Stefaan Verhulst
PSFK: “The state of your health shouldn’t be a mystery, nor should patients or doctors have to wait long to find answers to pressing medical concerns. In PSFK’s Future of Health Report, we dig deep into the latest in AI, big data algorithms and IoT tools that are enabling a new, more comprehensive overview of patient data collection and analysis. Machine support, patient information from medical records and conversations with doctors are combined with the latest medical literature to help form a diagnosis without detracting from doctor-patient relations.
The impact of improved AI helps patients form a baseline for well-being and is making changes all across the healthcare industry. AI not only streamlines intake processes and reduces processing volume at clinics, it also controls input and diagnostic errors within a patient record, allowing doctors to focus on patient care and communication, rather than data entry. AI also improves pattern recognition and early diagnosis by learning from multiple patient data sets.
By utilizing deep learning algorithms and software, healthcare providers can connect various libraries of medical information and scan databases of medical records, spotting patterns that lead to more accurate detection and greater breadth of efficiency in medical diagnosis and research. IBM Watson, which has previously been used to help identify genetic markers and develop drugs, is applying its neural learning networks to help doctors correctly diagnose heart abnormalities from medical imaging tests. By scanning thousands of images and learning from correct diagnoses, Watson is able to increase diagnostic accuracy, supporting doctors’ cardiac assessments.
Outside of the doctor’s office, AI is also being used to monitor patient vitals to help create a baseline for well-being. By monitoring health on a day-to-day basis, AI systems can alert patients and medical teams to abnormalities or changes from the baseline in real time, increasing positive outcomes. Take xbird, a mobile platform that uses artificial intelligence to help diabetics understand when hypoglycemic attacks will occur. The AI combines personal and environmental data points from over 20 sensors within mobile and wearable devices to create an automated personal diary and cross references it against blood sugar levels. Patients then share this data with their doctors in order to uncover their unique hypoglycemic triggers and better manage their condition.
In China, meanwhile, web provider Baidu has debuted Melody, a chat-based medical assistant that helps individuals communicate their symptoms, learn of possible diagnoses and connect to medical experts….(More)”.
Nicole Softness at Quartz: “Many Americans aren’t aware they don’t live in a direct democracy. But with a little digital assistance, they could be….Once completely cut off from the global community, Estonia is now considered a world leader for its efforts to integrate technology with government administration. While standing in line for coffee, you could file your tax return, confirm sensitive personal medical information, and register a new company in just a few swipes, all on Estonia’s free wifi.
What makes this possible without the risk of fraud? Digital trust. Using a technology called blockchain, which verifies online communications and transactions at every step (and essentially eliminates the possibility of online fraud), Estonian leadership has moved the majority of citizenship processes online. Startups have now created new channels for democratic participation, like Rahvaalgatus, an online crowdsourcing platform that allows users to discuss and digitally vote on policy proposals submitted to the Estonian parliament.
Brazil has also utilized this trust quite valiantly. The country’s constitution, passed in 1988, legislated that signatures from 1% of a population could force the Brazilian leadership to recognize any signed document as an official draft bill and vote. Until recently, the notion of getting sufficient signatures on paper would have been laughable: that’s just over 2 million physical signatures. However, votes can now be cast online, which makes gathering digital signatures all the more easy. As a result, Brazilians now have more control over the legislature being brought before parliament.
Blockchain technology creates an immutable record of signatures tied to the identities of voters. Again, blockchain technology is key here, as it creates an immutable record of signatures tied to the identities of voters. The government knows which voters are legitimate citizens, and citizens can be sure their votes remain accurate. When Brazilians are able to participate in this manner, their democracy shifts towards the sort of “direct” democracy that, until now, seemed logistically impossible in modern society.
Australian citizens have engaged in a slightly different experiment, dubbed “Government 2.0.” In March 2016, technology experts convened a new political party called Flux, which they describe as “democracy for the information age.” The party platform argues that bureaucracy stymies key government functions, which cannot process the requisite information required to govern.
If elected to government, members of Flux would vote on bills scheduled to appear before parliament based on the digital ballots of the supporters who voted them in. Voters could choose to participate in casting their vote for that bill themselves, or transfer their votes to trusted experts. Flux representatives in parliament would then cast their votes 100% based on the results of these member participants. (They are yet to win any seats in government, however.)
These solutions show us that bureaucratic boundaries no longer have to limit our access to a true democracy. The technology is here to make direct democracy the reality that the Greeks once imagined.
