On September 5th, 2023, Prifina hosted a panel discusion "Revolutionizing Risk: How Sensors, Ambient Data and AI Are Reshaping the Insurance."
Among the panelists were:
The panel discussion explored the current trends in the world where sensor-generated data and AI-powered applications permeate every aspect of our lives. Could such data be used to personalize insurance services and unlock new solutions to help us reconsider how we approach risk?
The event on the implications of sensors and data on insurance gathered much attention from various representatives of different industries. In the following post, we review some of the discussion topics and provide a list of innovative solutions for insurance services.
1. Paramount role of data for insurance
The starting premise of this event was the realization of the huge amount of data generated by users themselves (e.g., data from sensor-equipped fitness trackers) and ambient data from sensors in office buildings and public spaces. Yet, appr. 80% of such data lies idle, unutilized.
Markus Lampinen from Prifina opened the panel discussion by explaining the paradigm shift that is happening in the personal data market - a new data framework the value from data is captured on the users' side (not locked away in centralized silos):
“In the future, we want to see individuals getting the value from data captured across different data sources. We want to empower individuals with different types of applications that you own and that you run on top of your own combined data. Very simple things that help you sleep better or buy the right shoes, etc. But we already have those. The big picture? In 5 years, as an individual, I’d like to be able to predict what movie I’d like to see, and what better choices I should make.”
Ashley Greenwald from Huntsman AG explained the concept of "ambient data" - data from sensors embedded in spaces around us (temperature, noise, occupancy, vibrations, exposure light, humidity) - all of this data could be used to improve the efficiency of space management and human experiences. Such data from sensors in buildings is particularly interesting for building owners and renters.
2. Tight Regulations Limiting the Use of Personal Data
Signe from Datasolvr and Markus discussed the fact that data privacy regulations and well as risk-awareness of service providers limit the use of individual-level data for personalization. Companies don't want to face data discrimination lawsuits and opt not to use data in their services at all. While the individual-level data could be particularly interesting for creating different pricing models, data privacy regulations are tight both in Europe and in the US.
3. Building Predictive Health Care System with Data
Participants of the panel discussed the ways how user-generated and ambient data could be used to enable predictive health and wellness services. This would be a major juxtaposition to the current "reactive" medicine which is extremely costly.
"In reality, when you go the hospital, you realize that many health-related data could have been avoided if various data sets were caught and utilized earlier." - Markus Lampinen
Another truth of the fact is that we are running short of doctors, physicians and experts: there are appr. 10 million doctors in the world for a population of 8 billion people. And we will never have enough doctors. At the same time, people are increasingly eager to extend their well-being and the quality of life.
That's where sensor-generated data and data-powered AI applications become increasingly appealing:
"Harnessing data from devices like the Apple Watch could help increase individual awareness of stress and potentially prevent harmful effects using predictive AI. That's one of the biggest opportunity for insurance service providers who ultimately want to mitigate risks." - Sille Amid Holm (Datasolvr)
Individual-level use cases. The panelists explored several examples of utilizing user-generated data from wearables in insurance. For instance, renewing term life insurance is complex, with current pricing influenced largely by an individual's health condition, such as whether they smoke. For instance, smokers typically pay at least twice the premium compared to non-smokers of the same health. However, the potential use of comprehensive data collected over years could reshape this model. If data shows an individual quit smoking and improved their health over a decade, they might deserve a reduced premium, even if they're older. This concept suggests a more dynamic and responsive insurance model, though the decision rests with insurance companies.
Group-level use-cases. Group-level data from wearables as well as ambient data could be a powerful tool to innovate in the insurance services market. Imagine, if an employer could prove certain habits of the employees (e.g., employees chose to walk up the stairs and sleep on average 6.5 hours a night) to the insurance company, this could offer additional insights and price adjustments for various insurance plans.
4. Creating New Consumer Experiences with Data
The panelists discussed various opportunities and challenges when it comes to building new consumer experiences with data. Many consumers need super simple interfaces and huge incentives; there is also a huge learning curve ("data literacy"). A huge part of this relates to the experts working in the User experience/user interface domain: How do you show the value from data to the individual? How to help people to better understand what to look for in their data?
There're many interesting insights about how people have adopted wearable devices: e.g., we see how much more aware about their biometric data people have become.
However, it is quite difficult to build data-driven experiences in the insurance services market. The customer onboarding and customer journey has to be very different in insurance. Since more people interested in insurance services tend to be senior, the experience must be simple and understand. Here are some examples of gimmicks that could be used:
Accelerating innovation. The flip side argument of that is whether big players in the insurance market would like to innovate, or whether they'd rather prefer the status quo. Markus Lampinen from Prifina suggested that such a hold-out strategy by incumbents may not last too long especially when more innovative newcomers in the insurance market come up with more personalized and compelling products.
5. Personal AI agents powering a new line of insurance services
The panelists shared their common understanding that in the near future each of us will have our personal AI assistant experts (doctors, coaches, nutritionists, shopping agents). This world becomes possible as individuals get more ownership and control over their own data.
More generally, panelists agreed that user-generated and ambient opens new opportunities for virtually every stakeholder in the market, including innovation opportunities for insurance services that will become very personalized and specific.
Future vision. Imagine if your personal AI insurance agent negotiates on your behalf with AI-powered agents of insurance providers to find the best deal for your specific condition. The panelists even explored possible implications if an individual's own AI agent was aware of individual's DNA data and historical medical records and how this degree of data accuracy and automatization could transform the whole understanding of risk.
We want to thank all the panelists and guests who attended the event and stayed after the panel to network and continue the conversation about the emerging personal data ecosystem.
