Human Proofreading Vs. Machine Proofreading

Can the current proofreading tools/machine proofreading replace human proofreading?

If this is your question, this article is for you!

Towards the end of the 1990s, a chess-playing machine designed by IBM known as Deep Blue did an extraordinary thing; it beat the world chess champion, Garry Kasparov, in a chess match. What made this even more historic is the fact that, around that time, Dr Piet Hut, an astrophysicist at the Institute for Advanced Study in Princeton said, “it may be a hundred years before a computer beats humans at Go — maybe even longer.”

Less than twenty years later -far fewer than Dr Hut’s predictions- a popular game server in Asia watched one of its Go players dominate most of the world champions who played online. Many people were desperate to find out who this champion was, only to find out a few weeks later that ‘Master’ was DeepMind’s Al AlphaGo. This happened towards the end of 2016, and by May 2017, the Go world-champion was defeated by ‘Master’. By October, the same year, Google announced that it had a more sophisticated version of AlphaGo.

I am sure you are wondering by now what that has to do with anything; well, a lot; mainly, because there has been a lot of discussion today in academic and business circle about the benefits of machine-based proofreaders over human proofreaders. For many people, using programming tools is a convenience and cost factor; especially since there are many services available through cloud-based software and easy-to-use apps.

The lingering question now is, if computers can be taught how to beat the human world champions of chess and Go, can’t they be taught to proofread better than humans too?

Without a doubt, technology has invaded all areas of our lives, and the writing and editing process is not being left out. There are many proofreading tools and software out there now, and these tools are being updated every year. So if these machines are getting better at doing the proofreaders job, does that mean they are better or does that mean that we don’t need human proofreaders anymore?

Growth of Artificial Intelligence

Artificial Intelligence

Artificial intelligence, otherwise known as ‘Al’ is not one technology, rather a collection of technologies. They include expert systems, neural networks, advanced analytics, and machine learning. Al is being used in several different ways; most successfully those that are rule-based: targeted advertising, digital assistants, interpreting complex data, driverless cars, strategic games, photo tagging, and medical diagnosis. All these are powerful tools, but they lack something that humans have in abundance: common sense.

Editing and Proofreading Are Human Skills

The editing process is a 3-way dialogue starting with the author, down to the publisher and finally, the editor, undertaken within an editorial context that differs with every single publication. The editor will approach the document with a lifetime of knowledge based on facts, language experience, memories and perceptions culled from archaeology to polymorphism, all crucially overlaid with sensitivity and empathy to the author’s word. Different words carry different meanings, which can be far more powerful than any definition in the dictionary, and which arise over time from history, context, and life experience.  The human editor will easily recognize and understand these subtleties. A piece of software on the other hand can ‘know’ the definition of a word, but cannot understand the meaning of that word within the larger context. It will not and cannot understand the emotional response that each very word elicits.

Human Language

people talking together

Language is a process of free theory and also, every time we speak, we create a brand-new combination of words that may have never been in existence before. To achieve this; the brain must create infinite combinations out of finite list words. There are fixed rules for using these lists, albeit ambiguous and fluid. However, the ten manners in which the rules are used to generate is free and infinitely varied.

The process of learning a language itself gives a clue as to how difficult it is for a machine to simulate human language. For instance, a child learns a language by accumulating vocabulary (10-15 new word meanings a day). However, research indicates that these words aren’t taught directly. A child learns a language through experience and the context in which the words are used (Read Language Development Theories). The same process cannot be said about Al. In addition to this, language itself is constantly evolving so much that even dictionaries cannot keep up with the linguistic innovations. Take for instance, what a proofreading software would do to Shakespeare.

Where Can Software Help?

Still, I am not saying that there is no place in the editing process for editing tools. The new generation of editing software tools helps proofreaders with the mundane and mind-numbing part of the job. They help proofreaders speed up the mechanical side of their job; this allows proofreaders and copy-editors to improve their productivity and get to the more creative process quickly.

Conclusion

I believe the true Al software is yet to be invented. I do not believe that they are better than the human proofreader because proceeding and copy-editing is more than just correcting text. It is about comprehending and manipulating linguistic shade, nuance, and color, and software tools work in black and white. Another reason is that, more importantly, human language is insanely complex.

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2 thoughts on “Human Proofreading Vs. Machine Proofreading”

  1. proofreading tools are never as good as human proofreaders. I have used different proofreading tools and was perfect or close to good. They don’t have the human touch.

    Reply

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