How is design changing as a discipline and profession? How do we face these opportunities as a community?
I started a new podcast with AIGA called Design Future Now to explore these kinds of questions and more with creative leaders and practitioners. This also means that I will be taking a hiatus from FoossaPod, the podcast that David Colby Reed and I started back in 2017, to focus on Design Future Now. Check out the latest episode below:
Written by our friends and long-time collaborators Jeff Leitner and Andrew Benedict-Nelson, and designed by me and the Foossa team, See Think Solve is a simple guide to difficult problems.
Originally developed for a social work PhD program at the University of Southern California, it is written in an easy-to-read, jargon-free style for anyone interested in better understanding human behavior and how to design products, services, and programs that shift collective norms and culture. The ideas in the book have really shaped our consulting and teaching practice.
The main reason problems are hard to solve is that they involve people. People are funny. They don’t always believe the things they say they believe or do the things they say they are going to do. They can act one way in one situation and act completely differently in another situation. No one has ever completely figured this out. We call this the ‘mystery of human behavior.’
The mystery of human behavior shapes almost every problem worth solving.
That’s the bad news. But there’s good news too. The mystery of human behavior also helps us see problems in new ways. By paying attention to people, we can discover new aspects of problems that help us solve them more effectively.
The nine steps in See Think Solve are designed to do just that. They will help you make sense of the mystery of human behavior that surrounds all tough problems.
– The first six steps are about seeing — each of them shows you a new thing to look for in human behavior.
– The next two steps are about thinking — each one is a tool you can use to better understand the human behaviors you have observed.
– The last step is about solving — it describes what you can accomplish with your newfound knowledge.”
About the Design
When planning the design for the book, we wanted to communicate both “simplicity” and “humanity.” The book is meant to be a simple guide to difficult social problems. To reflect this intention, we created an iconography that references both the periodic table of elements and the New York City Subway signage system by Massimo Vignelli and Bob Noorda. The icons serve as a kind of way-finding for readers of the book and help them remember each of the steps in the See Think Solve process. To add a rich, humanistic feel to the visuals, we chose a color palette derived from traditional Japanese art and design. The book cover also features subtle curves on a dark grey background, which are meant to evoke a topographical map or electromagnetic waves.
How does NASA get its mojo back? What do big cities do with selfish billionaires? What’s wrong with art education? How are inner city youth the answer to urban renewal? What does the military have to do with the arts?
Innovation Dynamics is the first systematic approach to real social innovation and solving people-problems. Purchase includes a beautifully-designed, printed quick-start guide and 90-days of online access to The Short Course on Innovation Dynamics at The Academy for Social Change. The online course includes brief, animated instructional videos and an interactive workbook that can be printed for collaboration in teams. Buyers receive one unique access code to the online course with each printed guide.
The quick-start guide and multimedia introduction were developed by founders of GreenHouse, Insight Labs and UX for Good and innovators in residence at the University of Southern California. It emerged from years of work in the U.S., Europe and Africa with organizations like the U.S. State Department, NASA, Harvard Medical School, Starbucks, the Dalai Lama Center and the TED Conferences.
Users will learn how to:
Break problems down into their most essential parts
Reconcile various stories behind problems
Uncover hidden relationships among problems
See invisible rules that guide relationships and social systems
Leverage expectations to solve problems
Engineer deviance to disrupt the invisible rules
Innovation Dynamics was developed in consultation with social scientists and is a core element of the first-ever doctorate in social innovation.
Technology has advanced dramatically since 1997, and so have anxieties about artificial intelligence and the possibility of automated bots taking over human jobs. Some estimate that by 2025, up to 40% of jobs could go to robots. If machines can do our jobs better, what does our future at work look like?
Workers in almost every field will be affected in some way by automation. Machines are better than humans at repetitive, brute force tasks, and can now even beat humans in well-defined games like chess and Go. They could replace workers in service industries and administrative positions, and even have some management capabilities. But for innovators who are tasked with problem solving and imagining the future, human curiosity and playfulness will always have the advantage.
Take this recent scene at a Fortune 500 company where I worked. Senior level executives gathered on the floor of a cleared out conference room like preschoolers at recess. Recycled cardboard boxes, colorful shards of construction paper, gnarled pipe-cleaners, scented markers, and hot glue were peppered around the room. The participants huddled with their teammates around their prototypes and put the pieces in place, building thoughtfully as they work together.
In the non-profit and public sector, design thinking—which often looks like structured, open-ended play—has become a popular vehicle for creative problem solving and innovation.
In the real-life training session I described, an internal knowledge management software project was running late and over-budget. It was not clear if the work in progress really addressed the needs of the employees who would be using the tool.
The executives hit “pause” and “reset” on the project. They started from the beginning, using empathy as a tool. Through interviews and observations, they tried to understand their colleagues’ knowledge management needs. From there, they formulated a problem statement, reframing the original problem as needed.
If you look beyond the low-fidelity arts and craft aesthetics, the methodology that we teach is not that different from the scientific method: understand, hypothesize, test, rinse, and repeat until we get it right. Our approach goes beyond problem-solving and also works to cultivate a creative culture through a designer’s mindset.
This mindset begins with empathy for the needs of our fellow humans. It is open to a diversity of viewpoints and professional disciplines. It withholds judgement when it is time to ideate, and relies on evidence to make decisions about what works. This requires skilled facilitators who have built intuition through experience. This intuition helps us determine when to foster open-ended play, and when to switch to a more analytical, critical mode of thinking.
While computer artificial intelligence can help us optimize systems and processes, and even replace humans in many job functions, machines cannot yet have that intuition, nor the ability to empathize, reframe problems and truly innovate.
Technological innovation is attempting to bridge this gap. Last year, researchers reported that Google Translate had developed its own meta language to translate between languages it had not previously been trained to engage. In other words, in a vaguely frightening, sci-fi-like development, computers can now at-least partially program themselves, and their human masters don’t fully understand what is happening. But optimization is not the same as innovation. While Google Translate can make it easier to communicate in different languages, communicating beyond the language barrier is still distinctly human. Humans will always win on gestures, making mistakes, humor, and how that all feeds into human connection.
There may be a day when robots learn to brainstorm, play, and innovate, and therefore deliver an unfair advantage to human beings. But for now, humans corner the market on playful and divergent thinking—the kind that breaks through barriers and sparks new ideas. The robots may be coming for our jobs, but it is too early to call checkmate on human ingenuity.
Lee-Sean Huang is a designer, educator, and futurist based in New York City. He is a co-founder of Foossa, a service design and storytelling consultancy and a participant of the Allies Reaching for Community Health Equity (ARCHE) Public Voices Fellowship with The OpEd Project. He also teaches design and futures thinking at the Parsons School of Design.