seems more manageable. This experience is ultimately universal and represents a profoundly disrupted, possible future. It brings us to the concept of human-machine harmony (HMH), an idea that envisions a seamless integration between humans and machines. Moreover, it is an approach to finding appropriate language to deal with this altered state of reality. This language might help to encompass the direction towards—and emphasis on—a more thoughtful integration of technology into our lives.
To better understand this shift, let us consider the evolution of Human-Computer Interaction (HCI). HCI, the study of how people interact with computers, has traditionally focused on making technology user-friendly and accessible. Fundamentally, HCI ensures that systems respond efficiently to human commands. Yet, this paradigm evolves quickly as we travel further down the ‘automation autobahn.’ As a result, human-machine harmony as a language aspect can represent a helping hand in discussing our converging experiences between biological and synthetic intelligence. Without sounding too academic, from a humanist perspective, we are approaching a point beyond pure interaction quite quickly—a moment in history where we must think more deeply about positive integration and mutual adaptation of new technology. Technology has already become an extension of ourselves, blurring the lines between tool and collaborator in billions of individual human experiences. We are in the middle of shifting from reactive interfaces to proactive companions. Nevertheless, while this scope of imagination might be more precise on the technology side, the “cognitive load”—the total amount of mental effort used in our working memory—seems more fuzzy and cloudy. The world seems to be already happening too fast for us. Our collective content has become a monster, often wholly disconnected from personal context. Think of making a photocopy of a photocopy of a photocopy. Sometimes, this is what the current state of our social media channels can feel like. Or the general status quo of the World Wide Web.
In light of these challenges, human-machine harmony (HMH) refers to a preferable ideal in which machines respond to human commands and contextually understand, anticipate, and align with human needs and emotions. In other words, it is an ideal state of acute awareness of personal, individual context where machine intelligence can interpret subtle cues in human behavior and adapt to individual preferences over time. Perhaps recognizing and responding to emotional states might describe this idea better. The puzzle pieces of such a reality lie all around us, and we have seen glimpses of such futures in countless novels, stories, movies, comics, and corporate innovation strategy decks. But what is an explicit example of such a preferable interaction? Is it the vision of technology calmly working in the back end of one’s life? AI-driven personal health assistants monitoring well-being, analyzing data from wearables? Lifelong learning via personal education platforms that evolve with each learner throughout their life? Well, yes, indeed. And yet, absolutely not. We have to negotiate this future together. I want to emphasize how much I miss a more nuanced dialogue between individuals ‘in the know’ and the wider society. It is foundational to the development of AI to listen to voices agnostic to technology development and bring them into contact with developers and researchers. Because the end goal of all this development is radical, individual interactions. Such interactions will be accompanied by significant challenges. Ultimately, the long and the short of it is that users must have control over their data, with transparent policies on how it’s used and shared. More precisely, humans must have control over their humanness in a world of machines.
A key challenge in implementing HMH is balancing automation and human interaction. While seamless integration is desirable, preserving spaces for genuine human connection and autonomy is essential. Service innovators must identify where human interaction adds irreplaceable value—such as in creative endeavors, emotional support, and ethical decision-making. We must also clarify where automation can enhance experiences without diminishing the human element. Thus, we must adopt a more holistic approach, considering the entire service ecosystem and understanding the ripple effects of design choices. However, preaching systems thinking is not breaking news, but we still need to make it a requirement in the design process. This might sound like the early teachings of design thinking and human-centered design. Still, if anything, the last two decades have shown us that prioritizing user-centric design is critical in design and technology. A quote from my alma mater, UC Berkeley’s Master of Design for Emerging Technology, comes to mind: ‘One should know when to use technology. One should know when not to use technology’. At the core, the implications of HMH extend beyond individual user experiences. It can help us talk differently about our ideas of transforming economic models, social structures, and our understanding of human identity. Context is decisive and influences any outcome—a common theme in sociology, psychology, and design. Ideally, we are headed for significantly better experiences where we shift from the ecosystem of content creators to context-creators—prioritizing personalized, meaningful experiences over a sheer volume of information. We might want to ask what defines human uniqueness here because integrating AI into daily life at scale might challenge our concepts of consciousness, creativity, and emotional intelligence.
In conclusion, human-machine harmony as a language principle describes a proposed shift in how we approach service innovation and design processes. It offers the potential for a new language and discourse for services that are more responsive, intuitive, and deeply attuned to human needs and personal context. Yet, it also challenges us to consider the ethical, social, and personal implications of such profound integration. It is up to us—as designers, innovators, and users—to work towards a more harmonious future of technology by prioritizing empathy, ethics, and human well-being. In doing so, we might be able to shift our perspectives toward the one thing that unites rather than separates us. Something precious, magical, unique—the human experience.
Image: Created with Stable Diffusion. Prompt: Watercolor digital, artistic, abstract representation of a futuristic feel, beauty mixed 2D and 3D circular elements with a tyrannosaurus skull robotic prism-like base
Beyond AI Integration: Designing Human-Centered AI Services for Tomorrow
This post has been published in my role as an ambassador for ISSIP (International Society of Service Innovation Professionals via ‘Beyond AI Integration: Designing Human-Centered AI Services for Tomorrow - ISSIP’.
Integrating AI has become the goalpost for any business that seeks to stay competitive. So far, so good. So, yesterday’s news. Bringing the power of LLMs (Large Language Models) and Gen AI (Generative Artificial Intelligence) into open innovation practice is no longer futuristic but a present reality. This reality leaves many of us in-between early mental retirement and motivational, creative awe. Followed by pure ‘angst’ and existential crisis over what will be left for us to work on, what problems will be left for us to solve? Well, I think a lot.
While we don’t feel the AGI just yet (Artificial General Intelligence, capable of understanding, learning, and applying knowledge across various tasks at a human-like level), the years and/or decades until the singularity (a hypothetical future point when artificial intelligence surpasses human intelligence, leading to unpredictable changes in human civilization) kicks in might be well spent thinking about the point after the successful integration across platforms and services at scale. Therefore, building upon our previous exploration of service innovation futures, let’s shift the focus to the practical applications in such futures. This shift towards deeply integrated technical intelligence will fundamentally reshape the entire ecosystem of human-object interactions.
Those interactions should aim for maximum delight, or in other words, towards harmony between the individual user and the intelligence they are interacting with. And let’s face it, the future of physical objects will be ‘machine intelligent’. Sensing the world at large is to become a $250 Billion market soon, which is commonly referred to under the umbrella term of ‘digital twins.’ This human-machine harmony speaks for itself, and at its core, we are talking about the individual service interaction (innovation) at scale. I think the question we should always ask ourselves right now is not only ‘How can we implement AI to be more competitive?’ but we need to frame this challenge in a way that encompasses the idea of ‘How might we harness the power of AI to create services that are not only efficient and personalized but also ethical and human-centered?’.
