Amplified Learning: The Power of Error and the Reinforcement of Behavioral Change

News
09/02/2024

In this era of rapid advancements and profound transformations, continuous learning has become an imperative. “Lifelong Learning” is now a basic that we all need in our skillset. The ability to adapt, evolve and acquire new skills is vital, not only for individual growth, but also for the development of the companies with which we interact.

With technological advances catalyzing profound changes in all sectors, the concept of learning and development has been no exception. The traditional one-size-fits-all approach is gradually giving way to a more dynamic, engaging and experiential learning model, something we’ve been advocating at Immersis for the past 13 years.

Recently, the University of California at Berkeley revealed a reinforcement learning methodology that uses human input signals,1 a promising approach to improving the training of AI systems in complex environments. This method, which prioritizes recognizing errors rather than trying to ensure that the answer is perfect on the first try, mirrors a fundamental truth about human nature: learning from mistakes is one of the most powerful forms of personal and professional growth. . and it’s really interesting to see that it also works better for AI, demonstrating that error is a catalyst for development.

The basic idea is simple but remains powerful. Imagine a pianist learning a new piece. Playing this piece perfectly the first time will be difficult. It would involve lateral training, deep memorization and hours of mental simulation to ensure you get it right the first time, which is rare. The pianist is more likely to make mistakes, recognize them and correct them over time, resulting in a more realistic and effective learning process. This learning method is valuable because mistakes provide clues about what needs to be improved, allowing for more genuine and lasting growth and development. This is how you learn “best”.

At Immersis, we believe that learning should not be a journey to perfection, but rather a continuous process of experimentation, adaptation and overcoming. Rather than aspiring to flawless execution, we encourage the adoption of a “curiosity mindset” that embraces error as an opportunity for development… but is only the starting point.

In addition to recognizing and correcting individual errors, it is essential to develop systems that support and reinforce learning and continuous behavioral change. Nowadays, it is not enough for an individual to make an effort to change2 (and we all know how difficult it is to start new habits or upgrade our characteristics). You need a system around you that provides constant feedback, offers regular opportunities for reflection, and encourages deliberate practice. This system can include progress tracking tools, communities where you practice together, and structured times to review and adjust behavior.

I remember an extraordinary example by Seth Godin3 on this topic where the system was much more effective than calling for effort. For effective change, we need support systems like the ones he describes where robust structures complement individual dedication.

Nowadays, with the war for talent becoming more and more intense, organizations need to focus on more than just the benefits. Mechanisms that promote collaboration and growth are needed. Learning and behavioral change are not merely personal, but systemic, and must be supported throughout the company.

Our approach to learning is based on experience. We provide situations that challenge, invite reflection, and above all, promote awareness for change. It is through experience and interaction that knowledge is consolidated, skills expand and behavioral change solidifies. But we don’t stop there, because we know the journey is continuous.

The entire dimension of transfer, deliberate practice and behavioral transformation is yet to be worked on in Portugal. And these will be battles that we want to win in 2024 so that we can raise the level of experiential learning.

  1. https://venturebeat.com/ai/new-reinforcement-learning-method-uses-human-cues-to-correct-its-mistakes/ ↩︎
  2. http://freakonomics.com/podcast/live-philadelphia ↩︎
  3. https://seths.blog/2018/11/quality-and-effort/ ↩︎

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Amplified Learning: The Power of Error and the Reinforcement of Behavioral Change