Since I’m shutting down the Mixed Reality for All website, I want to preserve the final write up of the project’s strategy; here is is.
Cutting edge tech often takes a long time to reach low-income and marginalized communities. Hard-working community groups struggle to train a handful of people so that a trickle of the billions of dollars generated by this new tech reaches their community. But what if instead of being relegated to the back of the bus, these communities grabbed a seat at the front?
We believe there’s an opportunity to do this in the emerging fields of augmented reality (AR) and virtual reality (VR). Apple, Google, Microsoft, Facebook, and others are engaged in a fierce battle over which handful of players will dominate this new industry. If community groups work together, they can leverage this battle to ensure their communities can help shape the course of this new industry. In doing so they can:
- Create jobs, co-ops, small businesses, etc. and obtain a seat at the table so their communities benefit economically
- Create a model for communities to ensure all other emerging technologies benefit them economically — especially as robots/AI begin automating away other jobs
The Key: Make AR/VR Development More Accessible to All
For the tech companies competing over AR/VR, accessibility is a key strategic advantage. If we can make it much easier for regular people from South Central to Harlan County to develop AR/VR projects, it’ll also be easier for corporate developers, “power users,” and other staff to do so. Here’s how we’ll do it:
- Smooth The Learning Curve. Most new tech makes it easy to do a handful of tasks. But as soon as users need to go beyond the point-and-click basics, they hit a dauntingly steep learning curve. So, use user experience design (UX) to figure out how to redesign AR/VR development tools and frameworks to smooth out the learning curve from absolute beginner to seasoned pro. In doing so, ensure that over time more and more people in the community learn not only how to use existing tools and but how to create new ones — and in doing shape the industry’s direction.
- Create a Community-Oriented Approach. One-time trainings are a good place to start, but to gain fluency most people need ongoing technical and psychological support. So, develop an ecosystem of support, including strategies to plug into social institutions people already belong to.
Build a Model: use our experience with AR/VR development to create a model for changing the culture of emerging tech. The goal: all emerging tech is designed from the ground up so it’s easy for people in every community to get started and easy for them to “level up” their skills as needed. This model will also open up the debate over what it means to “democratize” technology.
- Community Groups: members of marginalized/low income community groups, whose voice and needs will drive the project. Their goal: to create jobs and business/co-op opportunities in their communities, building ownership and ensuring they control a seat at the emerging tech table.
Tech Community: a diverse group of tech designers, coders, and AR/VR experts who care passionately about working collaboratively with low-income communities and creating a diverse tech community. Their goal: help the community while learning new skills and building their resume
Tech Players: a few individuals from the main AR/VR players, to provide informal technical support/expertise and to begin a dialogue about what it means to “democratize” their technology. Their goal: to make their tech more accessible and help their company win a piece of the AR/VR pie.
About two weeks ago, I came to a very painful decision: I had to shut down the Mixed Reality for All project. I really, really didn’t want to do it. But to run a tricky project like, you need to be able to put in a lot more face time than I’d anticipated. It’s been almost seven years since I messed up my knees, and I thought I was finally at the point where I could sit as well as stand for long enough to be able to pull off an organizing project. That turned out not to be the case.
There’s a lot you can do remotely, through video chat, etc., but there are real limits. For example, if you’re trying to convince partners who aren’t sure what you’re proposing is feasible, you can do a lot online, but at the end of the day there’s no substitute for spending time face to face — especially for building the bonds of trust needed to be folks to take a leap of faith. Maybe a better organizer than I am could’ve figured out how; I couldn’t.
I’m still reeling from the decision. I got to work with some fabulous people, and the online community around A-Frame is just wonderful. And it’s hard in a situation like this not to feel like I’m letting some people down. But I’ve been running projects for long enough to know when it’s time to face reality and pull the plug.
That said, I learned a lot from working on Mixed Reality for All. In the next few weeks I hope to blog about some of the lessons I learned. But for now, it’s time to lick my wounds and decompress.
If someone tells you that AI won’t ever be a threat to us because why would it want to kill us, they really don’t get how brittle and nonlinearly weird this tech can be. A wonderful new paper compiles a bunch of examples from AI software that used evolutionary strategies that through trial and error discovered some… unusual solutions. For example,
when MIT Lincoln Labs evaluated GenProg on a buggy sorting program, researchers created tests that measured whether the numbers output by the sorting algorithm were in sorted order. However, rather than actually repairing the program (which sometimes failed to correctly sort), GenProg found an easier solution: it entirely short-circuited the buggy program, having it always return an empty list, exploiting the technicality that an empty list was scored as not being out of order.
Here’s another example where the AI “solved” a problem that technically fit the rules it was given:
In another project, to avoid runaway computation, the fitness function explicitly limited a program’s CPU usage: in response, GenProg produced programs that slept forever, which did not count toward CPU usage limits, since there were no computations actually performed
We rarely hear about these “solutions” because when AI come up with them, researchers tweak the victory conditions to bar them. That works just fine in a highly comtrolled, highly simplifted lab environment. But as we build more and more systems that are expected to work in ever more complex environments, catching all these novel solutions gets a lot harder. And if an AI thinks the best way to sort a list is to kill the list…
Does this mean we should be paranoid about AI? No. But blithely assuming it’ll never be a threat is equally foolish. We need to assume that Uncle Murphy will be a not infrequent guest of AI systems and act accordingly.
Spotify is about to go public, and it may be valued at as much as $23 billion. Its founders are about to become filthy rich. Record companies won’t do too shabby either.
The major record labels also own minority stakes in the company, as a result of licensing deals struck over the years. Sony has the largest, with 5.7 percent; the others were not disclosed.
And musicians? Most popular musicians are still making so little from streaming that their main source of income is from touring.
This is why future fights over who has a seat at the table — and therefore gets to decide how staggering amounts of wealth are divvied up — is going to be absolutely critical in the era of ubiquitous robots, AI, and other emerging tech. There’s no question our society is going to end up with an unprecedented bounty. What’s up for grabs: whether our society will ensure everyone has a real chance at enough of a slice of that bounty to live a good life, and whether our democracy survives.
Update: this piece is not an attack on Spotify. I listen to Spotify almost every day. And although I’m sure there are problems unique to Spotify, given the current rules of the road almost any music streaming service that became dominant would have most of the same core issues. This is a structural problem. If you treat it like the problem is just one “corrupt” company, you are letting yourself be played for a sucker.