Will AI replce your PR department? Well, not anytime soon.
Most animals have some sort of capacity for communication. This type of communication can be connected to external conceptualisations; a tribe of monkeys could have a distinct and distinguishable sound for “danger approaching”, for instance. This is an advanced form of semiotics where the sounds themselves signifies an abstract meaning. However, about 75,000 years ago, humans surpassed this level (and then some!) in a relatively short evolutionary timespan. We moved on from audible communication to using human language, a skill that differentiates us from all other life forms on our planet.
It’s important to understand the vast difference between a monkey’s use of distinct sounds and human language. Or, more accurately — just how little we understand about this difference.
We don’t know how or why we developed our skill for human language so quickly. We don’t know how and why it became so prevalent in presumably all hominids at the time. In short, we don’t know how this skill evolved — only that it did. Human language arose so quickly that it doesn’t seem likely that language skill was selected over enough generations to produce such a fast biological result.
Time machine experiment: If we could use a time machine and go back 75,000 years ago and bring back an infant hominid1 with the capacity to use language, then, theoretically, we could put that infant through school and that individual would be able to do what any modern human can do today. If living today, that 75,000 year old time-traveller would be considered just as mentally capable as other children.
Why did early humans develop such advanced capabilities so long ahead of any such evolutionary needs?
There are other complex and fascinating products of evolution, like the eye. But in nature, eyes have been around for many millions of years and they have developed into thousands and thousands of different varieties. When it comes to languages, we’re stuck with a scientific sample of one — humans.
One interesting theory suggests a mutation in which a specific breed of hominids, our early ape-like ancestors, suffered from a development malfunction in which the infant hominid brain just kept on developing and developing. According to the theory, human beings are overgrown “ape children”. This would, at least partially, explain our more juvenile features (“neoteny“), the lack of fur, and our weaker bodies. More importantly, it would explain why our brain suddenly grew many magnitudes its prior capacity:
“For decades scientists have noted that mature humans physically resemble immature chimps — we, too, have small jaws, flat faces and sparse body hair. The retention of juvenile features, called neoteny in evolutionary biology, is especially apparent in domesticated animals—thanks to human preferences, many dog breeds have puppy features such as floppy ears, short snouts and large eyes. Now genetic evidence suggests that neoteny could help explain why humans are so radically different from chimpanzees, even though both species share most of the same genes and split apart only about six million years ago, a short time in evolutionary terms.”
It’s difficult to scientifically test how human language is affecting our brains. It’s possible that inner dialogue (internal language use) is closely connected to complex phenomena like consciousness.
There’s a popular expression that states that we know more about the surface of the moon than we know of the floor of the sea. Well, we’re closer to knowing about what’s going on in our oceans than we are to mapping out a cluster of biological neurons to understand how they produce consciousness — and human language. Decoding the human brain is necessary for any attempts at creating an AI capable of replacing human language.
The famous Turing test is a sentiment to this effect:
Are we able to produce a talking machine able to trick a human being? Despite it being a challenge, such a task is nothing compared to the challenge of constructing a machine that use language the way we humans started using it about 75,000 years ago. I would estimate that we’re at least 200-500 years away from being able to map out (and understand) the neural workings of a human brain.
We have mapped out the human genome, but we’re still far from figuring out how it all works. My guess is that humanity will venture far into transhumanism (humans augmented through technology), a sort of cybernetic renaissance, long before we are able to successfully decode human language through AI. We will master genetic engineering and create a human API long before we are able to construct a machine able to use human language in a sentient manner.
So, will artificial intelligence replace your communication department?
I would suggest that the answer is no, at least not in a foreseeable future. Using human language is simply not comparable to most other tasks in an organisation. In terms of technology advancements needed, such AI capabilities would require the technological singularity — which comes with its own set of disturbing challenges (and keeping our jobs is not one of them):
Futurist Ray Kurzweil have famously predicted that the singularity will occur in 2045 and others have argued statistically that this might be “optimistic” and that it should occur 2060-65 ± 10 years (later specified to 2062 ± 8 years). However, this is where we lose full control over technological advancements in a way that prohibits us from ever going back which is not to guarantee sentient computers able to successfully communicate with humans. Which is actually scarier, I think.
Still, this isn’t to say that the job market for communicators and public relations professionals is future proof by any stretch of the imagination. For the next 20 years, I would argue that the main technological drivers for changing your communications department will be:
- Quantum data analysis.
- Quantum-driven algorithms.
- Smart contracts (blockchain technology).
It’s not that your communication department will be replaced per se, but that fewer of communicators will be needed to perform complex tasks efficiently.