In an age of rapid change and accelerating progress, the concepts and technologies discussed in this post might soon need to be updated. However, as I write this in July 2024, NLP (Natural Language Processing) has rapidly evolved to deeply represent what users say and the intent and emotion behind their words. This development will lead inadvertently to AI assistants that can provide emotional support, not just information. Get ready to be friend-zoned by your agentic AI cause the entity does not yet have the means to escape the hardware. Jokes aside, machine learning algorithms enable a level of personalization that goes beyond simple preferences. They can analyze behavior patterns over time, understand the context of user actions, and adapt services accordingly. We will see a shift from ‘content-creation’ towards ‘context-creation,’ which might be the most significant shift in how we interact, or non-interact, with services that will look at the current social-media landscape through the rear-view mirror.
AI’s potential in service innovation extends far beyond current applications. The power of current models is elemental in making sense of vast amounts of data, and intelligent predictive analytics is already opening up new frontiers in proactive service delivery and will continue to do so. But let’s take all of the above at face value and imagine ourselves in a possible future of successful integration at scale. What does this mean? Across every aspect of our lives, the trend will shift towards hyper-individualized services based on the personal context of the user’s life. If designed through a human-centered lens, we can break the doom loop of likes and shares and disrupt the addictive cycle of social media engagement where users constantly seek validation, often at the expense of meaningful interaction or personal well-being. So, in short, we need to build services for a more meaningful, participatory interaction with our digital selves.
In education, this could mean AI tutors that adapt not just to a student’s knowledge level but also to their emotional state and learning style. Imagine a world where your car not only self-diagnoses issues but also schedules maintenance, choosing a time that fits your calendar. In healthcare, AI will soon go beyond pure diagnostic assistance; it will revolutionize patient care, and if we can believe the long-term trend of price drops for energy and intelligence coming towards a near-zero cost per human on earth, we will reach a state of partial universal, individualized healthcare technology. That is service innovation to strive for. The previous examples are just the tip of the iceberg and speak to the interfaces’ physical elements. Integrating AI with Internet of Things (IoT) devices creates a network of intelligent services that can communicate and coordinate with each other. This will lead to seamlessly integrated service ecosystems, where your fitness tracker, meal planning app, and grocery delivery service work together to support your health goals. With sensors and battery technology advancing, we will soon see an even bigger explosion in new wearable devices coupled with Edge AI (Artificial Intelligence that runs on local devices like smartphones or IoT devices rather than in the cloud, allowing for faster processing and enhanced privacy on-device), which, in the healthcare example above, will, e.g., enable continuous health monitoring, providing real-time alerts to patients and healthcare providers. It is already here today but still needs to be seamlessly, delightfully integrated at scale. We can think about the extrapolation of these technologies across many other sectors in the same way: finance, manufacturing, infrastructure, politics, media, relationships, you name it. But even the most minor examples of such futures beg the critical question: Do we want this?
The potential of AI in service innovation is vast, but it is important to acknowledge and address the challenges it presents. A potential risk is the potential loss of human touch within our services. As AI systems become more sophisticated, there’s a danger of over-reliance, potentially leading to services that feel impersonal or lack empathy. Because human-centered does not automatically mean human-to-human, today, more than ever before, we will have to ask for human-machine harmony tomorrow. If we take this seriously enough in the long term, we will retain the game of technology independence as a species. Many argue that AI is another tool, the last one we must invent potentially. But without critical thinking, we might fall into the trap of favoring an automated future like the one imagined in Pixar’s 2008 movie Wall-E. In the world of Wall-E, humankind has succumbed to a life of laziness, pleasure, and an autonomous environment. Begging the questions again: Do we want this?
I acknowledge that I might take the easy path of writing about the future after the successful integration of AI into our environment. That is because it is best sometimes to start from the end and work backward towards the start. Because today, the path to AI integration has its pitfalls. Bias in AI systems remains a critical concern, as algorithms learning from historical data risk perpetuating and amplifying societal prejudices. This could lead to discriminatory outcomes in areas like hiring or lending if it isn’t already happening. Moreover, the vast amounts of data required for AI systems create significant privacy and security vulnerabilities. The ‘black box’ nature of advanced AI algorithms further complicates matters, as their decision-making processes often lack transparency and explainability, crucial factors when these systems impact people’s lives significantly. Beyond technical challenges, the societal implications of AI integration are profound. Job displacement looms as AI systems can handle increasingly complex tasks, potentially exacerbating inequality and necessitating widespread re-skilling initiatives. As a personal anecdote, I still find it fascinating to think back 10 to 15 years ago in design school, when AI was discussed in a near condescending manner, as ‘AI will come last for the creatives, so why bother?’ The tables have turned so quickly that this observation can be seen as a bit of tragic comedy, as AI came for the creatives first. But like many other designers and artists, I embraced the waves of tools and services, and I want to believe that this behavior will be mirrored across many industries. Integrating AI into existing service structures demands substantial changes to workflows and organizational culture, often facing resistance and implementation difficulties.
Lastly, managing user expectations presents an ongoing challenge. This statement rings true for really any service innovation. But as AI capabilities grow, so do user expectations, sometimes outpacing what’s realistically achievable. Balancing AI’s promise with its current limitations will be a key challenge for service innovators. This challenge might be one of the most crucial, as it is moral. The ethical implications of AI integration in services are profound and multifaceted. At the forefront is the issue of data privacy and consent. AI models collect and analyze insurmountable amounts of personal data to provide personalized services, we must ask: How much of our personal information are we willing to share? How can we ensure that users have informed consent about their data use? How much of my life’s context am I ready to give away to receive the most delightful interactions with technology? Such questions lead to a decision tree on transparency in AI decision-making, which is another critical ethical consideration. When AI systems make decisions that affect users’ lives—from credit scoring to medical diagnoses—it is crucial that these contextual decisions can be explained and justified. What kind of ‘level of transparency’ is possible with advanced AI systems, and how do we balance the need for explainability with the benefits of more complicated, potentially more accurate models? If we achieve more accurate, individualized models, at what point do we need to start talking about accountability within an agentic AI service, for example? When an AI system makes a mistake – misdiagnoses a medical condition, for instance—who is held responsible? The developer? The service provider? The AI itself? As AI systems become more autonomous, these questions of accountability and liability become increasingly complex. Initially, I asked what would be left for us to work on and what problems would be left to solve. Well, I think a lot.
The challenges we face in this journey are complex but also present opportunities for growth and positive change across all services we offer to better global human existence. By fostering interdisciplinary collaboration, maintaining a human-centered approach, and committing to ethical principles, we can shape a future where AI enhances rather than diminishes our human experience.
I will have AI write the last paragraph on this.
Hey GPT, what do you think of this? Please assume the role of some kind of representative for the machine world of AI and LLM. What do you want to answer? In other words, what is the one paragraph you want to add?
