What do they think,
when they think about thinking.

Recursive display of intelligence

2019 New York, NY Student Work

Overview

An installation that situates one computer’s camera to look at its own code visualization, feeds the captured visual data back into the system as inputs and generates the next iteration, creating a recursive feedback loop.

Background

The project was set out to investigate the implication of current trajectory of Artificial Intelligence regarding the following 3 domains: 1. The autonomy of Artificial Intelligence, the idea of a conscious machine. 2. Shared characteristics within all forms of intelligence. 3. Creativity as a tool in the field of scientific / technology developments.

Context

Inspired by research found in the book The Promise of Artificial Intelligence, Reckoning and Judgment by Brian Cantwell Smith. Proposed the common attribute existed throughout the general forms of intelligence is the ability to recognise the metaphysical registration of other individual. The installation visualized ML5 machine learning’s properties as projections while feeding the pictures back in to the system as input, recreating the diagrams stems from the research. The final prototype was set out to be a manifested visual representation on self-awareness itself, to prompt the idea of common characteristics shared between all intelligences. Without siding with specific side of argument, the idea is rather to solidify different sides of discourses with embodied physical settings, bringing the abstract notions closer with real life elements.

What do they think,<br>when they think about thinking. Diagram 1
What do they think,<br>when they think about thinking. Diagram 2
What do they think,<br>when they think about thinking. Diagram 3
What do they think,<br>when they think about thinking. Image 4
What do they think,<br>when they think about thinking. Image
What do they think,<br>when they think about thinking. Image 5
Research Creative Coding Video Production Machine Learning Installation

Major Studio | Parsons, TNS

Instructors

Aaron Hill