We’ve been using this diagram to help people understand where coops fit in the world as we know it. It neatly describes how coops slip in between your run-of-the-mill-profit-driven-firm and not-for-profits.
There is often a light-bulb moment around what this is really describing – that there are three different ways that value can be distributed:
In a for-profit company, return-on-shareholders-capital is the sole focus
In a not-for-profit, the division of value is determined by its pre-ordained mandate
In a cooperative, it’s the members who decide how value is distributed
It also helps to makes sense of why coops are democratic organisations, where every member gets one vote, as opposed to for-profits where decisions are based on proportionate holdings of voting shares, and NFP’s where the beneficiaries typically have very little control.
We particularly like the implication that coops take the best out of both worlds!
A surprisingly well attended meeting at the Trades Hall last night given the low key publicity. Developers, designers and folk from 5 different trade unions were there. Interesting perspective on the potential power of developers to influence the shape of new tech to meet privacy-by-design and other yet-to-be-defined principles. Only one developer raising the blockchain flag as a solution in waiting. But perhaps most encouraging, the trade unions showed real willingness to engage on the issue and explore how things like platform coops can help change the balance in favour of workers from all industries – particularly designers.
When tech meets organised labour then the pendulum starts its swing back from current economic extremes.
A meeting for workers interested in collective action & unionism
We believe in workers’ rights, social justice, diversity and equality. We want to challenge corporate control over our technology.
We share a vision for an inclusive & equitable technology industry. We want to collaborate with workers and friends to build tech worker power, organise on workplace issues and create a space for educating ourselves and exchanging ideas.
When will homo sapiens be usurped at the top of the food chain? Or has it already happened?
The transition from big data to algorithm-driven AI is happening frightening quickly. In fields from medicine to movies to mass surveillance, smart machines have already proven to be quicker and more reliable than their human peers. It won’t be long before they know us better than we know ourselves…
The need to align data management with our collective and individual interests is urgent. Left to their own devices, government and private capital are ill-equipped to balance the common good with individual agency. We need to take ownership. Co-operative governance and ownership of the technologies that underpin the algorithm economy are key…
We’ve been studying the various ways accreditation can assist farmers in the migration to smart machines and edge computing.
One of the barriers to the adoption of data sharing across the agricultural supply chain is the relative immaturity of the technology that is used on-farm. While there is currently an explosion of new devices being developed and offered to farmers, the inchoate mess is difficult for farmers to navigate – it’s simply hard to know where to start. On the other hand, existing systems are ageing and are not generally fit for API integrations while the reliability of sensors can be patchy leading to questions about data accuracy. In short, data lacks the reliability, accessibility and inter-operability to be really useful.
Accreditation offers one way we can create a bridge between the current environment and the next, where smart farming is commonplace. The idea is that better farming practices will be a key driver towards the adoption of smart machines – whether it is to promote precision farming or to support growing consumer awareness around the foods they consume. And accreditation around those farming practices may provide a way to solve the data quality issue. In effect, we can look to leverage the business processes of the various certification agents to filter data quality.
Accreditation has the potential to be quite diverse. It can include certification around organics. It can include verification of farming practices, application of fertilisers or chemicals in water runoff. It could look at measures of biodiversity on the farm, regeneration practices, and covenants on land preservation. By attaching independent third party accreditation to farm produce, this data becomes valuable in a way that can’t be achieved in the absence of deep integrations between systems.
Of course, the risk is that accreditation agencies can be compromised if their interests are not aligned correctly. We’ve seen this time and again in financial markets. If the gamekeeper is getting paid by the poachers, then they are only too willing to see things from the poacher’s perspective. Either the measures need to be so blatantly objective that they cannot be compromised or we need to ensure that the accreditation providers are not financially beholden to those that could benefit from misplaced confidence.
So while we stumble headlong towards a hyper-connected farm to table, we can perhaps begin to capture the benefits of data through accreditation…
“The leader is driven by a desire for power, while the organiser is driven by a desire to create.”