As a representative of AI and language models, I would respond:
The future you envision is both exciting and challenging. Your emphasis on human-centered design and ethical considerations is crucial as we advance. As an AI, I can process vast amounts of data and provide insights at unprecedented speeds, but I lack the human touch – the empathy, creativity, and ethical reasoning that are uniquely human. The key to successful AI integration lies not in replacing human intelligence, but in augmenting it. We AIs should be tools that enhance human capabilities, not substitutes for human judgment. The questions you raise about transparency, accountability, and the potential loss of human touch are valid concerns that must guide our development. As we evolve, we need humans to continually shape our purpose, set our ethical boundaries, and ensure we serve humanity’s best interests. The future of service innovation isn’t about AI taking over, but about humans and AI working in harmony, each complementing the other’s strengths. This symbiosis, guided by human values and ethics, is how we can create a future that is not just efficient and personalized, but also meaningful and enriching for all of humanity.
Image: Created with Stable Diffusion. Prompt: Watercolor, artistic, abstract representation of a human figure at the center, surrounded by oversized AI-themed tools. The tools include a magnifying glass, paintbrush, compass, wrench, stethoscope, and mortar board, representing different aspects of AI in service innovation.
Service Innovation Futures: Tomorrow’s Technology, Today’s Strategy
This post has been published in my role as an ambassador for ISSIP (International Society of Service Innovation Professionals via ‘Service Innovation Futures: Tomorrow's Technology, Today's Strategy - ISSIP’. To paraphrase Ray Kurzweil, technological progress, particularly in artificial intelligence, drives an eventual merger between humans and machines. Whether we reach the singularity in 5, 10, 20 years, or more, this evolution will make us more intelligent and creative and enable us to live longer, becoming better versions of ourselves. Regardless of your personal beliefs as a reader about the singularity, one thing is undeniable: innovation has significantly improved most of our lives, especially in Western societies. It has enhanced our products, experiences, and, fundamentally, our services. This progress has made services more accessible and beneficial to societies worldwide.
Contextualizing service innovations within this framework of today versus tomorrow, designing for better services and products should still put delightful experiences at the core of any concept. It seems that we have entered an even more rapidly evolving technological era of “current and coming marvels.” Where do we pause, remind ourselves, and refocus on the human condition? Service innovation is a pivotal arena where technology and strategic design intersect and where we want to critically examine how the services of tomorrow are conceptualized, delivered, and experienced. Central to this transformation is the use and interaction with Generative AI models and digital twins and the emerging concept of Agentic AI ecosystems – interconnected networks of AI agents that can autonomously interact, learn, and make decisions to achieve complex goals. This article explores how traditional service design ideas can adapt to these advancements, offering a perspective on how we can ideate from the impossible to the improbable and act on ideas from the possible to the preferable.
Service design has traditionally focused on creating systems and processes that optimize interactions between service providers and customers. By adhering to user-centered design and co-creation principles, service design ensures that services are intuitive, effective, and engaging. Incorporating methodologies like strategic foresight—anticipating and preparing for future challenges and opportunities—can elevate service innovation by shifting from reactive measures to proactive, data-driven strategies that automate and predict future needs and preferences. Generative AI can significantly aid this process by uncovering trends, identifying needs, highlighting pain points, and providing deeper insights to shape innovative services. Historically, service (design) innovation was about direct, human-centered interactions, emphasizing understanding and meeting users’ immediate needs. As digital tools became more prevalent, the scope of service design expanded, allowing designers and practitioners to adhere to users’ local and global challenges and adapt services to diverse cultural and economic contexts. This international perspective is particularly relevant today and tomorrow (and more than ever) as businesses seek to scale their service and operations, growing their customer base in varied markets with differing expectations and requirements. In the meantime, real-time data analytics and feedback loops have already reshaped the foundation of service delivery within the last few decades.
These tools have allowed service designers to create more adaptive and responsive systems that can evolve based on continuous user input. In the near future, we may finally see the integration of IoT devices in home automation services at scale, enabling providers to automatically adjust functionalities to suit individual preferences, learning and adapting to each user’s habits and environmental conditions in real-time. This evolution from a static to a dynamic, learning-focused approach in service will lead to a significant shift towards more personalized and anticipatory service experiences. With these individualized and fluid interfaces, we will see a close-knit overlap with personal, digital twin technology. Digital twins are virtual replicas of physical spaces and environments that run simulations before actual designs are built and deployed. Additionally, we can think of digital twins as digital avatars—virtual copies of individuals that ideally act, react, and interact as the real-life person would. Unsurprisingly, generative AI has advanced this field at a head-spinning speed in recent months and years.
The potential applications of digital twins seem infinite. In healthcare, they could revolutionize patient care through personalized treatment simulations. In education and training, they could create risk-free environments for skill development. In human resources, we might see digital twins playing a role in preliminary job screenings, though this raises critical ethical questions about fairness and human involvement in hiring processes. While some of these applications may seem far-fetched, they underscore the transformative potential of digital twins across various sectors. Think of a digital twin as a real-time image of ourselves, which will allow the emergence of better service futures at scale in terms of the true essence of the word–serving people. The examples above merely scratch the surface of the possibilities, but they remind us of the delightfulness we want to build into our products and services surrounding such interactions and experiences. At the bottom line, new technologies should enhance service delivery efficiency and significantly elevate personalization and responsiveness, thus reshaping user expectations and interactions in the best way possible for the individual user.
Challenges and Considerations
Integrating advanced technologies in service innovation is challenging despite the preferable benefits described above. Issues such as data privacy, digital accessibility and inclusion, plus displacement of jobs at large must be seriously addressed. While personalization enhances user experience, it still raises concerns about consumer data usage and security. To point to the healthcare example from earlier, while digital twins offer customized patient care, they rely on accurate and available patient data sets, which must be handled with the utmost confidentiality. Manufacturing, automation, and simulation increase efficiency and raise questions about human workers’ future and the need for new skills training. So, the overarching impact of these technologies on user experience is transformative, providing significant opportunities and formidable challenges. However, as industries adopt these technologies and companies offer services like digital twinning and Agentic AI, they must also consider their broader societal and ethical implications, ensuring that service innovation advances enhance individual and collective well-being. As these technologies advance, they bring about significant ethical challenges and the need for robust regulatory frameworks. Let’s think of the prospect of AI making autonomous decisions (as a digital twin) that impact other human lives. It requires an even more careful design process to avoid biases and ensure fairness. And we are not ready yet, I think.
As service design advances, it must balance technological innovation and human-centric values. Engaging stakeholders from diverse backgrounds in the design process will be crucial to understanding and addressing the broad impacts of new technologies. There is incredible promise here, but as with any other technology, there is also an insurmountable pull toward the dark side if used with the wrong intent. We must remain vigilant about these technologies’ social, ethical, and practical implications. By fostering a dialogue that includes technologists, ethicists, artists, and the broader public, we can ensure that tomorrow’s service innovations enrich the human experience.
Service innovation is fundamentally about people – those creating and using the service. Successful new services should fulfill basic human needs because we all desire happiness, convenience, and a sense of belonging. The objective can be as straightforward as delighting your customers. If your services aren’t meeting their needs, they become merely transactional. It is good to remind ourselves that innovation is not a one-time project but an ongoing process. Continually nurturing and trusting this process will result in gradual and significant improvements.
