Sixty years ago, illustrator Arthur Radebaugh drew scenes from the future — that is, our present — including, quite presciently, remote education and work, self-driving cars, and an “electronic home library.” His Sunday strip that ran in newspapers, including the Chicago Tribune, was called “Closer Than We Think.”
(Recliners + the scrolling text of a book on the ceiling, yes please.)
Like the colors he used in the strips, all of this was bright and optimistic, and, of course, only half of the story. Within these frames, Radebaugh could not tackle, say, the complexities and drawbacks that would inevitably accompany a “one-world job market” or “push-button education.”
Viewing Radebaugh’s work today is jarring, and oddly, it now seems monochromatic. With bestsellers such as Kim Stanley Robinson’s The Ministry for the Future, this past year has been a reminder that at its best, science fiction can act both as entertainment and as a kind of cognitive behavioral therapy, letting us imagine and visualize the future in advance, and thus, hopefully, temper its stress and impact. The problem for the SF author, as always, is how to balance wide-eyed amazement with more realistic engagement with the implications of what is to come.
In the latest issue of the Journal of Digital Media Management, Dony West, Caitlin Denny, and Rebecca Ruud, archivists at Paramount Pictures, have an interesting case study: “Integrating Artificial Intelligence Metadata Within Paramount’s Digital Asset Management System.” They ran AI tools over a hundred years of film stills from the legendary movie studio.
After reading this article, I hereby declare that we replace the Turing Test with the Vigoda Verification, in which the quality of an AI system is a measure of its ability to identify Abe Vigoda in a large corpus of images:
By using separate fields, the team can compare the AI-powered metadata against the metadata provided manually. A great example of the difference in keyword results can be seen by doing an ‘all content’ search and comparing numbers of images tagged with Abe Vigoda, the beloved actor from ‘The Godfather’ franchise.
The manually tagged metadata resulted in 119 images of the actor; in contrast, the AI-powered metadata fetched only 22 images from the same set of photographs.
Not great, but the authors note that this is just a start and the direction is promising:
Most of the new and correct ‘Celebrity’ tags created by the AI platform were of crew members on set and political figures at events — people that the librarians would not normally tag in the ‘Keywords’ field. For example, the AI tagged New York City Mayor Abraham Beame on the set of ‘Three Days of the Condor’ (1975) — someone who had not previously been manually tagged. The AI celebrity detection was also able to tag the same celebrity across their lifetime, recognising Gloria Swanson from her 1924 role in ‘Manhandled’ as well as in the 1950 film ‘Sunset Boulevard’.
There are lesser known talent or non-starring actors that rely on manual tagging based on the team’s personal entertainment and film knowledge…A Stills Archive team favourite ‘Keywords’ tag is of Catherine Coulson, most recognisable as the Log Lady in David Lynch’s ‘Twin Peaks’ television series, showing up as First Assistant Cameraperson on ‘Star Trek II:The Wrath of Khan’. This is someone who would not normally be listed in the set of talent to tag, but the team’s personal knowledge was used to identify and tag her. She was not tagged by the AI platform.
The Coulson Conundrum leads us once again to a common theme of this newsletter: We need to imagine a healthier, more productive collaboration between human experts and raw AI power. These processes and systems are yet to be developed, but seem like a key project for the 2020s.
Global Hip Hop Studies is a new academic journal, and I found one of its first articles utterly fascinating. Ethiraj Grabriel Dattatreyan and Jaspal Naveel Singh present an ethnographic study of a small rap studio in Delhi, India, in a way that borders on the cinematic. The drama follows the collision of local culture and a group of friends with YouTube and GarageBand and the world far beyond Delhi, with unexpected results.
A decade ago, Singh brought some do-it-yourself recording technology to the south side of Delhi, and introduced it to a cluster of young MCs who were working together on dance moves and rap styles. The impact of music tech and the internet — how a genre and culture that began in the Bronx made its way around the world, and through videos and MP3s posted online, to this corner of a huge city in India — is amazing to watch:
Sonal, a Sikh b-boy, who had travelled on the metro for over an hour from his working-class neighbourhood in West Delhi to participate in the day’s session, stood in the narrow area between the bed and the recording equipment. As he sat, he quietly and intently watched as Singh demonstrated how the recording and music production technology that he brought with him from Germany worked. A group of young men was on the veranda just outside the apartment, where Singh had placed a small cot and a couple of plastic chairs. They were huddled around a smart phone listening to a new track on YouTube that one of them wanted to share with the others; a Nigerian hip hop-inspired pop song recorded by an underground artist from Lagos.
All of these young men had been b-boying for several years prior to Singh’s and my arrival in Delhi to conduct research on the local hip hop scene, a scene each of us had got wind of through underground hip hop networks in our respective national contexts – the United States and Germany. Both of us were curious about how these young men living on the margins of Delhi’s explosive growth and development in the last ten years had found hip hop and had each, respectively, travelled to Delhi to do ethnographic research in the scene. As we got to know them, it became evident that the infrastructural imaginaries, made possible as a result of 3G and 4G network expansion in India, allowed these young men who live in the marginal habitations of Delhi to access and make b-boying their own. By watching YouTube videos and connecting with b-boys from all over the world on social media, they learned the latest takes on classic dance moves that originated in the South Bronx over five decades ago. Videos of b-boys from Seoul, Marseille, New York and Los Angeles taught them how to top rock, baby spin and airflare.
The concept of infrastructural imaginaries is new to me, but once you hear it and think about it, it sticks.
Sonal, by the way, is a pseudonym, and he went on to become one of the most famous rappers in India. And while that sounds like a great ending to the drama detailed in the article, the authors note the sad downside to what happened. The DIY tech that transfixed the young MCs in South Delhi ultimately ended up pushing them away from each other. What began as some teenage friends huddled around a smartphone, watching hip hop videos from America, France, Korea, and Nigeria, and then dancing those moves and rapping those verses together across the streets of their city, is lost as the ability to record and market themselves individually inevitably takes over.
A reminder that what technology and the internet can bring together, it can just as easily pull apart.
(E. Gabriel Dattatreyan and Jaspal Naveel Singh, “Ciphers, ‘hoods and digital DIY studios in India: Negotiating aspirational individuality and hip hop collectivity.” Global Hip Hop Studies, 1(1), pp. 25-45.)