New paper in Science: “Our society is increasingly relying on the digitized, aggregated opinions of others to make decisions. We therefore designed and analyzed a large-scale randomized experiment on a social news aggregation Web site to investigate whether knowledge of such aggregates distorts decision-making. Prior ratings created significant bias in individual rating behavior, and positive and negative social influences created asymmetric herding effects. Whereas negative social influence inspired users to correct manipulated ratings, positive social influence increased the likelihood of positive ratings by 32% and created accumulating positive herding that increased final ratings by 25% on average. This positive herding was topic-dependent and affected by whether individuals were viewing the opinions of friends or enemies. A mixture of changing opinion and greater turnout under both manipulations together with a natural tendency to up-vote on the site combined to create the herding effects. Such findings will help interpret collective judgment accurately and avoid social influence bias in collective intelligence in the future.”
See also: ‘Like’ This Article Online? Your Friends Will Probably Approve, Too, Scientists Say
The Power of Us: The Art and Science of Enlightened Citizen Engagement and Collective Action
New e-book: “Anita Estell has done it! She has published an easy-to-read handbook that promises to transform our individual and collective understanding of the federal government, how it really works, and most important, our own relevance in its operation. The Power of US is a must-have guide. It provides instruction for those possessing the audacity to seize the opportunities unfolding during one of the most transformational periods in American history. Estell shares insights, experiences, wisdom, and expertise, gained in more than twenty years of working at the federal level, in a way that not only invites and supports constructive engagement but also sheds light on the way forward. Estell provides an extraordinary panorama of information and instruction, melding a multidisciplinary suite of principles that underscore and bring texture to what Estell calls citizen-centricity, or citizen-centric engagement. The Power of US provides a profoundly creative approach relevant to policymakers and advocates. Estell’s treatment is a breath of fresh air in civic discourse—which can be stifled by stale approaches and potentially toxic hyperpartisan dynamics. In The Power of US, Estell establishes herself as a revolutionary thinker exhibiting the vision, knowledge, and personal power to move the compass of individual hope in the direction of collective freedom.”
A much-maligned engine of innovation
Review by Martin Wolf of The Entrepreneurial State: Debunking Public vs Private Sector Myths, by Mariana Mazzucato, Anthem Press: “…what determines innovation? Conventional economics offers abstract models; conventional wisdom insists the answer lies with private entrepreneurship. In this brilliant book, Mariana Mazzucato, a Sussex university professor of economics who specialises in science and technology, argues that the former is useless and the latter incomplete. Yes, innovation depends on bold entrepreneurship. But the entity that takes the boldest risks and achieves the biggest breakthroughs is not the private sector; it is the much-maligned state…
Why is the state’s role so important? The answer lies in the huge uncertainties, time spans and costs associated with fundamental, science-based innovation. Private companies cannot and will not bear these costs, partly because they cannot be sure to reap the fruits and partly because these fruits lie so far in the future.
Indeed, the more competitive and finance-driven the economy, the less the private sector will be willing to bear such risks. Buying back shares is apparently a far more attractive way of using surplus cash than spending on fundamental innovation. The days of AT&T’s path-breaking Bell Labs are long gone. In any case, the private sector could not have created the internet or GPS. Only the US military had the resources to do so.
Arguably, the most important engines of innovation in the past five decades have been the US Defense Advanced Research Projects Agency and the NIH. Today, if the world is to make fundamental breakthroughs in energy technologies, states will play a big role. Indeed, the US government even helped drive the development of the hydraulic fracturing of shale rock.”
Empirically Informed Regulation
Paper by Cass Sunstein: “In recent years, social scientists have been incorporating empirical findings about human behavior into economic models. These findings offer important insights for thinking about regulation and its likely consequences. They also offer some suggestions about the appropriate design of effective, low-cost, choice-preserving approaches to regulatory problems, including disclosure requirements, default rules, and simplification. A general lesson is that small, inexpensive policy initiatives can have large and highly beneficial effects. In the United States, a large number of recent practices and reforms reflect an appreciation of this lesson. They also reflect an understanding of the need to ensure that regulations have strong empirical foundations, both through careful analysis of costs and benefits in advance and through retrospective review of what works and what does not.”
A Videogame That Recruits Players to Map the Brain
Wired: “I’m no neuroscientist, and yet, here I am at my computer attempting to reconstruct a neural circuit of a mouse’s retina. It’s not quite as difficult and definitely not as boring as it sounds. In fact, it’s actually pretty fun, which is a good thing considering I’m playing a videogame.
Called EyeWire, the browser-based game asks players to map the connections between retinal neurons by coloring in 3-D slices of the brain. Much like any other game out there, being good at EyeWire earns you points, but the difference is that the data you produce during gameplay doesn’t just get you on a leader board—it’s actually used by scientists to build a better picture of the human brain.
Created by neuroscientist Sebastian Seung’s lab at MIT, EyeWire basically gamifies the professional research Seung and his collaborators do on a daily basis. Seung is studying the connectome, the hyper-complex tangle of connections among neurons in the brain.”
Can We Build A Kickstarter For Cancer?
Paul Howard in Forbes: “tarting you own band, writing your first novel, or re-publishing your favorite ‘80s tabletop RPG are all cool goals. You can do them all on Kickstarter. What would be cooler?
How about funding a virtual biotech company with one goal: Saving or extending the life of a cancer patient who doesn’t respond to “standard of care” treatments….
The Cancer Commons approach – a distributed framework for empowering patients and learning from every patient/treatment combination – breaks down traditional distinctions between clinical trials and patient treatment in the “real world.” Instead of developing treatments in a lab and then testing them on randomized patients in clinical trials (designed to benefit future patients), researchers would apply the latest scientific knowledge and tools to help each patient achieve the best possible outcome today based on what we know – or think we can predict – about a molecular subtype of cancer….
