I’m beyond thrilled to share that I’m now managing editorial for the Digital Impact portfolio hosted by the Digital Civil Society Lab at Stanford PACS. Funded by the Bill & Melinda Gates Foundation, Liquidnet, and Knight Foundation, the initiative works to improve digital culture and infrastructure by helping social sector practitioners and policymakers to use resources safely, ethically, and effectively.
Digital Impact includes a diverse portfolio of resources enriched with perspectives from every corner of the public sphere and beyond. Our community of expert contributors, virtual roundtable series, and dynamic toolkit draw on the experiences of organizations working toward integrating appropriate data management and governance throughout their work.
Do you have a unique viewpoint on how data is being used for social good? We’d love to hear from you. Visit digitalimpact.org and feel free to pitch me directly here.
Individuals can do things that increase or decrease how easy it is to publish their data, but the digital economy is designed to capture our data. Blaming users is like blaming a victim for getting kidnapped.
Which is not to say that civil society organizations have it easy – there’s no practical way to track the full range of commercially available applications, their data policies, or the number of ways they could collect or lose control of data and cause harm. Civil society organizations may understand how dangerous their situation is, but that doesn’t mean they can monitor the entire market.
The knee-jerk reaction is to push for government regulation or human rights. While we should always work toward better laws, there are a lot of flaws to putting all our eggs in that basket. The law isn’t good at classifying data or risk, regulators have limited jurisdictions, and courts are terrible at adjudicating these kinds of cases.
Even worse, the 2018 World Justice Report declared “a crisis for human rights,” after showing that rule of law and human rights systems are weakening in 2/3 of the countries measured. When it comes to data capture – the law isn’t particularly effective, and where it is, it’s good at punishing the criminal, not saving the victim.
The good news, is that like protecting yourself from kidnapping, there aren’t perfect answers, but there’s a lot of little things we can do that, together, make a big difference. We don’t need international treaties to write better procurement contracts, we don’t need government interdiction to have workplace policies, and we don’t need commercial regulation to negotiate privacy policies that do more than boilerplate terms of service.
Early efforts to use blockchain technology for financial transactions are gathering momentum with the launch of a pilot project between Propy, a blockchain startup, and a Vermont city to use the digital ledger to record real estate deals.
Blockchain serves as a distributed ledger framework that posts transactions in real-time as cryptographically unique “blocks,” visible to authorized users. These blocks cannot be reversed or changed, with new additions to the ledger posted on top of the register of existing transactions.
The agreement between state and local officials and the startup based in Palo Alto, California, is among the first government projects designed to use crypto-currency technology in property transactions. Propy touted the deal this week as “paving the way to further government involvement.”
I don’t think I fully grasped the implications of this until my own access was cut off from Rutgers University. Because of this, I cannot see beyond snippets of the latest articles written by my peers unless I’d like to pay the exorbitant per article fee.
Each of these obstacles is a microcosm of the systemic problems plaguing the academic world today. Information is hoarded by institutions more interested in profitability than pedagogy.
Ownership is privileged over access and universities become less bastions of public knowledge than toll-extracting gatekeepers, hoarding scholarship for the privileged few able to have the connections to get in and to afford skyrocketing tuition costs.
Access, in academia and beyond, is a political question relegated to the back burner, one that needs to be reckoned with to have any chance of saving “higher learning.”
The most important thing that’s lacking is actually any kind of private space where you are not being monitored by the corporations whose tools you’re using to have whatever conversation you’re having.
So, every time you have a conversation in a digital environment, all of it, there’s a third party who’s got that information — always a corporation. And then all of that exchange is also being monitored by the government.
If the fundamental premise is that this activity of non-profits happens outside of those realms, it literally doesn’t exist in digital space, because we’re playing in their house, if you will. We may well need and would all benefit from an environment that provides some protections for us in those spaces as they exist.
