Algorithms in art and culture: New publication explores music in the age of AI
How are algorithms influencing the production and consumption of culture? A new white paper (PDF) on artificial intelligence and music recommendation, released today by the Schwartz Reisman Institute and authored by Georgina Born (Oxford University), Jeremy Morris (University of Madison-Wisconsin), Ashton Anderson (U of T), and Fernando Diaz (Google), argues algorithms’ impacts are profound and far-reaching.
Global access to art, culture, and entertainment products—music, movies, books, and more—has undergone fundamental changes over the past 20 years in light of groundbreaking developments in artificial intelligence.
Users of streaming services like Netflix and Spotify are all-too-familiar with the role of data collection and algorithmic analysis of their streaming habits—and the subsequently generated recommendations. But this is only one angle of the many ways in which AI tools are transforming the arts and culture industries. AI is now used in the production process as well; algorithms can generate photos or write songs on their own. Warner Music “signed” an algorithm to a record deal in 2019.
But while artificial intelligence is drastically reshaping cultural industries around the world, we have yet to fully understand the consequences.
“The societal impacts these algorithmic developments are having on the production, circulation, and consumption of culture remain largely unknown,” says Schwartz Reisman Faculty Affiliate Ashton Anderson, an assistant professor of computer science at the University of Toronto.
Anderson’s research in an area known as computational social science aims to bridge the divide between computer science and the social sciences. He uses computation to study online well-being—for example, studying the impact of “echo chambers” on social media. Such interdisciplinary work is a key component of the Schwartz Reisman Institute’s mission to reconceptualize common notions of the ways technology, systems, and society interact.
In October of 2019, Anderson and his collaborators—Oxford Professor of Music and Anthropology Georgina Born; Jeremy Morris, associate professor of media and cultural studies at the University of Wisconsin-Madison; and Fernando Diaz, a research scientist at Google Montreal and Canada CIFAR AI chair—convened a CIFAR AI & Society workshop to explore the effects of AI on the curation of culture, with a particular focus on the music industry.
“We deliberately brought together communications and computer science scholars, musicians, industry members, and users to map out the major issues we could foresee now that cultural products are largely being distributed via algorithms on global platforms,” says Anderson.
A resulting report on the workshop’s findings and recommendations for further research is now available.
➦ Read the report: “Artificial intelligence, music recommendation, and the curation of culture” (PDF)
“I’m delighted to see us producing this report at SRI,” says SRI Director Gillian K. Hadfield. “This project is aligned with the work that SRI Engineering Lead Ron Bodkin is leading to improve AI systems’ objectives and recommender systems, surveying research in this area and building new techniques. Recommendation is a huge part of the daily role AI plays in our lives, and ensuring it’s aligned with human values is a key part of SRI’s mission.”
“I'm glad to see SRI contributing a thoughtful interdisciplinary perspective to the considerations of how AI is affecting media and culture,” adds Bodkin. “This report raises important topics for how various stakeholders should be able to participate and how to allow for more autonomy and diversity.
“I believe that incorporating a wider range of values and increasing agency is a critical direction for recommendation systems and algorithmically curated media,” says Bodkin. “The report's call for giving stakeholders meaningful controls over recommendation systems is important and it's an area where we're exploring how AI research can contribute.”
Three distinct themes emerged from the CIFAR AI & Society workshop
First, participants agreed there will be major long-term impacts of the use of AI-driven technologies on cultural consumption and creation. For example, if algorithms decide what to distribute and recommend—and to whom and when—then arts and culture creators, and the organizations who fund them, may be incentivized to produce content that is more likely to get listener exposure or reach fans, according to how algorithms work to connect audiences with content.
Second, participants all saw “a clear need to enrich existing AI-driven technologies so they can better serve diverse communities and genres of culture, art, and music,” says Anderson. If algorithms overly generalize information about certain groups, subcultures, or communities—whether by race, gender, or other identity markers—Anderson notes that “we risk reinforcing rigid and potentially harmful social boundaries.”
A third theme emerging from the workshop is that the curation of culture always has involved, and always will involve, balancing competing objectives. “The extraction of personal data has been privatized and corporatized by curation platforms, but as yet without any public debate or intervention for accountability and transparency,” says Anderson. In other words, how should we measure the convenience and increased accessibility that streaming platforms provide against the fact that they threaten to harm important ideals of public safety, such as the right to privacy and cultural sovereignty?
The workshop’s report considers almost every step of the music industry’s processes, from the ways in which algorithms manipulate the existing variety of content itself, to the ways in which content is produced, distributed, valued, understood, and consumed around the world—including the ways in which artists and creators are remunerated.
“We need to interrogate the theory of value built into these systems and the way that AI, as well as the increasing pressures to be seen and heard on these crowded platforms, are affecting not just users but the very production of music itself.”
Important questions explored in the report include:
What assumptions are built into media recommendation systems?
How do music streaming services and their algorithms posit a “listening subject”—one with uncanny resemblance to the neoliberal subject? What happens to the crucial role of social and community relationships at the heart of the experience of music?
How can we ensure appropriate cultural expertise is represented in algorithmic and technological design?
AI-based classifications of music may be highly efficient, but they do not necessarily reflect a truly “intelligent” analysis of music. Can they ever have any “real” understanding of what music is?
Will music and musical tastes become increasingly homogenized due to AI-based systems of production, promotion, and distribution? Do we risk mis- or under-representing marginalized communities, or their agency to represent themselves?
Is the personalization of algorithms too seductive? Do we risk no longer “thinking for ourselves”?
“This report is the first major document to recognize and describe the societal effects of the algorithmic revolution in cultural industries,” says Anderson. “Existing journals are virtually entirely aligned with only one of the many stakeholder groups that took part in this interdisciplinary effort so, unfortunately, publishing this report in one of these journals would be next to impossible.
“We’re very happy to have Schwartz Reisman publish this report, as our methodology and the cross-disciplinary expertise we convened is well-aligned with SRI’s mission to straddle traditional academic boundaries in the pursuit of understanding how powerful new technologies shape the world around us.”
Clockwise from top left: Georgina Born (Oxford University), Jeremy Morris (University of Madison-Wisconsin), Fernando Diaz (Google), Ashton Anderson (University of Toronto).