“Whoever wins the personal agent, that’s [going to be] the big thing. Because you will never go to a search site again, you’ll never go to Amazon again” - Bill Gates
By dr. Paul Jurcys
In the very near future, each of us will our personal AI assistants for every aspect of our lives. Each of us will have our personal AI doctor, personal AI coach, personal AI nutritionist, or digital assistant that will help us organize our calendars, schedule events, and purchase items on our behalf.
Such AI-powered assistants will augment our abilities and help get rid of time-consuming tasks, and focus on things that matter most.
Buzz In the Market
In the past few months, there has been quite a bit of excitement about the possibility of building truly personal AI:
A massive investment in InflectionAI could be seen as an attempt to stave off any potential competition and secure dominance in this rapidly emerging domain.
Shortage of Experts
Today, we are unfortunately facing a remarkable shortage of experts. With over 8 billion people on Earth, there are a mere 10 million doctors. Teachers struggle to spend enough time on direct interactions with every student in the class.
On a personal level, we often lack someone equally knowledgeable or passionate about our favorite topics. In times of grief, suffering, and emotional pain, the desire for a close companion to provide advice and understanding becomes ever more acute.
This is where the transformative power of AI comes in. In the near future, countless individuals, potentially everyone, will be able to augment their personal capabilities with our own personal AI assistants.
The trajectory toward universal access to intelligence is clearly mapped out: we can expect that any person with access to the internet and a hand-held device will have access to the same expert advice from a doctor, an educator, or any other specialist, all through their personal AI.
2 Ways to Build Personal AI
As technology continues to leap forward at ever-increasing speed, personal AI assistants are evolving to become more sophisticated and versatile.
There are two paths of bringing AI superpowers to humans:
A top-down approach: after the release of ChatGPT and other generative AI tools, we are witnessing an influx of various personal AI assistants that are supposed to hello us find information, summarize text, or generate images.
The top-down approach is rooted in creating software applications - personal AI assistants - that are marketed as tools to help us solve various daily tasks and assignments or offer us a companion, a buddy that is available 24/7. Think of InflectionAI’s Pi, Midjourney, Dalle, and countless others.
However, most of our essential tasks are rooted in the physical world: we need to eat, sleep, and and go to the bathroom. As cheap sensors are being integrated in our wearable devices and environments around us, individuals have tools and ability to track personal biological clock - we start living quantified lives. If you are a runner, you probably have a fitness tracker to measure your running distance and heart rate, as well as recovery rate. Also, our cars track hundreds of data points (e.g., acceleration, braking, engine performance, and outside factors).
Scientists around the world are building assistive robots to help us to recover from injuries or learn important skills.
These sensor-derived data sets also lead to the development of AI-powered applications that help optimize different aspects of our lives. This sensor-data-AI path resembles a bottom-up approach to building personal AI.
Data Eats the World, But How to Access Data?
AI assistants such as ChatGPT, or PI, are amazing in answering our general questions and performing general tasks. However, if you ask anything personal, something related to yourself, they stumble. Let’s see what responses we get to the question “How did I sleep last night?”:
How come!? Isn’t it odd that if you wear Apple watches that track our activity, sleep and process various biometric data, Siri - an AI assistant built by Apple for Apple’s products - is not able to answer such a simple question?!
Eventually, every company building personal AI will face the challenge of connecting the personal AI to the user’s own data.
To build a truly personal AI, we need not only general knowledge from publicly available sources and research repositories, we also need to bring this general, publicly available knowledge and correlate it with the specific data of each individual. In other words, to build a truly personal AI, Ai assistant must be able to access to the user’s personal data. Otherwise, the AI assistant will be a generalist, not a personal:
This is where Prifina’s human-centric approach to data comes into play: with Prifina’s user-held data model, it is possible to bring those personal AI assistants to each individual and run those personal AI assistants “on top of” each user’s own data, privately.
In Prifina’s personal data ecosystem, each individual user connects their data from personal data sources to their own data “vault”, where data is collected and unified. AI-powered apps and assistants run in each individual users’ data environment. Each individual user’s data is private by default.
A human-centric approach to data opens vast opportunities for the use of personal data: not only personal AI assistants can answer the question about last night’s sleep, but ML and LLMs can offer new possibilities for personalization and automation of tasks and generate new value for individuals.
So how many personal AI assistants can there be? And how many AI assistants can one person handle?
As humans, we have limited time and a limited attention span. Our guess is that each of us will be really interacting with 5, 7 or 10 digital agents (similar to a manager at a corporation who has 7-10 directly responding employees).
The image below illustrates the universe of digital assistants in the human-centric environment:
These digital agents will also vary in their expertise, capabilities, and proximity to the individual human being. It is likely, that people will have their own AI doctors, AI coaches, and AI-powered shopping assistants who will help to achieve specialized tasks.
Some of them will operate in the “inner orbit” - on top of the user’s own data, privately, while other AI assistants will be generalists, and will not have access to user’s own data.
In this multi-agent environment, one possible scenario is that each individual will have one primary and preferred assistant - we can call it “my personal AI.” But how will those digital agents and assistants interact with one another? What technological infrastructure is needed to make them talk to one another?
Assume you feel unwell and suffer from an upset stomach, which personal AI assistant do you go first? You might go to your “own private AI” and ask “Why do I feel pain in my stomach”? Your own personal AI may refer you to your personal AI doctor.
In this kind of scenario, it will be important to make sure that the initial inquiry made by you to your own personal AI is automatically transmitted to other agents. This will ensure that your AI doctor will already know your concern and will be able to continue the conversation.
Such communication between AI-powered agents can only be possible in the human-centric data environment, where all the AI experts run on the user’s side. Sharing sensitive data outside of the user’s own personal data environment is not optimal. In fact, such communication between agents would be impossible in the old, enterprise-centric data ecosystem where data is locked in separate silos.
