<aside> ⚠️ STATUS: DRAFT Want to contribute? Get in touch! T: @_digitalgaia / E: rafael.k@digitalgaia.earth

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TL;DR:

• For too long, climate and impact finance has been ineffectual. Now is the time to ensure that the money and energy going to climate is channeled into projects that have a measurable, lasting positive impact on the world.
• To achieve this, we will replace carbon credits as they exist today with high-integrity tokenized certificates of environmental impact.
• These impact certificates will be algorithmically issued, and derive their legitimacy not from attestation by authorities, but from the scientific method itself: an evolving and transparent paper trail of reproducible inferences, cross-validated against real-world data.
• High integrity will be achieved by design, through guardrails and tools, leveraging the experience of many other knowledge commons such as open source software, Wikipedia, and the scientific community.
• We foresee the emergence of a Web of Impact (WoI): an open global repository of quantitative, granular knowledge about environmental impact, built in the lingua franca of science - quantitative models and provenanced empirical data. Assessments, certificates and a wealth of other services will be algorithmically minted by a rich ecosystem of apps and agents on top of this commons.
• We are creating a Web of Impact Consortium to make this vision a reality. Please join!

The Impact Integrity Challenge

Today’s legacy markets for carbon credits and other impact certificates are broken. At their worse, they represent a way for savvy insiders to get paid, while achieving little (or even net-negative) environmental impact. The symptoms of this are clear:

• Misattribution: Credits are issued to the industry insiders who claim the projects, not the local organizations that create impact and often bear the costs.
• Miscalculation: Credit issuance often overstates projects’ net impact, by intentionally or accidentally mishandling issues of additionality, permanence, leakage, double-counting, and “unintended consequences” to biodiversity, soil, water and local communities.
• Fraud: In some jurisdictions, it is believed that a large fraction of credits originate from fake, for-show projects that raise money and never actually get executed.
• Irrevocability: Once retired to offset emissions, credits cannot be invalidated, even if their source is later shown to suffer from the above defects - effectively the equivalent of money laundering.

The integrity of this system is supposed to be guaranteed by incumbent organizations such as credit registries and verifiers, certifiers, project analysts and consultants, financial institutions and project developers/operators. There are several critical problems with this status quo:

• Lack of openness: The verification and certification bodies act as unaccountable autocracies, unilaterally cutting out any player that attempts to bring transparency and liquidity to this market.
• Lack of transparency: Unaccountable entities make unilateral decisions without consultation, justification or recourse. Methodological standards and reports are usually hidden behind paywalls or accessible only to insiders. Even when they are made accessible to the public, it is in the form of massive PDFs or even printed documents, with no accompanying paper trail or access to the source model spreadsheets or code. This obfuscation serves no purpose other than to hinder accountability and limit market access.
• Lack of scientific rigor: Credits and certificates are based on MRV reports that are impossible to justify, reproduce, validate, compare or improve on, but rather supposed to be taken at face value, on the authority of the issuing bodies.
• Lack of critique: As long as there is an entity willing to issue a credit, rebuttals from independent scientists or local communities are completely ignored. When scandals happen (see California debacle), there’s only a promise to “do better next time” and improve standards - too little too late. And of course, this is by design: regulatory capture so that the very same overgrazers can have their cake and eat it too.
• Lack of contextuality: All present methodological standards dictate static, one-size-fits-all assumptions about the “right” metrics, “valid” interventions, or “acceptable” data sources. When contextual variation is acknowledged, it is in the form of multiple **options (which beget exponential complexity), with of top-down processes to update methodologies or add new ones. This further hinders the most innovative and/or locally appropriate projects from entering the market.