Have you ever wondered how Amazon knows exactly how to tempt you with the perfect product recommendation? Machine learning can help create user-centric products by personalizing experiences to the individuals who use them. This has enabled computers to understand the things we say and what we see: from Google Photos creating an album of your cat, to Facebook providing relevant content to your feed. But how do you personalize in a way that’s well received and allows machines to account for user empathy? Connecting the human factor with machine learning is tricky. In order to get it right, UX and research play a big role in users’ reception.
UX design was once considered more of an art than an exact science. Now, there’s a transformation of the creation process that’s a balancing act between designing for human sensory while algorithms and data enable us to make tailor made digital experiences. Even within travel, Booking.com is utilizing machine learning to enable people to experience the world in a personalized way. But, sometimes user’s reactions to these predictions are not what you’d expect.
UX designers, must bridge the gap between Artificial Intelligence to real human behavior and emotion. This session explores why rethinking the traditional approach by adding context, creative copy and testing can lead to success, while also delving into the pitfalls of when data science and UX negatively impact the end user. During this talk, Allie will share examples of best practices for using machine learning within a human-centered design approach.
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