As we stand on the entrance gates to the age of AI, the future seems quite exciting: how will our lives change when each of us will be able to tap into the potential of our Personal AI? The integration of Personal AI agents into our daily lives is not a question of if, but when and how.
To bring this vision into reality, a shift in thinking is required. We need to embrace a human-centric data paradigm where our Private AI is operating on our side, on our own data, privately.
At Prifina we are building an infrastructure to empower each individual with such “steamengines of the mind”; we want to empower developers to build Personal AI applications for people to augment each individual’s creative potential. Join us!
On July 13, 2023, an event called “Augmenting Consumer Experiences in the Age of Data & AI” took place at the offices of New York Life Insurance Company's offices in San Francisco (kindly hosted by Boudjemaa Nait Kaci).
Augmented UX with AI
The event started with Jouko Ahvenainen from Prifina, who invited his fellow panelists to delve into their personal experiences, both triumphs and trials, relating to their interaction with the recently released AI and data-driven technologies.
Heather Whitney from Morrison Foerster shared her excitement at the launch of ChatGPT. She underscored the versatile potential of generative AI, highlighting its role in revolutionizing customer experiences across a variety of sectors, notably content creation, gaming, as well as gene editing and drug development.
Following up, AJ Tomas from Touchdown Ventures shed light on the latest unveiling from Humane Inc. — a secretive startup founded by former Apple executives — who have recently announced the forthcoming release of a cutting-edge gadget that generated quite a buzz in the tech world.
Amit Sharma shared his vision:
"We believe that generative AI has the potential to create innovative forms of content that go beyond the current video-based experiences on Instagram, YouTube, or Tiktok. These novel experiences will offer users the opportunity to engage with brands and services in a multimodal manner."
Aaron Mollin (CEO, Ichijiku) offered a fascinating observation, arguing that most AI-fuelled experiences are curated from a “top-down” perspective. He recognized the transformative nature of tools such as ChatGPT, but called to realize that oftentimes he felt that such tools are detached from how we interact with material objects around us.
Aaron shared an alternate viewpoint related to integrating AI-powered insights based on the data collected from ubiquitous sensor technology found in everyday physical objects, like wearable tech, IoT devices, and environmental sensors. He called this the "bottom-up" approach. One such example is a collaboration between his company, Ichijiku, and Prifina: their work has resulted in the creation of sensor-imbued luxury jackets (one of which he was wearing that night).
This conversation immediately led to a conversation with audience members about the fact that we, individual consumers, all have cell phones, and we find it cumbersome to interact with hundreds of separate apps and services. From the consumer perspective, rather than multiplying points of interaction, it would be better to reduce our reliance of more and more devices and apps and make the UX more user-centric.
Predicting the Future
Jouko then asked panelists to share their thoughts on what changes consumers could expect in the next coming years.
Amit did not hesitate to suggest that every aspect of consumer experience will change in the next few years. Some UX aspects will change faster than others, but gradually many industries will transform. E-commerce, online shopping, entertainment, and interactive experiences are the first ones to transform.
AJ Tomas predicted that another area of fast-moving development is personal productivity.
Aaron expressed his wonder about the impact of data on the way how individuals make decisions about their own lives. Lots of work appears to be needed to build personal recommendations and nudges for people.
Jouko reiterated his favorite idea about predictions: although we do not have a crystal ball, we can actually make quite certain predictions about the future. Jouko noted that we can anticipate that certain things will happen (e.g., self-driving cars), but the challenge is to identify the timing: will happen in a year? Two years? Five years?
Amit noted that the current developments in generative AI capture much attention of billions of people who are waiting to see what the actual breakthrough will actually look like:
“And if you go back to the 1980s, people knew there would be something called ‘a computer.’ But nobody knew what a computer would look like … it wasn't clear that it would be a box on your table with something called a keyboard and a mouse… This is true for smartphones and, most recently, Apple VisionPro. We can’t even imagine what Apple VisionPro 14 will look like. And that uncertainty is what makes people excited.”
Legal Issues To Be Resolved
Heather shared insights based on her hands-on experience from working with generative AI technology companies; she provided an overview of some of the key legal issues that revolve around copyright, the legality of the use of data, and data privacy. These issues are currently unclear and are currently discussed among legal experts and AI entrepreneurs:
Heather and Jouko shared their views about the emotional narrative around these generative AI tools: many artists feel hurt and believe their works have been unlawfully used to train AI without their permission.
The ethics of this debate raise controversial questions. On one hand, information in the public domain is supposed to be free. On the other hand, some stakeholders invoke strong arguments based on the ideas of exclusive ownership rights.
Ichijiku: Combining Fashion, Cultural Expressions and AIAaron shared his unique perspective on using traditional kimono silk materials to create bespoke fashion items.
Differently from the prevailing ideals in the luxury fashion industry, where consumers are made to feel that the luxury fashion items purchased just a few months ago are out of style and invited to purchase the next generation of items, Ichijiku aims to create life-long items that people could hold on to for their entire lives.
Ichijiku embeds sensors in those fashion items and uses data to extend the lifetime quality of the garments. By implementing sensors and generating data, Ichijiku jacket owners can monitor explore to humidity, sunlight, and heat; the first, humidity, being the most kind of serious culprit for the degradation of silk.
By using data and AI, Ichijiku aims to create a new type of experience that go even beyond the maintenance of one-of-its-kind silk. Additional information collected from other sensors, such as heart rate, could help people get insights into how they feel while wearing Ichijiku’s bespoke jackets. This is something that no one has ever been able to create.
