If you say the 6 letter acronym ‘QWERTY’ to almost anyone in a professional setting, they’ll instantly think of their work device – a keyboard on their computer, the pop-up on their tablets, and their numerical pads on their BlackBerrys.

If you ask most people why their keyboard is laid out in such a way they wouldn’t know the answer. In fact, it stems back to the mid 19th Century when budding entrepreneurs Christopher Sholes, Samuel Soule and Carlos Glidden came together to create the Remington 1, the first commercially successful typewriter. Their reason for the QWERTY keyboard? Telegraph operators used machines to transcribe Morse code over a series of iterations. The common misconception is that the keyboard was created to prevent keys jamming and for a mechanical reason.

What is extremely interesting and frustrating is that the keyboard has been designed as a reactive tool, and this has lead to what some argue is an inefficient typing mechanism. There are solutions – the Dvorak and Colemak keyboards are designed for frequent key use near the bottom row, but the opportunity cost in re-training yourself to type is too high to justify the switch.

But does changing the design and the frequency correlate to our ability to make typo? After all the curse of the “fat finger” happens away from the keyboard and when opening applications on a mobile device. It seems that there is no cure for the incessant problem grappling users across the globe.

But what if there is? Autocomplete is a function where an application predicts the next part of a string of text or numbers in order to prevent a user from typing in full. A time-saver, it also acts as a tool to eliminate typos by reducing the overall time it takes to type. But with autocomplete comes a whole new set of problems –  incorrect changes, the wrong word, a homophone or a different syntax.

Introducing machine learning and artificial intelligence – two buzzwords that are well integrated into the technology ecosystem. As demand has pushed business to focus on speed, it is important to ensure accuracy in an age where information is easy to send and therefore easy to send incorrectly. Machine learning allows users to continue using tools like autocomplete to maintain high speeds, but to reduce some of the risks – and sometimes key risks – when acting in such a velocity-driven environment. Typos are now being identified, caught, and changed correctly or with guidance.

But in answer to the question can we eliminate the typo, the answer is simple: no. But can we reduce the risks associated with typos? That’s a resounding yes.