We want a lawyer, pig!

OK, punks!

Nothing is grounded.

But I’d still like to buy an

elephant gun, please.

I am NOT an #Organism-Whole,

I am a

Well, as I’m

conscious, my

actions – and my

symbols for those

actions – are

grounded in the

OK, so we’re NOT

grounded directly …

… but we ARE grounded indirectly, since we learn to use

symbols from the texts arising from

YOUR grounded uses.

My words have

never carried so

much meaning now

that I can directly

ground them via

actions in the

Some colours

make me feel

While others

make me see

Some make me

with envy!

@everycolorbot is a minimalist data-only Twitterbot.

The bot generates a random six-digit color hex-code (for an R-G-B

Red/Green/Blue mix) and a swatch of corresponding color.

Though very simple, can we say that this bot’s use of RGB symbols is grounded in external visual reality?

Dulux uses pretentious names with positive effect, but a bot might call this one “cow urine” or “rusty battleship”.

This bot would exhibit humor and visual appreciation, while grounding its use of color symbols in real stimuli.

The RGB symbol-codes in @everycolorbot are not used as

linguistic symbols, and are not used to convey semantics.

What if we build a bot that assigns meaningful color names to these arbitrary RGB symbols?

First, let’s ground the meaning of color

words in actual RGB codes that a computer can render on screen.

When a bot combines color words, it can also combine their

RGB color codes.

A compositional semantics for linguistic symbols is paired to a compositional semantics for RGB codes,

so that we can also ground the meaning of complex phrases.

We can use Web n-grams to suggest attested combinations of

our color stereotypes, such as “paper tiger” and “rose garden”. Readymade combinations of words make much more sense

than purely random ones.

The lower the n-gram frequency, the less conventional the readymade ...

… so the more striking and unusual the color name that can be derived.

Questions / Judgments

@HueHueBot (Machine names)

ColorLovers.com (Human names)

Q1: Most Descriptive name

70.4% 29.6%

Q2: Most Preferred name

70.2% 29.8%

Q3: Most Creative name

69.1% 30.9%