Understanding Your Reactions - Defensive Reasoning and the Individual

Yesterday, we talked about the exciting yet sometimes unsettling arrival of AI in aviation. We touched upon the story of Captain Evans and his initial resistance to autopilot, a resistance rooted in a very human tendency towards what Chris Argyris calls "defensive reasoning."

Today, we're going to delve into the fascinating world of our own inner reactions to change.

Why do we sometimes resist new ideas, even when they might be beneficial? How can we become more aware of our own thought patterns and learn to navigate change more effectively?

Meet Your Inner Advocate (and Your Inner Critic)

Imagine you're presented with a new AI-powered tool designed to streamline your workflow. A part of you might be excited about the potential – the "inner advocate" sees efficiency, progress, and maybe even a chance to focus on more interesting tasks.

But another voice might whisper doubts – the "inner critic." This voice might say things like, "What if this makes my skills obsolete?" or "I don't trust this new technology," or even "This is just another management fad."

This internal tug-of-war is a classic example of how our minds work. And often, the "inner critic," fueled by a desire to protect our sense of competence and control, can lead us down the path of defensive reasoning.

Chris Argyris and the Two Models of Behavior

Chris Argyris, a brilliant organizational theorist, spent decades studying how individuals and organizations learn (or fail to learn) from experience. He identified two distinct models of human behavior: Model I and Model II.

Model I: The Defensive Mindset

Model I is essentially our default, defensive operating system. When we operate from Model I, our primary goals are to:

• Remain in unilateral control:?We want to be in charge and avoid feeling vulnerable.
• Maximize winning and minimize losing:?We strive to be right and avoid being wrong.
• Suppress negative feelings:?We avoid expressing emotions that might be seen as weak or disruptive.
• Behave "rationally":?We focus on logic and data, often to the exclusion of emotions and intuition. But we do so in a way that avoids engaging with data that does not align with our need to remain in control and win.

?Sound familiar??We all engage in Model I behaviors from time to time.

Here's how it might play out in everyday work situations:

• Dismissing a colleague's idea without truly considering it because you didn't come up with it yourself.(Control)
• Avoiding a difficult conversation with a supervisor because you're afraid of looking incompetent.?(Minimizing losing)
• Nodding along in a meeting even when you disagree, to avoid conflict.?(Suppressing negative feelings)
• Selectively presenting data that supports your viewpoint while downplaying data that contradicts it.(Behaving "rationally" to win)

Model II: The Learning Mindset

Model II, on the other hand, is about embracing a learning mindset. When we operate from Model II, our goals shift to:

• Valid Information:?We seek out accurate and complete information, even if it challenges our existing beliefs.
• Informed Choice:?We make decisions based on the best available data and with a clear understanding of the potential consequences.
• Internal Commitment:?We take ownership of our choices and are genuinely committed to following through.

?Single-Loop vs. Double-Loop Learning: Two Different Approaches to Problem Solving

Argyris connected these models to two types of learning:

• Single-Loop Learning:?This is like adjusting the thermostat when the room gets too cold. You address the immediate problem without questioning the underlying assumptions.?Example:?You encounter an error with a new AI tool and find a workaround.

You've solved the immediate issue but haven't investigated why the error occurred in the first place.

• Double-Loop Learning:?This involves questioning the underlying goals and assumptions. It's like asking, "Why is the room always cold? Is the insulation adequate? Is the thermostat calibrated correctly?"??Example:?Instead of just finding a workaround, you investigate the root cause of the AI tool error. You might discover a flaw in the training data or a need for better user interface design.

You are not just fixing a problem but are preventing future similar problems.

Espoused Theory vs. Theory-in-Use: The Gap Between What We Say and What We Do

Argyris also highlighted the difference between our?espoused theory?(what we say we believe) and our?theory-in-use(what our actions reveal about our actual beliefs).

For instance, we might espouse a belief in teamwork and collaboration (espoused theory), but our actions might reveal a tendency to dominate conversations and dismiss others' ideas (theory-in-use). That is a Model I behavior.

Identifying Your Triggers

So, how can you become more aware of your own Model I tendencies? Start by paying attention to your internal reactions to change or challenges. What are your triggers?

• Do you feel defensive when your ideas are questioned?
• Do you find yourself resisting new technologies or processes without fully understanding them?
• Do you avoid giving or receiving feedback that might be critical?
• Do you prioritize being right over finding the best solution?

The Question to Ponder

This week, I encourage you to reflect on this question:?How might you be unknowingly engaging in defensive reasoning in response to AI or other changes in your workplace?

Think about a specific situation where you felt resistance to a new idea or a change in your work environment. What were your thoughts and feelings? What actions did you take (or avoid taking)?

By becoming more aware of our own defensive patterns, we can begin to shift towards a more open, learning-oriented approach – an approach that is essential for navigating the exciting, yet complex, world of AI in aviation.

In our next issue, we'll explore how defensive reasoning can impact team dynamics and collaboration, and how we can start to build a more Model II culture within our teams.

Disclaimer: The thoughts and opinions expressed in this newsletter series are my own, inspired by recently listening to Alejandro Salazar and Robbie J Frye ?? ′s podcast, where they presented the fascinating work of organizational theorist Chris Argyris. His ideas, particularly the observation that “the smarter and more sophisticated people are, the less learning there is in their conversations,” resonated deeply with me and resonated with my experience in the aviation industry. I believe Argyris’s ideas, especially his concepts of Model I and Model II behaviors, have profound relevance to addressing the complexities of AI adoption in our field. I encourage readers to explore Argyris’s original work to better understand his theories. It is important to note that while these newsletters offer perspectives on leadership, learning, and change management, they should not be construed as a substitute for official guidelines or regulations. In the aviation industry, safety and compliance are paramount. Always consult and follow current rules and procedures set by relevant authorities (such as FAA, EASA, and ICAO) and your organization. The information shared here is intended to stimulate thought and debate, not to replace established protocols.