Info We Trust: How to Inspire the World with Data

Curated on Posted on by Stefaan Verhulst

Book by R.J. Andrews: “How do we create new ways of looking at the world? Join award-winning data storyteller RJ Andrews as he pushes beyond the usual how-to, and takes you on an adventure into the rich art of informing.

Creating Info We Trust is a craft that puts the world into forms that are strong and true.  It begins with maps, diagrams, and charts — but must push further than dry defaults to be truly effective. How do we attract attention? How can we offer audiences valuable experiences worth their time? How can we help people access complexity?

Dark and mysterious, but full of potential, data is the raw material from which new understanding can emerge. Become a hero of the information age as you learn how to dip into the chaos of data and emerge with new understanding that can entertain, improve, and inspire. Whether you call the craft data storytelling, data visualization, data journalism, dashboard design, or infographic creation — what matters is that you are courageously confronting the chaos of it all in order to improve how people see the world. Info We Trust is written for everyone who straddles the domains of data and people: data visualization professionals, analysts, and all who are enthusiastic for seeing the world in new ways.

This book draws from the entirety of human experience, quantitative and poetic. It teaches advanced techniques, such as visual metaphor and data transformations, in order to create more human presentations of data.  It also shows how we can learn from print advertising, engineering, museum curation, and mythology archetypes. This human-centered approach works with machines to design information for people. Advance your understanding beyond by learning from a broad tradition of putting things “in formation” to create new and wonderful ways of opening our eyes to the world….(More)”.

Artificial Unintelligence: How Computers Misunderstand the World

Curated on Posted on by Stefaan Verhulst

Book by Meredith Broussard where she “…argues that our collective enthusiasm for applying computer technology to every aspect of life has resulted in a tremendous amount of poorly designed systems. We are so eager to do everything digitally—hiring, driving, paying bills, even choosing romantic partners—that we have stopped demanding that our technology actually work. Broussard, a software developer and journalist, reminds us that there are fundamental limits to what we can (and should) do with technology. With this book, she offers a guide to understanding the inner workings and outer limits of technology—and issues a warning that we should never assume that computers always get things right.

Making a case against technochauvinism—the belief that technology is always the solution—Broussard argues that it’s just not true that social problems would inevitably retreat before a digitally enabled Utopia. To prove her point, she undertakes a series of adventures in computer programming. She goes for an alarming ride in a driverless car, concluding “the cyborg future is not coming any time soon”; uses artificial intelligence to investigate why students can’t pass standardized tests; deploys machine learning to predict which passengers survived the Titanic disaster; and attempts to repair the U.S. campaign finance system by building AI software. If we understand the limits of what we can do with technology, Broussard tells us, we can make better choices about what we should do with it to make the world better for everyone….(More)”.

AI is sending people to jail—and getting it wrong

Curated on Posted on by Stefaan Verhulst

Karen Hao atMIT Technology Review : “Using historical data to train risk assessment tools could mean that machines are copying the mistakes of the past. …

AI might not seem to have a huge personal impact if your most frequent brush with machine-learning algorithms is through Facebook’s news feed or Google’s search rankings. But at the Data for Black Lives conference last weekend, technologists, legal experts, and community activists snapped things into perspective with a discussion of America’s criminal justice system. There, an algorithm can determine the trajectory of your life. The US imprisons more people than any other country in the world. At the end of 2016, nearly 2.2 million adults were being held in prisons or jails, and an additional 4.5 million were in other correctional facilities. Put another way, 1 in 38 adult Americans was under some form of correctional supervision. The nightmarishness of this situation is one of the few issues that unite politicians on both sides of the aisle. Under immense pressure to reduce prison numbers without risking a rise in crime, courtrooms across the US have turned to automated tools in attempts to shuffle defendants through the legal system as efficiently and safely as possible. This is where the AI part of our story begins….(More)”.