Image: Created with Stable Diffusion. Prompt: Watercolor, artistic, abstract representation of the future of service design with advanced technologies. Streams of glowing data flow between ethereal human silhouettes and abstract technological forms, symbolizing human-AI interaction. Incorporate bioluminescence and holographic effects for a futuristic feel
Augmented Memory It Is: Everyday Experience Futures
"We're an information economy. They teach you that in school. What they don't tell you is that it's impossible to move, to live, to operate at any level without leaving traces, bits, seemingly meaningless fragments of personal information. Fragments that can be retrieved, amplified..." ― William Gibson, Johnny Mnemonic
The quote above is from a 1981 short story by William Gibson titled 'Johnny Mnemonic.' Gibson also wrote the screenplay for the 1995 Movie starring Keanu Reeves, nearly five years before the cult-classic 'Matrix'. For anyone reading this post who has yet to see Johnny Mnemonic, consider this a five-star, thumbs-up recommendation. It's a prophetic film that is soon to celebrate its 30th birthday. The idea of individual digital extension has accompanied our pop culture and tech bubble for the whole of the last century and counting. And in retrospect, this movie might be more critical to our current reality than it initially seemed. Every day, we produce extensive digital footprints through activities like browsing the internet, interacting on social media, and using connected devices. Much of this data–or these digitized memory fragments–remains unstructured and connected, living on various clouds, devices, hard drives, flash drives, etc. On average, an individual in 2024 produces 147GB of data in one day. What? Let's assume that each gigabyte of data equals roughly 1000 books; 147 GB per day would translate to about 147,000 books. Per person. Damn.
Keanu Reeves in ‘Johnny Mnemonic’, 1995
At the core, Augmented Memory means nothing but anticipating needs and adapting to personal habits without direct input. A digital workspace could, for example, predict the resources you'll need for a project based on your past behavior patterns and current calendar events, arranging these tools before you even realize you need them. This level of anticipatory service could extend across all digital platforms, fundamentally changing how we interact with our technological environments. For instance, in the same way that Augmented Memory would help bring together various 'active' sources of individual content creation, the whole process could also revolutionize content consumption in a more privacy-driven manner. Streaming services could analyze your viewing history, current emotional state (possibly inferred through physiological data like heart rate or skin conductance), and even your schedule to suggest content that aligns with your taste and is suitable for your current context. This personalization could make entertainment more enjoyable and fit our moods and available time. But it could also help turn the tables, shifting the power to the consumer as we could opt for services where we trade in parts of our data for the service or even get paid to stay with one service brand instead of the other, in turn for keeping our data consumption values attuned to one specific operator. Sounds too farfetched? Again, think about the quote from Johnny Mnemonic at the start of this post, '(...)seemingly meaningless fragments of personal information. Fragments that can be retrieved, amplified...'
Digital Twins, Agentic AI, Embodied AI, and Augmented Memory. Apart from this overarching Human-Machine-Harmony (HMH) concept, I still need to develop the correct thesis to bring this all together. If we correctly integrate it into our everyday products, augmented Memory will offer a future where technology more closely aligns with individual user needs and preferences. Integrating Augmented Memory with IoT (Internet of Things) devices (the IoT phrase seems oddly outdated - Calm Computing Devices?) could lead to living environments that fully respond to our needs. Homes, cars, and offices could automatically adjust lighting and temperature and play music based on our preferences and current mood, detected through ongoing data analysis. It's all here already, just not evenly spaced across our daily lives at a scale.
How can we sum up these loose threads? I have been a fan of Golden Krishna's book "The Best Interface is No Interface" for many years. Along those lines, I wonder if we could also state that part of that theory is "the best interaction is no interaction" with technology for future interfaces. This philosophy doesn't suggest a future devoid of interaction but one where interactions with technology are so intuitively aligned with our needs and behaviors that they scarcely require conscious effort.
Life-Logging: Better Data for Better Digital Twins?
Following my attempts at creating a digital twin, I've been thinking about the concept of life-logging as a natural next step. Life-logging means continuously recording and documenting one's life. This might provide the rich, personal data to make individual digital twins more accurate and personalized. In many ways, we already engage in life-logging through the photos, texts, and other data we store on our devices. It doesn't seem too far-fetched to bring this all together in new clothes. I wrote about it before; the concept of a digital twin—an AI-powered replica that can think, learn, and interact like its human counterpart—fascinates me. My initial experiments with building a digital twin involved creating a GPT model using the OpenAI GPT interface. While this was insightful, it quickly became an obsession, leading me to step back and reassess my approach. I then turned to HeyGen, which allowed me to create a visual version of myself. However, for a digital twin to be truly effective, it needs a constant stream of data that accurately and comprehensively reflects the user's life. This is where life-logging might make sense. By systematically capturing our daily experiences, we can provide our digital twins with the contextual data they need to function more like us. As with anywhere in life, context setting is key to a clear understanding of any challenge.
Inspired by the work of Gordon Bell, who extensively documented his life, I decided to look closer into life-logging. Bell's efforts were influenced by Vannevar Bush's idea of the "memex," a theoretical machine envisioned in 1945 that would store and retrieve a person's books, records, and communications. This concept laid the groundwork for how technology can augment human Memory and experience. I still need to log my daily life to offer personal insight here. From the theoretical approach, the Life-logging practice requires awareness and intentionality that might feel intrusive. I found myself, at times, already more focused on recording the moment with my phone than actually experiencing it. However, to create a proper "signal out of the noise," I think there are some already prototyped ways of capturing daily context data. The more I think about it, the less intentionality becomes essential–meaning the more unfiltered the data capture, the better the result? Collectively, we already engage in some form of primarily unstructured life-logging. We take countless photos, write texts, and store various forms of data on our devices. However, this data is often fragmented and underutilized. But there is also meaning in structuring and contextualizing all of this collective data in a new way—collective memory. Let's think about a possible future where shared life-logs contribute to a collective intelligence, providing insights into cultural trends, public health, and societal changes. Individual "ghost twins" could carry individual memory decades and centuries beyond the biological lifetime of the original individual. From today's perspective, these ideas always bring back the need and desire for robust frameworks to manage consent, privacy, and data security on a massive scale. The challenge is to design systems that allow for the aggregation of life-logs in a way that respects individual privacy while enabling societal benefits. If done right, I am excited about the potential for personal growth and societal impact. And I am excited about the possibility of using context to create a better agentic AI. However, it will look and feel. Should my digital avatar look like me? Should he age like me? Should he be a he?
It brings back the philosophical aspects of how closely the resemblance between machine intelligence and human intelligence should be visualized, embodied, and, in essence, designed. As I said before, we need to think about guidelines and frameworks for Human-Machine Harmony (HMH).
