Once you’ve got your principles straight, then it’s time to get to strategic. Remove anything creepy and watch out for regulation – AI shouldn’t decide which candidates to invite to job interviews, for example, because GDPR gives applicants a “right of explanation” for any algorithmic output based on their data. When you’re testing AI experiences, ask users if they’re comfortable with them. AI can even generate code in real time using TensorFlow machine learning blended with computer vision image recognition.
Using API-driven design, we can add value with chatbots and personal assistants to access our products and services – like Cyber-Duck’s UX Companion Alexa skill.ĪI needs careful planning, like this GP appointment booking system designed at a Cyber-Duck hackathon.Īs product and UX designers, we can use tools like AI assistant Otter to augment transcripts. What do your customers want? Can AI connect the dots for them? For example, if I haven’t logged in to check my mortgage for a while and I made an enquiry with the mortgage company over the phone, should the system make content and feature suggestions to me based on that behaviour when I next visit the website? UX can reveal common-sense applications for AI.
There’s no point implementing AI without proper data science, data collection and data cleansing, otherwise you can’t deliver and measure its impact. Use user centered design (UCD) to research user behaviour and service design blueprints to identify the points in your customer journeys where AI can improve the experience. What can be automated? Anything that takes less than five seconds to compute. So how can we do this? Let’s start with some principles. With tools like service blueprints, you can home in on the points in your customer journeys where AI can add the most value – and justify your investment. Putting your user at the heart of the process means you’ll develop experiences that put their interests first, protect their data and ensure you’re interacting with them with integrity and authenticity. Today, AI is powering genetic testing and computer vision in healthcare risk assessment and fraud detection in financial services even easing and automating government services.ĪI is complex and it’s not cheap, so how can you focus on the opportunities that’ll help your business?
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