Have you ever noticed the sound an ATM makes before dispensing cash? You may be withdrawing a single ₹500 note, yet the machine seems to spend several seconds counting a whole stack of currency before delivering your money. Most of us do not know the exact algorithm behind the process, but the sound is familiar to anyone who has stood waiting at an ATM.
Counting money is not as simple as it appears, especially when it is done manually. Whenever cash was withdrawn from the bank, my mother would always ask my father to count it before spending any of it. Counting currency is a surprisingly delicate task. Count one note twice and you are over-accounting; miss a note and you are under-accounting. Yet not every household finds it necessary to own a currency-counting machine.
When you watch your father or grandfather count a bundle of notes and confidently announce the total amount, there is no display screen showing the result. The number exists only in their mind. You trust that figure and proceed accordingly. If the count later turns out to be incorrect, there is often no way to prove where the mistake occurred. The figure lived in memory, and once spoken, it becomes difficult to verify whether it was accurate or influenced by human error.
Currency-counting machines changed this dynamic. The machine not only counts the notes but also displays the result. Some even provide a printed receipt. The count no longer resides solely in someone's mind; it exists as a visible and verifiable figure. If there is an error, there is at least a record that others can inspect. The invisible mental number is replaced by a documented one.
As we move toward a world where numbers increasingly appear not just in our minds but also on screens, receipts, and digital records, an interesting question emerges: Are we moving toward a world without bias?
Perhaps not.
Imagine sleeping on a bare floor. The floor offers no special treatment. It does not adjust itself according to who lies upon it. In that sense, it is completely impartial. It behaves the same way for everyone.
Now consider a mattress. A mattress changes its shape depending on the person using it. It responds to weight, posture, and movement. Its behavior is not identical for every individual. In a way, it exhibits a form of bias—not out of preference, but because it adapts to the person occupying it.
The same may be true of the systems we build. Records, machines, and digital figures can reduce certain forms of human subjectivity, but they do not necessarily eliminate bias altogether. They may simply shift it from one place to another—from the mind of an individual to the design of a system.
Yet people differ in what they value. Some deliberately choose to sleep on the floor, appreciating its simplicity and consistency. Others cannot imagine a good night's sleep without a comfortable mattress that adapts to them.
Perhaps the challenge is not to create a world entirely free of bias, but to understand which forms of bias we are willing to accept and which ones we seek to eliminate.