“God made man because he loves stories.” Elie Wiesel’s phrase, taken from an ancient Hassidic parable, couldn’t be more evocative. Nor could it be more capable of underlining that stories are intrinsically associated with the human condition. They accompany man’s existence from the very beginning and are – perhaps – the best that humanity has to offer.
The association between man and narrative dimension has deep roots. Since the dawn of myth, humans have used stories to give meaning to the world. Without them, our experience of the universe would be almost incomprehensible.
Also, the telling of stories has always been the exclusive domain of man. No other living creature has ever shown this inclination, linked to typically human prerogatives, such as symbolic thinking, language, creativity.
From now on, however, with a break of historical importance still difficult to understand, telling stories may no longer be a purely human undertaking. Although in the current phase algorithms and artificial intelligence (AI) tend to intervene mainly with help functions, they too can be considered – increasingly – not only mechanisms of reproduction, but real creators of new stories and tales.
It’s interesting to understand the current transition which is leading software, artificial systems, robots to seize the secrets of storytelling in crucial areas of contemporary communication: cinema, journalism, marketing, advertising, politics.
A completely new era is opening. Naturally, this is happening thanks to the impressive development of AI and robots in several fields, which is affecting our existence. But the fact that AI will soon be able to tell stories – and make sense of the world – suggests that this world will never be the same again.
Where does AI stand when viewed in this perspective? Let’s say, far ahead. Although it can’t be said that electronic ‘brains’ are wired for stories (they’re programmed or programmable for many other things), they’re already capable of collaborating and constructing interesting and attractive narratives. As I noticed in my latest book “Storytelling and Artificial Intelligence”, algorithms and robots are already becoming fantastic storytelling assistants. They indeed can:
- Help produce newspaper articles, facilitating and speeding-up the collection of documentary information
- Aggregate narrative elements from vast databases of verbal and visual information to get indications on the main trends of storytelling in specific areas
- Identify the prevailing emotional arcs and point out the most successful ones, which can be used for new creative projects
- Study new variations of stories/films’ narrative models and new sequences beyond the usual ones
- Support those who work on song lyrics by making available sophisticated combinations from large lyrics databases
- Increasingly enrich the experiences of interactive storytelling and improvisational storytelling
- Analyse huge amounts of Big Data on consumer behaviour to inspire advertising creativity
- Propose new hypotheses of formats and solutions for brand communication
- Provide narrative elements useful to inspire storytelling for training purposes on specific corporate or institutional themes
- Help setup political discourses by identifying the issues that most interest the public
- Find winning political and social slogans through the large-scale combinatorial elaboration of keywords
- Facilitate the interweaving of storytelling forms with innovative virtual reality and augmented reality solutions.
Undoubtedly, most people who, as storytellers or experts, deal with AI, believe that at this stage the best role of machines is to assist creative people’s work. But the issue of creativity in relation to processing algorithms is far from being put aside, and there’s a lively debate on this subject. According to various studies and tests, machines are already creative and can produce surprising results. In several cases, their works have passed the Turing test (they’ve been attributed to humans by an audience unaware of who made them), in fields such as music, painting, design, and journalism.
In music, for example, AI has already created new melodies, so original that they can withstand the scrutiny of the algorithm itself in its function as an anti-plagiarism tool. In journalism, important newspapers such as the New York Times and the Washington Post have assigned ‘bots’ the task of producing linear, repetitive short stories – news on the stock exchange, sports, and weather – without readers noticing. It’s easy to predict that these capabilities will expand and improve further, making algorithms capable of writing more complex articles and becoming mainstream in newsrooms globally.
Well, what does this mean for brands and the ability of researchers to support them? AI like Siri, Alexa and Cortana mark the way: we’re entering the era where brands are starting to take their own life in consumers’ pockets and homes. Software and algorithms will increasingly become the interlocutors that people face in many brand touchpoints. In the new situation it’ll be less possible to refer problems arising in conversations with brands to some human subject. In customer care, like many other areas, AI applications will have to cope with complex and unpredictable interactions by themselves.
This evolution, however, will pose problems for brand identity and image. And in this area, researchers’ contribution will be crucial, because they’ll have to ensure that the introduction of bots into the brand signification system respects its deep soul. For example, current technologies make it possible to go far beyond the standardised robotic voices of the first digital assistants. When companies decide which voice to give their brands, they can now choose based on several attributes including tone, depth, accent, and cadence of speech. This can determine a ‘sonic identity’ for their brand, a unique voice capable of conveying the brand story (like visual identity). But this isn’t a task most companies are equipped to handle.
Researchers have an important role to play, asking the company management questions such as:
- What is your brand’s AI voice (if you have one)?
- How carefully has it been studied?
- How much is it in-line vs. the overall brand identity?
- What impact does it have on your customers?
- And how does it differ from competitors’ voices?
Answering these questions will require a brand vision based on extensive marketing knowledge and psychological, sociological, and semiotic competences – as in the best tradition of market research.