We’ll need more than money to power a Kickstarter-for-cancer movement. We’ll need to encourage companies – from Big Pharma to “small” biotechs – to participate in distributed, Bayesian trials where new biomarkers or combinations of biomarkers are tested in patients with particular molecular profiles. And the FDA is going to have to be convinced that the system is going to generate high quality data that benefits patients, not sell them snake-oil cures.
In return for companies making their compound libraries and experimental drugs available for the “virtual biotechs” launched by cancer patients and their families, there should be a regulatory path established to take the most promising drugs and drug combinations to market.”
How to do scientific research without even trying (much)
Ars Technica: “To some extent, scientific research requires expensive or specialized equipment—some work just requires a particle accelerator or a virus containment facility. But plenty of other research has very simple requirements: a decent camera, a bit of patience, or being in the right place at the right time. Since that sort of work is open to anyone, getting the public involved can be a huge win for scientists, who can then obtain much more information than they could have gathered on their own.
A group of Spanish researchers has now written an article that is a mixture of praise for this sort of citizen science, a resource list for people hoping to get involved, and a how-to guide for anyone inspired to join in. The researchers focus on their own area of interest—insects, specifically the hemiptera or “true bugs”—but a lot of what they say applies to other areas of research.
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The paper also lists a variety of regional-specific sites that focus on insect identification and tracking, such as ones for the UK, Belgium, and Slovenia. But a dedicated system isn’t required for this sort of resource. In the researchers’ home base on the Iberian Peninsula, insects are tracked via a Flickr group. (If you’re interested in insect research and based in the US, you can also find dozens of projects at the SciStarter site.) We’ve uploaded some of the most amazing images into a gallery that accompanies this article.
ZooKeys, 2013. DOI: 10.3897/zookeys.319.4342 “
The Power of Hackathons
Woodrow Wilson International Center for Scholars: “The Commons Lab of the Science and Technology Innovation Program is proud to announce the release of The Power of Hackathons: A Roadmap for Sustainable Open Innovation. Hackathons are collaborative events that have long been part of programmer culture, where people gather in person, online or both to work together on a problem. This could involve creating an application, improving an existing one or testing a platform.
In recent years, government agencies at multiple levels have started holding hackathon events of their own. For this brief, author Zachary Bastian interviewed agency staff, hackathon planners and hackathon participants to better understand how these events can be structured. The fundamental lesson was that a hackathon is not a panacea, but instead should be part of a broader open data and innovation centric strategy.
The full brief can be found here”
Why you should never trust a data visualisation
John Burn-Murdoch in The Guardian: “An excellent blogpost has been receiving a lot of attention over the last week. Pete Warden, an experienced data scientist and author for O’Reilly on all things data, writes:
The wonderful thing about being a data scientist is that I get all of the credibility of genuine science, with none of the irritating peer review or reproducibility worries … I thought I was publishing an entertaining view of some data I’d extracted, but it was treated like a scientific study.
This is an important acknowledgement of a very real problem, but in my view Warden has the wrong target in his crosshairs. Data presented in any medium is a powerful tool and must be used responsibly, but it is when information is expressed visually that the risks are highest.
The central example Warden uses is his visualisation of Facebook friend networks across the United States, which proved extremely popular and was even cited in the New York Times as evidence for growing social division.
As he explains in his post, the methodology behind his underlying network graph is perfectly defensible, but the subsequent clustering process was “produced by me squinting at all the lines, coloring in some areas that seemed more connected in a paint program, and picking silly names for the areas”. The exercise was only ever intended as a bit of fun with a large and interesting dataset, so there really shouldn’t be any problem here.
But there is: humans are visual creatures. Peer-reviewed studies have shown that we can consume information more quickly when it is expressed in diagrams than when it is presented as text.
Even something as simple as colour scheme can have a marked impact on the perceived credibility of information presented visually – often a considerably more marked impact than the actual authority of the data source.
Another great example of this phenomenon was the Washington Post’s ‘map of the world’s most and least racially tolerant countries‘, which went viral back in May of this year. It was widely accepted as an objective, scientific piece of work, despite a number of social scientists identifying flaws in the methodology and the underlying data itself.”
Data Science for Social Good
Data Science for Social Good: “By analyzing data from police reports to website clicks to sensor signals, governments are starting to spot problems in real-time and design programs to maximize impact. More nonprofits are measuring whether or not they’re helping people, and experimenting to find interventions that work.
None of this is inevitable, however.
We’re just realizing the potential of using data for social impact and face several hurdles to it’s widespread adoption:
- Most governments and nonprofits simply don’t know what’s possible yet. They have data – but often not enough and maybe not the right kind.
- There are too few data scientists out there – and too many spending their days optimizing ads instead of bettering lives.
To make an impact, we need to show social good organizations the power of data and analytics. We need to work on analytics projects that have high social impact. And we need to expose data scientists to the problems that really matter.
The fellowship
That’s exactly why we’re doing the Eric and Wendy Schmidt Data Science for Social Good summer fellowship at the University of Chicago.
We want to bring three dozen aspiring data scientists to Chicago, and have them work on data science projects with social impact.
Working closely with governments and nonprofits, fellows will take on real-world problems in education, health, energy, transportation, and more.
Over the next three months, they’ll apply their coding, machine learning, and quantitative skills, collaborate in a fast-paced atmosphere, and learn from mentors in industry, academia, and the Obama campaign.
The program is led by a strong interdisciplinary team from the Computation institute and the Harris School of Public Policy at the University of Chicago.”