More so, increasing democratic participation will have positive ripple effects beyond participation in a direct democracy: Informed voting is the gateway to more active civic engagement and a more informed electorate, all of which raises the level of debate in a political environment desperately in need of participation….(More)”
Over the last decades, participatory approaches involving on-farm experimentation have become more prevalent in agricultural research. Nevertheless, these approaches remain difficult to scale because they usually require close attention from well-trained professionals. Novel large-N participatory trials, building on recent advances in citizen science and crowdsourcing methodologies, involve large numbers of participants and little researcher supervision. Reduced supervision may affect data quality, but the “Wisdom of Crowds” principle implies that many independent observations from a diverse group of people often lead to highly accurate results when taken together. In this study, we test whether farmer-generated data in agricultural citizen science are good enough to generate valid statements about the research topic. We experimentally assess the accuracy of farmer observations in trials of crowdsourced crop variety selection that use triadic comparisons of technologies (tricot). At five sites in Honduras, 35 farmers (women and men) participated in tricot experiments. They ranked three varieties of common bean (Phaseolus vulgaris L.) for Plant vigor, Plant architecture, Pest resistance, and Disease resistance. Furthermore, with a simulation approach using the empirical data, we did an order-of-magnitude estimation of the sample size of participants needed to produce relevant results. Reliability of farmers’ experimental observations was generally low (Kendall’s W 0.174 to 0.676). But aggregated observations contained information and had sufficient validity (Kendall’s tau coefficient 0.33 to 0.76) to identify the correct ranking orders of varieties by fitting Mallows-Bradley-Terry models to the data. Our sample size simulation shows that low reliability can be compensated by engaging higher numbers of observers to generate statistically meaningful results, demonstrating the usefulness of the Wisdom of Crowds principle in agricultural research. In this first study on data quality from a farmer citizen science methodology, we show that realistic numbers of less than 200 participants can produce meaningful results for agricultural research by tricot-style trials….(More)”.
Yuan Yang, Yingzhi Yang and Sherry Fei Ju in the Financial Times: “China, a surveillance state where authorities have unchecked access to citizens’ histories, is seeking to look into their future with technology designed to predict and prevent crime. Companies are helping police develop artificial intelligence they say will help them identify and apprehend suspects before criminal acts are committed. “If we use our smart systems and smart facilities well, we can know beforehand . . . who might be a terrorist, who might do something bad,” Li Meng, vice-minister of science and technology, said on Friday.
Facial recognition company Cloud Walk has been trialling a system that uses data on individuals’ movements and behaviour — for instance visits to shops where weapons are sold — to assess their chances of committing a crime. Its software warns police when a citizen’s crime risk becomes dangerously high, allowing the police to intervene. “The police are using a big-data rating system to rate highly suspicious groups of people based on where they go and what they do,” a company spokesperson told the Financial Times. Risks rise if the individual “frequently visits transport hubs and goes to suspicious places like a knife store”, the spokesperson added. China’s authoritarian government has always amassed personal data to monitor and control its citizens — whether they are criminals or suspected of politically sensitive activity. But new technology, from phones and computers to fast-developing AI software, is amplifying its capabilities. These are being used to crack down on even the most minor of infractions — facial recognition cameras, for instance, are also being used to identify and shame jaywalkers, according to state media. Mr Li said crime prediction would become an important use for AI technology in the government sphere.
China’s crime-prediction technology relies on several AI techniques, including facial recognition and gait analysis, to identify people from surveillance footage. In addition, “crowd analysis” can be used to detect “suspicious” patterns of behaviour in crowds, for example to single out thieves from normal passengers at a train stations. As well as tracking people with a criminal history, Cloud Walk’s technology is being used to monitor “high-risk” places such as hardware stores…(More)”
Austin Seaborn at Beeck Center: “Members of Congress have close connections with their districts, and information arising from local organizations, such as professional groups, academia, industry as well as constituents with relevant expertise (like retirees, veterans or students) is highly valuable to them. Today, congressional staff capacity is at a historic low, while at the same time, constituents in districts are often well equipped to address the underlying policy questions that Congress seeks to solve….
In meetings we have had with House and Senate staffers, they repeatedly express both the difficulty managing their substantial area-specific work loads and their interest in finding ways to substantively engage constituents to find good nuggets of information to help them in their roles as policymakers. At the same time, constituents are demanding more transparency and dialogue from their elected representatives. In many cases, our project brings these two together. It allows Members to tap the expertise in their districts while at the same time creating an avenue for constituents to contribute their knowledge and area expertise to the legislative process. It’s a win for constituents and a win for Member of Congress and their staffs.