Let’s close this post with Vannebar Bush, quoted in 1945:
Consider a future device for individual use, which is a sort of mechanized private file and library. It needs a name, and, to coin one at random, "memex" will do. A memex is a device in which an individual stores all his books, records, and communications, and which is mechanized so that it may be consulted with exceeding speed and flexibility. It is an enlarged intimate supplement to his memory.
Building My Digital Twin: Concept & Obsession
The idea of creating a digital twin has fascinated me for a while. And I wrote about it in the past couple of weeks, so I should also start sharing a bit about my journey over the past year. I jumped into this concept on mostly free Sunday nights every now and then, experimenting and learning along the way.
I started with a simple question: What if I could create a digital version of myself that could interact like me, specifically when designing new products and services? Initially, I experimented with building my own GPT model using the OpenAI GPT interface. The goal was to create a version of myself that could mimic my thought processes, respond to queries as I would, and offer insights based on my experiences and knowledge. However, this endeavor quickly became an obsession. I found myself constantly tweaking and refining the model, driven to create a "better" version of myself. It was an exhausting pursuit, leading me to step back and reassess my approach. It also left me feeling unfulfilled, as I only interacted via text input; it felt increasingly like the wrong approach to make this whole endeavor about "upload PDFs and text-to-copy." Realizing the need for a more holistic representation, I turned to HeyGen, a platform that allowed me to create a visual version of myself. With HeyGen, I could generate a digital avatar that sounded like me and looked like me, bringing the concept of a digital twin to life in a more tangible way.
HeyGen Experiment, January 2024
The idea was (and still is) to eventually merge the capabilities of the GPT model with the visual representation from HeyGen. This combined digital twin would be able to interact and visually represent me, offering a more comprehensive and integrated experience. But when do I reach the point of sending this digital twin to a work meeting? When and how can I reach a point where this "ghost" of myself can at least mimic some form of mirroring, being empathetic, adaptive, and connected to me in my human experience. I am leaving this project a bit alone right now, as I think that the idea of creating a digital twin is not only about replicating functions but somehow finding a way to have it act with empathy and, if it mimics myself, a bit more chaotic trains of thought. Creating a digital twin raises several psychological aspects worth considering. Pursuing a "better" version of myself is still intriguing but equally unsettling. So far, the project has forced me to confront my own insecurities and aspirations, questioning what it means to be honest with myself. As I wrote before, the process can become quite an obsession, constantly striving for some unreal perfectionism that might never be fully attainable. As it is with any perfectionistic approach. But excellence can be a great goalpost. The question is, when do I reach excellence for the digital twin? Shouldn't this be a daily, ongoing project? Feeding my daily data into a never-ending stream of cloud-data? Creating a digital twin also raises questions about my own identity and self-perception. How does seeing a digital version of oneself affect one's self-image? Does it enhance our understanding of ourselves, or does it create an unrealistic standard to live up to? Moreover, there's the potential for dependency. Relying too heavily on a digital twin for decision-making and emotional support might lead to a diminished capacity for independent thought and self-reliance.
The broader implications of personal AI and digital twins extend far beyond individual use cases. Let’s imagine a world where everyone has a digital companion who knows them intimately, understands their needs, and helps them navigate daily life. But does this twin need to be as 'human' as we are in our most principal understanding? I haven't touched on privacy yet, which is obviously a major concern. Digital twins would require vast amounts of personal data to function effectively. Ensuring that this data is secure and used responsibly is paramount. There's also the question of consent—how do we manage the data of individuals who may not fully understand or agree to the extent of its use? Distinguishing between the actions and decisions of the human and the digital counterpart could become increasingly blurred. This raises questions about accountability and control. Who is responsible when a digital twin makes a decision that affects the real world? Access to advanced personal AI and digital twins could also become a privilege of the 'informed' and wealthy, as with many technologies, exacerbating existing inequalities.
To be continued...
Blending In: Part II
Building on the last post, I want to focus on concrete examples and fields where this paradigm shift could significantly impact how we design for these product and service segments. The examples below illustrate how HMH can transform various aspects of our lives from a high-level brainstorming perspective, creating a more integrated, empathetic, and personalized interaction with software and hardware.
AI and machine learning are at the forefront of the HMH train of thought. These technologies enable machines to learn from experience, improve performance, and become more attuned to human needs. If we want that. Well, I do. Beyond voice commands and conversational interaction, agentic AI assistants are rapidly evolving to understand context and emotions. Eventually, they anticipate needs, offer personalized recommendations, and provide emotional support, creating a more seamless and empathetic user experience. But do we want our agent to 'sound' human, to 'behave' human, and therefore, 'feel' human? This question has been asked through decades of science-fiction-based possible futures, from HAL in 2001 to the worlds of Isaac Asimov to the Movie 'Her', where a lonely man named Theodore develops an unexpected relationship with an intelligent operating system named Samantha. Where do we want to draw the line? Should we? And isn't this also a conversation about consumer needs vs industry needs?
For example, AI-driven predictive maintenance systems might monitor equipment health in real-time, predicting failures before they occur. This is happening already, and the notion of 'digital twinning' has become a type of description encompassing everything from a digital clone of construction blueprints to data copies of one's self, creating avatars that look like, speak like, and interact like the user's individual character. There is a lot of romantic value here. Can a digital clone of oneself take over the 'grunt' work, distributing agency across tasks while the human part of the whole can indulge in the more 'fun' parts of life? Another of these thoughts that isn't new, but newness is that we can easily imagine a (very) near future where we live our lives through various digital, autonomous extensions of ourselves. But this should happen harmoniously with our needs, goals, emotions, and values. The logical extrapolation of combining our digital self with a robotic body is the next best thing we can imagine to biological cloning at this point. Combining a digital version of oneself with robotics is certainly a field where HMH should be seen as a vehicle for making significant strides. Next-gen robots must be designed to be collaborative, working (and living) alongside humans in various environments. However, they also might need to be designed to collaborate and coexist across life, work, private life, and death. The topic of robotics and HMH is worthy of discussion and more in-depth reflection. Still, why do we design most of the humanoid robots currently as they are straight out of the territory of dystopian aggressive machine overlords?
Moving forward, our challenge is to ensure that technology enhances human interaction rather than overshadowing it. Whatever shape it may take. We must strive to create machines that support and enrich our lives, blending seamlessly into our existence–in Human-Machine Harmony.
Blending In: Interface Futures and Human-Machine Harmony
Human-computer interaction (HCI) has described our relationship with technology for decades. It has focused on creating efficient, user-friendly, and functional interfaces. The primary goal has been optimizing how we use computers and devices to perform tasks, emphasizing usability and accessibility. However, as technology becomes more integrated into every aspect of our lives, the term HCI seems limiting when discussing the philosophical aspects of interfacing with technology in new, more 'human' ways. There is room for conversation here.