Machine Learning and the Rule of Law

Curated on Posted on by Stefaan Verhulst

Paper by Daniel L. Chen: “Predictive judicial analytics holds the promise of increasing the fairness of law. Much empirical work observes inconsistencies in judicial behavior. By predicting judicial decisions—with more or less accuracy depending on judicial attributes or case characteristics—machine learning offers an approach to detecting when judges most likely to allow extra legal biases to influence their decision making. In particular, low predictive accuracy may identify cases of judicial “indifference,” where case characteristics (interacting with judicial attributes) do no strongly dispose a judge in favor of one or another outcome. In such cases, biases may hold greater sway, implicating the fairness of the legal system….(More)”

Can I Trust the Data I See? A Physician’s Concern on Medical Data in IoT Health Architectures

Curated on Posted on by Stefaan Verhulst

Conference Paper by Fariha Tasmin Jaigirdar, Carsten Rudolph, and Chris Bain: “With the increasing advancement of Internet of Things (IoT) enabled systems, smart medical devices open numerous opportunities for the healthcare sector. The success of using such devices in the healthcare industry depends strongly on secured and reliable medical data transmission. Physicians diagnose that data and prescribe medicines and/or give guidelines/instructions/treatment plans for the patients. Therefore, a physician is always concerned about the medical data trustworthiness, because if it is not guaranteed, a savior can become an involuntary foe! This paper analyses two different scenarios to understand the real-life consequences in IoT-based healthcare (IoT-Health) application. Appropriate sequence diagrams for both scenarios show data movement as a basis for determining necessary security requirements in each layer of IoT-Health.

We analyse the individual entities of the overall system and develop a system-wide view of trust in IoT-Health. The security analysis pinpoints the research gap in end-to-end trust and indicates the necessity to treat the whole IoT-Health system as an integrated entity. This study highlights the importance of integrated cross-layer security solutions that can deal with the heterogeneous security architectures of IoT healthcare system and finally identifies a possible solution for the open question raised in the security analysis with appropriate future research directions….(More)”.

The Urban Commons: How Data and Technology Can Rebuild Our Communities

Curated on Posted on by Stefaan Verhulst

Book by Daniel T. O’Brien: “The future of smart cities has arrived, courtesy of citizens and their phones. To prove it, Daniel T. O’Brien explains the transformative insights gleaned from years researching Boston’s 311 reporting system, a sophisticated city management tool that has revolutionized how ordinary Bostonians use and maintain public spaces. Through its phone service, mobile app, website, and Twitter account, 311 catalogues complaints about potholes, broken street lights, graffiti, litter, vandalism, and other issues that are no one citizen’s responsibility but affect everyone’s quality of life. The Urban Commons offers a pioneering model of what modern digital data and technology can do for cities like Boston that seek both prosperous growth and sustainability.

Analyzing a rich trove of data, O’Brien discovers why certain neighborhoods embrace the idea of custodianship and willingly invest their time to monitor the city’s common environments and infrastructure. On the government’s side of the equation, he identifies best practices for implementing civic technologies that engage citizens, for deploying public services in collaborative ways, and for utilizing the data generated by these efforts.

Boston’s 311 system has narrowed the gap between residents and their communities, and between constituents and local leaders. The result, O’Brien shows, has been the creation of more effective policy and practices that reinvigorate the way citizens and city governments approach their mutual interests. By unpacking when, why, and how the 311 system has worked for Boston, The Urban Commons reveals the power and potential of this innovative system, and the lessons learned that other cities can adapt…(More)”.

A Survey on Sentiment Analysis

Curated on Posted on by Stefaan Verhulst

Paper by Siva Parvathi and Yjn Lakshmi: “Sentiment analysis or Opinion mining is one of the quickest developing fields with its call for and potential advantages growing every day. With the onset of the internet and modern technology, there has been a vigorous growth in the quantity of statistics. Each character is capable of specific his/her personal ideas freely on social media. All of this facts may be analyzed and used that allows you to draw benefits and high-quality statistics.

One such idea is sentiment analysis, here, the sentiment of the problem is taken into consideration and important facts is drawn out whether it be a product evaluation or his/her opinion on whatever materialistic. A few of such packages of sentiment evaluation and the method in which they’re carried out are defined. Moreover,the possibility of every of those works to impact any destiny work is considered and explained along with the analysis as to how the previous troubles in the equal area have been overcome….(More)”.

Blockchain Economics

Curated on Posted on by Stefaan Verhulst

NBER Working Paper by Joseph Abadi and Markus Brunnermeier: “When is record-keeping better arranged through a blockchain than through a traditional centralized intermediary? The ideal qualities of any record-keeping system are (i) correctness, (ii) decentralization, and (iii) cost efficiency. We point out a blockchain trilemma: no ledger can satisfy all three properties simultaneously.

