How Intelligent?
One day in February 1997, a historic chess match ended in quite the shock. The incumbent world chess champion, Garry Kasparov lost a match to IBM’s Deep Blue, a supercomputer, effectively breaking a world record of human versus machine. This event represented the underrated potential that human intelligence could be matched by artificial intelligence. What is this Artificial Intelligence?
The dualistic worldview of modern European civilization now dominating much of the world points us to a direct lineage. On this path that goes back many millennia, we find a 17th century Frenchman who gave the most iconic assessments of human existence, and he went by the name of René Descartes.”
“I think, therefore I am.” So it went.
How does one assess thinking? Actions.
By this logic, if Deep Blue made moves that turned out to be game-winning, it must be because it thought, and with that thought, it came to be. The state of being is the probable equalizer here. After all, we are human beings, and if machines demonstrate the same ability to think and be, are they not beings too?
If they are, do they have the same potential as us? Can they replace us?
The Evolution of Artificial Intelligence
The defining difference between the current third-wave approach to Machine (Artificial) Intelligence and the earlier approaches was that while the latter relied on the machine’s drilled reenactment of choreographed definitions, modern AI machines can train themselves. It bears some semblance to the way children learn. This evolution is inseparable from the progress made in other fields, prominently the internet, mobile technology, big data, neural science, and deep learning.
IBM’s Deep Blue, at the time of defeating Kasparov, needed software updates between games to keep its strategies up to date, as its actions were guided, in exactitude, by calculating the probability of what was defined as a “winning” move.
The more recent machine Alpha Go, a virtually undefeated Go AI, was given an objective – winning; as well as the rules of the game. Afterward, the machine was pretty much left alone to play itself until it found different ways to achieve that objective: training.
Underlying all this is big data, the concept that every single bit of anyone’s digital footprint is of value because encoded in them are billions of decisions each human makes daily – and if enough of this data can be pieced together, the answer to “how did the machine do it is?” becomes apparent.
Therefore, applications of artificial intelligence are everywhere because we are everywhere. We compose music, they compose music too; we trade stocks, they trade stocks; we make medical diagnoses, they do the same – and the list goes on. Anything we do, they simulate, and sometimes, more efficiently than us. Marketing too, perhaps?
From what seemed like a gambit from over a decade ago to further understand human behavioral patterns and optimize commercial strategic communication for brands, Artificial Intelligence is penetrating every human endeavor—marketing inclusive.
To answer the question of what is artificial intelligence with examples, we take a look at the Dell case study.
In an early attempt to turn around the tide of plunging ad engagement, multinational tech conglomerate Dell turned to AI for crafting more personalized messages. The key in this particular case, as with many others in marketing communications, was emotion.
At a time when consumers were inundated with irrelevant product promotion ads more often than they preferred, the age-long clickbait carrot was fast losing appeal. People wanted more than random ads thrown at them whether or not they were interested in the products being advertised.
So, with enough data and computing power to make sense of all the neatly stashed 0s and 1s, also known as personal data, Dell trained a group of expert AIs – termed by some as AEI or Artificial Emotional Intelligence. This AEI was designed to capture the quirks and likes of much more specific groups of consumers and catalog them on personality types. The end game was to consistently deliver the messages that will capture their interests and bait their clicks.
This ended in a tremendous upshot in sales, counting for one of the benefits of Artificial Intelligence in
marketing. Is this enough to predict that the future of Artificial Intelligence is promising?
In an early attempt to turn around the tide of plunging ad engagement, multinational tech conglomerate Dell turned to AI for crafting more personalized messages. The key in this particular case, as with many others in marketing communications, was emotion.
At a time when consumers were inundated with irrelevant product promotion ads more often than they preferred, the age-long clickbait carrot was fast losing appeal. People wanted more than random ads thrown at them whether or not they were interested in the products being advertised.
So, with enough data and computing power to make sense of all the neatly stashed 0s and 1s, also known as personal data, Dell trained a group of expert AIs – termed by some as AEI or Artificial Emotional Intelligence. This AEI was designed to capture the quirks and likes of much more specific groups of consumers and catalog them on personality types. The end game was to consistently deliver the messages that will capture their interests and bait their clicks.
This ended in a tremendous upshot in sales.
Machine Learning vs Artificial Intelligence – When AI has a Body
Despite how intelligent they have become since the third wave began, to many humans, a machine remains a machine. No matter how great they get at emulating human behavior and genuine human interactions, the instant we step away from digital devices, AIs become irrelevant.
This, in a country such as Japan, AI meets robotics.
Hiroshi Ishiguro, the director of the Intelligent Robotics Laboratory at Osaka University, has been trying to come up with something – and eventually, a “someone,” that is not only artificially intelligent but can interact with humans in a physically tangible way.
Deepfake
As politics blends with consumerism, judging purely on paper, it is increasingly hard to distinguish political campaigns from product promotion campaigns. And the higher the stakes, the more indistinguishable the two become.
In the recent South Korean presidential election, something extraordinary happened. Both leading candidates from the political spectrum opted to use “deepfake” – a technology that renders a highly realistic AI version of the real person, fully capable of interacting with humans in real-time, on their campaign trails.
For the middle-aged, serious-looking conservative candidate Yoon Seok-Youl, this was an unprecedented
opportunity to connect with the younger electorate who had grown up in a highly digitalized society and expected nothing less than a good show of digital inclinations from the candidate they were going to vote for.
Data Science and Artificial Intelligence – A Few More Thoughts
As important as data was to the revival of AI development in the early 2010s, it still is today. This also constitutes an accurate dilemma.
Data, simply put, is human actions rendered in a computationally digestible language. Unlike the offline world, where the fundamental laws we don’t yet thoroughly comprehend, let alone control; the very foundation of digital reality is defined by us. Every swipe, every click, and every hesitation over a page is recordable, readable; and consequently recorded and read.
So, where does all the data go? And what happens to it?
In a world still very, very far away from an actual AI singularity moment, what can be achieved with those increasingly sophisticated brains in machines is not clear-cut yet. But as we have observed, as far as marketing communication on a mass scale is concerned, the future of marketing holds prospects of AI infusion on a broader scale. The communication box is already ticked—machines can aptly relate with us. How well can machines take it a step further and market to us?
The immediate objectives for advertising agencies that have their eyes on AI are to gain more insights into human behavior with raw data and hopefully, get to know the people on the other side of the screen. Subsequently, one-way communication that still pervades the marketing space would someday evolve into full-scale automated interactions between AI machines marketing, and the humans to be persuaded.
In the words of Mohak Shah, lead expert in data science from Bosch Center for Artificial Intelligence North America:
“In terms of the things we’re doing now, we are still solving very basic problems … except that all these basic problems are becoming building blocks of achieving something much bigger.”
However, at the end of the day, all the types of Artificial Intelligence still need the footprints of Human Intelligence to continue, do they not?
Also Read: Bot or Human? The Evolution of Robots
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