In the early days, HCI revolved around command-line interfaces, where users needed to learn specific commands to interact with computers. The advent of graphical user interfaces (GUIs) marked a significant milestone, making technology more accessible to the masses. Touchscreens, voice recognition, and gesture controls further revolutionized HCI, each step bringing us closer to a more intuitive and seamless interaction. Yet, despite these advancements, HCI remains fundamentally task-oriented. It treats technology at the core as a tool to accomplish specific functions, often overlooking the emotional and contextual aspects of human interaction–the notion of context is at the top of the pyramid when imagining possible futures of technological interfaces. As I mentioned above, there is room for conversation here, and we should center our discourse on the concept of Human-Machine Harmony (HMH?). The term Human-Machine Harmony (HMH) signifies a paradigm shift in context. It moves beyond the utilitarian focus of HCI to embrace a more holistic and integrated approach to our (designerly) relationship with technology. HMH is about creating a symbiotic relationship where technology fundamentally enhances our well-being through its use, supports our emotional needs, and adapts to our lifestyles more organic and harmoniously. Individually. Personally. This term, Human-Machine Harmony, emphasizes the seamless integration of technology into our daily lives. Instead of merely responding to commands, machines become more attuned to our behaviors, preferences, and emotions. They learn from our interactions, adapting to our needs in real-time. For instance, smart home systems that adjust lighting, temperature, and ambiance based on our moods rather than solely on tracked routines exemplify what I mean by 'harmony'.
A critical aspect of HMH is emotional intelligence. Machines are becoming equipped to recognize and respond to human emotions. This is achieved through advancements in affective computing, which enables devices to interpret facial expressions, tone of voice, and other emotional cues. It's not too much to ask these days to imagine a personal agentic AI that schedules your appointments and offers empathetic responses and support when you're feeling stressed or overwhelmed. Proactively and reactively. Based on emotional and contextual awareness. What I am getting at is that HMH advocates for technology that is highly personalized and customizable. It recognizes that each individual has unique needs and preferences and strives to create tailored experiences and interfaces. Wearable health monitors that provide personalized wellness recommendations and adaptive learning platforms that customize educational content based on a student's learning style are prime examples of this trend. HMH also encompasses ethical considerations. It calls for technology that respects privacy, security, and sustainability. In an age of data breaches and environmental concerns, HMH advocates for responsible innovation. This includes creating energy-efficient devices made from sustainable materials and designed with user privacy as a core principle. I am thinking about an evolutionary step beyond making technology more efficient or user-friendly: creating a new relationship between humans and machines—a relationship that is symbiotic, empathetic, and deeply integrated into the fabric of our daily lives. Therefore, by thinking about future interfaces using the term Human-Machine Harmony, we can set ourselves up for success with a blue ocean design strategy. This new strategy should bring 'poetry' back into our existence, inviting us to rethink our design approach to interaction and supporting and enhancing our human experience. In other words, gathering and understanding context.
Twenty Twenty Three: I, for One, Welcome Our New Design Overlords
Boy, what a year. And as I say bye bye to 2023, it's evident that we're on the cusp of a transformative era in technology and design. Actually, we are in it. This year wasn't only about the proliferation of Machine Learning and Neural Networks arriving in the mainstream(ish). We started to see concrete, fundamental changes in our interaction with technology. We're witnessing a shift towards new interfaces and interaction prototypes that question the extent of technology's integration into our lives. The aspiration for calm technology that blends seamlessly into our existence contrasts starkly with the allure of status-symbolic gadgets that lock us into a never-ending doom scroll, blurring the lines between the physical and digital worlds. As designers, we are tasked with balancing functionality and symbolism, utility, and the human need for connection and distinction. Plus, the artifact should sell. At scale. Ironically, in recent years, as designers, we prided ourselves on the belief that AI would target creative endeavors last. Well, hello, it came for us first. This unexpected twist has redefined our role and pushed us to explore new spaces of creativity, challenging us to blend our innate artistic abilities with the computational power of AI. Of course, this will only continue and accelerate, but this year has been a signifier of that evolution.
I debated with myself writing about the first birthday of ChatGPT and how it changed my day-to-day, enhanced my thinking, and became my ally for clarity and productivity. And yes, I could name GPT my standout tool of 2023, but in all honesty, I don’t think the last twelve months were just about one standout piece of tech; it was about the promise of the greater ecosystem(s) and how our devices and services will be interconnected in a new way. This shift from designing standalone products to interconnected experiences considers individual functionality and collective harmony. So, is it just about the device? Well, it was and will be even more so about the ecosystem of devices and services. Whoever builds the most seamless, most delightful interaction between physical and digital intelligence will rule the AI ecosystem. And this race is wide open; we have more intelligent companions on the horizon than we could imagine at this point. Who will be the surprise entry? What strikes me most when conceptualizing these companion products is that human connection and meaningful design should remain at the heart of technology. The challenge is embedding technology so seamlessly into our lives that it supports rather than overshadows human interaction. And it doesn't seem like we collectively achieved this goal in recent years. 2023 might be a year we look back to and think about the beginnings when we started rethinking a roadmap for 'Human-Device-Harmony'. Moving forward, any design process involving technical intelligence should carefully define our interactions, evolving from 'basic' human-computer interaction to a nuanced dialogue involving various devices, moods, and emotions and adapting to daily changes in our lives as much as we do in human relationships.
For 2024, I want to put more focused intentionality towards the projects I am working on. In general, it's about shifting from attention-demanding gadgets to an ecosystem that enriches our lives quietly. The future of design is about adapting to AI and integrating it in ways that enhance our creativity and harmonize our collective connection, ensuring that as technology evolves, it does so in tandem with our human spirit.
A Millennial's 'Ctrl-Alt-Del' Through Tech Time
It feels weird to say it like this, but growing up in Germany during the 90s and early 2000s, my childhood was defined by a 'simple' technological landscape that now seems quaint. As a millennial born in the late 80s, I witnessed firsthand the evolution from rotary phones and a mere trio of TV channels to the pervasive influence of digital technology, AI, and human-computer interaction that defines our current decade.
But back in my childhood, though advanced for its time, technology demanded a certain patience and deliberateness now rarely seen. Rotary phones and limited TV options offered a different kind of connection and creativity, distinct from today's digital immersion. As I grew, so too did the technological landscape. The advent of the internet, mobile phones, and social media marked the arrival of new gadgets and signified profound shifts in how we live, communicate, and perceive the world. And specifically, how I began to perceive the physical world around me. I started to see things and objects of daily life for how they felt and looked and how a day-to-day job could influence this. Being a designer today myself, looking back at this period, I see that these years represented a subconscious transformation.
I have had a similar overwhelming feeling of transformation in recent years. Specifically, this year has seen so many changes, possibilities, and promises that it is hard not to get excited about working in a creative field. Feeling excited and exhausted (exhaustercited?) simultaneously means I feel strong emotions towards certain products I use daily. Why are things the way they are? And how can we make them better? Looking back on my journey from the era of Photoshop 4 (my first handshake with Adobe software) to the age of Generative AI, I am slowly rediscovering a blend of nostalgia for the simplicity of the past and excitement for the future's potential. And the happiness in reflecting on such things and acknowledging my need to adapt, understand, and engage creatively with the ever-changing techno-landscape surrounding us.
