EMILY SAPPINGTON

Creating Minimum Viable Intelligence & Setting User Expectations: We are entering the age of intelligence—a time when technologists imbue artificially intelligent components into many products without a clear framework for how such intelligence is delivered to users consistently. It is a product designer’s job to make AI feel human-like and magical, not overwhelming and scary to users. When designing for Artificial Intelligence scenarios, whether for a large enterprise or small startup, setting user expectations is critical to deliver a reliable product. I will share some best practices from designing for AI in both large and small organizations. No matter the company size, a minimum viable product is important to design and not to be the result of unplanned feature cuts. I will share what Minimum Viable Intelligence is for an AI product, and how designers can deliver a clear UX when solving problems efficiently. When thinking of how to design for intelligent products, first and foremost it needs to seem competent. Users must trust the AI agent or service with information and believe that it can achieve their goal. The bar for this depends on the expectations the designer sets. The most difficult thing about breaking out of scenario-focused AI is the lack of clear boundaries. Are you aspiring to create an entire conversational AI agent? Then the bar will be high, being that it is human-like in every way, including what it can respond to. A less intelligent Bot, however, will teach users the rails of its conversation early on to avoid disappointment. In this talk we’ll dig deeper into setting appropriate expectations when designing for AI across large and small applications. Designing AI touchpoints from conversational interfaces to more traditional UI leads a designer to solve for how to best explain the capabilities of AI without overwhelming or frightening the user. This can be achieved by drawing on human interaction models. Responsiveness when users expect it is only one part of this equation. Apps that explain processes in human ways, like thinking, seeing, or reading, can benefit from showing users where they are in a process, while explaining it in natural ways. Emulating true intelligence takes more than just seeming alive and being basically competent though. To surpass users’ expectations can be a delightful moment when the product seems truly and independently intelligent.

We are entering the age of intelligence—a time when technologists imbue artificially intelligent components into many products without a clear framework for how such intelligence is delivered to users consistently. It is a product designer’s job to make AI feel human-like and magical, not overwhelming and scary to users. When designing for Artificial Intelligence scenarios, whether for a large enterprise or small start up, setting user expectations is critical to deliver a reliable product. Emily will share some best practices from designing for AI in both large and small organizations. No matter the company size, a minimum viable product is important to design and not to be the result of unplanned feature cuts. Emily will share what Minimum Viable Intelligence is for an AI product, and how designers can deliver a clear UX when solving problems efficiently. When thinking of how to design for intelligent products, first and foremost it needs to seem competent. Users must trust the AI agent or service with information and believe that it can achieve their goal. The bar for this depends on the expectations the designer sets. The most difficult thing about breaking out of scenario-focused AI is the lack of clear boundaries. Are you aspiring to create an entire conversational AI agent? Then the bar will be high. A less intelligent Bot, however, will teach users the rails of its conversation early on to avoid disappointment. In this talk we’ll dig deeper into setting appropriate expectations when designing for AI across large and small applications. Emily will share how drawing on human interaction models helps designers know what to expect when people encounter their AI product. Responsiveness when users expect it is only one part of this equation. Apps that explain processes in human ways, like thinking, seeing, or reading, can benefit from showing users where they are in a process, while explaining it in natural ways. Emulating true intelligence takes more than just seeming alive and being basically competent though. To surpass users’ expectations can be a delightful moment when the product seems truly and independently intelligent. About Emily Emily Sappington is the Product Director at Babylon Health. Previously she served as VP of Product at London-based AI startup, Context Scout. Emily has spent the bulk of her career in the United States designing Cortana for Microsoft across devices, particularly Natural Language & UI interactions with the assistant. Emily is a lecturer, US patent-holder, career coach for Ada School (the National College for Digital Skills in the UK), and is a recipient of an Exceptional Talent Visa from the UK Government and Tech Nation. @sappingtonemily LinkedIn/emilysappington

In the first of Graphite's Virtual CX Sessions, we heard from two inspirational thought leaders as they spoke about AI in the context of creating better digital customer experiences for people. Firstly, we heard from Emily Sappington, Product Director for Voice & Conversational Applications at Babylon Health who spoke about 'Designing for AI: Setting User Expectations'. We also heard from Adam West, Head of Marketing at Satalia as he spoke about 'Innovation in the context of AI'.