Qualitative reasoning is based on abstract data, while quantitative reasoning is based on numerical values. It is used in artificial intelligence to mimic human thinking and decision making. Engineers have enabled technologies to perform some types of qualitative reasoning, which could alter the role of technology in society.
Qualitative reasoning is reasoning based not on numbers, but on a more abstract or sophisticated set of data. It is often compared to quantitative reasoning, which, by definition, is based on numerical values or statistics. Some might describe qualitative reasoning as “intuitive” reasoning, where the logical outcomes involved are based on less technical factors. Many also see it as a “higher level” type of reasoning than purely quantitative reasoning, which requires only a specific number of calculations to be successful.
One of the interesting things about qualitative reasoning in the twenty-first century is that it has been applied not only to human thought, but also to artificial intelligence. Artificial intelligence is the ability of technologies to mimic human or animal thinking and to make decisions based on changing factors. In this research, qualitative reasoning plays a prominent role, as part of the challenge for developing technologies is to use more than just numbers to produce logical results. This is just a small part of how scientists are trying to help technologies reproduce the functions of an organic brain, where modern science has produced some impressive successes, but has also faced some seemingly insurmountable challenges.
Experts would define qualitative reasoning as anything that isn’t just based on numbers. A qualitative reasoning project might take a set of images or conditions and attempt to analyze them from a less technical perspective than quantitative reasoning would require. In the early years of computers, scientists focused almost exclusively on quantitative reasoning, as early computers also excelled at this type of logical operations. Indeed, while computers were capable of vastly surpassing human capacity for quantitative reasoning, they were originally unable to match most human capacity for qualitative reasoning.
In current times, this equation is rapidly changing, as engineers have managed to enable technologies to perform some fundamental types of qualitative reasoning. For example, programmers may be able to plug some general environmental factors into a computer program and get some logical results, even when unexpected factors are then introduced; older technologies often simply crashed in such situations. This kind of “observational logic” has vast ramifications for the future of artificial intelligence; it may be that future scientists will allow computers to further shape human thinking and, consequently, human behaviors, which could drastically alter the role of technology in global society.
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