Reading 2: Amplifying The Uncanny

The reading begins with explaining that in recent years, machine learning systems grew excellent at producing images, with major focus on creating human faces that seem very real, resulting in possible controversies with technology such as deepfake.

Deepfake is a technology of generating faces by referring to existing images, to create brand new faces which cannot be found through image searches due to them being unique, which leads to the reading further explaining machine learning where the machine finetunes information to develop better or more realistic images. In which leads to the concept of the uncanny valley, which explains how the closer something resembles human, the more welcome it would be, except for particular range of resemblance which seems creepy.

While uncanniness is usually avoided, the reading explores pushing uncanniness to the limit, exaggerating certain facial features to make them look unpleasant, even pushing further to extending to a group of people. The takeaway I find from the reading is that while machines can extend a process, it does not know the limits and can push beyond what we find desirable, for better or for worse.

What does this mean for us? It’s the human’s physical touch and control that adjusts generative art to something that is useful for our purposes. A system that runs without control is likely to create a disaster, so from an artist’s point of view, we need to learn what the limits should be and how to control them to reach a parallel with uncanniness.

Exploratory Generative Study: Deckbuilder

A physical deckbuilder card game with a range of random results to keep replay value.

What it contains:

  • A goal
  • A list of tools of the player in the form of cards
  • Randomised combination of choices (dependent on card draw)
  • Randomised hindrances to achieving the goal (random event deck)
  • Control by the players in the form of choosing which tools to use
  • Lack of full control as the randomisation might act against the player’s decisions, leading to unexpected or chaotic results

Possible other additions:

  • Die rolls to raise random results (controlled to create interesting results; 6 isn’t necessarily better than 1)
  • Multiplayer (increases entropy and unpredictability)
  • Multiple goals

Example inspirations:

  • Aeon’s End
  • Gloomhaven
  • Slay the Spire
  • Monster Train
  • Joking Hazard

Monster Train might be the best deckbuilder since Slay The Spire | Rock Paper Shotgun

Joking Hazard Game

Reading 1: Closed systems: Generative art and Software Abstraction

Marius Watz describes generative art as “a computational model of creativity combining principles of unpredictability with the purity of logic”. He explains that from results that cannot be created through human hands, the nature of work is complex, even unpredictable. Generative art often takes inspiration from nature, but there is a struggle between natural forms and mechanical forms; what artists balance is how it can appear natural yet refined through their control, creating a chaotic work that flows in a direction they wish.

Put simply the artist allows the computer to create countless results then handpick possibilities that suit their demands, controlling the process that it remains random yet able to only produce results that they find desirable. As long as the results are desirable, the more chaotic the variations of results the more preferable. This means they do not heavily restrict what can possibly happen; they just control the general direction of the work’s flow. Ultimately a level on unpredictability is a boon, the bane is when it goes fully out of control. What they want is an aesthetic mess that conveys their intentions; controlling so is the skill of the artist.

As a reminder, generative art isn’t a movement, it’s just a strategy for creating art. In fact generative art techniques have been dated in human history, from early days of medieval art techniques to later random computer generated screensavers. Artists have always employed chaos as a technique to keep their art lively, and produced unexpected results which are later studied and capitalised on.

Nowdays, generative art is actively used as a concept in creating works by artists. This is interesting for me, for it means that art can be presented at a partially developed stage, and results can be flexible, sometimes even affected by the audience or users of the work, creating more personal results. This has been used often in interactive media, such as games where the input of players may affect how the story or events turn out; the artists basically create what is known as a sandbox which allows many possible unique outcomes, many of which even unplanned by the artist themselves, hence creating a large range of experiences, allowing different people to share how they interacted with it in different lights.