When we talk about digital civil society we always say, ‘Look, we need to invent this, because we don’t have it.’ The best way to protect somebody else’s digital data in that environment is to not collect it. If you don’t have it, then it’s not at risk.
Non-profits have been excited to use things like free online documents and spreadsheets that are stored in the cloud and shared across organizations, and this comes at no direct financial cost to them. If you upload to those systems the names of everyone participating in your programs, with their address their email and their phone number, you’ve just given it away to other parties.
But, if you collect that information and don’t store it online, for one, or you encrypt it, for two, or you store it on your own servers and not in other people’s houses, as I like to think about it, then you are providing the same degree of integrity to that data that you again provide to the money that you rely on to do your business in the first place. You’re treating it with integrity toward your mission.
And if your mission, for example, is helping vulnerable people in your community, don’t do it in such a way that you essentially make them more vulnerable.
At the Linked Data-driven company of the near future:
1. You will find it curiously difficult to distinguish between “traditional” data workers (analysts, data scientists, etc.) and those in other functional areas who, at other companies, are less reliant on data. The agent of change here is the unambiguous way that Linked Data represents the world.
2. You will marvel at the volume and variety of data accruing from disparate sources, flowing from team to team, integrating with other data, producing unexpected insights, available to anyone at any time.
The data, for example, would be browseable and searchable by humans, crawlable and queryable by machines. Additionally, just like the Web, Linked Data enjoys a remarkable network effect in that each data set added to the network increases the incremental value of every data set in the network.
3. You will be inspired by the rapid creation and adjustment of models and automated processes in response to real-time data. Much of this agility is fueled by machine learning models being deployed at a far faster pace than can be achieved without the aid of Linked Data.
This is because the output of machine learning is tightly correlated with the quality of input data. People who work in this area spend much of their time cleaning and preparing input data, whereas semantically linked data has been “pre-understood” and embedded with knowledge.
[Now,] the energy devoted to the costliest, slowest phase of data work — preparation — can finally be reallocated to more productive activities like analysis.
Drilling for data is a massive undertaking that requires more resources than most nonprofits have. Outside experts can help, but work cultures need to change. How can digital nomads become full-time partners in this new data endeavor?
The number of fed, state and local civilian employees eligible for retirement has risen sharply. Meanwhile, new talent isn’t flocking to fill open government positions.
Massachusetts Comptroller Tom Shack suggests technology as a solution. “No one is going to hire their way out of the Silver Tsunami. We’re going to have to tech our way out of it.” Shack launched CTHRU, a cloud-based, open records platform that eliminates hundreds if not thousands of hours of work by his staff to access and share data. Rather than keep the state’s financial information locked in PDFs, individual computers, or in the customized, cumbersome, legacy finance systems, CTHRU shows payroll, budget, and spending data to anyone on a mobile device.
Shack understands the urgency of unearthing as much data as possible before employees with valuable institutional knowledge of programs retire from state service. Governments produce vast amounts of data. Of all the ways technology can reduce staff workloads, making data standardized and accessible in the cloud is one of the most impactful. Unlocking “tribal knowledge” trapped in employees’ minds and their computers opens up nearly endless avenues for process improvement.
With automated data flows, agencies can give the new workforce the empowerment of analyzing and learning from the data, not just the job of collecting and storing it.
Microsoft executives renewed calls for a Digital Geneva Convention and for tech companies to act as “medics in cyberspace,” much like the Red Cross on a battlefield. The enterprise can help fill the gaps in international law relating to cyberattacks, according to Microsoft’s Brad Smith and Carol Ann Browne.
Quayside, as the project is known, will be laden with sensors and cameras tracking everyone who lives, works or merely passes through the area. In what Sidewalk Labs calls a marriage of technology and urbanism, the resulting mass of data will be used to further shape and refine the new city.
But extending the surveillance powers of one of the world’s largest tech companies from the virtual world to the real one raises privacy concerns for many residents. Others caution that, when it comes to cities, data-driven decision making can be misguided and undemocratic.