Over the past year, machine learning and artificial intelligence technology have made significant strides. Specialized algorithms, including OpenAI's DALL-E, have demonstrated the ability to generate images based on text prompts with increasing canniness. Natural language processing (NLP) systems have grown closer to approximating human writing and text. And some people even think that an AI has attained sentience. (Spoiler alert: It has not.)

And as Ars' Matt Ford recently pointed out here, artificial intelligence may be artificial, but it's not "intelligence"—and it certainly isn't magic. What we call "AI" is dependent upon the construction of models from data using statistical approaches developed by flesh-and-blood humans, and it can fail just as spectacularly as it succeeds. Build a model from bad data and you get bad predictions and bad output—just ask the developers of Microsoft's Tay Twitterbot about that.