“For me, it's just all about, creating pieces that will stand the test of time. … Ichijiku aims to create these unbelievably beautiful, arguably one of the most intrinsically valuable items on the planet. And that I think, is what's going to really appeal to people. Technology will never be the selling point, although it is definitely appealing. We're using vintage silk fabrics, which ties closely to sustainability ideas. People understand just how beautiful the items they are buying. The use of data and technology helps us further the story.” -- Aaron Mollin
One of the remarkable features of the data and AI-related events currently happening in San Francisco is that people come to meet one another, learn about each other and what others are building.
The same spirit could be felt at our event: attendees spent the remainder of the evening at our venue socializing, getting to know each other, and connecting on various social media platforms to stay in touch in the future.
We at Prifina are excited to be at the heart of this historical moment; we feel inspired and motivated to continue building our Human-centric data platform for AI-powered apps and services.
On June 8, 2023, Paul Jurcys, one of the co-founders of Prifina, attended a panel discussion entitled "Real Laws for Unreal Lands" hosted at the HQ of Treasury. Two other panelists were Max Sills (General Counsel, Midjourney) and Barath Chari (attorney, Wilson Sonsini), the event was moderated by John Manoochehri (CEO, Treasury).
The panel discussion revolved around three main topics: the ownership of legal assets, legal liability for personal virtual agents, and future directions in setting forth the legal framework for new digital interactions.
You can watch the entire discussion on YouTube... Or you can continue reading for some highlights of the discussion.
Do real laws apply to unreal worlds?
Barath emphasized the importance of recognizing that virtual worlds, despite being distinct from the physical realm, still have a significant impact on real-world individuals. He noted that there must be a way to establish responsibility and accountability within these digital environments.
He further highlighted the need to navigate the gaps between current laws and emerging technologies, such as AI-generated content. For instance, the question arises of whether platforms creating virtual worlds can maintain their neutral platform status.
“There's always somebody ultimately responsible for what happened. The practical challenge is determining how that responsibility gets allocated under the law. ” - Barath Chari
Paul Jurcys from Prifina started by challenging the notion that real laws do not apply to unreal worlds. He emphasized that existing legal frameworks are indeed applicable to digital spaces. Although these laws may not be perfect or fully aligned with the unique aspects of virtual environments, they serve as a foundation for understanding the legal implications:
Max Sills shared some insights from the law and economics perspective. First, the concept of transaction costs suggests that laws should be designed to minimize these costs for private parties within the digital realm. Second, the concept of the "cheapest cost avoider" doctrine suggests that the responsibility for preventing harm in the real world and also in virtual worlds should lie with the party that can most efficiently address the issue. Finally, Max Sills explained that intellectual property (IP) laws are primarily designed to facilitate creativity rather than benefiting only those who possess preexisting property.
The complex issue of owning digital assets
The event moderator, John Manoochehri, wondered who owns virtual lands and what happens when the server goes down: is that land no longer available? Is the law clear on who owns what and who is liable for lost digital assets?
Barath suggested that when we think about the concept of virtual land ownership, we need to identify what exactly constitutes virtual land. Is it a collection of digital bytes residing on a server within a specific environment? In reality, it boils down to the ability to exclude others from accessing or profiting from objects in the virtual space. This access right is usually achieved through contractual agreements. He suggested that one way to look at ownership issue could be through the lens of responsibilities: who is responsible for what?
Paul Jurcys offered an example of user-generated data (e.g., data individuals generate through the use of wearable devices or mobile apps). Historically, data has been viewed as a public good, not owned by anyone and freely accessible: “Information wants to be free.”
Defining data as an asset proves challenging due to its intangible nature and the absence of clear boundaries. However, if we think about the data collected and stored in one secure locker (e.g., user A’s personal data cloud), such data becomes unique and clearly defined and could meet the legal requirements to be considered as a “thing”. Paul emphasized, that as we generate more data in our daily lives, it becomes crucial to explore the concept of ownership and the necessary conditions to claim it.
Max Sills noted that ownership of digital assets hinges on a stable legal and enforcement regime. In the absence of law, ownership becomes irrelevant as power dynamics prevail. To establish a meaningful concept of ownership for digital assets, competent and vested legal and enforcement systems are necessary to ensure stability between parties.
“Look at a developing country where there is no stable government. It does not matter who owns a piece of property because if you come on someone's property, they'll kill you.” - Max Sills
Additionally, Max addressed one of the most remarkable recent development: Japan Copyright Law modification allowing to train AI on any data. In a global environment, the competition among legal regimes becomes more and more apparent. As we move forward, the existence and choice of legal frameworks play a crucial role in defining ownership.
The issue of ownership in the digital age involves complex considerations of excludability and rivalrousness. While private property traditionally relies on excluding others from its use, data poses challenges as it can be used simultaneously by multiple parties. The question arises: How can one retain ownership and prevent others from accessing their data? This issue remains unsolved in the data age, leading to resistance against traditional ownership premises. Japan's recent legal development allowing the use of copyrighted data for training datasets reflects the evolving nature of law in response to the value and accessibility of data.
The panelists agreed that conventional ownership frameworks struggle to encompass the characteristics of digital assets, which often escape excludability criteria while being beyond rivalrousness. This is quite an exciting domain to follow because new approaches are evolving fast.
Are new laws for avatars needed?
The next topic that the panelists were asked to discuss revolved around avatars: as avatars are becoming our agents in various real-life and virtual environments, who is responsible for their behavior? Is it the person whom the avatar is representing? Or is it the provider of the virtual platform for avatars to interact with one another? How about third parties who embed AI-powered features into avatars?
