By Kathryn Parkes.
I like to think of the role of a designer as a translator in the business world marrying together user needs, business goals and technology.
To do this, designers need to be multi-lingual. In the language of business and technology development, as well as in the language of our users and be able to switch between these with ease. Fluency in all languages is not a necessity but designers should know enough to be able to contribute to the conversation and translate outcomes back to the user.
We are currently seeing user-centred design move in two distinct directions. Leading companies are recognising the importance of Design, with representation at C-Level becoming much more prevalent. This shift can be seen from Venture Capital companies bringing designers in-house, to the startup world where practices such as the Business Model Canvas have evolved from the application of a user-centred approach to business models.
But there is also a move in a second direction & this is in the direction of systems thinking. The environment in which we work as designers is evolving into a complex world of interconnected devices, sensors, networks and diverse systems with vast volumes of data and requires a more holistic view to problem solving. Service Designers are creating solutions that bring a unified view across all channels in a business.
Currently user experience design, is mostly focused on a user interacting with a singular ‘thing’ be that a mobile phone, desktop UI, medical device or some other tangible interface. Designers consider multiple users in many contexts in their design work but there is still, in most cases, some type of close relationship between the user and the thing they are interacting with. It is possible for the designer to observe, design for & influence that tangible interaction.
However we are now dealing with much broader, more complex technology environments where direct interaction is less evident – this is the world of IoT, robotics, automation, machine learning and nanotechnology. How can and should an interaction designer exist in such eco-systems?
To work within complex systems requires a bit of a shift of mindset from the current approach where the user is the centre of our world. It's like how the pre-Copernican world had to adapt to the realisation that the sun did not evolve around the earth but that the earth was part of a far larger system. That system itself was just a part of an even greater one. So our design work should still focus on humans but with more awareness of how our decisions fit into the wider systems of the environment and what the knock-on effects might be on related eco-systems.
The systems we deal with are so complicated now that no one understands them in their entirety. I'm not sure whether that is comforting to know or just disturbing? But here’s the thing, humans have always been dealing with complexity and designers are well adapted to work at the fuzzy end of thinking.
But if no one understands the whole system then have we lost control of it? Or is just that we need to spread the understanding across a broader base at many different levels? Advances in machine learning mean machines are beginning to be able to move from being pure computation machines into understanding fuzzy logic, thinking through inductive reasoning rather than just deductive. Machines are beginning to be able to act on that most human of concepts ‘intuition’.
So it seems that learning the language of data science and machine learning is another useful arrow to add to the designers bow. You’ll come across the usual intricacies and oddities as you do in most languages. Data science is actually an amalgam of a whole bunch of different disciplines. There’s lots of new terminology but like learning any language just making a small effort can go a long way. In fact machine learning uses lots of methods that are just like those in design research just at much larger scale. For example, searching for patterns in information and clustering is exactly what designers do in card sorting exercises. An algorithm can search for patterns in hundreds of thousands of cards in seconds though.
Right now is an important time for everyone to get further involved in understanding the potential of machine learning. There are amazing advances happening in healthcare, science, music, art and design all propelled forward by machine learning. Machines are able to generate their own music and artworks based on the styles they have learned from classic artists, such as Bach and Rembrandt. Discovering how machines learn has in fact taught us so much more about how humans learn & behave.
But there are also concerns about machine learning - many fed by sci-fi movies but some justified. The machines learn from what we teach them. When things go wrong, we somehow seem to see machines as being removed from us. We created them. We need to be aware of our own biases that we are feeding into the system as the algorithms can rapidly magnify them. There are a multitude of ethical, political and sociological implications of where these advances in technology will take us. The conversations and direction of development needs a diversity of inputs. Designers can bring their skills in systems thinking into these conversations.
I’ll leave you with the words of visionary designer Buckminster Fuller from his ‘Operating Manual for Spaceship Earth’ written in 1968:
If you are in a shipwreck and all the boats are gone, a piano top buoyant enough to keep you afloat that comes along makes a fortuitous life preserver. But this is not to say that the best way to design a life preserver is in the form of a piano top. I think that we are clinging to a great many piano tops in accepting yesterday’s fortuitous contrivings as constituting the only means for solving a given problem.