A centralized record-keeper extracts rents due to its monopoly on the ledger. Its franchise value dynamically incentivizes correct reporting. Blockchains drive down rents by allowing for free entry of record-keepers and portability of information to competing “forks.” Blockchains must, therefore, provide static incentives for correctness through computationally expensive proof-of-work algorithms and permit record-keepers to roll back history in order to undo fraudulent reports. While blockchains can keep track of ownership transfers, enforcement of possession rights is often better complemented by centralized record-keeping….(More)”

Looking after and using data for public benefit

Curated on Posted on by Stefaan Verhulst

Heather Savory at the Office for National Statistics (UK): “Official Statistics are for the benefit of society and the economy and help Britain to make better decisions. They allow the formulation of better public policy and the effective measurement of those policies. They inform the direction of economic and commercial activities. They provide valuable information for analysts, researchers, public and voluntary bodies. They enable the public to hold organisations that spend public money to account, thus informing democratic debate.

The ability to harness the power of data is critical in enabling official statistics to support the most important decisions facing the country.

Under the new powers in the Digital Economy Act , ONS can now gain access to new and different sources of data including ‘administrative’ data from government departments and commercial data. Alongside the availability of these new data sources ONS is experiencing a strong demand for ad hoc insights alongside our traditional statistics.

We need to deliver more, faster, finer-grained insights into the economy and society. We need to deliver high quality, trustworthy information, on a faster timescale, to help decision-making. We will increasingly develop innovative data analysis methods, for example using images to gain insight from the work we’ve recently announced on Urban Forests….

I should explain here that our data is not held in one big linked database; we’re architecting our Data Access Platform so that data can be linked in different ways for different purposes. This is designed to preserve data confidentiality, so only the necessary subset of data is accessible by authorised people, for a certain purpose. To avoid compromising their effectiveness, we do not make public the specific details of the security measures we have in place, but our recently tightened security regime, which is independently assured by trusted external bodies, includes:

  • physical measures to restrict who can access places where data is stored;
  • protective measures for all data-related IT services;
  • measures to restrict who can access systems and data held by ONS;
  • controls to guard against staff or contractors misusing their legitimate access to data; including vetting to an appropriate level for the sensitivity of data to which they might have access.

One of the things I love about working in the public sector is that our work can be shared openly.

We live in a rapidly changing and developing digital world and we will continue to monitor and assess the data standards and security measures in place to ensure they remain strong and effective. So, as well as sharing this work openly to reassure all our data suppliers that we’re taking good care of their data, we’re also seeking feedback on our revised data policies.

The same data can provide different insights when viewed through different lenses or in different combinations. The more data is shared – with the appropriate safeguards of course – the more it has to give.

If you work with data, you’ll know that collaborating with others in this space is key and that we need to be able to share data more easily when it makes sense to do so. So, the second reason for sharing this work openly is that, if you’re in the technical space, we’d value your feedback on our approach and if you’re in the data space and would like to adopt the same approach, we’d love to support you with that – so that we can all share data more easily in the future….(More)

ONS’s revised policies on the use, management and security of data can befound here.

New mathematical model can help save endangered species

Curated on Posted on by Stefaan Verhulst

Blogpost by Majken Brahe and Ellegaard Christensen: “What does the blue whale have in common with the Bengal tiger and the green turtle? They share the risk of extinction and are classified as endangered species. There are multiple reasons for species to die out, and climate changes is among the main reasons.

The risk of extinction varies from species to species depending on how individuals in its populations reproduce and how long each animal survives. Understanding the dynamics of survival and reproduction can support management actions to improve a specie’s chances of surviving.

Mathematical and statistical models have become powerful tools to help explain these dynamics. However, the quality of the information we use to construct such models is crucial to improve our chances of accurately predicting the fate of populations in nature.

Colchero’s research focuses on mathematically recreating the population dynamics by better understanding the species’s demography. He works on constructing and exploring stochastic population models that predict how a certain population (for example an endangered species) will change over time.

These models include mathematical factors to describe how the species’ environment, survival rates and reproduction determine to the population’s size and growth. For practical reasons some assumptions are necessary.

Two commonly accepted assumptions are that survival and reproduction are constant with age, and that high survival in the species goes hand in hand with reproduction across all age groups within a species. Colchero challenged these assumptions by accounting for age-specific survival and reproduction, and for trade-offs between survival and reproduction. This is, that sometimes conditions that favor survival will be unfavorable for reproduction, and vice versa.

For his work Colchero used statistics, mathematical derivations, and computer simulations with data from wild populations of 24 species of vertebrates. The outcome was a significantly improved model that had more accurate predictions for a species’ population growth.

Despite the technical nature of Fernando’s work, this type of model can have very practical implications as they provide qualified explanations for the underlying reasons for the extinction. This can be used to take management actions and may help prevent extinction of endangered species….(More)”