This is the full version of my piece published on Queen’s Business Review.
Artificial Intelligence. The term has become ubiquitous in this digital age. Highly complex, opaque yet celebrated. We are grateful for the ease it brings through recommendation engines on retail, music and streaming platforms. Nevertheless, overwhelming choices have led us to trade in our purchasing behaviour and transaction data for an algorithm that simply reinforces our own tastes of the past.
What is “taste?”
How is it possible that the world’s most valuable company built an empire reimagining appearance of an ancient consumer-electronics industry, receive as many praises as criticism for their “timeless design?”
Through a philosophical lens, natural taste is “not a theoretical knowledge; it is a quick and exquisite application of rules which we do not even know.” The unknowingness of whether something is tasteful to us cannot be measured or captured by a singular algorithm.
Companies such as Facebook and Amazon dominate our digital identities — sorting us into behaviour-based clusters. Even with top Ph.D. hires, algorithms in these companies are heavily reliant on tracking our past behaviours, limiting our field of vision to extensions of the rearview mirror as opposed to organically new and creative content we may find tasteful down the road. Before Netflix dictated our next show and Amazon suggested our next purchase, we had to discover and make these choices for ourselves. The friction between decisions led to the consideration of various options, and through this, we aggregated our unique personal taste.
It is time to recognize the implications behind how advanced technologies of the modern day, such as artificial intelligence, may do more to set us back than propel us forward. Behind the noisy celebrations of buzzwords, algorithms are quietly curating and promoting generic content that can drastically alter our personal tastes.
Perhaps one of the greatest examples is a platform that boasts 83 million active users in a bid to define and rework artistic taste. In 2017, Spotify listeners spent half their time on the app exclusively listening to playlists. The service serves up a weekly “Discover” playlist that’s reportedly fine-tuned to each listener’s preference based on their Spotify “taste profile.” The playlist is curated strictly by machine and aims to find songs for the user that feed their particular music appetite. However, in a post by avid Spotify user Adam Pasick in Quartz, he outlines his shock when he heard the exact same tracks being played in a coffee shop as his Discover playlist. Homero, a barista and band member, was “given a nearly identical mixtape” as Adam that week. The reality that even having two billion playlists filtered through a supposedly advanced algorithm can still churn out identical results for two different listeners, proves the threat of AI promoting generic taste and content for all.
In 2015, EDM artist Tiesto released “Burn” on Spotify, a piece commissioned directly by the music streaming service catered for their workout playlists. Burn was created specifically to adapt to the running pace tempo of any listener. Unfortunately, the intent of artistic creation in the music industry has drastically progressed in this direction. The practice of making music designed to game algorithms and be successfully picked up by a Spotify playlist has inevitably created an era of “easy music.” George Ergatoudis, the former head of content at Spotify, admits that the industry is moving towards creation centred around understanding streaming algorithms: “There are pitches for specific playlists more often now. This didn’t happen even a year ago.” When artists notice that virality and popularity are being prioritized for vanilla musicians, they start to credit their idiosyncratic and unique musical styles as inferior. The intent of creating future music for the sake of pure artistic expression and vision is dwindling as a victim of demand for AI-driven homogeneity.
Furthermore, the potential of challenging, innovative and groundbreaking music has been put at stake. Algorithms like Spotify’s favour spikes in listenership and viral content. Studies have shown that consistently working safe and “easy music” into all playlists are fundamentally changing listeners’ collective preference and taste for what they consider a “good song” in the future. The Spotify-induced phenomenon of “lean back listening” has consequently spawned a new genre of music creation. Algorithmically optimized playlists entitled: “Ambient Chill,” “Chill Covers,” and the particularly popular “Chill Tracks” with over 2.4 million followers place easygoing and anesthetized tracks at the fingertips of listeners. A label owner commented bluntly, “the more vanilla the release, the better it works for Spotify. If it’s challenging music? Nah.” He continued by stating that much of their comparatively experimental and aggressive music goes unheard on the platform due to unfavourable exposure by Spotify algorithm. “It leaves artists behind. If Spotify is just feeding easy music to everybody, where does the art form go? Is anybody going to be able to push boundaries and break through to a wide audience anymore?”
Cultivating an ephemeral culture filled with mainstream pop music can only shape our taste towards uniform linearity and consequently damage authentic creativity in the long run. As Marian Mazzone, an art professor at the College of Charleston eloquently puts it, “Eventually, we may opt to shift our definition of art in order to make accommodation for the [so-called] creativity of artificial intelligence.” What used to be a boundless form of art to release frustration, passion, hunger, anger and personal identity has shrunk to feeding the automation of Musak.
The trend parallels across other industries. The Echo Look — Amazon’s take on a computerized fashion advisor — purports to recommend the ideal fashion, style, and taste for each user albeit standing as a lifeless black-box camera on shelves.
An interview with the director of a recent Netflix hit: All The Boys I’ve Loved Before, Susan Johnson, reveals that the movie was requested solely based on Netflix’s digital analysis. “[Netflix has] teams everywhere literally looking for what people are searching for. So they realized that people were looking for romantic comedies.” Evidently, investing in a film-version of the novel was not a consequence of Netflix investing in creativity, but in fuelling their commercial algorithm. Johnson even called the process “a little Big Brother,” with Netflix controlling what and how we consume. Moreover, Netflix stated that their recommendation algorithm “influences choice for about 80% of hours streamed” on the service. Thus, Netflix’s own content will undoubtedly benefit, being forcefully advertised regardless of each viewer’s true taste preference. In the end, not only was All The Boys I’ve Loved Before a mega-success, but it helped the service influence over 80 million subscribers to watch content in the rom-com genre for the remainder of Summer. Talk about generalizing taste.
In actuality, the increasing role of artificial intelligence does not make our fashion sense or music tastes more distinct — but instead silos us into a homogenizing box, calculating where we land in the “average” identity. The fact that these average identities come in minute shades (a song or two different on the Discover playlist), only means that they are far from unique.
Artificial Intelligence is undoubtedly shaping individual choices and the wider social fabric at every moment. Taken individually, it appears that sacrificing privacy and data is worthwhile for the ease of convenience and efficiency. Presently, at scale, our preferences are being driven by the hands of the massive technology companies whom we’ve handed the wheel. In this case, the salient tradeoff in this glossy AI age is not privacy, but our personal taste and identity.
The manipulation of an entire industry led by Spotify’s algorithms has become the operating motive and expected standard for music lovers and artists. Conforming to the algorithm game stifles innovation borne of colliding tastes and ideas. Needless to say, colouring outside of the lines is nearly impossible when constrained in a future of singular taste and bland inspiration. The subtle yet damaging outcome of displacing the judgment of taste to algorithms will inevitably rob us of our humanity.
In all, we should tread gently on our reliance on leading-edge technology, remaining wary of its threatening ability to suppress true novelty and cultivate a homogenous view on creativity.
