Microlearning resources are most commonly and effectively delivered via digital technology (but microlearning is not defined by technology).

Microlearning can be achieved on the go when the learner wants it or needs it.

The Internet‐connected smartphone is a major driver of microlearning because it provides access to learning on the go (i.e. mobile learning) and is nearly always accessible to most people.

Microlearning on Web 2.0 applications also offers the benefit of a collaborative learning space.

Lisa says she would’ve expected the Copyright Office to focus more on the nature of the inputs

how much human involvement does a creator have to exert over a machine to claim ownership of its output? 

This isn’t the first time the legal system has wrestled with that question. It first came up when cameras were invented; the argument then was that you couldn’t protect a photograph as your own, since the machine was the one capturing the image.

The Copyright Office, surprisingly, introduced this predictability standard instead.

He used the amusing analogy of Jackson Pollock, who made his art by flinging paint around and seeing what happened; nobody questioned his ability to copyright those works.

But in a more salient point for creators, the lawyer argued that the Copyright Office was “incorrectly focusing on the output of the tool rather than the input from the human.”

the best thing you can do is to be sure you’re employing as much human creativity in the process as possible.

This might mean writing prompts with as much detail as possible

A final note: as Lisa points out, the Copyright Office did indicate that if someone sufficiently modifies generated output, that could be protectable. So, If you’re using generative AI as a starting point — e.g., using ChatGPT to create a rough draft and then re-writing it for your own voice — be sure you document the changes you made before you try to file for copyright protection, and then explain it in the application.