Can Crowdsourcing and Collaboration Improve the Future of Human Health?

Curated on Posted on by Stefaan Verhulst

Ben Wiegand at Scientific American: “The process of medical research has been likened to searching for a needle in a haystack. With the continued acceleration of novel science and health care technologies in areas like artificial intelligence, digital therapeutics and the human microbiome we have tremendous opportunity to search the haystack in new and exciting ways. Applying these high-tech advances to today’s most pressing health issues increases our ability to address the root cause of disease, intervene earlier and change the trajectory of human health.

Global crowdsourcing forums, like the Johnson & Johnson Innovation QuickFire Challenges, can be incredibly valuable tools for searching the “haystack.” An initiative of JLABS—the no-strings-attached incubators of Johnson & Johnson Innovation—these contests spur scientific diversity through crowdsourcing, inspiring and attracting fresh thinking. They seek to stimulate the global innovation ecosystem through funding, mentorship and access to resources that can kick-start breakthrough ideas.

Our most recent challenge, the Next-Gen Baby Box QuickFire Challenge, focused on updating the 80-year-old “Finnish baby box,” a free, government-issued maternity supply kit for new parents containing such essentials as baby clothing, bath and sleep supplies packaged in a sleep-safe cardboard box. Since it first launched, the baby box has, together with increased use of maternal healthcare services early in pregnancy, helped to significantly reduce the Finnish infant mortality rate from 65 in every 1,000 live births in the 1930s to 2.5 per 1,000 today—one of the lowest rates in the world.

Partnering with Finnish innovation and government groups, we set out to see if updating this popular early parenting tool with the power of personalized health technology might one day impact Finland’s unparalleled high rate of type 1 diabetes. We issued the call globally to help create “the Baby Box of the future” as part of the Janssen and Johnson & Johnson Innovation vision to create a world without disease by accelerating science and delivering novel solutions to prevent, intercept and cure disease. The contest brought together entrepreneurs, researchers and innovators to focus on ideas with the potential to promote child health, detect childhood disease earlier and facilitate healthy parenting.

Incentive challenges like this award participants who have most effectively met a predefined objective or task. It’s a concept that emerged well before our time—as far back as the 18th century—from Napoleon’s Food Preservation Prize, meant to find a way to keep troops fed during battle, to the Longitude Prize for improved marine navigation.

Research shows that prize-based challenges that attract talent across a wide range of disciplines can generate greater risk-taking and yield more dramatic solutions….(More)”.

The Social Media Threat to Society and Security

Curated on Posted on by Stefaan Verhulst
George Soros at Project Syndicate: “It takes significant effort to assert and defend what John Stuart Mill called the freedom of mind. And there is a real chance that, once lost, those who grow up in the digital age – in which the power to command and shape people’s attention is increasingly concentrated in the hands of a few companies – will have difficulty regaining it.

The current moment in world history is a painful one. Open societies are in crisis, and various forms of dictatorships and mafia states, exemplified by Vladimir Putin’s Russia, are on the rise. In the United States, President Donald Trump would like to establish his own mafia-style state but cannot, because the Constitution, other institutions, and a vibrant civil society won’t allow it….

The rise and monopolistic behavior of the giant American Internet platform companies is contributing mightily to the US government’s impotence. These companies have often played an innovative and liberating role. But as Facebook and Google have grown ever more powerful, they have become obstacles to innovation, and have caused a variety of problems of which we are only now beginning to become aware…

Social media companies’ true customers are their advertisers. But a new business model is gradually emerging, based not only on advertising but also on selling products and services directly to users. They exploit the data they control, bundle the services they offer, and use discriminatory pricing to keep more of the benefits that they would otherwise have to share with consumers. This enhances their profitability even further, but the bundling of services and discriminatory pricing undermine the efficiency of the market economy.

Social media companies deceive their users by manipulating their attention, directing it toward their own commercial purposes, and deliberately engineering addiction to the services they provide. This can be very harmful, particularly for adolescents.

There is a similarity between Internet platforms and gambling companies. Casinos have developed techniques to hook customers to the point that they gamble away all of their money, even money they don’t have.

Something similar – and potentially irreversible – is happening to human attention in our digital age. This is not a matter of mere distraction or addiction; social media companies are actually inducing people to surrender their autonomy. And this power to shape people’s attention is increasingly concentrated in the hands of a few companies.

It takes significant effort to assert and defend what John Stuart Mill called the freedom of mind. Once lost, those who grow up in the digital age may have difficulty regaining it.

This would have far-reaching political consequences. People without the freedom of mind can be easily manipulated. This danger does not loom only in the future; it already played an important role in the 2016 US presidential election.

