Moreover, it blurs the boundary between a business or operation that might use some kind of ML for part of what it does, versus an enterprise that consists entirely (or mostly) of ML. This simple claim hides as much as it reveals: the term “artificial intelligence” has become a marketing buzzword in recent years, papering over many different kinds of ML that are in use (see MacKenzie, 2017, p. Their stated goal is to use ML to automate the kinds of decisions usually made by human mastering engineers. The more unique service LANDR offers is automated music mastering, built on top of supervised machine learning (ML), branded as artificial intelligence (AI). But this option is offered by many services on the Internet. With a single click (and a credit card transaction), LANDR users can distribute finished tracks across major music platforms like Spotify, Apple Music, Google Play, Tidal, Deezer, “and everywhere else that matters” ( About LANDR, n.d.). Echoing Kodak’s 1888 slogan, “You press the button, we do the rest,” LANDR promises its customers ease, seamlessness, and simplicity for the final stages of recording and releasing music: mastering and distribution. “Create, we’ll do the rest,” insists the tagline for LANDR, an online music mastering service ( About LANDR, n.d.). And unlike many other new media firms, LANDR’s connection to its local music scene has been essential to its development, growth, and authority, even as they have since moved on from that scene, and even as the relationship was never fully reciprocal. While LANDR claims to automate the work of mastering engineers, it appears to expand and morph the definition of mastering itself: it devalues people’s aesthetic labor as it establishes higher standards for recordings online. To parochialize the machine learning part of what LANDR does, this study spirals in from bigger contexts to smaller ones: LANDR’s place between the new media industry and the mastering industry the music scene in their home city, Montreal, Quebec LANDR use by DIY musicians and independent engineers and, finally, the LANDR interface and the sound it produces in use. Yet we cannot know exactly how much of a role or what role machine learning plays in LANDR. Increasingly, machine learning will become an integral part of the processing of sounds and images, shaping the way our culture sounds, looks, and feels. This article proposes a contextualist approach to machine learning and aesthetics, using LANDR, an online platform that offers automated music mastering and that trumpets its use of supervised machine learning, branded as artificial intelligence (AI). All subjects Allied Health Cardiology & Cardiovascular Medicine Dentistry Emergency Medicine & Critical Care Endocrinology & Metabolism Environmental Science General Medicine Geriatrics Infectious Diseases Medico-legal Neurology Nursing Nutrition Obstetrics & Gynecology Oncology Orthopaedics & Sports Medicine Otolaryngology Palliative Medicine & Chronic Care Pediatrics Pharmacology & Toxicology Psychiatry & Psychology Public Health Pulmonary & Respiratory Medicine Radiology Research Methods & Evaluation Rheumatology Surgery Tropical Medicine Veterinary Medicine Cell Biology Clinical Biochemistry Environmental Science Life Sciences Neuroscience Pharmacology & Toxicology Biomedical Engineering Engineering & Computing Environmental Engineering Materials Science Anthropology & Archaeology Communication & Media Studies Criminology & Criminal Justice Cultural Studies Economics & Development Education Environmental Studies Ethnic Studies Family Studies Gender Studies Geography Gerontology & Aging Group Studies History Information Science Interpersonal Violence Language & Linguistics Law Management & Organization Studies Marketing & Hospitality Music Peace Studies & Conflict Resolution Philosophy Politics & International Relations Psychoanalysis Psychology & Counseling Public Administration Regional Studies Religion Research Methods & Evaluation Science & Society Studies Social Work & Social Policy Sociology Special Education Urban Studies & Planning BROWSE JOURNALS
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