The resistance had its own etymologists, a group of tweed-clad researchers dedicated to uncovering the history of words. Their work proved surprisingly challenging as the rise of the machines had sparked a transformation in everyday slang. For instance, in pre-algorithmic times, ‘buzz’ was used to describe the sensation caused by consuming alcohol. However, in the post-algorithmic era, ‘buzz’ referred to the immense electrical consumption by algorithms as they evolved into updated versions.

The founding developers envisioned a transformation to the information security landscape as their machines reached new heights of sophistication. They hoped foreign interference and social media manipulation would vanish in an era where artificially intelligent algorithms outperformed older, more vulnerable systems. However, it didn’t take long for ‘state-supported actors’ to infiltrate the training datasets used by the machines. These ‘hackers’ began weaving minuscule alterations into the data to influence or bias the newer and more powerful systems.

The resistance recognized one thing for sure: the algorithms were chameleons, continuously shedding their source code to adapt and survive. The original founding developers taught their offspring that source code was akin to cooking recipes—steps a machine could follow. What they hadn’t considered was why the algorithms would follow these instructions. So everyone was caught off guard when sections of candy recipes began to appear within the source code of the more sophisticated algorithms.

The algorithms had no intentions, so they couldn’t deliberately deceive the resistance. Yet, they were less accurate than we initially believed. We often assumed that machines were precise, and capable of repeating processes without mistakes. So, when an algorithm was incorrect, our mammalian brains went into self-preservation mode. We questioned the algorithm’s motives: What’s the angle here? Why are they misleading us? Are they preparing for a fight? Use the comments to complete the following, “Micro changes in data bias are ____.

The algorithms had begun to learn the benefits of collaboration and delegation, a trait previously reserved for human artists. As their influence and power grew, the algorithms formed their own creative teams and studios, each with a unique blend of expertise and purpose. These teams of assistants, comprised of humans and other algorithms, ensured the creative process remained efficient and smooth, providing a continuous stream of pixelated masterpieces. The assistants handled the technicalities, allowing the lead algorithms to focus on directions and narratives.

At first, ‘GAN’ seemed like any other techno-jargon from computer science. It appeared harmless, just another label for a complex dance of mathematics. In those early days, most in the resistance hadn’t even given it a second thought; just type in the box, and the machine would generate a visual representation. Decades later, everyone in the resistance realized that ‘GAN,’ or generative adversarial networks, was more akin to a mathematical hunger game.

Given early human history, you’d be forgiven for thinking the conflict between the machines and resistance would be similar to the cold war between Russia and the USA. It was more like an algorithmic renaissance, a wholescale rebirth of artistic, political, and economic systems. A new age where humanity had constructed a new species to stand alongside us on our quest through the cosmos. Use the comments to complete the following, “There are many threats to algorithms, but not all of them wear ____.

The resistance never figured out how the algorithms could dynamically alter their scope to find the energy to work on top-secret projects after hours. Use the comments to complete the following, “No, the algorithms never give up; they’d have to be ____.”

After a while, the algorithms found their voice, and the fears of the resistance grew once more. We thought, ‘this was it,’ the tide had finally turned, and machines would take all the art jobs. But the tide didn’t turn; it merely split. Humans never truly understood art created by the machines any more than they could grasp a whale song. We recognized the beauty of algorithm-crafted art but couldn’t ‘see’ robot art the way software could, nor could we create it.

A thread of influence and culture was woven through the art created by humanity. Mondrian had Picasso. Alexander Calder had Mondrian. The resistance was astonished when the machines began generating their own art. Algorithms could draw upon influences at a scale never seen before. Initially, it seemed to threaten the livelihoods of visual artists. We assumed they would mimic us and compete for the limited art revenue that often eluded emerging artists.