There is an even more alarming prospect on the horizon: an alliance between authoritarian states and large, data-rich IT monopolies, bringing together nascent systems of corporate surveillance with already-developed systems of state-sponsored surveillance. This may well result in a web of totalitarian control the likes of which not even George Orwell could have imagined….(More)”.

Observation and Experiment: An Introduction to Causal Inference

Curated on Posted on by Stefaan Verhulst

Book by Paul R. Rosenbaum: “In the daily news and the scientific literature, we are faced with conflicting claims about the effects caused by some treatments, behaviors, and policies. A daily glass of wine prolongs life, or so we are told. Yet we are also told that alcohol can cause life-threatening cancer and that pregnant women should abstain from drinking. Some say that raising the minimum wage decreases inequality while others say it increases unemployment. Investigators once confidently claimed that hormone replacement therapy reduces the risk of heart disease but today investigators confidently claim it raises that risk. How should we study such questions?

Observation and Experiment is an introduction to causal inference from one of the field’s leading scholars. Using minimal mathematics and statistics, Paul Rosenbaum explains key concepts and methods through scientific examples that make complex ideas concrete and abstract principles accessible.

Some causal questions can be studied in randomized trials in which coin flips assign individuals to treatments. But because randomized trials are not always practical or ethical, many causal questions are investigated in nonrandomized observational studies. To illustrate, Rosenbaum draws examples from clinical medicine, economics, public health, epidemiology, clinical psychology, and psychiatry. Readers gain an understanding of the design and interpretation of randomized trials, the ways they differ from observational studies, and the techniques used to remove, investigate, and appraise bias in observational studies. Observation and Experiment is a valuable resource for anyone with a serious interest in the empirical study of human health, behavior, and well-being….(More)”.

Free Speech in the Filter Age

Curated on Posted on by Stefaan Verhulst
Alexandra Borchardt at Project Syndicate: “In a democracy, the rights of the many cannot come at the expense of the rights of the few. In the age of algorithms, government must, more than ever, ensure the protection of vulnerable voices, even erring on victims’ side at times.

Germany’s Network Enforcement Act – according to which social-media platforms like Facebook and YouTube could be fined €50 million ($63 million) for every “obviously illegal” post within 24 hours of receiving a notification – has been controversial from the start. After it entered fully into effect in January, there was a tremendous outcry, with critics from all over the political map arguing that it was an enticement to censorship. Government was relinquishing its powers to private interests, they protested.

So, is this the beginning of the end of free speech in Germany?

Of course not. To be sure, Germany’s Netzwerkdurchsetzungsgesetz (or NetzDG) is the strictest regulation of its kind in a Europe that is growing increasingly annoyed with America’s powerful social-media companies. And critics do have some valid points about the law’s weaknesses. But the possibilities for free expression will remain abundant, even if some posts are deleted mistakenly.

The truth is that the law sends an important message: democracies won’t stay silent while their citizens are exposed to hateful and violent speech and images – content that, as we know, can spur real-life hate and violence. Refusing to protect the public, especially the most vulnerable, from dangerous content in the name of “free speech” actually serves the interests of those who are already privileged, beginning with the powerful companies that drive the dissemination of information.

Speech has always been filtered. In democratic societies, everyone has the right to express themselves within the boundaries of the law, but no one has ever been guaranteed an audience. To have an impact, citizens have always needed to appeal to – or bypass – the “gatekeepers” who decide which causes and ideas are relevant and worth amplifying, whether through the media, political institutions, or protest.

The same is true today, except that the gatekeepers are the algorithms that automatically filter and rank all contributions. Of course, algorithms can be programmed any way companies like, meaning that they may place a premium on qualities shared by professional journalists: credibility, intelligence, and coherence.

But today’s social-media platforms are far more likely to prioritize potential for advertising revenue above all else. So the noisiest are often rewarded with a megaphone, while less polarizing, less privileged voices are drowned out, even if they are providing the smart and nuanced perspectives that can truly enrich public discussions….(More)”.

Regulatory sandbox lessons learned report

Curated on Posted on by Stefaan Verhulst

Financial Conduct Authority (UK): “The sandbox allows firms to test innovative products, services or business models in a live market environment, while ensuring that appropriate protections are in place. It was established to support the FCA’s objective of promoting effective competition in the interests of consumers and opened for applications in June 2016.

The sandbox has supported 50 firms from 146 applications received across the first two cohorts. This report sets out the sandbox’s overall impact on the market including the adoption of new technologies, increasing access and improving experiences for vulnerable consumers as well as lessons learnt from individual tests that have been, or are being, conducted as part of the sandbox.

