Tag: artificial intelligence

Mark Zuckerberg and Daniel Ek on Why Europe Should Embrace Open-Source AI: It Risks Falling Behind Because of Incoherent and Complex Regulation, Say the Two Tech CEOs

Editor’s Note: At Spotify, we believe that AI has the potential to offer real benefits for innovation and creators. Read on for thoughts from our CEO, Daniel Ek and Meta CEO, Mark Zuckerberg’s on the promise of open source AI and its ability to drive progress and create economic opportunity globally. 

This is an important moment in technology. Artificial intelligence (AI) has the potential to transform the world—increasing human productivity, accelerating scientific progress and adding trillions of dollars to the global economy.

But, as with every innovative leap forward, some are better positioned than others to benefit. The gaps between those with access to build with this extraordinary technology and those without are already beginning to appear. That is why a key opportunity for European organisations is through open-source AI—models whose weights are released publicly with a permissive licence. This ensures power isn’t concentrated among a few large players and, as with the internet before it, creates a level playing field.

The internet largely runs on open-source technologies, and so do most leading tech companies. We believe the next generation of ideas and startups will be built with open-source AI, because it lets developers incorporate the latest innovations at low cost and gives institutions more control over their data. It is the best shot at harnessing AI to drive progress and create economic opportunity and security for everyone.

Meta open-sources many of its AI technologies, including its state-of-the-art Llama large language models, and public institutions and researchers are already using these models to speed up medical research and preserve languages. With more open-source developers than America has, Europe is particularly well placed to make the most of this open-source AI wave. Yet its fragmented regulatory structure, riddled with inconsistent implementation, is hampering innovation and holding back developers. Instead of clear rules that inform and guide how companies do business across the continent, our industry faces overlapping regulations and inconsistent guidance on how to comply with them. Without urgent changes, European businesses, academics and others risk missing out on the next wave of technology investment and economic-growth opportunities.

Spotify is proud to be held up as a European tech success but we are also well aware that we remain one of only a few. Looking back, it’s clear that our early investment in AI made the company what it is today: a personalised experience for every user that has led to billions of discoveries of artists and creators around the world. As we look to the future of streaming, we see tremendous potential to use open-source AI to benefit the industry. This is especially important when it comes to how AI can help more artists get discovered. A simplified regulatory structure would not only accelerate the growth of open-source AI but also provide crucial support to European developers and the broader creator ecosystem that contributes to and thrives on these innovations.

Regulating against known harms is necessary, but pre-emptive regulation of theoretical harms for nascent technologies such as open-source AI will stifle innovation. Europe’s risk-averse, complex regulation could prevent it from capitalising on the big bets that can translate into big rewards.

Take the uneven application of the EU’s General Data Protection Regulation (GDPR). This landmark directive was meant to harmonise the use and flow of data, but instead EU privacy regulators are creating delays and uncertainty and are unable to agree among themselves on how the law should apply. For example, Meta has been told to delay training its models on content shared publicly by adults on Facebook and Instagram—not because any law has been violated but because regulators haven’t agreed on how to proceed. In the short term, delaying the use of data that is routinely used in other regions means the most powerful AI models won’t reflect the collective knowledge, culture and languages of Europe—and Europeans won’t get to use the latest AI products.

These concerns aren’t theoretical. Given the current regulatory uncertainty, Meta won’t be able to release upcoming models like Llama multimodal, which has the capability to understand images. That means European organisations won’t be able to get access to the latest open-source technology, and European citizens will be left with AI built for someone else.

The stark reality is that laws designed to increase European sovereignty and competitiveness are achieving the opposite. This isn’t limited to our industry: many European chief executives, across a range of industries, cite a complex and incoherent regulatory environment as one reason for the continent’s lack of competitiveness.

Europe should be simplifying and harmonising regulations by leveraging the benefits of a single yet diverse market. Look no further than the growing gap between the number of homegrown European tech leaders and those from America and Asia—a gap that also extends to unicorns and other startups. Europe needs to make it easier to start great companies, and to do a better job of holding on to its talent. Many of its best and brightest minds in AI choose to work outside Europe.

In short, Europe needs a new approach with clearer policies and more consistent enforcement. With the right regulatory environment, combined with the right ambition and some of the world’s top AI talent, the EU would have a real chance of leading the next generation of tech innovation.

We believe that open-source AI can help European organisations make the most of this new technology by levelling the playing field, and we hope that the EU doesn’t limit the possibilities that we are only starting to explore. Though Spotify and Meta use AI in different ways, we agree that thoughtful, clear and consistent regulation can foster competition and innovation while also protecting people and giving them access to new technologies that empower them.

While we can all hope that with time these laws become more refined, we also know that technology moves swiftly. On its current course, Europe will miss this once-in-a-generation opportunity. Because the one thing Europe doesn’t have, unless it wants to risk falling further behind, is time.

Mark Zuckerberg is the founder and chief executive of Meta. Daniel Ek is the founder and chief executive of Spotify.


Originally published at https://www.economist.com/by-invitation/2024/08/21/mark-zuckerberg-and-daniel-ek-on-why-europe-should-embrace-open-source-ai © The Economist Newspaper Limited, London, 2023

How Spotify Uses Design To Make Personalization Features Delightful

Every day, teams across Spotify leverage AI and machine learning to apply our personalization capabilities on a large scale, leading to the features, playlists, and experiences Spotify users have come to know and love. And when you spend your days working with emerging technologies, it’s easy to get transfixed by complicated new advancements and opportunities. So how do our forward-thinking teams ensure they can tackle this technical work while also prioritizing the experience of our users? 