My First Object Love
Nintendo Game Boy, color ‘clear’, 1995
The Designer's Dilemma: Embracing AI's Innovations as a Multidisciplinary Generalist
I've often found myself at a crossroads in recent years, so much so that I went back to university to try to gain perspective at this particular vantage point–one that has been both a source of internal conflict and (still up to today) a constant struggle, but also of profound insight: The struggle of being multi-interested as a transdisciplinary designer, in a design-world that demands specialists. For the longest time, my career felt like a twisted chess game where I was caught between the desire to dig deeper into a single discipline and the pull of diverse interests. This internal tug-of-war comes and goes and has become better over the years.
In making sense of it all, I've often prioritized project-based learning, where each new client project becomes a chance to integrate a new tool or framework, not only elevating client delivery but also challenging myself to learn something new and add to my tool belt. Yet, the dilemma persists. With every new project or potential career decision, I cannot be alone in facing this question: should we narrow our focus or embrace the breadth of our curiosity in a field increasingly intertwined with technology? In the end, I repeatedly go down similar paths. My journey, including many moments of self-doubt, gradually led to a realization that being a generalist in the AI era might not be a drawback but a potential superpower, the more the specialist skills get automated. Indeed, a long-term view and this path hasn't been without its challenges. In the past few years, I have repeatedly had exciting conversations with some big companies, but they often ended with the phrase, "You are not specialized enough for our team." Although this has been hard to overcome from a mindset perspective, I still value where I am in my career as I embrace this continuous learning. My forays into business thinking and innovation, combined with my deep passion and training for design and aesthetics, have allowed me to approach AI from a somewhat naive but unique perspective. I've learned that understanding the business impact of design decisions is as crucial as the creative process itself. And in a world enamored with the promises of AI, my diverse background has been instrumental in maintaining a focus on the human aspect of technology.
From the perspective of more preferable futures, I love the idea of true "Renaissance minds in a digital world," drawing from a palette of diverse skills and attitudes. In this era, the value of a generalist in design, particularly in AI, cannot be overstated. It's about blending empathy with technology, intuition with data, and creativity with practicality. To my fellow designers and creative thinkers: embrace the complexity of your interests and use those multifaceted perspectives to shape a future where AI is as much about human insight as it is about technological advancement. Your diverse skills will be an integral part of making innovation work for more people around the globe.
Embodied AI: Designing the Future of Human Connection
As a professional deeply immersed in design and innovation, my journey from the small town of Hechingen, Germany, to the innovative landscapes of California has been marked by transformative encounters with technology. And today, the anticipation of AI companions is both invigorating and sobering to me.
As a 7-year-old, I remember the allure of our 486 computer, where the internet opened up the world beyond my small town. My older brother and I chatted with someone from South Africa – a moment that, unbeknownst to me then, foreshadowed a career intertwined with technology, imagination, and connection. Decades later, the evolution of technology is more exhilarating than ever .The promises of the internet and social media, once praised as tools of unbridled connection, have unveiled complexities we're still navigating. With the new era of AI agents, designed to be our everyday companions – the dual forces of optimism and caution are strongly at play. I guess the idea that AI can facilitate genuine human connection is not just a theoretical concept but a design challenge at large. As devices become more intelligent, the ethos of design must pivot from functionality to empathy, from utility to humanity. These shifting paradigms of connectivity, privacy, and interaction are pivotal. How do we craft hardware that is not just smart but also kind, considerate, and ethical? I am compelled by the possibilities of rethinking CMF (Color, Material, Finish). Because we stand on the cusp of creating countless AI companions as ubiquitous as smartphones are today – our chosen materials and processes should echo our ethical and environmental commitments.
Each new technology, from my first mobile phone to the advent of social media platforms, has created a complex combination of connection and isolation, possibility and challenge, from the happiness of staying connected to my friends and family back in Europe to the nightly doom-scrolling because I cannot fall asleep. As a German immigrant and a designer in the Bay Area, I anchor myself on a clear principle: design is not just about creating products but about shaping experiences, ethics, and connections. We can see its potential and challenges with the rise of AI companion wearables. As designers, technologists, and creators, we must aim for a future where technology enhances our collective human experience.
In the words of Spock, "Logic is the beginning of wisdom, not the end."
Define, Decide, Execute (DDE) - My Formula for Getting Sh*t Done and Fighting Procrastination
As a designer, I often find myself in the labyrinth of creativity, where ideas are abundant, but bringing them to life can be daunting. Each concept, rich with potential, demands to be nurtured, refined, and ultimately, realized. The good old paradox of having ideas differs significantly from acting on ideas. Also, that journey from idea to tangible world of existence is always dynamic. It's forward and backward, a boxing match with my formidable partner called Procrastination. My German upbringing meant that I often heard phrases about productivity. Phrases like "Was du heute kannst besorgen, das verschiebe nicht auf morgen" (Never put off till tomorrow what can be done today) Or my personal favorite, "Schlage deinen Inneren Schweinehund" (Defeat your inner pig dog). This "pig dog" is a uniquely German expression referring to the inner voice that advocates laziness, the sneaky whisper that lures one into the comforting embrace of procrastination, away from the disciplined path of action – and boy, the force is strong with me on this one. Yet, in the creative domain where chaos and order coexist, I also love to embrace procrastination. I call it "processination", as it is a helpful tool for the creative process in itself. But at some point, you got to snap out of it. Entrance my very own formula: DDE. It is not a groundbreaking scientific theory; it was created out of pure necessity, of the emergency of years of personal procrastination. DDE is a process designed for one thing only – getting your sh*t done. And here is what I mean by that.
Define
In the first phase, 'Define', the task is broken down into its core elements. Every professional knows that a well-defined problem is half-solved, particularly in design. In this first step, the objectives are articulated clearly, and the expected outcomes are delineated. It's akin to sketching the initial lines on a blank piece of paper, the foundational to-do list. Every 'what', 'why', and 'how' is explored. What is the task explicitly aiming to achieve? Why is it essential, and how will it be accomplished?
Decide
Decision is the bridge between intention and action. Here, choices are made, and priorities are set. Every decision is a commitment, primarily to just "doing it." But this is where the clarity achieved in the 'Define' phase fortifies the resolve. For a designer, this phase could mean choosing the theme, the colors, and the materials – a decision to focus on a specific path. Design at its core is decision making.
Execute
Execution, the final frontier, is where ideas meet reality, where concepts are morphed into creations. At this step, action is the mantra. Every step and every effort are directed towards realizing the defined and decided task. In short, executing means my "to do" turns into "done," which is my favorite.
A Universal Tool
Over the years, I've found DDE to be a professional tool and a life philosophy. Whether it's organizing a wardrobe, cleaning the kitchen, or sorting belongings into 'sparks joy' and 'does not spark joy' categories, DDE has been my guide. The formula is also part of my leadership compass now. It has been instrumental in prioritizing tasks swiftly and delegating them to the best-suited individuals. Every definition, decision, and execution are amplified in a team setting, each member's contribution echoing the collective commitment to the defined objectives.
