From Big Green to Big GreenDAO

The Ethelo team was fortunate to collaborate with Big GreenDAO (BGD) and had the opportunity to play a role in the DAO’s journey towards progressive decentralization — a process in which the initial stakeholders of an organization relinquish control by degrees, over time. 

As a decentralized autonomous organization (DAO) BGD’s journey towards gradually sharing more decision-making power, started sometime before Ethelo came on board. In fact, it started before Big GreenDAO was a DAO and instead was just Big Green; a non-profit organization with “the mission and belief that growing food changes lives, and that it opens up people’s eyes to the impacts of climate change, weather volatility, and connection to nature” Mattew Markman, one of Big GreenDAO’s original co-architects, explains. 

Big Green was established in 2011 by Kimbal Musk and Hugo Matheson. The non-profit provided funding and infrastructure to implement school gardens, which would function as outdoor classrooms for students to learn about healthy foods. 

The organization was continuing to develop and had no plans to suddenly change its mission or its operations; but then COVID hit. “Schools closed. And even once they reopened, they were really restricted. So Big Green couldn’t do their traditional operations”, MathewMattew Markman tells us. Big Green needed to pivot, so “they ended up shifting more into a grantmaker role where they started supporting teachers at those schools.”

Big Green’s shift into more of a grantmaking operation, inspired more conversation about how “Web3 technology could be used to implement a more participatory grantmaking process at scale” Mattew Markman recalls. These conversations were the seed of what would eventually become Big GreenDAO. 

As one of the DAO’s co-architects, Mattew Markman explains, “I came on as an external consultant and expert in the Web3 and DAO building space and, you know, worked initially for several months with Kimball Musk to really think out the scope and architect of the DAO. And once we did that, then we’ve been in a process for the past year of truly operationalizing it, onboarding its community members and implementing its operational processes as well as building its technological infrastructure, which is part of where we came into contact with Ethelo.”

The Evolution of Big GreenDAO

What was initially a traditional charity evolved into a centralized grantmaking organization and then came to be a DAO with the mission to radically democratize and decentralize philanthropy by putting frontline organizations in the food justice sector in the driver’s seat of the grant-making process. Mattew explains this evolution and says that “by building the DAO structure and, partnering with Ethelo in particular for the participatory grantmaking aspect of it, we were able to involve, first 6 frontline organizations, then 16, then I think 45, and now about a total of 75 organizations in this process of grantmaking.” Big Green DAO has now grown to 160 organizations.

BGD’s innovative organizational structure is composed of a process in which the initial core members invite the very organizations that receive grant funding to be part of the DAO and collectively decide which organizations should receive a grant in the next round of funding. Then these new organizations are invited to be part of the DAO and the process repeats itself after every round, thus increasing the membership of the DAO. 

Mattew Markman explains the first few granting rounds in detail: 

“The first round was about identifying, onboarding, and collaborating with core contributors and stakeholders in the food justice sector. And so, that was sort of a handpicked round of organizations that we approached and engaged with, to see if there was alignment for the mission – both the food justice mission in general and the participatory grantmaking structure in particular.”

“In the second round, through a consensus-based deliberative process, the DAO committee decided that the best way to do the second round was to bring in core allies, and each of the original 6 grantees who are on the DAO committee got $50,000 that they could distribute to one or two ally organizations. So, either $50,000 to one or $25,000 to two. So as a result, we brought in additional 10 organizations through that mechanism. And then we launched the participatory process with Ethelo for the next two rounds.”

Decentralizing and Co-designing with Ethelo

Ethelo’s collaboration with BGD started on granting round 3 when the number of organizations participating in the grantmaking process significantly increased. Before working with Ethelo the DAO used Snapshot (one of the most used governance tools in the web3 space) to vote and allocate grant funding. Due to some limitations and challenges with the tool, there was a need to explore alternative ways to do decision-making. The DAO architects needed a tool that would be more engaging and that could better capture the complexity of their desired decision-making process – Ethelo turned out to be the perfect fit!

Mattew Markman explains the decision to use Ethelo and says that “Ethelo stood out as the most robust DAO governance tool I’ve encountered. Unlike simple yes/no votes, it emphasizes the process before voting, which is crucial. Many DAOs focus solely on voting, leading to rubber-stamping or division. Ethelo’s engaged process, flexibility, and adaptability to handle complex scenarios with multiple stakeholders and customizable algorithms perfectly suited our unique needs.”

