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The growth of digital assistants has led to a surge in organizations working on voice user interfaces as a form of interaction. There’s been a particular focus on making the interaction natural whilst achieving the user’s objective. Although best practice around user experience still applies, dealing with the medium of voice has some unique challenges. Our experimentation led us on a journey of discovery around how to plan the dialogue, consider context, build adaptability, and efficiently execute intent.

Many years ago, I worked for a technology division of the BBC that eventually spun off to become a standalone digital agency. Their offices were such a contrast to the bland corporate workspaces I had worked in previously. Meeting rooms were converted into green screen studios, and large playout control rooms delivered 60+ channels to live television. Amongst all the visual pizazz, was a team responsible for audio describing what was happening on a television show. They used IBM Via Voice to caption and explain what was happening on live TV. It was my first encounter of speech-to-text in action solving a real-world problem. Yet for all its technological sophistication, I was amazed to observe that the speakers had adapted their voices to be robotic to improve accuracy. …


Digital assistants have become a part of our everyday lives. As they become more useful, we’re beginning to get over the friction of speaking to phones, speakers, watches, and computers. With the technology rapidly improving, we’ve also seen a bunch of companies working on augmenting this with realistic digital characters in the hope of improving the overall experience. Our research and experimentation have challenged our thinking around how to do this well, if at all. Factors like appearance, proficiency, discrimination, and comfortability all come into play.

My early exposure to artificial intelligence with some sort of visual representation first came from sci-fi movies. Most were machine-like, but some introduced digital depictions that had humanistic characteristics. Although not intelligent in any capacity, my most memorable real-world example was the annoying Clippy that appeared when I least wanted it in Microsoft Office. When I couldn’t be bothered turning it off, I recall defaulting to The Genius character because it was more familiar. Yet both failed because they didn’t offer any meaningful interaction or solve any problems. …


As digital assistants invade our lives, the opportunity and limitations are becoming more evident. Natural language processing and the digital manifestation of these, reinforced by machine learning, is rapidly developing. When the opportunity to understand and evaluate digital human technology came along, I leapt into the deep end with a team of equally enthusiastic specialists. As I write on the learnings, I thought it would be worthwhile to describe the set up for context.

The scope was to learn as much as we could about this new type of interaction. The team engaged with stakeholders and used a series of lean and design-thinking workshops to come up with assumptions to test and use-cases to apply. Perhaps the most critical questions we wanted answers to were, are people ready for this type of interaction? And, what variables could be changed to improve the experience? For this, we would need to set up a digital human-powered by AI to understand and execute a task based on natural language processing. …

About

Prashant Ranchhod

Creative technologist, leader, and product mentor. Passionate about putting people at the centre of design and experience.

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