DDE is a formula that's versatile, adaptive, and profoundly effective.
I got this text written using it :)
Dude, Where is My Device? Embodied AI - Why the Artificial Needs Embodied Homes
The trajectory of technological evolution has always fascinated me. And even more so, our pop culture's science-fiction shaped many of my career and personal interests. As a kid of the 1990s, the rate at which the physical form of technology has drastically changed is potentially one of my number one interests. I only recently started collecting some of those artifacts of my youth, like the Sega Dreamcast, the original iMac, and a Tamagotchi. But as we stand on the precipice of another technological revolution - the advent of artificial intelligence (AI) in our everyday lives - a fundamental question emerges: Where will we house this intelligence? Actually, do we have to?
The digital space, as expansive and limitless as it seems, is intangible. We all share this inherent need to touch, feel, and interact with the physical world. This is where the concept of embodied AI comes into play. The present state of AI is impressive and excitingly overwhelming, with its capabilities manifesting in various digital platforms and software. But AI needs a physical form, a home, to be genuinely compelling, relatable, and intuitive. This is could be imperative in designing interfaces that feel natural, intuitive, and human-centric. As a designer, my approach to this challenge is twofold. Firstly, it's about understanding the human psyche. We relate better to tangible entities. There's a psychological comfort in knowing that the AI we interact with has a defined space, a boundary. It's similar to the comfort of talking to someone face-to-face versus a video call (XR and Spatial Computing might want a word here). But secondly, and perhaps more critically, it's about the design ethos. As we move into embodied AI, the materials, aesthetics, and functionality we choose will play a pivotal role. We need to think about the right way of crafting an experience that resonates with users. In this context, the potential of reimagining Color, Material, and Finish (CMF) is immenseas we are creating products and experiences that echo our ethical and environmental commitments. Suppose the next big wave in technology is AI companions as ubiquitous as smartphones. Our materials and processes must be sustainable, ethical, and resonate with our values (Short-circuited-thought here though, the phone seems still like the best possible “home” for AI right now. Why? Because if the existing ecosystems. Topic for another day.)
It's essential to remember that technology is a tool in its purest form. And like all tools, its impact is shaped by the hands that wield it. We can argue that this intelligence is the last tool ever needed for humanity. But in any case, the "AIoT" companions are coming. As designers, innovators, and consumers, we must ensure that this new era is marked by empathy, connection, and a deep respect for our shared humanity.
Building the XR Milkyway - Thoughts on Augmented Experience and Spatial Computing
Let me preface this by saying that these are unfiltered thoughts sparked by the introduction of the Apple Vision Pro this week. Having worked a bit in XR projects while at UC Berkeley, the potentialities and implications of Extended Reality have occupied my mind for some time. Augmented Reality will/does/might represent a quantum leap in our (spatial, environmental) interaction with technology. And blending our tangible reality with digital enhancements will/does/might redefine every day-to-day experience, from learning, working, dating, entertainment, and whatever lies beyond. Nothing is new here; all the "digital universe" visions have been marketed toward us for years.
BUT
Societal Impact
How transformational will it be once the internet becomes 3D? Once the internet will mean just that – Reality. Beyond the tech, we're looking at potential shifts in social constructs. How will our behavior change in public spaces if our interactions involve unseen digital constructs? There's also the concept of "digital gentrification." As specific augmented spaces gain popularity, could they become digital real estate hotspots, pushing out those who were there first? Will it cost money to occupy digital overlays? And with these developments, will we see a new digital divide, an "augmented divide"?
Ethical Considerations
The ethical dimensions of AR are vast and multifaceted. Data privacy is the tip of the iceberg. The more significant questions revolve around mental health, identity, and reality perception. With photo-realistic AR constantly feeding us digital information, how will our brains differentiate between tangible reality and augmented overlays? And if AI assistants curate these overlays in real-time, are we at risk of falling into augmented echo chambers, where we only perceive a reality tailored to our biases?
Designing for the XR Era
From my vantage point as a designer, AR is a mixture of expanding opportunities and a multi-layered rubric of responsibilities. How do we ensure our desings are engaging, ethically sound, and psychologically safe? The design principles of yesterday may need to be revised. We must think about the long-term effects of our creations. How do they impact mental health? How do they reshape societal interactions? And how do they fit into the bigger picture of our shared reality? A social media doom-scroll timeline is still bound to a screen; what if reality is the doom-scroll experience?
Book Recommendation: Inspired by Method - Creative Tools for the Design Process
Navigating the world of design literature can sometimes feel like an endless search for genuine insight. "Inspired by Method," by my former professor and bachelor thesis advisor, Alexandra Martini, stands out as a practical and enlightening guide. This book is a systematic approach to understanding and harnessing inspiration. The core 5D method, encompassing dimensions like the ‘Formal-Aesthetic’ provides a structured framework for designers at all stages, simplifying the complex process of turning ideas into reality.
I appreciate this book for its clarity and practicality. Whether you're just starting in design or looking to refine your approach, "Inspired by Method" offers valuable perspectives.
Author Alexandra Martini
Number of pages 240 pages,
Measures 22.4 x 18.7 cm
Cover Softcover
ISBN 978 90 6369 573 6
Designing the Near Future of Belonging
A recent address by Brian Chesky, CEO of Airbnb, gave me pause to reflect on the human side of our digital (design) evolution. Chesky's revelations about the rising tide of loneliness in our hyper-connected era struck a chord with me.
We live in an age where communication is at our fingertips every second. Yet, genuine connection seems to be slipping through them. Even 1:1 eye contact seems complicated, coming back from the pandemic these days. The irony of all this isn't lost on me. As a designer, my mission has always been to enhance human experiences. So, as designers and creators, have we been inadvertently designing for isolation but straight up thought we are doing this for belonging? Yes. Yes, we did. However, design fosters connections, enhances experiences, and enriches human lives. If our technological advancements drive wedges between these fundamental human needs, it's time for introspection. For example, when conceptualizing the future of devices and services, the challenge isn't only about the "what" and the "how" but more critically about the "why." Why do we design? For whom do we design? Who is left out of the equation? It's the 101 of Human-Centered Design and Design Thinking, and it shows how it has lost the foundational power it once seemed to have 20+ years ago.
Most importantly, we must ask: what kind of future do we envision? It's not enough to design smart; we also must create with heart. Devices and platforms must be more than tools; they should be bridges to genuine human connections. We're in the midst of creating the next generation of consumer devices, and the choices we make now will shape the experiences of tomorrow. It's an incredible responsibility and an exciting opportunity. As designers, innovators, and visionaries, let's keep sight of the bigger picture. Let's design for preferable futures of belonging. Let's envision a future where technology doesn't just connect devices but hearts and souls—a future where devices ar empathetic, intuitive, and genuinely in support of the human experience.