It is important to note that the United States lags behind other democracies in experimenting with more inclusive methods during the policymaking process. In the United Kingdom, for example, the UK Parliament has experimented with a variety of new digital tools to engage with constituents. These methods range from Twitter hashtags, which are now quite common given the rise in social media use by governments and elected officials, to a variety of web forums on a variety of platforms. Since June of 2015, they have also been doing digital debates, where questions from the general public are crowdsourced and later integrated into a parliamentary debate by the Member of Parliament leading the debate. Estonia, South Africa, Taiwan, France also…notable examples.
One promising new development we hope to explore more thoroughly is the U.S. Library of Congress’s recently announced legislative data App Challenge. This competition is distinct from the many hackathons that have been held on behalf of Congress in the past, in that this challenge seeks new methods not only to innovate, but also to integrate and legislate. In his announcement, the Library’s Chief Information Officer, Bernard A. Barton, Jr., stated, “An informed citizenry is better able to participate in our democracy, and this is a very real opportunity to contribute to a better understanding of the work being done in Washington. It may even provide insights for the people doing the work around the clock, both on the Hill, and in state and district offices. Your innovation and integration may ultimately benefit the way our elected officials legislate for our future.” We believe these sorts of new methods will play a crucial role in the future of engaging citizens in their democracies….(More)”.
What can be done to address this deficit? Beyond meeting legal standards, all relevant institutions must take care to show themselves trustworthy in the eyes of the public. The lapses of the Royal Free hospitals and DeepMind provide, by omission, valuable lessons.
The first is to be open about what data are transferred. The extent of data transfer between the Royal Free and DeepMind came to light through investigative journalism. In my opinion, had the project proceeded under open contracting, it would have been subject to public scrutiny, and to questions about whether a company owned by Google — often accused of data monopoly — was best suited to create a relatively simple app.
The second lesson is that data transfer should be proportionate to the task. Information-sharing agreements should specify clear limits. It is unclear why an app for kidney injury requires the identifiable records of every patient seen by three hospitals over a five-year period.
Finally, governance mechanisms must be strengthened. It is shocking to me that the Royal Free did not assess the privacy impact of its actions before handing over access to records. DeepMind does deserve credit for (belatedly) setting up an independent review panel for health-care projects, especially because the panel has a designated budget and has not required members to sign non-disclosure agreements. (The two groups also agreed a new contract late last year, after criticism.)
More is needed. The Information Commissioner asked the Royal Free to improve its processes but did not fine it or require it to rescind data. This rap on the knuckles is unlikely to deter future, potentially worse, misuses of data. People are aware of the potential for over-reach, from the US government’s demands for state voter records to the Chinese government’s alleged plans to create a ‘social credit’ system that would monitor private behaviour.
Innovations such as artificial intelligence, machine learning and the Internet of Things offer great opportunities, but will falter without a public consensus around the role of data. To develop this, all data collectors and crunchers must be open and transparent. Consider how public confidence in genetic modification was lost in Europe, and how that has set back progress.
Public dialogue can build trust through collaborative efforts. A 14-member Citizen’s Reference Panel on health technologies was convened in Ontario, Canada in 2009. The Engage2020 programme incorporates societal input in the Horizon2020 stream of European Union science funding….(More)”
Tom Kalil on “getting things done in large organizations“: “For a total of 16 years, I had the honor and privilege of working at the White House, first for President Clinton (1993-2001) and later for President Obama (2009-2017). My colleagues and I had the opportunity to help design, launch, and sustain dozens of science and technology policy initiatives. We launched major research initiatives to create the “industries of the future,” such as robotics and advanced materials. We worked with Congress to give every agency the authority to support incentive prizes of up to $50 million, and to make it easier for startups to raise capital and go public. We built coalitions of government agencies, companies, foundations, universities, and nonprofits to prepare 100,000 K-12 STEM teachers, foster more vibrant startup ecosystems all over America, advance the Maker Movement and accelerate the commercialization of federally funded research. On a good day we were able to serve as “policy entrepreneurs,” which involved generating or spotting new ideas and taking the steps needed to identify and evaluate policy options, support a sound decisionmaking process, ensure implementation, and monitor the effectiveness of the president’s policies and initiatives….(More)”
Book by Cristiano Bee: “…provides an overview of key issues in the debate concerning the emergence of active citizenship in Europe.
The specific focus of enquiry is the promotion of patterns of civic and political engagement and civic and political participation by the EU and the relative responses drawn by organizations of the civil society operating at the supranational level and in Italy, Turkey and the UK. More specifically, it addresses key debates on the engagement and participation of organized civil society across the permanent state of euro-crisis, considering the production of policy discourses along the continuum that characterized three subsequent and interrelated emergency situations (democratic, financial and migration crises) that have hit Europe since 2005. …(More)”.
