Chapter 1: A Nostalgic Look at Early Predictive Text

Recently, while composing some haikus on my mobile device, I was reminded of an ancient predictive typing software I encountered back in the early 1990s—a time that now feels like a tech dark age.

At the British firm where I worked, the IT team had just received IBM PCs, and they were quite basic. I had one of the more advanced machines, boasting a substantial 50 MB hard drive, compared to the standard 20 MB. The system operated on Windows 3.1, and our primary word processor, Multimate, was an early competitor to Microsoft Word, lacking many features we now take for granted.

During this period, I stumbled upon a free software program from a tech magazine that promised predictive auto-completion based on my typing habits. Intrigued, I decided to give it a try on my work computer.

The program functioned—sort of. However, I encountered two main issues: first, I was skilled at touch typing, and second, the software was sluggish. By the time it figured out what I intended to write, I had already moved on to the next thought. Ultimately, it hindered my productivity, and I uninstalled it.

A colleague, skeptical of my claims, decided to install the same software on his computer and spent a few days in learning mode. We then held an informal competition to see who could type a given text faster.

While he relied on the old hunt-and-peck method, I typed with all ten fingers flying across the keyboard. Despite my occasional errors, I completed the task much faster than he did.

In today's context, this might seem outdated. Now, I use SwiftKey on my Android device, which not only offers more accurate predictive text but also allows for continuous swiping when entering words. Although it still makes mistakes, it significantly enhances typing efficiency compared to earlier mobile keyboards.

I often wonder how long it will take before keyboards become obsolete. The answer could lie in advancements in voice recognition software or even thought-controlled computing.

Voice recognition has made remarkable progress since I first encountered it in the late 1990s. My IT director once asked me to test a voice-activated web browser. Since my personal computer lacked the necessary specifications, I procured a new one at work, set it up, and installed the browser.

The experience was frustrating. I could occasionally get it to respond, but it rarely executed my commands correctly, and the lag was exasperating. My IT director, perhaps believing I was using it incorrectly, tried it himself with no better results. In an attempt to troubleshoot, he spoke in an American accent, and surprisingly, the software responded much more accurately. It became evident that the program was calibrated for American accents, not British ones.

Although he had hoped to implement it across his teams for improved efficiency, the idea of an entire office filled with employees speaking in American accents was comical—and not particularly effective.

Since then, we've seen significant advancements in software, including the latest versions of Dragon, along with applications like Alexa, Cortana, and Siri, which are now available on most smartphones and standalone devices.

Perhaps one day, conversing with computers will be as natural as it is depicted in sci-fi series like Star Trek. While that may not render keyboards entirely obsolete, certain professions, such as graphic design, may still rely on traditional input methods for a while.

However, the widespread adoption of voice recognition could lead to a noisy environment, especially in public spaces where people converse with their devices.

The ideal solution might be thought-controlled software. Fictional works like the book Firefox, which was adapted into a film, showcased the potential of thought-controlled technology as early as 1977. It's likely that the military has explored this area and made strides.

In reality, there are already devices designed to assist individuals with disabilities in performing tasks through thought control. It’s only a matter of time before this technology becomes more accessible and practical.

If that occurs, the necessity for keyboards could eventually vanish. This shift could have significant implications—less demand for raw materials to produce these devices, fewer job opportunities in certain sectors, a reduction in obsolete devices ending up in landfills, and potentially decreased pollution levels.

While I may not live to witness this future, it is on the horizon—provided humanity can sustain itself long enough to see it through.

Chapter 2: The Rise of Modern Predictive Text

In recent years, advancements in predictive text technology have transformed how we interact with devices.

The first video discusses free word prediction tools that assist with spelling, showcasing various software options available today.

The second video explores Poio, a predictive text application aimed at promoting language diversity through grassroots technology.