Decoding Art powered by Artificial Intelligence

Artificial Intelligence-Art
This entry is part 2 of 3 in the series AI & ART

Introduction

Can Artificial Intelligence powered machines create art? Let’s explore the question further this week. We will start by focusing on two questions:
  • What is Artificial Intelligence is?
  • How is it different from traditional computing?

AI is different from the Human Brain–and that’s OK.

There are many misconceptions of what Artificial Intelligence is. The biggest one is that Artificial Intelligence needs to function like the human mind to achieve the same feats as humans. People talk about computers not having imagination or creativity, emotions, or experiences. The implication is that without these properties AI can never match human performance. The truth, as we will see, is that Artificial Intelligence powered machines have a different way of functioning. One that still allows them to match the human brain even when it comes to creativity.
 
We use many different terms when talking about the domain of Artificial Intelligence. These include ‘machine learning’ and ‘deep learning.’ For the sake of convenience, we’ll treat them as having more or less the same meaning: AI.

The Shifting Goal Posts for Artificial Intelligence 

What we mean by Artificial Intelligence is always evolving. For example, at one point, we considered Optical Character Recognition (OCR) to be the domain of AI. But as the technology became standard, people started to think of it as mere computing, and not AI. So it might be difficult to define AI in terms of what it does. Instead, we need to understand AI in terms of how it functions.

From Traditional Computing to Artificial Intelligence

This may be an oversimplification, but it is easier to understand what AI is not by comparing to how the human mind works, but by comparing it to how traditional computing works. In traditional computing, you write the rules, then you put in the data, and you request a fixed result. For example, you teach a computer about numbers and maths, then give it a problem to solve (‘What is 2+2?’) and the computer gives you a fixed result based on the rules you have defined earlier. The value of such computing, of course, comes from the processing power that computers have. We humans can also solve 2+2 quickly enough, but if you had a million such calculations to do, a computer can process it all for you in seconds.
 
Artificial Intelligence differs from traditional computing in important ways: the data it works with is not fixed. AI will almost always begin with a fixed set of data, but along the way, it may choose to discard some data, or it may add the results of its own actions as additional data—learning from the results of its own actions, as it were.

Artificial Intelligence: Rules and Results

Similarly, unlike in traditional computing, the process or the reasoning that an Artificial Intelligence machine follows—the rules that it works with—are not fixed. An AI machine can have an open-ended mandate to achieve a certain result, and the reasoning, the path it takes to get to that result is flexible, unpredictable and determined by the machine itself.
 
In the same way, the results that Artificial Intelligence delivers can also be open-ended. A complex AI machine can work with an open mandate such as ‘run city traffic lights with maximum efficiency and prioritize ambulances and school buses’ rather than fixed results such as saving a document or calculating a formula.
 
This is a very different way of functioning than the human mind, but the results that AI computers can achieve already exceed human performance in many areas. AI already powers things like search engines, security surveillance, health prognostics, predictive customer service, dynamic and intelligent product pricing technologies, and much more. And AI machines do this far more efficiently than humans can.

Artificial Intelligence to Original Art

With these abilities, how would a machine go about creating art? A machine will not wait for inspiration, of course. And a machine does not grow up listening to stories or learning to sing and dance during childhood. So the first step would be to show a machine what art is.
 
From there, machines can ‘reverse engineer’ the properties of art. Reverse engineering is an important concept here that, in simple terms, refers to extracting knowledge or design patterns from a dataset (such a collection of paintings) and identifying what makes up a painting: the colors, the canvas, the textures, lines, color densities and hues, and so on.
 
Once a machine ‘knows’ what art is, it needs to get creative in order to produce new art. In the next article, we’ll explore how an AI-powered machine can create original art in mediums such a painting and music.
Image Source: Wikimedia
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