Early indications suggest the sandbox is providing the benefits it set out to achieve with evidence of the sandbox enabling new products to be tested, reducing time and cost of getting innovative ideas to market, improving access to finance for innovators, and ensuring appropriate safeguards are built into new products and services.

We will be using these learnings to inform any future sandbox developments as well as our ongoing policymaking and supervision work….(More)”.

Smarter New York City: How City Agencies Innovate

Curated on Posted on by Stefaan Verhulst

Book edited by André Corrêa d’Almeida: “Innovation is often presented as being in the exclusive domain of the private sector. Yet despite widespread perceptions of public-sector inefficiency, government agencies have much to teach us about how technological and social advances occur. Improving governance at the municipal level is critical to the future of the twenty-first-century city, from environmental sustainability to education, economic development, public health, and beyond. In this age of acceleration and massive migration of people into cities around the world, this book explains how innovation from within city agencies and administrations makes urban systems smarter and shapes life in New York City.
Using a series of case studies, Smarter New York City describes the drivers and constraints behind urban innovation, including leadership and organization; networks and interagency collaboration; institutional context; technology and real-time data collection; responsiveness and decision making; and results and impact. Cases include residential organic-waste collection, an NYPD program that identifies the sound of gunshots in real time, and the Vision Zero attempt to end traffic casualties, among others. Challenging the usefulness of a tech-centric view of urban innovation, Smarter New York City brings together a multidisciplinary and integrated perspective to imagine new possibilities from within city agencies, with practical lessons for city officials, urban planners, policy makers, civil society, and potential private-sector partners….(More)”.

Small Data for Big Impact

Curated on Posted on by Stefaan Verhulst

Liz Luckett at the Stanford Social Innovation Review: “As an investor in data-driven companies, I’ve been thinking a lot about my grandfather—a baker, a small business owner, and, I now realize, a pioneering data scientist. Without much more than pencil, paper, and extraordinarily deep knowledge of his customers in Washington Heights, Manhattan, he bought, sold, and managed inventory while also managing risk. His community was poor, but his business prospered. This was not because of what we celebrate today as the power and predictive promise of big data, but rather because of what I call small data: nuanced market insights that come through regular and trusted interactions.

Big data takes into account volumes of information from largely electronic sources—such as credit cards, pay stubs, test scores—and segments people into groups. As a result, people participating in the formalized economy benefit from big data. But people who are paid in cash and have no recognized accolades, such as higher education, are left out. Small data captures those insights to address this market failure. My grandfather, for example, had critical customer information he carefully gathered over the years: who could pay now, who needed a few days more, and which tabs to close. If he had access to a big data algorithm, it likely would have told him all his clients were unlikely to repay him, based on the fact that they were low income (vs. high income) and low education level (vs. college degree). Today, I worry that in our enthusiasm for big data and aggregated predictions, we often lose the critical insights we can gain from small data, because we don’t collect it. In the process, we are missing vital opportunities to both make money and create economic empowerment.

We won’t solve this problem of big data by returning to my grandfather’s shop floor. What we need is more and better data—a small data movement to supply vital missing links in marketplaces and supply chains the world over. What are the proxies that allow large companies to discern whom among the low income are good customers in the absence of a shopkeeper? At The Social Entrepreneurs’ Fund (TSEF), we are profitably investing in a new breed of data company: enterprises that are intentionally and responsibly serving low-income communities, and generating new and unique insights about the behavior of individuals in the process. The value of the small data they collect is becoming increasingly useful to other partners, including corporations who are willing to pay for it. It is a kind of dual market opportunity that for the first time makes it economically advantageous for these companies to reach the poor. We are betting on small data to transform opportunities and quality of life for the underserved, tap into markets that were once seen as too risky or too costly to reach, and earn significant returns for investors….(More)”.

How Universities Are Tackling Society’s Grand Challenges

Curated on Posted on by Stefaan Verhulst

Michelle Popowitz and Cristin Dorgelo in Scientific American: “…Universities embarking on Grand Challenge efforts are traversing new terrain—they are making commitments about research deliverables rather than simply committing to invest in efforts related to a particular subject. To mitigate risk, the universities that have entered this space are informally consulting with others regarding effective strategies, but the entire community would benefit from a more formal structure for identifying and sharing “what works.” To address this need, the new Community of Practice for University-Led Grand Challenges—launched at the October 2017 workshop—aims to provide peer support to leaders of university Grand Challenge programs, and to accelerate the adoption of Grand Challenge approaches at more universities supported by cross-sector partnerships.

