MAKING TOMORROW'S CULTURE TODAY

Ben Bogart explores the concept of “machine subjectivity” within the realm of artificial intelligence and machine learning. Bogart delves into the intricate relationship between human cognitive processes and autonomous machines. They challenge the conventional view of machine learning as merely objective statistical models, proposing instead that these systems can be seen as subjective entities capable of autonomous learning and decision-making. Bogart discusses how machines, through unsupervised learning algorithms, categorize and interpret data, (…)

Allison Parrish, a programmer, poet, and educator at NYU’s Interactive Telecommunications Program, discusses her latest project on computer-generated poetry. Her book, “Articulations,” explores poetic similarity using a corpus from Project Gutenberg and the CMU Pronouncing Dictionary to model phonetic resemblances. Parrish’s work involves constructing poetry by linking lines that sound alike, creating a unique phonetic cohesion. She emphasizes that her approach to poetry involves using computational tools not just to mimic human creation but to extend artistic capabilities and explore new forms of expression. Parish critiques the notion of AI replacing human creativity, arguing instead for a view of AI as an enhancement that brings new dimensions to poetic exploration. She highlights the influence of randomness and procedural generation in art, referencing historical and contemporary examples to underline that art made with computational methods still reflects the artist’s intent and personality.