Paul Jurcys from Prifina noted that there are three categories of avatars that we can envision: (i) those that really act for the sole benefit of the individual herself (e.g., my own avatar that helps me better understand my sleep patterns); (ii) avatars that act as our agents (e.g., help my buy tickets to my favorite band’s concert); and (iii) avatars that interact with other agents in virtual words. Only the avatars in the latter category are likely to cause harm and lead to complex legal issues.
“It is important to realize that avatars are not independent/autonomous entities; they are extensions of individuals' digital identities and act as human agents. The legal debate surrounding independent and autonomous avatars with legal personhood is mostly theoretical.” - Paul Jurcys
Max Sills offered a very clear answer to this question of avatar liability:
“I think everything will become corporate law. Corporations already have rights of free speech, they can commit crimes. … Establishing LLCs (limited liability corporations) for avatars will be the market-oriented way to organize liability.”
Charting Legal Frameworks for the Digital Frontier
As we are witnessing rapidly evolving digital technologies, many intricate questions remain unanswered: who owns virtual representations of the real world? Is it possible to flex the legal muscle of current laws and regulations or are these laws outdated?
Barath noted that copyright and intellectual property laws are just one of the possible tools to address the issue of digital ownership. Paul suggested that creators and developers would benefit immensely from clear rules that define what are the rules of the game. In this regard, recently adopted amendments to the Japanese Copyright AI provide a valuable guidepost and increase regulatory competition between Europe, Japan and US.
“As we're moving forward, we need to think about new regulations that would not be reactive (based on things that happened), but forward-looking. … What kind of framework could we build based on what we anticipate from the new technological revolution?” - Paul Jurcys
Max Sills made a great observation about financial incentives: For ownership to exist, there must be a financial system and a bustling market where transactions occur.
“ Similarly to the “least cost avoider” approach which is applied for liability, rules defining the allocation of ownership should be based on the cost-benefit analysis: Who can utilize the assets in the most efficient way?” -- Paul Jurcys
The panelists agreed that current legal frameworks that exist to help navigate in real laws will evolve and be adapted to how humans interact with one another in digital environments. Forward-looking, incentive-based, transaction-cost-reducing rules are desirable and needed.
Bottom-up approaches and standards are very likely to emerge. One good example of such bottom-up regulation is Creative Commons licenses that help people manage their own copyrights with regard to works published in the current internet-based environment. The panelists agreed that we will see similar solutions emerging for more complex digital assets such as data, or three-dimensional representations of the real world.
“From a legal perspective, we're gonna see a really chaotic period (which is happening now), and then … it will be very exciting.” - Max Sills
Unlocking the Lifelong Value of Data: Personalization of Consumer Experiences in the Insurance Market
Prifina’s CEO Markus Lampinen spoke to Alex Bond on the podcast about the current trends with personal data and how individualized data-driven innovation could be introduced to the insurance services market.
Markus: My name is Markus Lampinen, I'm based in San Francisco where I run a company Prifina. We help make products smart. We do this by embedding sensors into different types of physical products. For example, I'm wearing - not that you can see it on the podcast - a really nice kimono-based silk jacket produced by a Tokyo-based company Ichijiku. This jacket has an embedded sensor that can measure a number of different things around, e.g., how the jacket is doing, surrounding data like humidity, etc. Our role at Prifina is to overlay different types of datasets like the sensor data and correlating them with other types of data, e.g., your heart rate when you wear the jacket.
Prifina allows companies to build different types of applications that enable them reimagine the end-user experience for how we interact with not only physical products but data. Our vision is that in the future, have more data than ever - how can we use it to create new experiences? Something that's different from what we've had?
Alex: That's great. I think that when people hear about sensor-driven technology in clothing, they think about performance, sportswear. But it's much more than that, isn't it?
Markus: That's right. We work with pro athletes that want to improve their performance, e.g., top basketball clubs. For them, it's about understanding performance, recovery, sleep, stress, hormonal activities, and so on. From a player’s point of view, how can players themselves understand what's going on with their body and their environment to essentially get better? But it's not just about performance sports, it's also about stress - how do you manage stress?
There is a lot of data that we already have, e.g., our sleep data.
We can go all the way to, for example, luxury fashion and thinking about how does the clothing that you wear impact your your mood or happiness? As for all this data, we're kind of sitting on this goldmine: we, individuals, have so much data but we're just not using it. It's a huge opportunity.
With user-generated data, it is possible to build new types of experiences.
Alex: We're now talking at the MENA Insurance Summit. How does this relate to, for example, insurers?
Markus: We work with a lot of insurance companies around the world are looking look at preventative health, mental health and wellness. If you can make your policyholders healthier and happier, then they're going to be better customers for the insurance company, because they have very similar incentives as the insurance company does.
Alex: Okay, applications are really wide for the insurance industry. … Markus, you explained that it's not just about kind of tracking the data, but it is about the lifetime value of a product that is enhanced by your own data.
Markus Lampinen: Indeed, the lifetime value is one important aspect of a product. How are you maintaining your car? Are you driving it too fast, and so on and so forth.
But then, we get into this very delicate balance as well: the data should benefit you as an individual, not the insurance company alone. At the end of the day, for example, when it comes to different types of collectibles, tracing the entire value chain (where everything came from, who actually owns it, etc.) becomes important, especially for maintaining the value and also secondary transactions.
This fits into a broader conversation about what is authentic, especially in the digital environments powered by applied AI and deep fakes. We have Barack Obama thats now trying to sell you some skin care product. How do you know that something is authentic?
But our focus is very much on reimagining the whole of the consumer experience using data. There are incredible applications as we move forward. For example, cars generate a lot of data. So do you as an individual. What if you could just enter into the car which already knows that, am I a five star driver today? Or that I am only a three star driver today? If you slept really poorly of if you had a little bit more than one drink…? We're not talking about sharing it anywhere, but using your own data for your own benefit.
