a version 0.0.1 launch
💻 We’re creating an open-source (and open-thought) community of civil servants, private-sector technologists, and academics to encourage government to embrace data-driven decisions and accelerate the adoption of data analytics in governance.
Anyone can see the massive acceleration being brought on by recent advancements in AI/ML. We can also see the ethical risks these innovations pose, along with the ever-threatening spectre of massive government IT/data projects that fail on launch or even before they see the light of day.
Already convinced you want to help? Jump immediately to the sign-up form!
🇺🇸 Digital transformation of the US government has made incredible progress over the last 10 years. There is still tremendous work to do in delivering digital public services (eventually, just services) and in unwinding the systemic structural problems that stymie and destabilize practitioners in government. At the same time, it is incumbent upon us to start preparing for the next phase and look forward*.*
This pivot to data will fuel the next transformative phase. We believe there will be less focus on the process of delivering digital services (as they will have become norms) and more on the data they ingest and create. This will bring technology practitioners even closer to decision makers as they will be able to spend the majority of time discussing what to do about the data as opposed to how they’re going to access it.
UIs will be easy to spin up and effectively free to customize to each individual or process. Natural-language interfaces to query and analyze the data will quickly become the new standard for the majority of people.
But how can we get there without falling into the pitfalls of the past, much less the novel problems these technologies create? If even Google’s AI usage ends up recommending that people put glue on their pizza how can much smaller teams with fewer resources avoid the same fate, especially if people’s lives and livelihoods are on the line?
Ultimately, we think practitioners will begin to start drowning in data, if they haven’t already. AI accelerationists think the price of intelligence will be too cheap to meter within the decade. We think the price of information will trend ever downward.
What continues to be scarce, in either scenario, is insight.
Insight requires careful thought and asking the right questions of these systems in the first place. Our goal is to leverage AI/ML for it’s productivity gains - without blindly trusting it.
🚧 We’re not doing an extensive stealth run to build this up in private before a big overwrought launch. If you’re reading this, you’re coming in not just at the ground floor — this is literally the construction site for the ground floor. Whether you sign up on launch day or in a year, your place in the community will be recognized by your contributions. We intend to build iteratively, in the open, in collaboration with the people impacted**.**
❓We don’t pretend to have the right answers just yet—or maybe even the right questions! To start, we must begin. But, we have two ideas that we think will help shape and sharpen our future investigations. In general, we’re looking to provide guidance for a healthy adoption and acceleration of data analytics and AI.
🧑🏽‍💻 Three immediate projects you can help us build out: