Blog: Artificial Intelligence (AI): What About The User Experience? – Forbes
One of the key drivers of the AI (Artificial Intelligence) revolution is open source software. With languages like Python and platforms such as TensorFlow, anybody can create sophisticated models.
Yet this does not mean the applications will be useful. They may wind up doing more harm than good, as we’ve seen with cases involving bias.
But there is something else that often gets overlooked: The user experience. After all, despite the availability of powerful tools and access to cloud-based systems, the fact remains that it is usually data scientists that create the applications, who may not be adept at developing intuitive interfaces. But more and more, it’s non-technical people that are using the technology to achieve tangible business objectives.
In light of this, there has been the emergence of a new category of AI tools called Automated Machine Learning (AutoML). This uses simple workflows and drag-and-drop to create sophisticated models – allowing for the democratization of AI.
But even these systems require a background in data science and this can pose tricky issues with the development of the UI.
“Our mission when we designed Dataiku was to democratize data and AI across all people and to unite all of the various technology pieces out there,” said Florian Douetteau, who is the CEO of Dataiku. “We kept this mission in mind when we embarked on our UI. Enterprise AI is the future, and that means hundreds and thousands of people are using Dataiku every day as the core of their job, spending hours a day in the tool. So we keep the UI of Dataiku simple, clean, modern, and beautiful; no one wants to work in a space — virtual or otherwise — that is cluttered or that looks and feels old, especially when data science and machine learning are such cutting-edge fields. Another important consideration is ease of use, but not at the expense of robustness. That means making sure that Dataiku’s UI is simple for those on the business side — many of whom are used to working in spreadsheets — who don’t have extensive training in advanced data science as well as the most code-driven data scientist – but none of this as a tradeoff for deep functionality.”
Yes, it’s a tough balance to strike – but it is critical.
Actually, to get a sense at how this can work, consider Intuit’s TurboTax. The software deals with an incredibly important but complex topic for consumers. The technology also involves advanced AI systems and algorithms, such as by leveraging data to surface industry-specific personalized topics.
“When we went out and asked thousands of consumers about their tax preparation, most responded with emotions of fear, uncertainty and doubt,” said Eunie Kwon, who is the Director of Design at Intuit. “Once we started to unpack their reasons for these feelings, we found opportunities to influence their experience by applying some basic psychological principles and laws of UX heuristics to simplify through mindful design. To reduce cognitive load, we balanced the fundamental elements of design through content, visual expression, animation, and recreated the informational experience to reduce fatigue, friction and confusion. To improve workflow, we dissected the complicated tax forms into adaptable and consumable interview-like experiences. We added ‘breather’ screens where we acknowledge to the customer how much they’ve completed and the accuracy of their input. We also added ‘celebration’ screens to drive confidence that informs them of their progress while educating them on the changes in tax laws along the way.”
Such approaches are simple and make a lot of sense. But when developing software, they may not get much priority.
“The main lesson learned when designing for TurboTax is balancing simplicity while ensuring 100% confidence for a customer’s tax outcome,” said Kwon. “Every year, we are faced with new mindsets that evolve the behavior of how consumers interact with products and apps. The expectations for simplicity and delight change so often that we need to look at our experience and find improvements that meet those expectations, while driving complete confidence through their tax experience.”
Tom serves on the advisory boards of tech startups and can be reached at his site.