The style transfer example in the Humans in the Loop essay reminds me of a tool that won the audience's favorite award at the SIGGRAPH 2019 conference that I attended. It was a Microsoft-Paint-style tool where the user can choose various painting utensils and colors to draw things on a canvas, and a photorealistic version of what they have painted would show up in the space to the right. For example, if I painted the bottom part of the canvas solid blue, a partial picture of some body of water would show up at the bottom of the image on the right. I could then add mountains by painting green triangles on top of the blue solid region. The live demonstration of this mighty tool took the audience by storm. However, I personally did not appreciate the tool as much as the rest of the audience seemed to do, for similar reasons mentioned in the essay. This tool essentially allows users to quickly and easily create an image of a scenery that looks real, replacing the need for using Photoshop to achieve the same result. Just like how "when we imagine “automating” a pursuit like music making, we’re forced to balance the product of work with something deeper — the meaning we derive from the process of doing it," this tool takes away the fun and meaning of using Photoshop to create a photorealistic scenery that doesn't exist in real life. One part of the fun about composing an image in Photoshop is that we pick the materials we'll use as parts of the final image, and a lot of thinking and exploring goes into that process. The ability to fine tune layers in Photoshop is also something that an automation tool might not offer. Moreover, the user might not feel that this piece of work is really their creation because of how easy it is to generate an image of fake scenery photo.

The work that Allison Parrish has done with words and poems is incredibly fun! You can feel that the results are not generated by a human as the words and sentences in the modified poems often don't exactly make sense, yet they still provoke certain familiar responses in us.