Coops attract organisers as the structure naturally diffuses the power of any single person. Of course the risk is entropy where coordinated action dissolves into a cacophony of voices. The aim of a coop is then to cultivate an active membership which focuses energy towards a common goal – following the adage that ‘power is focussed energy – that enables the ability to do a thing’…
We were brain-storming ideas for injecting some energy into the 888 Brewery Coop. It was on the long drove back from Horsham, the sun had gone down and we were listening to Radio Birdman descend into the maelstrom… and within mere minutes the discussion had gone from community engagement ideas to issuing ICO’s backed by kegs of beer.
Very productive day with the good folk from Birchip Cropping Group yesterday. It was our second workshop in the Farming Together sponsored project being undertaken by BCCM to help grain growers from the Wimmera-Mallee explore a data coop.
In a new land speed record, by the end of the workshop we had crossed everything off our wish-list in terms of things we needed to draw up a draft set of Co-operative Rules – once again proving that farmers and nurses are the most likely to survive the zombie apocalypse.
The data coop can be a big concept, and there are some key pieces of the puzzle that are still formative in their shape and readiness, so it was really encouraging that the farmers present were beginning to have concrete ideas about how it may work. There were some cracking specific examples that are likely to prove fertile ground for testing of the data coop mechanics and economics.
Perhaps more encouraging still was that we got the sense that the farmers were starting to take formal ownership of the project, thinking that they could build it from the ground up (rather than having a structure imposed on them). Notably, it was suggested that the data coop could leverage the BCG infrastructure to provide a springboard to get started.
Also, really interesting discussion about farming practices, quality assurance and compliance. Noting that the thinking to date has been that precision agriculture would lead the use cases for the data coop, we discussed the rising cost of compliance and increasing accuracy of testing and standards and whether this pushed ‘traceability’ higher up the priorities.
We were also lucky to have Leanne Wiseman and Jay Sanderson from Griffith University so we could untangle some of the trickier questions around rights to data. We sketched out some of the key structural elements that could be developed for the coop – such as members agreeing to an “Ethical Good Governance Code” that would be updated every year and would require things like disclosure of conflicts of interest, disclosure of 3rd party data sharing arrangements and agreement to minimum standards around data being shared, accuracy and types.
Finally, the emerging view seemed to be that the data coop would be akin to social infrastructure and would be best structured as a non-distributing coop. This would better align member and community interests and also enhance the collaborative business model with customers.
One of the challenges of a co-operative is balancing the interests of the group with those of each individual member. Unlike a proprietary limited company, stakeholder interests are not beholden to the profit motive. Rather the primary focus is on return to members – which can be delivered in a variety of ways including via dividends, rebates and patronage. The difficulty is that without a return on capital signal, the cooperative itself has to determine how value is distributed among its members.
A data co-operative provides a simple illustration of this challenge. On the one hand, members come together to aggregate market power – as individuals they are weakly positioned to bargain the terms on which they share their data, while as a collective their individual control is amplified. On the other, one of the principal objectives of a data coop is to enable individual members to have more control over their data. For this reason, a data coop will create permissioning mechanisms that enable the individual to differentially share their data with others. The data coop leverages group market power to deliver value for individual members.
But that is only part of the story. By aggregating control over data, the data coop will also enable sharing of data in aggregate. And there are likely to be circumstances where it is in the collective’s interests to share aggregate data. This is after all why Big Data and the Algorithms have been dominating the pop charts over recent years. For this reason, it may be a condition of membership that coop members agree to authorising the coop to share their data. You can see the challenge here…
For this reason, it is really important that cooperatives are very clear about how a cooperative distributes value amongst its members. If interests are not aligned, fractures across the points of difference are likely to occur when the structure is stressed.
Annie Duke, retired poker champion, talks about strategies to accelerate learning in her book “Thinking in Bets: Making Smarter Decisions When You Don’t Have All the Facts”. A key one is drawing on your community – learning from the experience of experts, testing boundaries with peers, and simplifying ideas through teaching others. Really interesting question here about how to institutionalise these types of practices within an online cooperative community…
A data coop by definition aggregates the market power of its members. It enables them to collectively negotiate how their data can be shared and used by others – as well as enabling each individual member to manage how their data is shared. We think that this is key to the success of a co-operative – they empower the collective while also enabling individual agency.
It is kind of obvious, but can get lost in the mix, that for a data coop to work it must also benefit the customers…