The university community has identified extensive opportunities for collaboration on these Grand Challenge programs with other sectors:

  • Philanthropy can support the development of new Grand Challenge programs at more universities by establishing planning and administration grant programs, convening experts, and providing funding support for documenting these models through white papers and other publications and for evaluation of these programs over time.
  • Relevant associations and professional development organizations can host learning sessions about Grand Challenges for university leaders and professionals.
  • Companies can collaborate with universities on Grand Challenges research, act as sponsors and hosts for university-led programs and activities, and offer leaders, experts, and other personnel for volunteer advisory roles and tours of duties at universities.
  • Federal, State, and local governments and elected officials can provide support for collaboration among government agencies and offices and the research community on Grand Challenges.

Today’s global society faces pressing, complex challenges across many domains—including health, environment, and social justice. Science (including social sciences), technology, the arts, and humanities have critical roles to play in addressing these challenges and building a bright and prosperous future. Universities are hubs for discovery, building new knowledge, and changing understanding of the world. The public values the role universities play in education; yet as a sector, universities are less effective at highlighting their roles as the catalysts of new industries, homes for the fundamental science that leads to new treatments and products, or sources of the evidence on which policy decisions should be made.

By coming together as universities, collaborating with partners, and aiming for ambitious goals to address problems that might seem unsolvable, universities can show commitment to their communities and become beacons of hope….(More)”.

‘Epic Duck Challenge’ shows drones can outdo people at surveying wildlife

Curated on Posted on by Stefaan Verhulst

Jarrod Hodgson, Aleks Terauds and Lian Pin Koh in the Conversation:”Ecologists are increasingly using drones to gather data. Scientists have used remotely piloted aircraft to estimate the health of fragile polar mosses, to measure and predict the mass of leopard seals, and even to collect whale snot. Drones have also been labelled as game-changers for wildlife population monitoring.

But once the take-off dust settles, how do we know if drones produce accurate data? Perhaps even more importantly, how do the data compare to those gathered using a traditional ground-based approach?

To answer these questions we created the #EpicDuckChallenge, which involved deploying thousands of plastic replica ducks on an Adelaide beach, and then testing various methods of tallying them up.

As we report today in the journal Methods in Ecology and Evolution, drones do indeed generate accurate wildlife population data – even more accurate, in fact, than those collected the old-fashioned way.

Assessing the accuracy of wildlife count data is hard. We can’t be sure of the true number of animals present in a group of wild animals. So, to overcome this uncertainty, we created life-sized, replica seabird colonies, each with a known number of individuals.

From the optimum vantage and in ideal weather conditions, experienced wildlife spotters independently counted the colonies from the ground using binoculars and telescopes. At the same time, a drone captured photographs of each colony from a range of heights. Citizen scientists then used these images to tally the number of animals they could see.

Counts of birds in drone-derived imagery were better than those made by wildlife observers on the ground. The drone approach was more precise and more accurate – it produced counts that were consistently closer to the true number of individuals….(More)”.

An AI That Reads Privacy Policies So That You Don’t Have To

Curated on Posted on by Stefaan Verhulst

Andy Greenberg at Wired: “…Today, researchers at Switzerland’s Federal Institute of Technology at Lausanne (EPFL), the University of Wisconsin and the University of Michigan announced the release of Polisis—short for “privacy policy analysis”—a new website and browser extension that uses their machine-learning-trained app to automatically read and make sense of any online service’s privacy policy, so you don’t have to.

In about 30 seconds, Polisis can read a privacy policy it’s never seen before and extract a readable summary, displayed in a graphic flow chart, of what kind of data a service collects, where that data could be sent, and whether a user can opt out of that collection or sharing. Polisis’ creators have also built a chat interface they call Pribot that’s designed to answer questions about any privacy policy, intended as a sort of privacy-focused paralegal advisor. Together, the researchers hope those tools can unlock the secrets of how tech firms use your data that have long been hidden in plain sight….

Polisis isn’t actually the first attempt to use machine learning to pull human-readable information out of privacy policies. Both Carnegie Mellon University and Columbia have made their own attempts at similar projects in recent years, points out NYU Law Professor Florencia Marotta-Wurgler, who has focused her own research on user interactions with terms of service contracts online. (One of her own studies showed that only .07 percent of users actually click on a terms of service link before clicking “agree.”) The Usable Privacy Policy Project, a collaboration that includes both Columbia and CMU, released its own automated tool to annotate privacy policies just last month. But Marotta-Wurgler notes that Polisis’ visual and chat-bot interfaces haven’t been tried before, and says the latest project is also more detailed in how it defines different kinds of data. “The granularity is really nice,” Marotta-Wurgler says. “It’s a way of communicating this information that’s more interactive.”…(More)”.