Lev Manovich’s The Language of New Media outlines five key principles that define new media: numerical representation, modularity, automation, variability, and transcoding. These principles distinguish digital media from traditional media and influence its creation, distribution, and consumption.
One passage that stands out is:
“A new media object is subject to algorithmic manipulation. In other words, media becomes programmable.”
This refers to the principle of automation, which highlights how digital media can be created, modified, and managed with minimal human intervention. Unlike traditional media, where editing was a manual and laborious process, new media leverages algorithms to streamline and even generate content.
A clear example of automation in today’s world is AI-driven content creation, such as machine-generated art or auto-captioning in videos. Platforms like TikTok, which heavily rely on algorithmic filtering and automated effects, showcase this principle in action.
However, Manovich’s insight also raises questions about authorship and creativity. If media can be algorithmically generated, where does human creativity fit in? While automation empowers creators, it also introduces ethical concerns, brought out by creations such as deepfakes and AI-generated misinformation.
From my perspective as a computer science major studying AI, automation represents both an exciting innovation and a complex challenge. Machine learning models can generate text, images, and even videos rather accurately, but they also inherit biases from training data and can be difficult or even impossible to control. The development of explainable AI and ethical AI frameworks is crucial to ensuring that automation serves as a tool for enhancing creativity rather than replacing human input entirely.
Understanding Manovich’s principles helps us critically analyze how technology shapes media. Automation makes content creation more accessible, but it also challenges traditional notions of authorship. As we continue integrating automation into software and media, we need to strike a balance between efficiency and authenticity.