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.
Some days the new world order just plumps itself down in front of you like an overweight chook… So today while scraping Tim Mazzarol’s fabulous co-operative and mutual database (here), I got to thinking about what was going on here.
The website gives access to the most complete list of co-operatives and mutuals in the country. It is all publicly available. And yet, the developers didn’t make it easy to download the database.
Why create the artificial barrier? Perhaps there is some residual sense of ownership of the data. Perhaps it’s an attempt to make the site a destination for accessing the data. It’s a little hard to know.
The thing is that this approach is all back-to-front. It’s the kind of thinking that gave us CRM’s that pretend that customer data is something you own. It is not the way the emerging data-driven culture works.
We are moving to a world where we choose to share data. It becomes an asset that we control – we need to be motivated to share it (even if it means agreeing to your capricious terms of service Mr Zuckerberg).
There is an opportunity in this. At incubator.coop, we have been working on developing a co-operative operating system. A software-as-a-service model that will enable coops of whatever size to access an integrated website, member engagement app, and share registry. It’s intended to be a co-operatively owned solution for the co-operative sector.
Now here’s the thing. Very much like painting the Sydney Harbour Bridge, the CEMI database is out-of-date by the time it is finished. It relies on the collection of static data. At its simplest however the coop mgt system offers a way for coops to share their data. They can choose what data they share to create a dynamically updating database that is truly open for anyone to use. And open, accessible data – that is shared by those that control it – is the way value can be created in the new world order.
Listening to a back edition of Seth Godin’s Akimbo podcast “Game Theory & the Infinite Game”, it struck me that a co-operative is, by design, an attempt to collectively escape the prisoner’s dilemma.
To recap the parameters of the ‘game’, two people are caught red-handed for a crime. They are going to serve a year’s jail-time for this. But they are wanted for a bigger crime too. So they are each offered a way out of jail-time, rat on your partner for the bigger crime and you will go free but your partner will get 50 years. The trouble is that if they both sing, then they will both get 5 years.
The expectation is that the rational selfish response will be to rat on the other. In practice, humans have demonstrated a systemic bias to co-operate – we seem to understand that the pursuit of single-minded self-interest can lead to a bad outcome for all.
So now I have added The Evolution of Cooperation by Robert Axelrod to my reading list (here for the abridged version). This book reports on a Prisoner’s Dilemma tournament where he invited game theory experts to submit programs that would be paired off against each other to see which did best over repeated interactions.
“Amazingly enough, the winner was the simplest of all candidates submitted.
This was a strategy of simple reciprocity which cooperates on the
first move and then does whatever the other player did on the previous
He called it the Tit-for-Tat strategy.
By analysing the top-scoring strategies, Axelrod stated several conditions necessary for a strategy to be successful:
Nice – Almost all of the top-scoring strategies were nice, that is, it will not defect before its opponent does.
Retaliating – A successful strategy must not be a blind optimist. It must sometimes retaliate to avoid being exploited by others..
Forgiving – Though players will retaliate, a successful strategy will once again fall back to cooperating if the opponent does not continue to defect. This stops long runs of revenge and counter-revenge.
Non-envious – The best strategies did not strive to score more than the opponent.
Whether the players trust each other or not is less important in the long run than whether the conditions are ripe for them to build a stable pattern of cooperation with each other. The successful strategy learns through trial-and-error that it is better to co-operate than not.
Governance is a hashtag that has been growing in popularity. So it’s great to see the coop sector responding with the BCCM’s impending release of Co-operative and Mutual Enterprise Governance Principles for the Australian co-op and mutual sector. And folk like Coop News dedicating a Governance Edition to analyse the subject.
We’re interested in how this emerging thinking applies to data.
Data governance is the mechanism through which values and expectations with respect to data can be translated into effective management practices.
Good governance is a function of the clarity of shared intent and trust in expected behavior. As Dee Hock writes: “This is not to say that contracts, laws, and regulations do not serve a purpose. Rather it is to point out that…rules and regulations, laws and contracts, can never replace clarity of shared purpose and clear, deeply held principles about conduct in pursuit of that purpose.”
By these definitions, good data governance is broader than legal frameworks or codes of practice – it bridges the gap between the expectations and values that folk have with respect to their data, and the mechanisms by which these are made tangible. It encompasses legal documentation and decision-making protocols that are agreed between the actors involved. And it includes the social interactions that enable these to be made real.
The Cambridge Analytics seraglio exposed the under-belly of the market that preys on our data. And the GDPR has done wonders for focussing attention on data management practices. Next step is to get some clarity around the governance practices that will lay the foundation for better matching of expectations with practice.
PS – An example of a emerging model for personal data, Sovrin have a pretty comprehensive Trust Framework