Design and Data
Where There's Data, There's People
How to see humans in a world of data.
Being truly human means respecting our own, and each other’s, humanity. Being a good designer means honouring that humanity when we create. It means understanding people’s aspirations, abilities, efforts, and emotions. What we offer to the world should reflect all of these things, and make their lives better in some way. This is our mission.
Advances in data science, machine learning and artificial intelligence have the potential to enhance people’s lives, and the services they use. Computers can analyse and respond to data in really smart ways. Algorithms can identify and create patterns of human behaviour. But, these algorithms don’t understand human behaviour. (Not yet, at any rate.) The information they spit out isn’t necessarily ready for human consumption, or attuned to human needs. It can be raw, uncompromising, and impenetrable.
This presents a unique opportunity for designers. We can humanise that data, by translating and pulling insights from the outputs of those algorithms. That way, human knowledge and understanding can make sense of the results.
Why it’s important to humanise data
It creates a conversation
Humanising data means seeing the rich, relevant insights and presenting them in an empathetic way. This allows us to have a two-way relationship with algorithms and machines, and sparks a conversation from which both sides can learn.
It gives us a new lens on data
Seeing people in the data gives us new-found respect for it. This is true when we’re trying to create insightful outputs, researching problems, or designing solutions.
It can serve as protection for humans
The raw output of machines and algorithms can potentially be damaging or hurtful to humans, especially if they are vulnerable or apprehensive. A thoughtful and careful interpretation of data means they can be protected against that.
How can we make data more human?
Change the perspective
We need to have empathy, and put ourselves in the shoes of those receiving the data. What will the figures and the stats mean for them? What might the impact of the data be? Try to translate and analyse the data so that it makes sense for people. Also, try to be sensitive to the effects of that data on a person. For example, if you are presenting cholesterol levels, you can tell someone that they scored 5. But it would be a lot more helpful and reassuring, if we let them know their level is just one point over the average. (And offer some tips to reduce it.)
Make it real
Sometimes big percentages or unwieldy pie charts can wash over people. They don’t relate to real life or experience. What if we translate the data into a language that people can understand more clearly. So, for example, you might be 75% complete on a project, or 3 steps away from your end goal. The context and cushioning of data is really important, especially when it comes to health and wellness information.
Find a balance
An overload of figures and percentages can be overwhelming. We need to find the right balance between the stats and visuals that really bring the data to life. In this way data, interaction, visual, and content design can come together to create a really meaningful and engaging piece.
Keep people at the heart
As designers, our relationship with data at this scale is new. We search for new methods, standards and rules to help us understand it. But in fact, our design compass shouldn’t change: It should always be about people. Are we listening to those people? Are we respecting and trying to augment their lives? Are we answering the right questions? Are we adapting out service for different needs? These key questions and principles will help to keep us focused, and to ensure that people are at the heart of our creative process.
Seeing the bigger picture
Algorithms can only go so far, we need human reasoning to make sense of the data produced.
We need to make sense of that data, to analyse it and to find the patterns and themes that will impact on humans. We can explore and expand on that content in smart, beautiful ways. So, in order to make the result more human, we need human input. Simple, right?
We’ve always been good at making sense of stuff. We make sense of nature and the cosmos with physics and of ourselves with psychology. Now we’re trying to make sense of algorithms, different types of intelligence, how we relate to the digital world - and are ultimately augmented by it with design.