One of the most insidious effects of relying solely on averages is the perpetuation of discrimination. In fields like medicine, where research often focuses on understanding diseases and treatments, averages can mask disparities in health outcomes among different demographic groups. For instance, a medical study might find that a certain treatment is effective on average, but fail to acknowledge that it may be less so for specific populations due to genetic or socioeconomic factors. This oversight can lead to inadequate healthcare provision for marginalized groups, exacerbating existing health inequalities.

Moreover, the uncritical use of averages can result in injury, both physical and psychological. In sports science, for example, coaches and trainers frequently rely on average performance metrics to assess athletes. However, this approach fails to account for individual differences in physiology, training history, and injury susceptibility. As a result, athletes may be pushed beyond their limits or subjected to training regimens ill-suited to their needs, leading to overuse injuries and long-term damage.

While averaging techniques have undoubtedly revolutionized scientific research, their overreliance has led to discrimination and injury in various fields. By recognizing the limitations of averages and embracing more inclusive methodologies, researchers can strive to produce knowledge that is both accurate and equitable. Only then can science fulfill its promise of serving the betterment of all humanity.