What is the power of data visualization/feedback systems to engineer and optimize human behavior?
The concept of feedback is central to many behavioral models and theories. Live feedback systems are used to close the gap between the current state and a desired level, and their effectiveness is judged on their potential to close that gap.
When feedback systems are live and interactive, they can lead to a continuous cycle of action, assessment, and adaptation. Live feedback systems are increasingly recognized as powerful tools for engagement and behavior change.
For instance, a study published in Sustainability explored the effects of AI-enabled real-time feedback on group dynamics and individual behavior. The findings revealed that such immediate feedback can significantly affect participants' behavior, especially in digital collaboration environments, by promoting self-reflection and critical thinking skills that are essential for sustainable growth in corporate and educational settings.
Similarly, a review of meta-studies published in Energies discussed how providing consumers with customized feedback on their energy consumption could support changes in behavior and encourage investments in energy efficiency and sustainable energy use.
Perhaps the most famous of these is known as the Prius Effect, which we have personal experience to validate:
One of our team has a Prius and every morning they and their kids play a game on the school run which involves using the Trip display that shows up-to-the-moment MilesPerGallon readings to monitor and game how much gas they use.
They also keep the display open throughout the day and typically get between 40-45 MPG. In those periods when it is not on, it's 30-35 MPG.
So we're talking about roughly a 30% differential in gas consumption just based on having a background display signaling while driving.
The Prius Effect is one of the most compelling examples of consumer-facing data-viz that drives behavior change. It’s one of the reasons we are so passionate about building generative objects to help humans - both individually and collectively - see and optimize their behavior.
But maximizing gas consumption is one thing, changing behavior at civilizational scale to accelerate the regeneration of earth systems is another. And this is where there is an even more critical reason to make the shift from the current 2D static images of planetary status, to generative modules that ‘live-signal’ those living systems.
And that is because when a system status signal is evolved to a generative object - like a HALO for earth systems - that signal becomes an ‘actionable entity’. Meaning, because it is comprised of, and responsive to, data feeds from all of its subsidiary inputs it can be directly tethered to instruments of data capture (called ‘feeder apps’) all the way down the chain, from the planetary collective to the individual human.
So, in a generative framework, nation-states, organizations, and individuals can be directed toward actions that materially, statistically move the planetary signal toward the desired state. And in so doing, they can see the immediate feedback of their actions - while micro-incremental, still mathematically-real - in that signal. When humans are given these tools at scale - we can envision mass events to shift the live signal as a form of collective action for global community.
These are the directives to a global society that is on the brink of an evolutionary shift. The question remains, will the masters of the current outdated signals willingly make the upgrades or will we have to launch our own platforms to supplant the non-operational ones.
