Paradigm-shifting inventions/technologies have spurred the anthropology of digital media to expand into several subfields. In the last thirty years, technological advancement has been rapid from dial-up internet to smartphones and social media. Each one of them has significantly influenced how humans form and maintain relationships, shaping the nature and content of social interactions. With the advancement in AI, we now sit on the precipice of another fundamental shift in how humans communicate in a social purview.
AI intelligence has now evolved into deep learning. Researchers studying the anthropology of deep learning explain the role of bias in deep learning algorithms. Deep learning is a subset of machine learning that broadly uses a hierarchy of convolutional operations arranged specifically to process and analyze large amounts of data. It has become increasingly important in a wide range of applications, from image recognition to natural language processing. In recent months, Large Language Model (LLM) AI is perceived as the foremost aspect of this academic overlap between hard and soft sciences. Several new cultural facets are surfacing in this age, not just the ones embedded in the algorithms but those among the users such as the culture of condensed knowledge.
This paper looks at how the advent of AI models that are both accessible and produce salient output is understood in society. It discusses how we need to broaden our studies of human nature through this advent of machine learning asking pertinent questions about the resultant job insecurities and the rising tensions in creative fields over the sanctity of software-generated art and music. We further delve into the impact on academic culture with the onset of LLM.