That’s where there's this interplay between all the data that we have and all the things around us. How can we tie them into a unique importable experience going forward? It's a very, very big theme, of course, but that's kind of something that we look at as an inevitable trend.
Alex Bond: I think people are just starting to wake up to be protective of that. I’d like to finish with one more question: what does it mean for insurance? I'm an insurance guy. What about applications for the insurance sector?
Markus Lampinen: Sure. Insurance emerged as a very clear secondary market for personal data use-cases. Let's take an example. After today’s summit here in Doha, I'm traveling to Switzerland where we're working with our partner that has a sensor embedded into both the left and the right ski boot as well as the helmet.
So you can actually get your triangulate the skier and their position to maybe help them improve. Now, performance athletes may care about the angle of tilt on their 760 turn on the mountain. But most skiers don't.
But if you start essentially hitting this type of data on skiers, could you create individualized insurance per skier per day in dynamic conditions? Could you give them incentives to ski safer based on those? These are some things that are currently really hard to price dynamically. But if you started having this type of data, could he actually create almost like reverse marketplaces for these types of products? Could you do this on, let's say, a resort by resort basis? You can also use it as, let's say recommendations for routes on different types of ski resorts. You can also use it for insurance products as well.
So that's been very much our foray into thinking about starting off in a very, very clear value prop for the individual, but then realizing that there's this entire ecosystem.
Alex Bond: Markus, you've been very generous with your time. Thanks for being a guest.
You find the entire conversation on , here it is.
San Francisco-based tech company Prifina and Tokyo-based luxury fashion brand Ichijiku are pleased to announce a groundbreaking partnership that aims to fuse the worlds of fashion and technology. With a shared vision of innovation and a passion for creating unique experiences, Prifina and Ichijiku are set to revolutionize the luxury fashion industry.
Ichijiku, renowned for its exquisite craftsmanship and commitment to preserving kimono history and culture, specializes in one-of-a-kind apparel and fashion accessories made from the highest quality authentic kimono fabric. By blending traditional elements with modern designs, Ichijiku has established itself as a global symbol of elegance and luxury.
In their quest to push the boundaries of fashion, Ichijiku has chosen to collaborate with Prifina to embark on an exciting new venture: sensorized jackets. These innovative garments will be embedded with cutting-edge sensors, enabling wearers to enjoy a truly immersive digital experience. By measuring variables such as light, humidity, and temperature these sensorized jackets will provide wearers with real-time data about their surroundings. This data can be utilized for myriad purposes, including allowing the owner to ensure the jackets are maintained in ideal conditions.
Last week, the Prifina team had the privilege of visiting Ichijiku's headquarters in Tokyo, where they met with the passionate and forward-thinking team behind the brand. Over a series of meetings and a delightful lunch, ideas were exchanged, and the groundwork for this transformative partnership was laid.
Ichijiku's ambitious plan involves integrating sensors into all their jackets, expanding their offering beyond visual aesthetics to include a dynamic and interactive element. With the ability to collect and analyze environmental data, wearers will gain insights into their surroundings, allowing them to make informed decisions about their well-being and comfort.
In return, Prifina will extend a warm welcome to the Ichijiku team in mid-July, inviting them to their headquarters in San Francisco. This exchange of knowledge, expertise, and cultural influences will undoubtedly fuel collaborative efforts, leading to groundbreaking advancements in the fashion-tech industry.
The partnership between Prifina and Ichijiku represents a significant step toward the future of luxury fashion. By embracing technology and incorporating it seamlessly into its designs, Ichijiku is poised to redefine how we experience and interact with fashion. Through this collaboration, both companies are committed to pushing boundaries, breaking norms, and creating a new era where fashion and technology intertwine harmoniously.
As fashion continues to evolve, this exciting venture signifies the importance of embracing innovation to cater to the ever-changing demands of consumers. Prifina and Ichijiku's partnership represents a fusion of expertise, creativity, and a shared commitment to pushing the boundaries of what is possible. Together, they are set to revolutionize the luxury fashion industry and pave the way for a new era of sensorized fashion experiences.
Stay tuned as Prifina and Ichijiku work tirelessly to bring their sensorized jackets to life. The future of luxury fashion is here, and it's poised to be an extraordinary blend of tradition, innovation, and limitless possibilities.
In the heart of Bern, Switzerland, an innovation and future conference - The 2291 Festival - recently provided a platform for Prifina to showcase its remarkable progress in collaboration with its Swiss partner companies. This event brought together visionaries, industry leaders, and venture capital firms, highlighting the transformative potential in the areas of sensors, personal data and AI.
Prifina, along with Heierling, known for their high-end ski boots and equipment, took center stage at the event. We unveiled next-generation of ski boots and helmets that collect skiing data and seamlessly integrate it into their personal data cloud provided by Prifina. Users can then access applications that leverage this data, such as an AI ski coach, providing personalized insights and recommendations.
Markus Lampinen and Jouko Ahvenainen took the stage to deliver thought-provoking talks during the event. Their focus centered on the fundamental question of personal data ownership and control, emphasizing that it is not only about owning the data but also enabling ordinary individuals to access applications built on their personal data.
“Empowerment with personal data is crucial for individuals to lead healthier and more fulfilling lives.” - Jouko Ahvenainen
Prifina's current primary focus revolves around leveraging data and applications to enhance people's well-being based on health and wearable data. By harnessing the power of personal data, Prifina aims to provide individuals with the tools they need to lead healthier lifestyles and make informed decisions about their well-being.
