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Zen and the art of artificial intelligence

By Olivia Atkins, Branded Content Writer



The Drum Network article

This content is produced by The Drum Network, a paid-for membership club for CEOs and their agencies who want to share their expertise and grow their business.

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September 30, 2019 | 9 min read

Zen koans (or riddles) are short questions which can be difficult or even impossible to answer. Things along the lines of 'What is the sound of one hand clapping?' or 'Can a submarine swim?'

Firehaus question the creative potential of AI, using the memorable AlphaGo campaign as an example of its development.

These questions do not just confuse the recipient, but also force them to think in a different way; to move forward without a precise destination in mind.

This technique can seemingly be applied for creativity in business. Many business and marketing books are written on the importance of trying to reveal the underlying challenge a brand has to solve. It's critically important to know the problem you want to resolve before figuring out what the solution should be.

In the last ten years, there has been a surge in a lot of new business - think Uber and AirBNB for starters. They've become successful by finding a new solution to problems that have emerged within an existing category. So, can AI help us to think in differently? Could AI open our minds using Zen koans and make us think more creatively? As far as I can see, the answer is yes and no... So far, so Zen.

The gradual AI evolution

One of the early successes in AI was a programme called ELIZA, developed by Joseph Weizenbaum in 1966. He was determined to pass the Turing Test; to fool a human that they were talking to a human when in fact they were conversing with a machine. He realised that an easier way to do this - influenced by therapy - was to always ask open questions. So he programmed ELIZA to always respond this way:

Client: Men are all alike.


Client: They’re always bugging us about something or other.


Client: Well, my boyfriend made me come here.


Client: He says I’m depressed much of the time.


However, as great as ELIZA was, it didn’t take long for Weizenbaum and others to realise the limitations that conversations with the machine offered. There was no real benefit to the questions; and on this front, things haven’t improved much since.

In this instance, the questions put forward by the AI and its algorithm were too formulaic and therefore deemed useless.

However, scientists then questioned whether AI and machine learning could respond to non-verbal enquiries and answer questions through action rather than by responding to a specific question.

Proof in the pudding

Think of Chess programmes, where Chess Grand Masters and Chess World Champions can be beaten by a machine. The AI system, AlphaGo, has even defeated internationally recognised players in Go - a Chinese game considered to be far more complex than Chess and less likely to be beaten by brute force.

So, how did AlphaGo do it? The software asked questions through the medium of Go. In move 37 of the second game of four against Go World Champion Lee Sedol, AlphaGo placed a black stone on the line five steps in from the edge of the board. Everyone was shocked.

It turns out that in Go, in the early stages of the game, you only play stones on the outer four lines. Playing on the fifth is considered suboptimal and was ridiculed by the commentators at the time. But, you can guess what happened, right? AlphaGo’s unorthodox move set-up a strategic play that left Sedol open in the latter stages of that same game. AlphaGo won and went on to win the series 4-1, setting a new standard for AI.

AlphaGo questioned the orthodoxy of the game. Up until that point, Go players and culture had found a ‘local maxima’ - what they believed was the high point of Go based on a set of rules and principles leading to optimum performance.

But AlphaGo discovered that there was a higher level of performance that could be unlocked by what was traditionally considered a bad move. It exploited this and beat Sedol.

Since that moment, this move has changed the course of the game with players now routinely using the fifth line throughout its early stages. So put more succicntly, AI changed the world of Go.

"Humanity has played Go for thousands of years, and yet, as AI has shown us, we have not yet even scratched the surface," said Go champion, Ke Jie. "The union of human and computer players will usher in a new era."

The effect of AI on advertising

So, does AI have the power to ask probing and creative questions, verbal or non-verbal, that can change the state of play within a game, or more importantly for us, for a brand? Well, yes... But, no as well... Still Zen!

AlphaGo did ask an open question, but it was very much within the concrete frame of reference within the game of Go. This is far more rigid than most situations an organisation would find itself in.

So, to be able to compare AI's knowledge bank to the creative process, it has to be able to operate in environments where rules or parameters don't exist to be able to create something truly new.

Psychologist Margaret Boden suggests there are three types of creativity, that context plays an important part.

  1. COMBINATORIAL: When there is an unfamiliar combination of familiar ideas. The kind of creativity we often see in a lot of collage-based artwork, poetry, a lot of advertising. This is where AI can be used to create familiar elements to evoke an unfamiliar result? Machine learning is good at this; when the human asks, the machine responds.
  2. EXPLORATORY: Where the existing styles of conventions can generate novel structures or ideas, whose possibility may or may not have been realised before. This is where the AI may stick within the rules, but push the limits as much as possible and go beyond the local maximum. AlphaGo beating Lee Sedol sits within this category. The machine ‘questioned’ what was right and possible within the game of Go, and discovered a new peak of achievement. Exploratory creativity is not to be sneezed at. Most scientists and artists will produce creative work of this type and achieve great things. Here. AI can answer some questions set by humans but also pose new questions within the framework of a particular medium or context.
  3. TRANSFORMATIONAL: Where some deep dimension of the conceptual space is altered so that ideas and concepts can now be generated which could not be generated before, and which do not necessarily conform to the previous style. Imagine a game of chess where the pawns can jump over pieces... This is the domain where the ‘What if?’ question lives; expect answers to fundamentally shake up categories that have built and defined brands.

So, can AI help marketers into the transformational space?

Unfortunately, there’s little evidence that they can. Most examples of creative AI focuses on exploratory creativity and doesn’t break the rules. Even those on the inside of the AI revolution, like Judea Pearl, computer scientist and philosopher, best known for championing the probabilistic approach to artificial intelligence, thinks that our current techniques are limited.

"Current machine-learning systems operate almost exclusively in a statistical, or model-blind, mode, which is analogous in many ways to fitting functions to a cloud of data points," she said. "Such systems cannot reason about 'What if?' questions and, therefore, cannot serve as the basis for Strong AI."

Obviously, most powerful ideas are rejected at first; so even if we did have an AI capable of producing them, it's unlikely that the operator would understand the value of its output?

AI can ask questions and sometimes, those questions can be useful and surprising, but only if they're based within the constraints of a particular way of thinking. For now, the only place to get truly transformational creativity is from ourselves and our peers; we need to keep asking better questions and prioritise that ahead of creating better answers.

Like any Zen master - who typically answers every question with another question - before thinking of your next problem to solve at work, take a step back, look at your brand and try to come up with a better question first.

As Profsssor Luciano Floridi, puts it: "Data do not speak by themselves, we need smart questioners."

Nick Barthram, founder and strategy partner at Firehaus.


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