Last week, AnswerLab hosted three experts in artificial intelligence and conversation design at our San Francisco office to share their take on the future of AI and user experience. Coming from a variety of different backgrounds, ranging from journalism and conversation design to engineering and development, our three panelists presented a diverse set of perspectives that we as researchers aren’t always the experts on. However, despite their differences, we found they aligned on a few key principles that drive successful AI. In case you missed it, you can watch the full panel here or read our key takeaways below.
When it comes to chatbots, users have less patience and higher expectations. If your chatbot doesn’t understand a user’s request or can’t answer the question, don’t get stuck in an error loop by repeating an error message over and over. After a few failed attempts, offer a friendly apology, acknowledge that it can’t help with that kind of request yet, and create some ways to continue the conversation and help the user find the answer to their problem. Creating a route for the user to get what they need even if it means passing them off to a human customer service agent not only increases overall customer satisfaction, but leaves the user more open to future interactions with the chatbot for other tasks.
AI is still early in its development, and because of that, companies have to understand that building AI is very experimental. You could spend six months building a model without it ever creating anything that will turn into profits. But, that doesn’t mean you should give up altogether. Building AI is a process and if your team is willing to invest in it, it could make a big difference down the road. Get on board now before it’s too late.
Noelle built an Alexa skill called Mindfulness where users can take a minute to stop, breathe, and receive affirmations through the device. While she built it when the Echo was the only way to access it, when Alexa for the Car came out, they told her her skill was broken. She realized the first interaction is telling the user to close their eyes. As new ways to access these skills emerge, we have to respond with a deep understanding of the new context and continue to adapt and build with many situations in mind.
While we often think about designing for multi-modal experiences, we also need to think about location-based context when it comes to voice. If you’re in the car, your interactions will be much different than if you’re in a public place or in your home. We have the data to understand where the users are and how they’re accessing these devices. Now it’s time to use the information to build a better and more inclusive experience.
AI is still very unknown, and with that comes apprehension. It’s our duty to build experiences that are transparent and honest. Building trust demystifies AI for users. All of our panelists pointed to ways you can foster trust from disclosing where information is being gathered to creating honest depictions of the technologies users are interacting with. By pulling back the curtain, users have a more sincere experience with the technologies and companies that produce them. Building ethical AI is a conversion that must be fostered and prioritized at all stages of the development process to create inclusive, helpful experiences for all users.
Ticket proceeds from this event and all of our events this quarter are being donated to AI4ALL, a nonprofit working to increase diversity and inclusion in artificial intelligence. AI4ALL creates pipelines for underrepresented talent through education and mentorship programs around the U.S. and Canada giving high school students early exposure to AI for social good. Learn more about AI4All and find out how you can join us at an upcoming event!