Data Scientists Are The Next UX Designers

User experience is now about far more than the look and feel of a website or app


Traditionally when we think of UX design, it is around how people design websites, apps and the layout of digital products. It allows people to move through the digital space as seamlessly and efficiently as possible, all within an attractive and well-designed environment. It has as much to do with aesthetics as it does with the way that customers or users interact with a site. This has meant that it is generally seen as a creative aspect of the business with more in common with traditional design roles.

However, the world of UX is beginning to diversify, with the increased use of chatbots and personal assistants creating a new field of UX. Here, the idea isn't necessarily to make sure that things look good, create a customer journey or make a site looks clean, it is to interact effectively with somebody asking a question of the technology.

This move puts the onus of UX not on looks, but instead on knowledge and understanding of the question being asked. Having a chatbot that looked good but couldn't understand many questions asked of it would be the equivalent of having a really nice looking taxi, but a taxi driver who didn't know their way around - it may be well designed, but you are still going to get frustrated when you don't get where you want to go.

This new form of UX is being driven by data, AI, and cognitive computing, meaning that those who can understand and implement data-driven insights will become one of the most important members of these new UX teams. We are equally going to see an increasing number of copywriters becoming integral to their development, with Anna Kelsey (who was hired straight out of Harvard), the AI interaction designer at - a startup creating a chatbot - saying 'The whole idea of creating a character, and thinking very technically about the way specific words or groupings of words can make people react and respond, is something I thought about all the time in college.' It will also empower those who maybe before had a bit part in company perception, with Ben Brown, co-founder of Howdy - a chatbot run within Slack - claiming that 'All of a sudden [micro-copywriters are] the king because it’s nothing but microcopy now. That little form validation error message, or whatever, is now the full and total sum of your brand’s representation [in this interface].'

However, although the tone of the bot and how it says things will be important, the most important will be how it works, which is where data takes the lead.

Firstly, the ability to find answers to questions through mining billions of web pages, APIs and social media feeds has reached a stage where it brings up the correct answer more often than not, compared to fairly limited capabilities only a couple of years ago. We have seen through the development of cognitive computing technologies, like IBM's Watson, that the practical uses aren't a sci-fi future, but very much a current proposition. However, it is not simply in the answering of questions, but in the analysis of the questions in the first place through semantic analysis. We may not be at a stage where a virtual assistant can understand the complexities of tone, like sarcasm or anger (the word ’sick', for instance, could have multiple meanings, but only one to a virtual assistant) but through AI, sentiment analysis and voice analysis of millions of interactions and outcomes, these systems are building a better understanding of meaning, even in colloquial speech.

The big challenge that currently exists is the use of these not as standalone apps, but within other apps and alongside other apps. This increases the reliance on data-driven insight, but also opens up technology for even more uses. For instance, it would be possible for a virtual assistant to set reminders about birthdays from Facebook, appointments from calendar applications and order food knowing your preferences from your previous online shopping experiences. It would essentially be able to create an entire dataset focussed on the individual far superior to anything that a single company could collect at present. This will create the ultimate seamless UX experience where the technology can learn about the individual elements of people's lives, but with this amount of information, the only people who can truly utilize it will be those who can already work with huge amounts of data. 

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