Cut Climate Tech Invention-to-Innovation Time
The cycle of invention (idea successfully prototyped) to innovation-at-scale (widespread implementation of the new practices) typically takes decades. For climate change, we just don’t have that time. Yet, we can intentionally compress it with existing technologies and organizational design.
Every science- and ultimately technology-based revolution typically takes decades to percolate deeply into the world, because of the slow process of “learning by doing” — often starting with academia, some R&D pilots being successfully executed, then the most innovative managers adopting the new practices, and finally most others following — many years later.
This is innovation’s death by thousands of small cuts. One of the most striking examples of that problem is the slow progress in evolving healthcare systems across the world, with its immense amount of variance in the deployment of tried and true practices (e.g., India’s Aravind eye care process for cataract treatment, with its order-of-magnitude costs improvement at comparable quality, which a decade after scale, is still not adopted extensively worldwide).
We can’t rely on established knowledge-transmission mechanisms
For climate change, the “typical cycle” is not nearly good enough. We can’t wait for five years until heat-pump installation capacity ramps up; we can’t wait for established regenerative agriculture practices for specific microclimates to spread to enough farmers who don’t speak English well; we can’t wait for enough municipal utilities to learn how to incentivize and enable citizens for efficient energy usage; we can’t wait for a serendipitous uptake in the long tail of cities, regions, and countries that are not exposed to the most recent technology, methods, and applications.
Many strictures exist: from upstream scientific to downstream practitioners access to knowledge repositories is not always as easy as it should be (academia and media); many professionals don’t know how to thoroughly harness social media where new ideas surface; language barriers make it hard for the “global South”, among others, to access and share new things. And the natural tendency of experts to silo their knowledge and try to find the next big thing in their field, whereas we know that innovation comes from the combination of existing ideas.
Industry and generally internet media are also not doing that job well enough. Thanks to algorithms tuned to maximize advertising and stickiness, meme-able noise often obfuscates the signal, and finding what’s relevant is still too hard or expensive (e.g., paywalled content).
So despite the excitement about climate startup funding and corporate net-zero commitments, at least one aspect remains seriously neglected: the intentional crystallization and sharing of practical, specialized, knowledge so it productively “touches the ground” and can be recombined with existing ideas, processes, operations etc. That’s a clear multiplier of impact but unsexy for many entrepreneurs and investors, and often left to either individual firms’ marketing, or to well-intentioned but under-resourced NGOs and other public institutions — including educational ones — that struggle with both granularity of information and speed of change. The outcome is a frequent reinvention of wheels.
We can do better today
This is not just about media or training. Both of them help, but in isolation, and when executed in a traditional manner, they have significant limitations. What works is a new organization for the knowledge of networks of people, augmented by intelligent technology: Augmented Collective Intelligence.
Today we have access to methods for knowledge formalization, retrieval, and sharing, vastly superior compared to the past. Google, Wikipedia, and the Web2 revolution (from WordPress blogs to Reddit, LinkedIn, Substack, Medium, etc.) have shown potential; yet they’re not yet “finishing the job” of making relevant and practical climate-change information efficiently available to most relevant people. A minority of experts and practitioners know many information sources and can monitor them efficiently, but most others can’t. That’s significant leakage in the invention-to-innovation cycle. We can do better.
The table below summarizes the main idea. Hyperspecialized collective-intelligence “utilities” could accelerate the spread of high-momentum/low-signal content (both practical enablement and broader learning), and support the identification and engagement of relevant people (experts and practitioners). These infrastructures can use new natural language capabilities, and build knowledge graphs that facilitate two crucial processes: first, finding and combining granular information, i.e. the “what” (e.g., new ways of implementing heat pumps cost-effectively in areas where energy is expensive and unreliable); and second, pinpointing experts, i.e. the “who” (e.g., people or organizations who have codified the respective processes and can help on the ground).
The uptake would be that the new granular, practically implementable knowledge could now reach not just the pioneers or the “hackers”, but also mainstream professionals open to new ideas. That is the early majority of users.
There isn’t a clearly defined category for this type of work. Its sits between social media, professional networks, education, training, open-source solutions, and even thought-leadership marketing. But the building blocks already exist. For instance, Microsoft has Viva, Linkedin, and Bing, which — combined — potentially have the full solution both within and outside of organizations. Others could use off-the-shelf tools that combine content and social media scrapers, perhaps using additional sources such as Google’s open-source science and data repositories, the amazing G-DELT machine-translated world news, or interesting new tools like Diffbot. Climate solutions startups like Ubuntoo (disclosure: I am an advisor there) already curate knowledge for innovation. Content providers, from scientific journals to Twitter, Reddit, and Quora, could make it easier to access rich APIs for this.
The sharing and combination of the world’s relevant collective knowledge can be intentionally engineered thanks to new digital technology and practices. We could soon live in a world where detailed, specialized “how-to” knowledge for climate mitigation and adaptation is available on a browser that millions of people can readily access. Then, a broader base of people will have a fighting chance to tackle the largest challenge humanity has ever faced.
Let’s ignite thousands of climate “superminds” powered by a common infrastructure. Get in touch if you’re ready to build yours.
This post complements the organizational design materials at www.supermind.design and my previous blog posts (here, here and here, for example) on designing an AI-augmented collective intelligence. I recommend reading them if you’re interested in using these techniques in your own organization.