Seven design principles for using blockchain for social impact


Stefaan Verhulst at Apolitical: “2018 will probably be remembered as the bust of the blockchain hype. Yet even as crypto currencies continue to sink in value and popular interest, the potential of using blockchain technologies to achieve social ends remains important to consider but poorly understood.

In 2019, business will continue to explore blockchain for sectors as disparate as finance, agriculture, logistics and healthcare. Policymakers and social innovators should also leverage 2019 to become more sophisticated about blockchain’s real promise, limitations  and current practice.

In a recent report I prepared with Andrew Young, with the support of the Rockefeller Foundation, we looked at the potential risks and challenges of using blockchain for social change — or “Blockchan.ge.” A number of implementations and platforms are already demonstrating potential social impact.

The technology is now being used to address issues as varied as homelessness in New York City, the Rohingya crisis in Myanmar and government corruption around the world.

In an illustration of the breadth of current experimentation, Stanford’s Center for Social Innovation recently analysed and mapped nearly 200 organisations and projects trying to create positive social change using blockchain. Likewise, the GovLab is developing a mapping of blockchange implementations across regions and topic areas; it currently contains 60 entries.

All these examples provide impressive — and hopeful — proof of concept. Yet despite the very clear potential of blockchain, there has been little systematic analysis. For what types of social impact is it best suited? Under what conditions is it most likely to lead to real social change? What challenges does blockchain face, what risks does it pose and how should these be confronted and mitigated?

These are just some of the questions our report, which builds its analysis on 10 case studies assembled through original research, seeks to address.

While the report is focused on identity management, it contains a number of lessons and insights that are applicable more generally to the subject of blockchange.

In particular, it contains seven design principles that can guide individuals or organisations considering the use of blockchain for social impact. We call these the Genesis principles, and they are outlined at the end of this article…(More)”.

Creating value through data collaboratives


Paper by  Klievink, Bram, van der Voort, Haiko and Veeneman, Wijnand: “Driven by the technological capabilities that ICTs offer, data enable new ways to generate value for both society and the parties that own or offer the data. This article looks at the idea of data collaboratives as a form of cross-sector partnership to exchange and integrate data and data use to generate public value. The concept thereby bridges data-driven value creation and collaboration, both current themes in the field.

To understand how data collaboratives can add value in a public governance context, we exploratively studied the qualitative longitudinal case of an infomobility platform. We investigated the ability of a data collaborative to produce results while facing significant challenges and tensions between the goals of parties, each having the conflicting objectives of simultaneously retaining control whilst allowing for generativity. Taken together, the literature and case study findings help us to understand the emergence and viability of data collaboratives. Although limited by this study’s explorative nature, we find that conditions such as prior history of collaboration and supportive rules of the game are key to the emergence of collaboration. Positive feedback between trust and the collaboration process can institutionalise the collaborative, which helps it survive if conditions change for the worse….(More)”.

Waze-fed AI platform helps Las Vegas cut car crashes by almost 20%


Liam Tung at ZDNet: “An AI-led, road-safety pilot program between analytics firm Waycare and Nevada transportation agencies has helped reduce crashes along the busy I-15 in Las Vegas.

The Silicon Valley Waycare system uses data from connected cars, road cameras and apps like Waze to build an overview of a city’s roads and then shares that data with local authorities to improve road safety.

Waycare struck a deal with Google-owned Waze earlier this year to “enable cities to communicate back with drivers and warn of dangerous roads, hazards, and incidents ahead”. Waze’s crowdsourced data also feeds into Waycare’s traffic management system, offering more data for cities to manage traffic.

Waycare has now wrapped up a year-long pilot with the Regional Transportation Commission of Southern Nevada (RTC), Nevada Highway Patrol (NHP), and the Nevada Department of Transportation (NDOT).

RTC reports that Waycare helped the city reduce the number of primary crashes by 17 percent along the Interstate 15 Las Vegas.

Waycare’s data, as well as its predictive analytics, gave the city’s safety and traffic management agencies the ability to take preventative measures in high risk areas….(More)”.

Driven to safety — it’s time to pool our data


Kevin Guo at TechCrunch: “…Anyone with experience in the artificial intelligence space will tell you that quality and quantity of training data is one of the most important inputs in building real-world-functional AI. This is why today’s large technology companies continue to collect and keep detailed consumer data, despite recent public backlash. From search engines, to social media, to self driving cars, data — in some cases even more than the underlying technology itself — is what drives value in today’s technology companies.

It should be no surprise then that autonomous vehicle companies do not publicly share data, even in instances of deadly crashes. When it comes to autonomous vehicles, the public interest (making safe self-driving cars available as soon as possible) is clearly at odds with corporate interests (making as much money as possible on the technology).

We need to create industry and regulatory environments in which autonomous vehicle companies compete based upon the quality of their technology — not just upon their ability to spend hundreds of millions of dollars to collect and silo as much data as possible (yes, this is how much gathering this data costs). In today’s environment the inverse is true: autonomous car manufacturers are focusing on are gathering as many miles of data as possible, with the intention of feeding more information into their models than their competitors, all the while avoiding working together….

The complexity of this data is diverse, yet public — I am not suggesting that people hand over private, privileged data, but actively pool and combine what the cars are seeing. There’s a reason that many of the autonomous car companies are driving millions of virtual miles — they’re attempting to get as much active driving data as they can. Beyond the fact that they drove those miles, what truly makes that data something that they have to hoard? By sharing these miles, by seeing as much of the world in as much detail as possible, these companies can focus on making smarter, better autonomous vehicles and bring them to market faster.

If you’re reading this and thinking it’s deeply unfair, I encourage you to once again consider 40,000 people are preventably dying every year in America alone. If you are not compelled by the massive life-saving potential of the technology, consider that publicly licenseable self-driving data sets would accelerate innovation by removing a substantial portion of the capital barrier-to-entry in the space and increasing competition….(More)”

Quantifying Bicycle Network Connectivity in Lisbon Using Open Data


Lorena Abad and Lucas van der Meer in information: “Stimulating non-motorized transport has been a key point on sustainable mobility agendas for cities around the world. Lisbon is no exception, as it invests in the implementation of new bike infrastructure. Quantifying the connectivity of such a bicycle network can help evaluate its current state and highlight specific challenges that should be addressed. Therefore, the aim of this study is to develop an exploratory score that allows a quantification of the bicycle network connectivity in Lisbon based on open data.

For each part of the city, a score was computed based on how many common destinations (e.g., schools, universities, supermarkets, hospitals) were located within an acceptable biking distance when using only bicycle lanes and roads with low traffic stress for cyclists. Taking a weighted average of these scores resulted in an overall score for the city of Lisbon of only 8.6 out of 100 points. This shows, at a glance, that the city still has a long way to go before achieving their objectives regarding bicycle use in the city….(More)”.