AI Augmentation: The Real Future of Artificial Intelligence
I love Grammarly, the writing correction software from Grammarly, Inc. As a writer, it has proved invaluable to me time and time again, popping up quietly to say that I forgot a comma, got a bit too verbose on a sentence, or have used too many adverbs. I even sprung for the professional version.
Besides endorsing it, I bring Grammarly up for another reason. It is the face of augmentative AI. It is AI because it uses some very sophisticated (and likely recursive) algorithms to determine when grammar is being used improperly or even to provide recommendations for what may be a better way to phrase things. It is augmentative because, rather than completely replacing the need for a writer, it instead is intended to nudge the author in a particular direction, to give them a certain degree of editorial expertise so that they can publish with more confidence or reduce the workload on a copy editor.
This may sound like it eliminates the need for a copy editor, but even that’s not really the case. Truth is, many copy editors also use Grammarly, and prefer that their writers do so well, because they usually prefer the much more subtle task of improving well wrought prose, rather than the tedious and maddening task of correcting grammatical and spelling errors.
As a journalist I use Cisco’s Webex a great deal. Their most recent products have introduced something that I’ve found to be invaluable – the ability to transcribe audio in real time. Once again, this natural language processing (NLP) capability, long the holy grail of AI, is simply there. It has turned what was once a tedious day long operation into a comparatively short editing session (no NLP is 100% accurate), meaning that I can spend more time gathering the news than having to transcribe it.
These examples may seem to be a far cry from the popular vision of AI as a job stealer – from autonomous cars and trucks to systems that will eliminate creatives and decision makers – but they are actually pretty indicative of where Artificial Intelligence is going. I’ve written before about Adobe Photoshop’s Select Subject feature, which uses a fairly sophisticated AI to select that part of an image that looks like it’s the focus of the shot. This is an operation that can be done by hand, but it is slow, tedious and error prone. With it, Photoshop will select what I would have most of the time, and the rest can then be added relatively easily.
What’s evident from these examples is that this kind of augmentative AI can be used to do those parts of a task or operation that were high cost for very little value add otherwise. Grammarly doesn’t change my voice significantly as a writer. Auto-transcription takes a task that would likely take me several hours to do manually and reduces it to seconds so that I can focus on the content. Photoshop’s Select Subject eliminates the need for very painstaking selection of an image. It can be argued in all three cases, that this does eliminate the need for a human being to do these tasks, but let’s face it – these are tasks that nobody would prefer to do unless they really had no choice.
These kinds of instances do not flash “artificial intelligence” at first blush. When Microsoft Powerpoint suggests alternatives visualizations to the boring old bullet points slide, the effect is to change behavior by giving a nudge. The program is saying “This looks like a pyramid, or a timeline, or a set of bucket categorizations. Why don’t you use this kind of presentation?”
Over time, you’ll notice that certain presentations float to the top more often than others, because you tend to choose them more often, though occasionally, the AI mixes things up, because it “realizes” through analysing your history with the app that you may be going overboard with that particular layout and should try others for variety.