Throughout the event, there were compelling discussions on the role of innovation in improving the lives of people. It was acknowledged that while technological advancements have the potential to revolutionize various aspects of our lives, there are also concerns about how companies and governments may misuse personal data for control. In this context, the consensus was that giving individuals better control over their personal data can empower them to lead better, healthier lives.
Switzerland, known for its commitment to individual freedom and empowerment, has always held personal data control in high regard. The Swiss people recognize the importance of safeguarding personal data and ensuring that individuals retain the rights to make decisions regarding their own information. It is this shared belief that has facilitated a fruitful collaboration between Prifina, Heierling and Code Fabric, as they work together to redefine personal data ownership and control.
Prifina’s collaborations with Swiss companies shows the immense potential with user-generated personal data. By combining our expertise in technology, skiing equipment, and personal data management, we are pushing the boundaries of what is possible. This represents a unique opportunity for other consumer brands seeking innovative approaches to their product offering that have a positive impact on people's lives.
Our general takeaway is that the future with user-generated personal data looks promising. Our vision of empowering individuals through personal data control resonates strongly with the Swiss people and the global community at large.
Stay tuned for more updates as Prifina strives to revolutionize the way we experience sports and personal data, ultimately enhancing our lives in ways we never thought possible.
On May 3rd, 2023, the Prifina team with its co-organizers at New York Life, hosted a panel on how AI-driven innovation and advances will impact consumer experiences. The event was sold out and we thank all attendees who braved the spontaneous rain in San Francisco to join in person.
We’re grateful for such lively audience participation and brilliant questions for our panel, which included Mickey McManus, BCG, Malavica Sridhar, Founder, Northstarre, Markus Lampinen, Co-Founder and CEO, Prifina and moderator Amber Wang, Women in AI / Cerebral Valley.
The panelists together raised various observations and addressed the trends in the current market:
With such a boom in generative AI, personal data and private use of personal data become fundamentally important. Not only because of privacy concerns but also because of representation; if apps and services are built utilizing individual models that represent the users, we can truly deliver private AI that helps us achieve what we want in life. Like an audience member asked: which human activities should we trust to AI and which should we want to perform ourselves?
Questions like these are at the very heart of the debate, but should it not be our choice as individuals based on our preferences? After all, studies show that outsourcing tasks and chores you do not wish to do increases your overall satisfaction in your life.
Thank you all for the wonderful debate and we cannot wait to see you soon to showcase more of what Personal AI can deliver, privately, to each of us.
Imagine you have your own Personal AI assistant that can help you get any answer about yourself - your wellness and well-being, your health, or your daily routines - and those answers are based on real data from the fitness devices and apps that you use everyday day, what would you ask?
If such an opportunity to better understand your daily metrics arrives, why would you choose not to have your own Personal AI assistant?
For years, consumer brands have tried to create products that give us the inner feeling of freedom, empowerment, and happiness. How have brands adapted to rapid technological change, and what will the consumer experience look like in the age of AI?
Image credit: Levi's Strauss.
Denim as a Decadent Symbol of Liberty
Let’s travel back in time. During the Cold War, jeans were considered a symbol of capitalism. Denim was banned behind the iron curtain and jeans-wearers were enemies of the communist state.
International fashion trends, however, could not be stopped at the iron curtain, and Levi’s jeans have become the most sought-after item for the youth in the East: a part of the West many of them dreamed to obtain.
One of the most famous commercials of all time was Levi’s advertisement “1984 Russia.” It told a story of a young man returning from abroad to a Soviet airport. The security personnel opened his suitcase to check for any illegal goods, but they are momentarily distracted and the man returns home with his most prized possession. The traveler would risk everything for his Levi’s.
When Everything Changed
It seems that the year 1984 changed the world as we know it: it was the year when Apple introduced Macintosh. The ad responded to the fear of those days when people were surveilled by Big Brother, and offered the hope that the new Mac would actually “set people free”:
Several decades later, Apple’s executives still refer to that early concept of Mac and reiterate, that the information we as individuals create by using Apple’s products belongs to us and that by using Apple’s products we will be happier every day.
Reinventing Denim with Sensors
Fast-forward to 2018 when Google and Levi's have teamed up to create a new - sensorized - version of the iconic Trucker Jacket, which featured Google's Jacquard technology. This technology allowed the wearer to interact with their smartphone through touch-sensitive areas on the jacket's sleeve. The jacket has a range of functions, including the ability to control music playback, answer calls and get directions, all without needing to take out the phone.
The collaboration between the Google and Levi’s aimed to create a wearable that seamlessly integrates technology into everyday clothing. The new Trucker Jacket is a step towards creating more intuitive and functional wearable technology that can enhance people's lives and make the use of technology more seamless.
Customer Engagement in the Age of AI
The concept of creating personal AI assistants is not new, but the currently available voice assistants in the market have limited utility. This could be due to the fact that Siris and Alexas are based on limited data which users generate using specific companies’ products and services.
With so much data that each of us generates, it is necessary to rethink the architecture of how personal data is aggregated and used. Individuals need to have all of their data - not just data from a device or one app - on their side. Then, we can expect AI assistants to actually empower consumers.
One of the key lessons that ChatGPT taught us is seamless user experience and the availability of easy-to-use tools for any individual. When it comes to our personal life, sensorized devices and services we use in our daily personal lives, AI assistants must be tools available at your fingertips. Personal AI assistants of the future must allow us to ask anything about myself, about things that matter to us
Similar to how the denim movement could not be stopped in the 1980s, AI's development is not asking for permission, whatever technology and data leaders may presume. The question is how we develop it and what type of incentives we give our AIs.
At Prifina, we strongly believe that individuals should be represented by their own AI that runs on individuals side, advocates for them and works for them.
