"Now the whole point about machines is they are designed not to be random. When you call up a word processing program on your computer, you don't want it to be different every time you call it up. You want it to stay the same"

Rupert Sheldrake's quote underscores the fundamental principle of predictability in mechanical and digital systems. At the heart of his statement is the idea that machines are built to offer consistent, trusted results instead of random variability. This predictability is vital for their performance and our dependence on them.

Think about a word processing program as an example. When a user opens such a program, they expect it to work the same method each time, providing a familiar user interface and a set of features that facilitate performance. This consistency permits users to perform jobs efficiently without needing to relearn operations or adjust to unexpected habits. If word processors or other software application were to behave unexpectedly, it would significantly prevent their utility, triggering confusion and aggravation for users. This would negate the very purpose of having makers, which is to enhance procedures and minimize the cognitive and physical problems on human beings.

Sheldrake's mention of non-randomness likewise touches on the wider function of makers in society, which is to function as tools that extend human capabilities through their precision and repeatability. From commercial machinery to daily customer electronic devices, predictability guarantees devices deliver expected results, which is fundamental to planning, analysis, and execution in various domains ranging from making to data processing.

Furthermore, the quote subtly contrasts makers with human imagination and idea, which can be random and innovative. While randomness and originalities are the bedrock of human versatility and advancement, machines are created to help by offering a stable structure.

Nevertheless, the rise of expert system and machine learning introduces a nuanced layer to Sheldrake's viewpoint. While conventional devices are designed to be non-random, AI systems can introduce components of variation and learning. Nonetheless, even in AI, predictability in achieving goals is vital, although the paths can artistically adapt.

In summary, Sheldrake's observation highlights the need of stability and predictability in machines, ensuring they fulfill their purpose as trustworthy aides to human activity.