As Jean mentioned, there are shifts and mindsets that come with deeply learning in action. In this phase very little comes naturally, as it forces us to abandon our need to be right, our fear of rejection and our anguish of having to start over, after coming this far. For this phase, we look deep into psychological constructs, to understand psychological makes or breaks for good experimentation. One such barriers standing in our way from learning in action is, our fear of failure, for many of us are aversion to failing is deeply rooted. Psychologist Carol Dweck, the mother of growth mindset research finds that, many of us have internalized the insidious belief that, being smart means having the right answer. As a consequence, we spend much of our lives avoiding new situations, where we might make mistakes. Professor E Tory Higgins identifies this as prevention, avoiding action to prevent the possibility of error, versus promotion which is taking action to seek something better. Kathryn Schulz warns us that, the negatives associated with such certainty of rightness, go far beyond just being proven wrong. They result in the loss of imagination and empathy, which are necessary to deeply experienced DT. Experimentation requires learning, but in order to learn from testing, we have some unlearning to do. Psychoanalysts have studied unlearning for decades, particularly as a foundational success factor for therapy. Unlearning old beliefs, and the ways we think and act is critical to learning. As articulated by author and Franciscan friar Richard Rohr, transformation is often more about unlearning than learning. Research by psychoanalyst Otto Rank shows that, we must recognize habits of the mind and heart, that drive the way we currently behave. Then let go of aspects of our past, to let come new realizations and possibilities. Organizational theorists also have studied what it takes to unlearn. They find that, it takes a significant amount of emotional work, because we are invested in our established ways of perceiving the world. Deep unlearning may surface confusion, anxiety, fear, blame, guilt or shame. It is serious business that requires action, as well as reflection. The fields of learning theory, organizational theory and education are ripe with this notion that, action coupled with reflection provides the most robust form of learning. Learning theorist David Kolb describes four specific components of a learning cycle that, ends with actively experimenting with changing situations. It is necessary to put learning into action, to try various options and react to outcomes and iterate based on what really works, as opposed to simply watching a situation. Similarly, research on after action reviews demonstrates that, conducting and reflecting on experimental results simulates a retrospection. That improves future performance by reviewing both successes and failures, and understanding why events happen the way that they do. While I've already mentioned our fear of failure, researchers have found that we are even less likely to learn from success. Because in order to do so, we have to dig deep to understand specific detailed causes of that success that we can replicate, which takes extra time, effort and motivation. This effortful reflection mixed with external feedback, accelerates performance. But unfortunately, even reading feedback signals much less responding to them is no easy feat. Coping with fear of failure, and successfully unlearning are stymied by an especially powerful set of human cognitive biases. As we mentioned at the start of this course, the category three biases are the most powerful and most researched of all. When we test, we find ourselves hoping to see what we want to see, who doesn't love hearing that people love their ideas, and we worry about if they don't like them. The source of this tension is surprisingly simple, we seek pleasure and avoid pain. Being right feels great, while being wrong feels awful. Our brain helps us cope with this by, tricking us into overlooking results that go against what we want to see. This creates major challenges when we try to manage risk, luckily the solution brings us back to primary school, and Sir Isaac Newton, known as the father of science. Newton depicted an empirical method for acquiring knowledge in the 17th century. For many of us, the scientific method is likely just a hazy memory that is rarely discussed in organizations, outside of laboratories and universities. But its components are what help us break free from our biases, and learn from our experiments. It advocates problem solving, through a formal process of generating and testing a hypothesis. Or a bold guess as he put it in this quote, the value of being hypothesis driven really hits home, when we try to learn in action. But the kind of hypothesis testing done by scientists is, different than that done by designers, scientists discover and designers invent. Scientists used the method to explain what is, while designers deal primarily with what could be, but doesn't necessarily exist yet. Design hypotheses are prescriptive in this nature, describing what we might do rather than scientists descriptive hypothesis about, what is currently going on. While scientists can decide if a descriptive hypothesis is true, or false based on present data. Prescriptive hypotheses about the future can never be proven true in the present, until we build the solution, and introduce it to the world. But in order to manage risk, we can't just build the new solution at scale. So the best we can do to test design solutions is, to surface the descriptive hypotheses that underlie the prescriptive ones. Starting with make or break assumptions, this allows us to marshal evidence. To convince others that, our particular story about the future is worth investing in. To reiterate, learning in action is counterintuitive to the many ways our brain copes with risk, uncertainty, validation and the need for closure. While unlearning and subsequent learning through testing is possible, we need to focus on what makes it one of the hardest phases in the DT process.