Book edited by Manuel Pedro Rodríguez Bolívar: “…examines the introduction of smart technologies into public administrations and the organizational issues caused by these implementations, and the potential of information and communication technologies (ICTs) to rationalize and improve government, transform governance and organizational issues, and address economic, social, and environmental challenges. Cities are increasingly using new technologies in the delivery of public sector services and in the improvement of government transparency, business-led urban development, and urban sustainability. The book will examine specific smart projects that cities are embracing to improve transparency, efficiency, sustainability, mobility, and whether all cities are prepared to implement smart technologies and the incentives for promoting implementation. This focus on the smart technologies applied to public sector entities will be of interest to academics, researchers, policy-makers, public managers, international organizations and technical experts involved in and responsible for the governance, development and design of Smart Cities….(More)”.
Stefaan Verhulst and Andrew Young in The Conversation Global: “The modern era is marked by growing faith in the power of data. “Big data”, “open data”, and “evidence-based decision-making” have become buzzwords, touted as solutions to the world’s most complex and persistent problems, from corruption and famine to the refugee crisis.
While perhaps most pronounced in higher income countries, this trend is now emerging globally. In Africa, Latin America, Asia and beyond, hopes are high that access to data can help developing economies by increasing transparency, fostering sustainable development, building climate resiliency and the like.
This is an exciting prospect, but can opening up data actually make a difference in people’s lives?
Getting data-driven about data
The GovLab at New York University spent the last year trying to answer that question….
Our conclusion: the enthusiasm is justified – as long as it’s tempered with a good measure of realism, too. Here are our six major takeaways:
1. We need a framework – Overall, there is still little evidence to substantiate the enthusiastic claims that open data can foment sustainable development and transform governance. That’s not surprising given the early stage of most open data initiatives.
It may be early for impact evaluation, but it’s not too soon to develop a model that will eventually allow us to assess the impact of opening up data over time.
To that end, the GovLab has created an evidence-based framework that aims to better capture the role of open data in developing countries. The Open Data Logic Framework below focuses on various points in the open data value cycle, from data supply to demand, use and impact.
2. Open data has real promise – Based on this framework and the underlying evidence that fed into it, we can guardedly conclude that open data does in fact spur development – but only under certain conditions and within the right supporting ecosystem.
One well-known success took place after Nepal’s 2015 earthquake when open data helped NGOs map important landmarks such as health facilities and road networks, among other uses.
And in Colombia, the International Centre for Tropical Agriculture launched Aclímate Colombia, a tool that gives smallholder farmers data-driven insight into planting strategies that makes them more resilient to climate change….
3. Open data can improve people’s lives Examining projects in a number of sectors critical to development, including health, humanitarian aid, agriculture, poverty alleviation, energy and education, we found four main ways that data can have an impact….
4. Data can be an asset in development While these impacts are apparent in both developed and developing countries, we believe that open data can have a particularly powerful role in developing economies.
Where data is scarce, as it often is in poorer countries, open data can lead to an inherently more equitable and democratic distribution of information and knowledge. This, in turn, may activate a wider range of expertise to address complex problems; it’s what we in the field call “open innovation”.
This quality can allow resource-starved developing economies to access and leverage the best minds around.
And because trust in government is quite low in many developing economies, the transparency bred of releasing data can have after-effects that go well beyond the immediate impact of the data itself…
5. The ingredients matter To better understand why some open data projects fail while others succeed, we created a “periodic table” of open data (below), which includes 27 enabling factors divided into five broad categories….
6. We can plan for impact Our report ends by identifying how development organisations can catalyse the release and use of open data to make a difference on the ground.
Recommendations include:
· Define the problem, understand the user, and be aware of local conditions;
· Focus on readiness, responsiveness and change management;
· Nurture an open data ecosystem through collaboration and partnerships;
· Have a risk mitigation strategy;
· Secure resources and focus on sustainability; and
· Build a strong evidence base and support more research.
Next steps
In short, while it may still be too early to fully capture open data’s as-of-yet muted impact on developing economies, there are certainly reasons for optimism.
Much like blockchain, drones and other much-hyped technical advances, it’s time to start substantiating the excitement over open data with real, hard evidence.
The next step is to get systematic, using the kind of analytical framework we present here to gain comparative and actionable insight into if, when and how open data works. Only by getting data-driven about open data can we help it live up to its potential….(More)“