Machine Learning

“Machine Learning” is the ability of a computer algorithm to improve on its own, taking a data set and extrapolating from it to make predictions and decisions without any additional programming. Over the past few years, advances in this field have led to some incredible innovations—self-driving cars, fraud detection, and voice assistant software—and technologies with troubling implications—informational echo chambers, data privacy, and advances in the finance industry. Over the past few months, I’ve become entirely reliant on computers for human connection, art, business, and communication, more so than at any other time in my life. The ability of computers and algorithms to mimic the natural world, provide the feeling of genuine human connection, and predict and understand our emotions and desires has been a saving grace during the coronavirus pandemic, and it is hard to imagine what life was like during the 1918 pandemic without any of these technologies.

 As someone who loves playing Baroque music, especially the works of Bach, I love his ability to spin an entire piece out of a small motive, using techniques of counterpoint and form that are not unlike an algorithm. As I went back and forth from the piano to the computer over the course of the past few months, I’ve felt surrounded by algorithms of different sorts, curating my newsfeed, music choices, and social connections, in ways that are simultaneously wonderful and worrisome. “Machine Learning” begins with an intricate, searching texture, which ultimately settles on a quiet, syncopated motive in the piano. I structured the rest of the piece on this motive, this small data point, which then could be extrapolated to form each section of the piece. Much like our experience of the computer-curated world we’ve all been inhabiting over the past few months and years, I aimed to write music that was simultaneously beautiful, exhilarating, overwhelming, and exhausting. Thank you to the musicians from Copland House for their dedicated performance of the piece, especially given the difficult circumstances.