Subscribe to Pioneering Spirit to receive new posts directly to your inbox.
If we want to make real progress on climate action, we have to be honest with ourselves: asking people to sacrifice in the name of a better future only gets us so far. Sure, there are moments of altruistic inspiration. But enduring systems change? That happens when we make the sustainable path the easy, obvious, and self-interested one—when it works better, faster, cheaper.
In other words, we need to design climate action that doesn’t just appeal to our better angels, but to our everyday incentives—whether you're a city planner under pressure, a homeowner comparing utility bills, or a business optimizing logistics.
This means getting the system incentives right. And as Nils Gilman puts it so clearly:
Aligning Prices for Justice: Actively using fiscal tools (like differential VAT rates) to ensure that essential “clean” goods and services (e.g., organic food, train travel) are priced competitively with, or even cheaper than, their “dirty” counterparts. This directly tackles the affordability barrier for ecological prisoners, making the sustainable choice the economically rational one. Complementary mechanisms like solidarity loyalty cards could further target support.
Integrating Health and Environment: Embedding environmental determinants of health (pesticides, air pollution) directly into mainstream public health strategies, like national cancer plans, and funding remedial actions and support for affected sectors (like agriculture) through social security budgets. This frames ecological action as a direct investment in public well-being, leveraging a domain where public support for state intervention is traditionally strong.
Combating Collective Waste: Shifting the focus from individual behavioral nudges to tackling the systemic drivers of waste embedded in production, distribution, infrastructure, and consumption patterns (e.g., planned obsolescence, excessive packaging, urban sprawl inducing long commutes, advertising driving overconsumption). This reframes waste as a structural problem requiring collective, systemic solutions, potentially identified through deliberative citizen processes.
This framing nails the stakes. But here's the rub: you can't align prices, embed health strategies, or combat systemic waste without measuring what’s actually going on. And that’s where things get tricky.
It’s tempting to think that the challenge is simply political will. But often it’s a more basic—and fixable—problem: the right data doesn’t exist in usable form. There’s no shared view of where we are, what’s working, or where the bottlenecks are.
That’s where data collaboratives come in. As outlined in the California Public Technology Roundtable post, data collaboratives offer a financially sustainable and institutionally nimble way to tackle this problem. They bring together public agencies, nonprofits, and private actors to pull, clean, and harmonize data—not just for compliance or transparency, but for problem-solving.
Instead of passively hoping the data shows up, they build the shared plumbing to make it useful. This is the kind of boring-but-crucial infrastructure that enables good governance in the age of AI.
We’ve seen early proof points in water infrastructure and permitting data, but there’s massive potential in other domains. Data collaboratives for the circular economy, remote sensing, air quality, the food-water-energy nexus, massive shifts in mobility and really every aspect of modern urban infrastructure.
The pitch for circular economy initiatives—recycling, reuse, repair—sounds great. But ask a practitioner and they’ll tell you: the data is a mess. What's the actual waste composition in different communities? How much material is recoverable? Where are the most impactful intervention points?
AI tools can help—if they’re fed the right information. A properly trained model can identify contamination hotspots, optimize pickup routes, and even suggest tweaks to packaging design. But without solid ground-truth data from local jurisdictions, facilities, and field staff, it's just another glossy dashboard with bad inputs.
That’s why surfacing this information in structured, shared ways isn’t a side quest—it’s the main storyline. It’s how we turn buzzwords like “smart city” and “AI for climate” into something real and grounded.
So how do we scale this approach? How do we keep it human-centered and accountable while moving fast enough to matter?
This is where protocols come in.
The Summer of Protocols defines a protocol as:
“A set of rules that guide interactions.”
In the context of climate adaptation and energy transition, protocols are more than technical standards. They're the connective tissue between data, decision-making, and civic participation. They encode how people and institutions share information, who gets to act on it, and what values are embedded in those actions.
Think of a protocol that enables street-level field workers to upload tagged images of infrastructure conditions. Or a procurement protocol that rewards low-waste supply chains. Or a community data-sharing protocol that protects privacy while enabling research.
Protocols let us operationalize values—equity, sustainability, transparency—at scale. They give us tools to navigate the real political economy tradeoffs without hand-waving. And they make space for iterative learning in complex systems.
If we want a climate transition that’s not just bold but workable, we’ll need more than good intentions. We’ll need smart plumbing. We’ll need data collaboratives and AI. And we’ll need protocols—living tools that help us build the future we actually want to live in.
Let’s get to work.
This post was developed in collaboration with ChatGPT.
Over 200 subscribers
