Article by John McKenna: “We’ve all heard about donating blood, but how about donating data?
Chronic non-communicable diseases (NCDs) like diabetes, heart disease and epilepsy are predicted by the World Health Organization to account for 57% of all disease by 2020.
Today over 600,000 patients from around the world share data on more than 2,800 chronic diseases to improve research and treatment of their conditions.
People who join the PatientsLikeMe online community share information on everything from their medication and treatment plans to their emotional struggles.
Many of the participants say that it is hugely beneficial just to know there is someone else out there going through similar experiences.
But through its use of data, the platform also has the potential for far more wide-ranging benefits to help improve the quality of life for patients with chronic conditions.
Give data, get data
PatientsLikeMe is one of a swathe of emerging data platforms in the healthcare sector helping provide a range of tech solutions to health problems, including speeding up the process of clinical trials using Real Time Data Analysis or using blockchain to enable the secure sharing of patient data.
Its philosophy is “give data, get data”. In practice it means that every patient using the website has access to an array of crowd-sourced information from the wider community, such as common medication side-effects, and patterns in sufferers’ symptoms and behaviour….(More)”.
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)”.
Ida Rademacher at the Aspen Institute: “…At the Aspen Institute Financial Security Program, we sense a growing need to ground these numbers in what people experience day-to-day. We’re inspired by projects like the Financial Diaries that helped create empathy for what the statistics mean. …the Diaries was a time-delimited project, and the insights we can gain from major banking institutions are somewhat limited in their ability to show the challenges of economically marginalized populations. That’s why we’ve recently launched a consumer insights initiative to develop and translate a more broadly sourced set of data that lifts the curtain on the financial lives of low- and moderate-income US consumers. What does it really mean to lack $400 when you need it? How do people cope? What are the aspirations and anxieties that fuel choices? Which strategies work and which fall flat? Our work exists to focus the dialogue about financial insecurity by keeping an ear to the ground and amplifying what we hear. Our ultimate goal: Inspire new solutions that react to reality, ones that can genuinely improve the financial well-being of many.
Our consumer insights initiative sees power in partnerships and collaboration. We’re building a big tent for a range of actors to query and share what their data says: private sector companies, public programs, and others who see unique angles into the financial lives of low- and moderate-income households. We are creating a new forum to lift up these firms serving consumers – and in doing so, we’re raising the voices of consumers themselves.
One example of this work is our Consumer Insights Collaborative (CIC), a group of nine leading non-profits from across the country. Each has a strong sense of challenges and opportunities on the ground because every day their work brings them face-to-face with a wide array of consumers, many of whom are low- and moderate-income families. And most already work independently to learn from their data. Take EARN and its Big Data on Small Savings project; the Financial Clinic’s insights series called Change Matters; Mission Asset Fund’s R&D Lab focused on human-centered design; and FII which uses data collection as part of its main service.
Through the CIC, they join forces to see more than any one nonprofit can on their own. Together CIC members articulate common questions and synthesize collective answers. In the coming months we will publish a first-of-its-kind report on a jointly posed question: What are the dimensions and drivers of short term financial stability?
An added bonus of partnerships like the CIC is the community of practice that naturally emerges. We believe that data scientists from all walks can, and indeed must, learn from each other to have the greatest impact. Our initiative especially encourages cooperative capacity-building around data security and privacy. We acknowledge that as access to information grows, so does the risk to consumers themselves. We endorse collaborative projects that value ethics, respect, and integrity as much as they value cross-organizational learning.
As our portfolio grows, we will invite an even broader network to engage. We’re already working with NEST Insights to draw on NEST’s extensive administrative data on retirement savings, with an aim to understand more about the long-term implications of non-traditional work and unstable household balance sheets on financial security….(More)”.
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)”
Aliya Ram and Madhumita Murgia at the Financial Times: “The UK government should force Google, Apple, Uber and others to share their mapping data so that other companies can develop autonomous cars, drones and transport apps, according to an influential campaign group. The Open Data Institute, co-founded by Tim Berners-Lee at MIT and Nigel Shadbolt, artificial intelligence professor at the University of Oxford, warned on Tuesday that big tech companies had become “data monopolies”.
The group said the UK’s Geospatial Commission should ask the companies to share map data with rivals and the public sector in a collaborative database or else force them to do so with legislation.