After grant round 3 ended and $780K was distributed to 27 unique organizations, the DAO was able to learn from this experience and use these learnings to design a better process for grant round 4. This new and improved design involved the separation of the process into two stages: in stage 1) the DAO members would vote for the amount of the overall budget that should be used and in stage 2) the membership would allocate the budget and distribute it among a set of 114 new organizations. 

The second stage of voting would use quadratic voting – a voting system that accounts for the number of people voting for an option as much as it does the amount of voting power (often in the form of dollars) participants stake on each option. In this case, instead of dollars, voting participants were each given a limited amount of “seeds” (114 each) and were asked to stake their seeds on the organizations they thought were most deserving of funding. 

Voting participants had a set of options to indicate their level of support for a grantee and each option contained a number of seeds to be allocated to that same grantee: 

Option 1: 0 Seeds

Option 2: 3 Seeds

Option 3: 7 Seeds

Option 4: 14 Seeds

Option 5: 28 Seeds

Option 6: 57 Seeds

Option 7: 114 Seeds

Effectively, if a participant felt very strongly about the work done by one organization they could choose to allocate all of their seeds to one organization. But this would not mean that the organization with the most seeds would necessarily get the most funding because the emphasis on the number of voters (not just the number of seeds) supporting an organization, which the quadratic voting system enforces, would not allow this. The final results are a set of organizations with a mixture of a high number of seeds allocated to them (signifying intensity of support) but also a high number of total voters supporting these organizations (signifying overall support from the group).  

In addition to the quadratic voting methodology, the Ethelo consensus-making algorithm was used alongside this new voting design approach. Matthew Markmen elaborates on this coupled voting methodology: “And so, in rounds 4, we kind of had a two-part process with money and points (or seeds) to try to integrate our multi-layered voting algorithm, which is sort of like, a mixed quadratic weighted average voting algorithm, which isn’t what Ethelo normally uses. And so, we were able to use Ethelo’s base algorithm as sort of a validating mechanism to see where our votes aligned with (i.e the overall consensus) which was also really cool.”

In summary, Mattew explains, “we were able to simplify the interface, enhance the user experience and even increase or advance the complexity of the actual voting algorithm itself… so we made the experience more simple and more engaging but at the same time able to increase the complexity of the algorithm and have a more robust voting algorithm which was based on building on the iterative process of working from round to round, which is great because we were able to really work as co-designers and collaborators with Ethelo’s team. It felt like we were involved in a generative process together.”  

A New Approach To Urban Planning

The Smart Cities Challenge is a new way the Government of Canada is helping communities become healthier, more inclusive and livable. By challenging communities to use data and connected technologies to address their most pressing problems, the Smart Cities Challenge encourages innovation through competition.

The competition awarded one top prize of up to $50 million, two prizes of up to $10 million each, and one prize of up to $5 million. All cities could apply to the $50 million category, but the other two were restricted by city size.

Of the 130 proposals received, 46 cities applied for $5 million, 71 applied for $10 million, and 13 applied for $50 million. Each group was evaluated by a panel of government officials and other professionals with experience in infrastructure and public projects.

Each proposal needed to be evaluated quickly, but thoroughly, with a goal of selecting 20 to advance to the next round of competition. Ethelo provided the framework necessary to make this happen in an innovative way — much like the ideas being evaluated in the Smart Cities Challenge.

Process

Measuring Innovation, Fostering Collaboration

Following a brief initial consultation, Ethelo and the Smart Cities Canada team worked to set up an evaluation platform for 13 jury members based on 17 criteria, including the potential for economic growth and commitment to a healthy environment.

Kathleen Bouchard, a senior analyst on the Smart Cities Challenge, said the team did not know how many proposals they would receive and wanted a tool that could handle 20 just as easily as it could handle 200. The team also wanted a tool that was flexible enough to accommodate all 17 criteria. They found that flexibility in Ethelo.

Using Ethelo, jury members viewed each proposal in their assigned category and made comments on how well it adhered to each of the criteria. Rather than working individually, Ethelo allowed reviewers to see each other’s comments and provided the opportunity for group interaction.

The Smart Cities Canada team monitored progress throughout the evaluation period and communicated with evaluators if their scores and comments appeared to be out of line with the others.

“We were able to quickly calibrate who judged low and who judged high,” Bouchard said. “If we noticed a discrepancy, we could call [the specific judge] back about rating scale. It was definitely a time saver on our side.