WHY is Digital?

Digital

Digital information is stored using a series of ones and zeros. Computers are digital machines because they can only read information as on or off -- 1 or 0. This method of computation, also known as the binary system, may seem rather simplistic, but can be used to represent incredible amounts of data. CDs and DVDs can be used to store and play back high-quality sound and video even though they consist entirely of ones and zeros.

Unlike computers, humans perceive information in analog. We capture auditory and visual signals as a continuous stream. Digital devices, on the other hand, estimate this information using ones and zeros. The rate of this estimation, called the "sampling rate," combined with how much information is included in each sample (the bit depth), determines how accurate the digital estimation is.

For example, a typical CD audio track is sampled at 44.1 KHz (44,100 samples per second) with a bit depth of 16 bits. This provides a high-quality estimation of an analog audio signal that sounds realistic the human ear. However, a higher-quality audio format, such as a DVD-Audio disc, may be sampled at 96 KHz and have a bit depth of 24 bits. The same song played on both discs will sound more smooth and dynamic on the DVD-Audio disc.

Since digital information only estimates analog data, an analog signal is actually more accurate than a digital signal. However, computers only work with digital information, so storing data digitally makes more sense. Unlike analog data, digital information can also be copied, edited, and moved without losing any quality. Because of the benefits digital information offers, it has become the most common way of storing and reading data.

Overconfidence effect

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The overconfidence effect is a well-established bias in which a person's subjective confidence in his or her judgements is reliably greater than the objective accuracy  of those judgements, especially when confidence is relatively high.[1] Overconfidence is one example of a miscalibration of subjective probabilities. Throughout the research literature, overconfidence has been defined in three distinct ways: (1) overestimation of one's actual performance; (2) overplacement of one's performance relative to others; and (3) overprecision in expressing unwarranted certainty in the accuracy of one's beliefs.[2][3]

The most common way in which overconfidence has been studied is by asking people how confident they are of specific beliefs they hold or answers they provide. The data show that confidence systematically exceeds accuracy, implying people are more sure that they are correct than they deserve to be. If human confidence had perfect calibration, judgments with 100% confidence would be correct 100% of the time, 90% confidence correct 90% of the time, and so on for the other levels of confidence. By contrast, the key finding is that confidence exceeds accuracy so long as the subject is answering hard questions about an unfamiliar topic. For example, in a spelling task, subjects were correct about 80% of the time, whereas they claimed to be 100% certain.[4] Put another way, the error rate was 20% when subjects expected it to be 0%. In a series where subjects made true-or-false responses to general knowledge statements, they were overconfident at all levels. When they were 100% certain of their answer to a question, they were wrong 20% of the time.[5]