However, data-driven insights are not the only components of a digital customer experience. Brands should continue exploring possible ways to increase brand value for customers and find new modalities for emotional engagement with the product.
We have an opportunity to not only be empowered by the jeans we wear but also personalized applications that help us reach the goals we set in our lives. The possibilities are endless, and we are excited to be at the forefront of this technology.
By Paul Jurcys
If you could ask your personal AI assistant anything about your personal life what would you ask? What would you like to know about yourself based on your own data?
Based on my current level of restfulness, if I want to have a productive day tomorrow, how should I prepare for it? Based on my data about this week’s exercise records and routines, what improvements can I make to increase my performance next week?
The current ChatGPT boom has spawned many new generative and general intelligence startups utilizing different large language models. These models are trained on public data sources and can answer various questions based on this training data set.
However, they have limitations as it comes to answering more personal questions and with privacy concerns, there are opportunities to build new AI models on personal data frameworks like Prifina’s user-held data model. In this post, we explore how personal applications and “AI” solutions can be realized on a more individualized basis.
Can Everyone Train Their Own AI?
We are at the turning point where the human-centric technology ecosystem becomes real and individuals actually control their own data. Federated cloud architecture and edge computing technologies have now matured to empower individuals with their data.
Prifina’s human-centric data model refers to a data infrastructure that is built around an individual consumer who can collect data from various personal data sources in real-time and have actual ownership and control of such data.
This human-centric approach to personal data is built on the principle that an individual’s personal data should be private by default and not shared with anyone unless the user decides otherwise.
The idea of individuals owning their data is not new. In the early days of the internet, entrepreneurs working at up-and-coming companies thought that user’s data should belong to them.
Being able to access, collect and own your personal data from different sources is the major condition for individuals to train their personal AI.
Prifina's User-Held Data Ecosystem
Prifina’s user-held data platform has two distinct features.
First, each individual user has their personal data cloud where they can collect data from various data sources: personal sensors, wearables such as smart watches, fitness or sleep trackers, and online data sources (e.g., the location from Google Maps, Amazon shopping history, activity while using social media services, apps, etc.).
In Prifina’s ecosystem, each personal data cloud has an embedded software robot that unifies the data regardless of the format it comes to the personal data cloud.
Second, developers and companies can use Prifina’s open-source tools to build new applications that “come to the user” and run locally (i.e., “on top of” user-held data).
Instead of sending data to centralized siloed environments of iOS or Android or any other company providing a sensorized device, individuals in Prifina’s user-held data environment can benefit from full ownership and control: personal data is private by default.
Prifina’s user-held data model opens new opportunities with personal data: developers can easily build apps without having to solve complex data (back-end) problems. Prifina’s approach to personal data frees developers from the hefty burden of complying with data privacy regulations because apps run locally (“on top of” user-held data) and generate value from personal data on the user’s side (instead of being centralized in a service provider’s platform).
Understanding Your Data with Personal AI
If you think about your own personal data - data from your personal fitness trackers, smart watches, personal IoT devices at home, and all apps on your phone - are you actually able to benefit from all the data you have generated over the years?
At Prifina, we start from the premise that each individual should have a master copy of their data. In our user-held data ecosystem, individuals can connect all their data sources and create their own personal data hubs.
Once you have all your personal data in one place (your personal data cloud), you can start exploring it: your personal AI assistant will answer questions about your own personal data (not random public data that has no relevance to you).
For example, you can ask your Personal AI assistant how well you slept last night, or after finishing your daily morning exercise, you can ask your personal AI assistant about your performance today and what circumstances during the past few weeks contribute to better or work physical condition.
Here are some more specific examples of Personal AI assistants that We at Prifina built to empower individuals with their own personal data:
Example #1: My personal avatar
At Prifina, we built a personal avatar that takes into account data from an individual's personal fitness devices and, based on various biomarkers, appears differently. So, if you were staying well hydrated, got enough sleep and also managed to exercise, your avatar appears fit and energetic. However, If you worked long hours today and did not have enough rest last night, the avatar will appear sluggish and unhappy.
You can also interact with your personal avatar and ask: “what is my readiness level now?” “How can I improve my productivity today?” The avatar will give you a response based on your own personal, and if relevant, some public data (e.g., weather conditions during your recent activity, etc.).
Example #2: My Data Diary
Imagine if you could connect multiple data sources to your daily calendar: your wearable fitness devices, sleep trackers, home IoT devices and your online accounts (such as Spotify or Netflix, etc.) and that you talk to your data diary, what would you ask?
For instance, you could ask your data diary about your readiness level before and after the meeting, or how focused you were before the meeting.
Based on your wearables and other data, you could also ask your personal data diary about the music or surrounding circumstances that make your day more productive, wouldn’t that be great?
What else would you like to explore with your intelligent data diary?
Empowering Developers: Liberty. Equality. Data.
Prifina’s open developer platform empowers developers to build applications that can correlate different data sources - both private and public.
At Prifina, we are gradually releasing resources for developers to build on top of user-held data and to integrate various machine-learning tools into apps. These tools help developers and brands build applications to help individuals get adily value from their data - to interact with their data and ask anything.
Consider all possible use cases where individuals could benefit from their personal data: health and wellbeing, emotional state, connected home and offices, optimizing daily routines, and so on.
In Prifina’s personal data infrastructure, personal AI tools can be embedded in any application. Such personal AI assistants could take different forms: a simple chat window or voice-to-text where you can ask your personal AI any question and get an answer based on your personal data and publicly available data.
Most importantly, Prifina’s user-held data model ensures the privacy and safety of personal data because every user’s data is private by default.
Welcome to the human-centric data ecosystem, powered by Prifina!