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Early projection test, Waterfall of Meaning

People + AI Reseach (PAIR)2019/2019

Barbican Centre

Barbican Centre
London, United Kingdom

A poetic glimpse into the interior of an AI, showing how a machine absorbs human associations between words.

The starting point
Once the Barbican reached out to PAIR about having an installation at their More than Human exhibit, the team knew they wanted to show visitors machine learning in a way that would be very relatable. Language is something that everyone uses and associating words is something humans do and a machine learning model learns.

The project in a nutshell
Language is subtle. Words may have multiple meanings and the same word can be used in different ways. This flexibility speaks to the richness of human language, full of associations and subtext. We may subconsciously consider certain words to be new or old, good or bad, male or female. When machines “read” text--from books, articles, letters--they start to learn how language is used and to pick up on the multiple associations that may exist. For example: how are the words “caviar” and “pizza” used? Do they show up in the same context? Are they used in the same way? Waterfall of Meaning uses technology called ‘word embeddings’ to analyse millions of existing English sentences and map words’ meaning based on their use. When a word crosses one of the axes, its location shows where it falls on the spectrum: more or less male or female, for instance.

The technology
Waterfall of Meaning is based on a technology in which a machine learning system analyzes millions of sentences to create a geometric "map" of word meanings. Such maps, known as "word embeddings," have become common in modern AI software. However, unlike a conventional map (which exists in two dimensions) or a globe (in three), the word embedding used in this piece exists in a space of hundreds of dimensions.

These dimensions help the machine represent some of the subtleties of language usage: in a sense, it's a way of transforming meaning into math. Certain directions in a word embedding map may reflect contrasts such as female vs. male, or good vs. bad. Understanding how these implicit dimensions form is currently a subject of great interest, both as a scientific question and as a type of transparency, helping us peer inside the black box of this type of AI. But we can also view the embedding a model of how humans have collectively used words, giving us a way to measure connotations quantitatively. In the end, this piece is not so much a portrait of a machine but a picture of how humans speak.
To this end, any biases that are found in the data will be reflected in the model as well. For this reason, it's paramount to ensure that these models are not being used in ways that enforce existing biases, and to continue developing ways to de-bias these models.

The exhibition
The Barbican's AI: More than Human (16 May-26 Aug 2019) is an major exhibition exploring creative and scientific developments in artificial intelligence demonstrating its potential to revolutionise our lives. Part of Life Rewired, the Barbican's 2019 season exploring what it means to be human when technology is changing everything.

Details

  • Title: Early projection test, Waterfall of Meaning
  • Creator: People + AI Reseach (PAIR)
  • Date: 2019/2019

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