AI and Context 

Algorithms, like all math based decision–making systems are completely blind to context.

Because machines operate on averages they simply are incapable to make sense of different situations. We (humans, designers, coders) cushion them with scenarios, narratives and views on what could happen, a list of meanings a human might be seeking.

A grand undertaking for us, because we’re asking ourselves to map out the entire human condition

The core principle of binary (Shannon) is that machines need not know what they’re conveying, and because of that all they do is pass around sealed envelopes of human–talk.

It is like someone would send you to meet 10 new people and ask you to write everything you’re going to say beforehand, put it an envelope and open it when you need to say something.

Better design of meaning and context (on the human side), together with experimentation in system architecture (machine) is could help with the collective friction we’re all feeling right now.

Published by Nitzan

I am a designer, writer and strategist with interest in machine learning, liminal thinking and complexity science. In my commercial work I help companies build innovative tools, design better qualitative processes, and lead that human machine collaboration with complexity in mind.

Leave a comment

Leave a Reply

This site uses Akismet to reduce spam. Learn how your comment data is processed.