Event Recap: "Augmenting Consumer Experiences in the Age of Data & AI"

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:

• The legality of data scraping and using such publicly available data to train machine learning models: Do you have to license that data? Or can you scrape the entire internet and use that? Is that going to be deemed as copyright infringement and thus not permissible? Could it be excused under the copyright law doctrine of fair use? 
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• Data privacy: what if the data scraped from the internet contains some personal information of individuals? Could such data be used to train ML models? Which laws should be applied to such activities (the law of the state where the allegedly infringing  AI company is based or is operating? The law of the place where individuals whose personal information is use? Or some other country’s law?). 
  
  
• Then there's the question about the model itself. An understanding of what they receive from its training data. People don't fully understand that yet. And engineers don't understand exactly how to describe that yet. And what it really means from a legal perspective is still in flux. They just don't know. And it is not currently 100% knowable. 
  
  
• The legality of outputs generated with AI tools: what is the relationship between your training data and the outputs? Could output results be considered to be “derivative works” (in a copyright law perspective) of the training data? If so, then it is possible that there will be massive restrictions on how those outputs can be used. What about the commercialization of these models? The use of outputs are likely to be curtailed as long as there is no clear answer whether the outputs are not infringing (copyright law). 
  
  
• Rights to outputs generated with generative AI tools. Having (any) rights to the output generated with the help of AI tools is a huge problem that will determine whether such works can be commercialized. 

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

Post-Event Networking 

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.