That’s a question constantly on the mind of Emily Galloway, Spotify’s Head of Product Design for Personalization. Her team’s role is to design content experiences that connect listeners and creators. This requires understanding our machine learning capabilities as they relate to personalization to leverage them in a way that is engaging, simple, and fun for our users. 

“Design is often associated with how something looks. Yet when designing for content experiences, we have to consider both the pixels and decibels. It’s more about how it works and how it makes you feel,” Emily explains to For the Record. “It’s about being thoughtful and intentional—in a human way—about how we create our product. I am a design thinker and a human-centric thinker at my core. People come to Spotify to be entertained, relaxed, pumped up, and informed. They come for the content. And my team is really there to think about that user desire for personalized content. What are we recommending, when, and why?”

The Personalization Design team helps create core surfaces like Home and Search, along with much-loved features like Discover Weekly, Blend, and DJ. So to better understand just how to think about the design behind each of these, we asked Emily a few questions of our own.

How does design thinking work to help us keep our listeners in mind?

When you work for a company, you know too much about how things work, which means you are not the end user. Design helps us solve problems by thinking within their mindset. It’s our job to be empathetic to our users. We have to put ourselves in their shoes and think about how they experience something in their everyday life. A big thing to keep in mind is that when using Spotify, phones are often in pockets and people look at the screen in quick, split-second moments. 

Without design, the question often becomes, “How do we do something technically?” For those of us working at Spotify, we understand how or why we’re programming something technically in a certain way, but users don’t understand that—nor should they have to. What they need is to experience the product positively, to get something out of it. We’re accountable for creating user value. We really are there to keep the human, the end user, at the forefront. 

Without this thinking, our products would be overcomplicated. Things would be confusing and hard to use, from a functionality perspective. Good design is about simplicity and should largely remain invisible. 

But design is also additive: It adds delight. That’s what I love about projects like DJ or Jam that are actually creating connection and meaning. Design is not afraid to talk about the emotional side—how things make you feel. 

How does design relate to personalization?

Personalization is at the heart of what we do, and design plays an important role in personalization.  

Historically, Spotify’s personalization efforts happened across playlists and surfaces like Home and Search. But over time we utilized new technologies to drive more opportunities for personalization. This started from a Hack Week project back in the day to become Discover Weekly, our first successful algorithmically driven playlist. It then gave way to Blend, which was designed for a more social listening experience. And more recently, to DJ, our new experience that harnesses the power of AI and editorial expertise to help tell artists’ stories and better contextualize their songs. It utilizes an AI voice that makes personalization possible like never before—and it’s a whole new way for our listeners to experience Spotify’s personalization. 

When designing personalized experiences like these, we must think “content first,” knowing people come to Spotify for the content. Design ultimately makes it feel simple and human and creates experiences that users love. If recommendations are a math problem, then resonance is a design problem.

But we also have to have what I like to call “tech empathy”—empathy for the technology itself. My team, which is a mix of product designers and content designers, has to understand how the technology works to design our recommendations for the programming. Personalization designers need to understand the ways in which we’re working with complex technology like machine learning, generative AI, and algorithms. Our designers need to consider what signals we’re getting that will allow our recommendations to get better in real time and overtime. And when a recommendation is wrong, or a user just wants a different mood, we need to design mechanisms for feedback and control. That really came into play when we developed our AI DJ.

Tell us the story of the inception of DJ.

We’re always trying to create more meaningful connections between listeners and creators in new and engaging ways. And we use technology to deliver this value. DJ is the perfect example of how we’re driving deeper, more meaningful connections through technology.

Prior to generative AI, a “trusted friend DJ” would have required thousands of writers, voice actors, and producers to pull this off—something that wasn’t technically, logistically, or financially possible. Now, new technologies have unlocked quality at scale. Xavier “X” Jernigan’s voice and personality delivers on our mission of creating more meaningful connections to hundreds of millions of people. Generative AI made the once impossible feel magical.

To bring DJ to life we answered some core experiential questions knowing we are taking listeners on a journey with both familiar and unfamiliar music. We asked questions such as: What does it mean to give context to listening? How do we visualize AI in a human way? You can see this in how the DJ introduces itself in a playful way—owning that it’s an AI that doesn’t set timers or turn on lights. 

We also put a lot of thought into how we designed the character, since it is more than a voice. 

Ultimately, we really wanted to lean into making it feel more like a trusted music guide, as well as having an approachable personality. So much of our brand is human playfulness, so we made a major decision to acquire Sonantic and create a more realistic, friendly voice. And that led to Xavier training the model to be our first voice. His background and expertise made him the perfect choice.

With new technologies like generative AI, what are some of the new ways you’re thinking about your team and their work?

I’m challenging our team to think differently about the intersection of design and generative AI. We keep coming back to the conclusion that we don’t need to design that differently because our first principles still stand true. For example, we are still taking a content-first approach and we continue to strive for clarity and trust. We’ve realized that tech advancements are accelerating faster than ever, which makes design’s role more important than ever. 

Because there’s so much more complexity out there with generative AI, it means the human needs must be kept in mind even more. At the end of the day, if our users aren’t interested in a product or they don’t want to use it, what did we create it for? 

Emerging technology inspires you to think differently and to look from different angles. The world is trying to figure this out together, and at Spotify we’re not using technology to use technology. We’re using technology to deliver joy and value and meet our goals of driving discovery and connections in the process.