‘Digital communication’ is becoming an increasingly literal phrase. Thanks to rapid advances in AI-driven natural language programs, people aren’t just talking to other people online – they’re interfacing directly with machines (and according to some studies, most of us actually prefer it that way).
Artificial intelligence is changing the fundamental nature of digital communication, making it faster, more efficient, more personal. Deep learning technology has become part of the new communications curriculum. It’s no longer enough for businesses to talk to their customers. They need to understand them first.
AI vs Machine Learning
It’s worth pausing here to quickly define the difference between AI and Machine Learning, because they impact digital communication in different ways. AI thought leader Stewart Rogers puts it this way: machine learning is about finding patterns in data, AI is about altering those patterns to meet a specific goal. When it comes to online content, for example, machine learning can curate articles or videos based on a customer’s behaviour, location or psychographic profile. Artificial intelligence is better at predicting that user’s behaviour, and prompting them to do something about it (like make a purchase).
Am I speaking to a human?
Chatbots are the most obvious example of AI-driven digital communications. They’ve been around since the 1960s (when Joseph Weizenbaum built the very rudimentary ELIZA program). However, advances in deep learning algorithms and natural language processing (NLP) have created a new generation of sophisticated, intuitive and human-like chatbots, which can parse conversational logic through almost any platform, from Slack to Facebook Messenger. Not only are more and more companies turning to chatbots to enhance the cross-channel customer experience, customers themselves are leading the charge: one study found three out of four people prefer interacting with a chatbot, even when presented with a human alternative.
Curating the future
The future of digital communications is curated. This is where machine learning and artificial intelligence really come into their own: sifting through usage data to enhance the customer experience with tailored, specific and relevant communications. We’ve already seen this Facebook’s news feed, YouTube’s feed recommendations and, of course, Netflix. Interestingly though, in the case of Netflix, the company is moving towards some sort of AI-human hybrid model, where algorithms generate shows based on your browsing history, while experts hand-pick ‘collections’ based on “genre, tone, storyline and character traits.”
Artificial diversity
As artificial intelligence expands the horizon of digital communications, it’s more important than ever to think about ethics and diversity. AI is like anything else: if you feed an algorithm biased data, you’ll get a biased result. In 2016, for example, Microsoft launched a Twitter bot, Tay, which quickly learned to mimic online racism and misogyny. Gender diversity in certain devices, like virtual assistants, is also quite poor (a recent analysis of 300 digital assistants found that 67 per cent of them were female). Advances like ‘Q’, the world’s first genderless digital assistant, are a step in the right direction, but there’s still a long way to go. It’s part of the reason education providers, like RMT Online, are putting such a focus on artificial intelligence: new communications graduates will need to understand what this technology can do. The good as well as the bad.
Can machines win storytelling?
Think of the future. How much content will be written by people? How much will be written by machines? This is one of the most interesting frontiers of machine learning. Many news outlets are already combining digital listening tools with AI-powered language processors to write simple breaking stories – and brands aren’t far behind. Forbes uses a content management system called Bertie to suggest on-brand headlines. The Washington Post recently released Heliograf, which can generate entire articles from raw, quantitative data. Apps like Crayon can be used by marketing teams to suggest viral content and keep an eye on competitors.
There are limitations to this technology, of course, and humans will still be required to steer natural language processors in the right direction. More than that, experts still believe communications professionals provide something machines have yet to master: storytelling. Generating emotional connection. Leading consumers along a journey. Machines might be able to write basic blogs, but creativity, morality and critical thinking are something else all together.
Want to learn more about Digital Communications? Check out RMIT Online’s new Graduate Certificate in Digital Communications.
