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In 1992, Edward de Bono argued that "creativity is the most important human resource of all." But might computers have the capacity to be creative? Could artificial intelligence outperform us in even the most human of phenomena? These questions have moved to the forefront of society with the launch of ChatGPT and DALL - E, two powerful deep learning models capable of creating art.

Where human creativity comes from is a complex and heavily-debated topic. One theory supposes that creativity emerges from solving problems in new ways. The game designer Mark Rosewater explains that "if you use the same neural pathways, you get to the same answers, and with creativity, that's not your goal." But studies from the University of Virginia suggest humans most default （默认）to solving problems by building on known solutions, restricting originality. Some neuroscientists propose another theory regarding creativity. Research from the University of Calgary reveals that when being creative, humans don't use the same brain regions associated with thought and problem-solving, implying that creativity is primarily an unconscious process. According to this theory, the brain solves problems best when not directly focusing on them using the frontal lobe（前额叶）, instead letting the other parts of the brain take over.

A. I. cannot currently emulate（仿真） the full complexity of the human mind. Do these deep learning networks even have the required components that we use when we are creative? Douglas Hofstadter explains how "emergent phenomena," such as creativity, correspond to connections between levels within mental systems. Similar connections could exist in artificial neural networks, even if the mechanics differ. For example, modern artificial intelligence employs attention circuits that may cause it to behave similarly to the frontal lobe where most of the brain's focusing tendencies come from.

The emergent nature of creativity opens the door for similar tendencies in machines, but they are tuned so carefully to copy existing ideas that it may not be enough for true originality. Mr. Rosewater's theory on creativity suggests that for A. I. to be creative, it should be able to solve problems in new ways, which is difficult because A. I. is based so heavily on already existing ideas. Alternatively, if creativity is an unconscious process as the University of Calgary research suggests, then it occurs mostly outside the frontal lobe and may not exist in machine learning networks. Either way, current A. I. probably lacks the capacity for genuine creativity and originality, but it can combine existing ideas in interesting ways.

The question of machine creativity has repercussions in many areas, such as developing copyright law regarding A. I. works, considering A. I. submissions in art contests, and determining the use of ChatGPT as a tool for school assignments. Creativity may be, at least for now, a unique human quality. Computers are not yet starting revolutionary artistic movements, but they are already combining what exists into something new, challenging us to look deeper into our own creativity.