We are a Learning Organization

Innovation requires learning. Learning requires experimentation. By normalizing retrospection, we create a habit of learning together and improving as we go.

Why managing AI risk presents new challenges

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The difficult of using AI to improve risk management

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How to bring AI into managing risk

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Pros and cons of using AI to manage risks

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Benefits and opportunities for risk managers applying AI

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Innovation requires learning. Learning requires experimentation. As a learning organization, we know that the only failure is a failure to learn.

What this value means:

We learn as fast as we can, as often as we can

  • We know that learning requires experimentation.

  • And we know that experimentation requires risk.

  • We embrace The Power of Now to experiment with as many shots on goal as we can. Sometimes we are successful. Most of the time, we learn. And then we try again, utilizing our learnings.

  • We prioritize being better over being right.

We focus on what’s “safe to try”

  • Part of experimentation and learning is to start by starting.

  • Sometimes it can be hard to know whether it's OK to try something new. A great framework to use is "Is this safe to try?"

  • We are consent vs. consensus-based

Consensus = “does everyone agree?” and no action is taken until everyone does agree.

Consent = “does any one person object?” and action is taken by default unless anyone objects.

See more detail below on "valid vs. Invalid objections"

How to live this value:

Even/Over Statements for this value:

  • The best way we know today over The right way

  • Guardrails over Gates

Putting it into action:

  • Understand and live our Culture of Retrospection

  • Do a “3Ls” or similar retro at least weekly with your teams

  • Retrospect in external meetings as well — clients, vendors, board members, etc.

  • Understand the difference between fixed and growth mindsets. "Cultivate your growth mindset."
  • Everything is up for innovation / iteration / progress.

  • We do no not hold anything as precious or rigid

  • Everyone is always learning — no one is “beyond” learning

  • Learn about “valid” vs. “Invalid” objections: Is this safe to try? If we moved forward would this cause irrevocable harm?

Valid objections:

  • This will cause irrevocable harm, and here’s how [state the harm]

  • Historical data has shown this will cause serious harm

  • We don’t have the authority to make this decision

  • It will impede my ability to do my role

Invalid objections:

  • Because I don’t like it or it makes me nervous

  • Stating a pre-existing issue (that team doesn’t get a long, I’m worried how people react.)

  • Fear of future fears (“If we do [x], then [y] might happen”)

  • Stating future tensions that may never come to fruition

  • I want to make the proposal better

What this value doesn’t mean:

  • We’re not advocating for “failure.” We are here to win. We believe the best way to win is to treat failure as learning, pick ourselves up, and try again.

Why this value is important to us:

  • Knowledge work innovation is often non-obvious, as we describe below. The best way to win is to create a culture that prioritizes velocity to create as many shots on goal as possible, and learning as much as possible from each rev.

What is a Learning Organization?

  • Knowledge work innovation is often non-obvious (example: it sounds like a terrible idea for me to go to your house when you're not home… eat the food in your fridge, sleep in your bed, use the soap in your shower, and then pay you $100. But that idea is… AirBnB, a company worth over $100Bn), which means that to find those innovative ideas, your organization has to become great at learning.

  • In order to learn, you must re-think the concept of failure, because learning requires experimentation, and experimentation requires shots on goal — many of which will result in "failure." But without these shots on goal; without iterating, you will not be able to innovate.