“Google along with all of the other companies like Apple and Uber are trying to deliver an excellent service to their clients and customers,” said Jeni Tennison, chief executive of the Open Data Institute. “The status quo is not optimal because all of the organisations we are talking about are replicating effort. This means that people are overall not getting the best service from the data that is being collected and maintained. “The large companies are becoming more like data monopolies and that doesn’t give us the best value from our data.”
On Tuesday, the UK government said its Office for Artificial Intelligence had teamed up with the ODI to pilot two new “data trusts” — legal structures that allow multiple groups to share anonymised information. Data trusts have been described as a good way for small business to compete with large rivals that have lots of data, but only a handful have been set up so far.
The trusts will be designed over the next few months and could be used to share data, for example, about cities, the environment, biodiversity and transport. Ms Tennison said the ODI was also working on a data trust with the mayor of London, Sadiq Khan, and local authorities in Greenwich to see how real time data from the internet of things and sensors could be shared with start-ups to solve problems in the city. London’s transport authority has said ride hailing apps would be forced to turn over travel data to the government. Uber now provides public access to its data on traffic and travel conditions in the UK….(More) (Full Report)”.
Report by the World Bank: “…Decisions based on data can greatly improve people’s lives. Data can uncover patterns, unexpected relationships and market trends, making it possible to address previously intractable problems and leverage hidden opportunities. For example, tracking genes associated with certain types of cancer to improve treatment, or using commuter travel patterns to devise public transportation that is affordable and accessible for users, as well as profitable for operators.
Data is clearly a precious commodity, and the report points out that people should have greater control over the use of their personal data. Broadly speaking, there are three possible answers to the question “Who controls our data?”: firms, governments, or users. No global consensus yet exists on the extent to which private firms that mine data about individuals should be free to use the data for profit and to improve services.
User’s willingness to share data in return for benefits and free services – such as virtually unrestricted use of social media platforms – varies widely by country. In addition to that, early internet adopters, who grew up with the internet and are now age 30–40, are the most willing to share (GfK 2017).
Are you willing to share your data? (source: GfK 2017)
On the other hand, data can worsen the digital divide – the data poor, who leave no digital trail because they have limited access, are most at risk from exclusion from services, opportunities and rights, as are those who lack a digital ID, for instance.
Firms and Data
For private sector firms, particularly those in developing countries, the report suggests how they might expand their markets and improve their competitive edge. Companies are already developing new markets and making profits by analyzing data to better understand their customers. This is transforming conventional business models. For years, telecommunications has been funded by users paying for phone calls. Today, advertisers pay for users’ data and attention are funding the internet, social media, and other platforms, such as apps, reversing the value flow.
Governments and Data
For governments and development professionals, the report provides guidance on how they might use data more creatively to help tackle key global challenges, such as eliminating extreme poverty, promoting shared prosperity, or mitigating the effects of climate change. The first step is developing appropriate guidelines for data sharing and use, and for anonymizing personal data. Governments are already beginning to use the huge quantities of data they hold to enhance service delivery, though they still have far to go to catch up with the commercial giants, the report finds.
Data for Development
The Information and Communications for Development report analyses how the data revolution is changing the behavior of governments, individuals, and firms and how these changes affect economic, social, and cultural development. This is a topic of growing importance that cannot be ignored, and the report aims to stimulate wider debate on the unique challenges and opportunities of data for development. It will be useful for policy makers, but also for anyone concerned about how their personal data is used and how the data revolution might affect their future job prospects….(More)”.
Jasmin Gray at Huffington Post: “The NHS has pulled out of a controversial data-sharing arrangement with the Home Office which saw confidential patients’ details passed on to immigration enforcers.
But on Tuesday, NHS Digital announced that it was cutting itself out of the agreement altogether.
“NHS Digital has received a revised narrowed request from the Home Office and is discussing this request with them,” a spokesperson for the data-branch of the health service said, adding that they have “formally closed-out our participation” in the previous memorandum of understanding.
The anxieties of “multiple stakeholder communities” to ensure the agreement made by the government was respected was taken into account in the decision, they added.
Meanwhile, the Home Office confirmed it was working to agree a new deal with NHS Digital which would only allow it to make requests for data about migrants “facing deportation action because they have committed serious crimes, or where information necessary to protect someone’s welfare”.
The move has been welcomed by campaigners, with Migrants’ Rights Network director Rita Chadra saying that many migrants had missed out on “the right to privacy and access to healthcare” because of the data-sharing mechanism….(More)”.
