After a contentious early meeting of Green Taxi Cooperative’s driver-members, then in the process of forming the largest taxi company in the state of Colorado, I asked the board president, Abdi Buni, about self-driving cars.
The state legislature had started clearing the way for them on our roads, after all, and the airport was giving Uber and Lyft preference over the local taxis. Buni’s competitors were thinking about them, so what about him?
“We’re really trying to feed a family for the next day,” he said. “When it happens, we’ll make a plan.”
He said this with the kind of weariness about technological wonders that I’ve frequently found among co-op directors – and I could easily understand why. Uber and Google were testing their automatons with billions of dollars from Wall Street in the bank, while Green Taxi was running on what membership fees its mainly immigrant drivers could scrape together.
But the reality was that the self-driving cars were not some distant future that could be put off. As investors poured money into the car-sharing apps in anticipation of automation, the apps put so much pressure on Denver’s taxi industry that drivers fled their old companies for a better deal in their own co-op.
In that sense, it was as if the robots had already come. Green Taxi owed its existence to them.
There are two stories commonly told about robots these days. One is that, in the not-too-distant future, some enormous percentage of jobs currently being done by people will be taken over by computers, and the workers will be left twiddling their thumbs. The other is that, like past periods of technological change, job markets will simply evolve, and new, better things will arise for us to do.
The truth is neither – and everything in between. I say so, not by having any special insight into the future, but by noticing certain features of the present.
For instance, while it might look to some observers in affluent, urban areas that we’ve entered a post-industrial age, more stuff than ever is being produced on this planet, with human hands very much involved – it’s just that this is happening in different places.
Even where old factories have turned into apartment lofts, jobs show no particular sign of going away – they’re just less secure. People in places where it was once possible to support a family on one standard, career-long salary are becoming used to lifetimes of gigs, found and mediated by machines. Social contracts are shifting, while companies, governments, workers, and myth-makers are vying to set the new rules. It’s not a sudden robot apocalypse, it’s a longer, slower tug-of-war.
The winners will be the owners. Many of the world’s highest valued firms claim the title because they own vast, vast stores of data – data about us, data that can feed their algorithms.
Ownership is the ground where the tug-of-war for the next social contracts is being played. Who owns what will determine who really benefits. The owners, also, decide which tasks to invest in automating and what happens to the people who used to do those tasks.
Right now, a few very powerful conglomerates are likely to dominate this contest, companies based primarily on the west coast of the United States and in China. They are only getting stronger, as is their capacity to pull what they need from the rest of society and remake the rules on their terms. In new guises, this is a story we have seen before. It’s the story of railroad barons, big banks, and big boxes, of economic bullies that provoked people to create their own economies of scale through co-operative enterprise.
It begins with thinking about automation like owners do, not like victims of it. In worker co-ops, rather than fearing how machines might take work away, workers can imagine how they could use those machines to make their lives easier – in ways better and fairer than the investor-owners would. Consumer, purchasing, and marketing co-ops can use data visualization to demonstrate the superiority of their supply chains. The less people have to do to maintain all this, the more they can turn to opportunities for creativity.
Co-ops thrive when they discover how to do what other kinds of companies can’t or won’t do. Co-operative AI, also, may be intelligent in ways the investor-owned counterparts can’t be.
TheGoodData harvests the proceeds from members’ web-browsing habits for micro-lending programs, and Robin Hood Co-operative runs an algorithm that prowls financial markets for opportunities to fund public-domain projects. This kind of data can in turn inform future co-op robots, like the flying drones that Texas utility co-ops used last year to restore power after Hurricane Harvey struck the state.
Rather than worrying about how robots and apps will make their current business models harder, co-ops should ask how smart, member-focused automation can set them apart. But the barriers are real: This takes economies of scale, and co-ops need to band together to create them.
For instance, there are driver co-operatives like Green Taxi all around the world – what if they created a shared hailing app that customers could use wherever they go, and pooled the data for mutual benefit?
Meanwhile, consumer car-sharing co-ops like Modo in Vancouver are well-poised to be leaders in adopting driverless vehicles – accountable to the local community, not to far-away investors. In hard-to-automate service professions like house-cleaning and childcare, platforms like Loconomics and Up & Go are using co-operation to automate marketing and payment so workers can focus on –and get paid better for – doing their core jobs.
The 20th century was full of science fiction about technology making people’s lives better and freer, but we’ve wound up with a 21st century of worsening inequality and insecure incomes.
The world of The Jetsons doesn’t arrive automatically. In order for the benefits of technology to be shared more widely, the ownership of it must be shared, too. Co-operation is uniquely well-suited to do this.