Check out all the on-demand sessions from the Intelligent Security Summit here.

In the era of conversational commerce, user experience experts are becoming completely absorbed by one thing: They love talking about how to talk.

We are learning the art of conversation at a whole new level — not only how to talk to clients, but also how to make the conversation meaningful. We want the conversation experience to be empowering and within the correct social and global context. We don’t want to speak in tongues; we want the conversation to roll off the tongue, to be authentic.

In the UX field, we are researching, creating customer journeys, prototyping, and experimenting. We use the design thinking process to try to get to the core of a customer problem or need, to find a solution to customer communication that is not only elegant and frictionless, but also pleasant, natural, and worthy of trust.

Teaching machines how to learn to communicate with us is no longer just science fiction.


Intelligent Security Summit On-Demand

Learn the critical role of AI & ML in cybersecurity and industry specific case studies. Watch on-demand sessions today.

Watch Here

“Alexa, open the pod-bay doors.” If you say this, Alexa will answer, “I’m sorry, Damien, I’m afraid I can’t do this; I’m not Hal and we’re not in space!”

By combining voice recognition technology and artificial intelligence, we are seeing that we can get there, that meaningful conversation between machines and humans are beginning to happen, but along the way, we are discovering new challenges that we never thought we would encounter.

These are the conversational interface challenges we continue to experience and work on:

1. The technology still needs improvement

Language is complex. While we are way more advanced than ever, there are still limitations on what we can do to make machines understand our languages. Large companies such as Google, Facebook, and Amazon are investing a lot in research, and in the developer community, to improve AI. Collaborative development will get us there.

2. We must examine the context of usage

The line between public and private spaces has become skewed. Do customers want to interact with a bank machine using their voice? What about privacy? Is the robot, always listening for a command, capable of hearing things it should not hear? It’s not yet natural, in our public spaces, to speak to a computer, and not everyone is comfortable with it. It cannot be forced; we have been typing for a long time to communicate with others. Are people comfortable with AI and voice interfaces that are always listening? Are those agents recording? Are they connected to the cloud?

3. Is a voice interface appropriate?

Just because it’s new doesn’t mean we need it. While the technology is useful in many contexts, sometimes a graphical user interface would work better, or maybe both voice and graphics. With new options available to designers, design thinking is more important than ever. We really have to dig deep and figure out where the true conversation pain points are — to create solutions to real problems, instead of creating new problems.

4. Can robots encompass brand personality and build trust?

Trust of app is the same as trust of brand. As we embark on the journey with new technologies, we are bound to have errors — we’re not going to catch everything. Siri is a good example of a conversational interface that suffered from early adoption and lack of maturity in the technology. Often, Siri is slightly off the mark. In addition to misunderstandings, Siri can’t always follow a complex conversation. Even though you just asked her about a city, she can’t connect the dots when you ask her to find a coffee shop in the next sentence without you naming the city again. Accuracy and speed are needed for trust in machines to begin.

5. Multilingual challenges abound

Montreal, the Canadian city where I live, is a bilingual city, which presents a big challenge. Different accents, street names in another language, expressions that are unique to the environment — they often cannot be understood. Language is sophisticated, and it will take time for machines to learn the myriad variations of how we speak and the associated context.

My recommendation is to tread carefully as you prepare to have the conversation about conversation. Teaching machines to talk to humans is delicate business.

Eve Larichelière is a lead UX designer at Valtech, a global digital agency.

VentureBeat's mission is to be a digital town square for technical decision-makers to gain knowledge about transformative enterprise technology and transact. Discover our Briefings.