Paper by Bill Howe et al: “Data too sensitive to be “open” for analysis and re-purposing typically remains “closed” as proprietary information. This dichotomy undermines efforts to make algorithmic systems more fair, transparent, and accountable. Access to proprietary data in particular is needed by government agencies to enforce policy, researchers to evaluate methods, and the public to hold agencies accountable; all of these needs must be met while preserving individual privacy and firm competitiveness. In this paper, we describe an integrated legaltechnical approach provided by a third-party public-private data trust designed to balance these competing interests.
Basic membership allows firms and agencies to enable low-risk access to data for compliance reporting and core methods research, while modular data sharing agreements support a wide array of projects and use cases. Unless specifically stated otherwise in an agreement, all data access is initially provided to end users through customized synthetic datasets that offer a) strong privacy guarantees, b) removal of signals that could expose competitive advantage for the data providers, and c) removal of biases that could reinforce discriminatory policies, all while maintaining empirically good fidelity to the original data. We find that the liberal use of synthetic data, in conjunction with strong legal protections over raw data, strikes a tunable balance between transparency, proprietorship, privacy, and research objectives; and that the legal-technical framework we describe can form the basis for organizational data trusts in a variety of contexts….(More)”.
Paper by Bill Howe et al: “Data too sensitive to be “open” for analysis and re-purposing typically remains “closed” as proprietary information. This dichotomy undermines efforts to make algorithmic systems more fair, transparent, and accountable. Access to proprietary data in particular is needed by government agencies to enforce policy, researchers to evaluate methods, and the public to hold agencies accountable; all of these needs must be met while preserving individual privacy and firm competitiveness. In this paper, we describe an integrated legaltechnical approach provided by a third-party public-private data trust designed to balance these competing interests.
Basic membership allows firms and agencies to enable low-risk access to data for compliance reporting and core methods research, while modular data sharing agreements support a wide array of projects and use cases. Unless specifically stated otherwise in an agreement, all data access is initially provided to end users through customized synthetic datasets that offer a) strong privacy guarantees, b) removal of signals that could expose competitive advantage for the data providers, and c) removal of biases that could reinforce discriminatory policies, all while maintaining empirically good fidelity to the original data. We find that the liberal use of synthetic data, in conjunction with strong legal protections over raw data, strikes a tunable balance between transparency, proprietorship, privacy, and research objectives; and that the legal-technical framework we describe can form the basis for organizational data trusts in a variety of contexts….(More)”.
Doubtlessly, there is truth in these statements. But a major, often unacknowledged problem is how much data remains inaccessible, hidden in siloes and behind walls.
For close to a decade, the technology and public interest community has pushed the idea of open data. At its core, open data represents a new paradigm of information and information access.
Rooted in notions of an information commons — developed by scholars like Nobel Prize winner Elinor Ostrom — and borrowing from the language of open source, open data begins from the premise that data collected from the public, often using public funds or publicly funded infrastructure, should also belong to the public — or at least, be made broadly accessible to those pursuing public-interest goals.
The open data movement has reached significant milestones in its short history. An ever-increasing number of governments across both developed and developing economies have released large datasets for the public’s benefit….
Similarly, a growing number of private companies have “Data Collaboratives” leveraging their data — with various degrees of limitations — to serve the public interest.
Despite such initiatives, many open data projects (and data collaboratives) remain fledgling. The field has trouble scaling projects beyond initial pilots. In addition, many potential stakeholders — private sector and government “owners” of data, as well as public beneficiaries — remain sceptical of open data’s value. Such limitations need to be overcome if open data and its benefits are to spread. We need hard evidence of its impact.
Ironically, the field is held back by an absence of good data on open data — that is, a lack of reliable empirical evidence that could guide new initiatives.
At the GovLab, a do-tank at New York University, we study the impact of open data. One of our overarching conclusions is that we need a far more solid evidence base to move open data from being a good idea to reality.
What do we know? Several initiatives undertaken at the GovLab offer insight. Our ODImpactwebsite now includes more than 35 detailed case studies of open government data projects. These examples provide powerful evidence not only that open data can work but also about howit works….
We have also launched an Open Data Periodic Table to better understand what conditions predispose an open data project toward success or failure. For example, having a clear problem definition, as well as the capacity and culture to carry out open data projects, are vital. Successful projects also build cross-sector partnerships around open data and its potential uses and establish practices to assess and mitigate risks, and have transparent and responsive governance structures….(More)”.
