The Role of Big Data Analytics in Predicting Suicide

Curated on Posted on by Stefaan Verhulst

Chapter by Ronald C. Kessler et al: “…reviews the long history of using electronic medical records and other types of big data to predict suicide. Although a number of the most recent of these studies used machine learning (ML) methods, these studies were all suboptimal both in the features used as predictors and in the analytic approaches used to develop the prediction models. We review these limitations and describe opportunities for making improvements in future applications.

We also review the controversy among clinical experts about using structured suicide risk assessment tools (be they based on ML or older prediction methods) versus in-depth clinical evaluations of needs for treatment planning. Rather than seeing them as competitors, we propose integrating these different approaches to capitalize on their complementary strengths. We also emphasize the distinction between two types of ML analyses: those aimed at predicting which patients are at highest suicide risk, and those aimed at predicting the treatment options that will be best for individual patients. We explain why both are needed to optimize the value of big data ML methods in addressing the suicide problem….(More)”.

See also How Search Engine Data Enhance the Understanding of Determinants of Suicide in India and Inform Prevention: Observational Study.

Rescuing Human Rights: A Radically Moderate Approach

Curated on Posted on by Stefaan Verhulst

Book by Hurst Hannum: “The development of human rights norms is one of the most significant achievements in international relations and law since 1945, but the continuing influence of human rights is increasingly being questioned by authoritarian governments, nationalists, and pundits. Unfortunately, the proliferation of new rights, linking rights to other issues such as international crimes or the activities of business, and attempting to address every social problem from a human rights perspective risk undermining their credibility.

Rescuing Human Rights calls for understanding ‘human rights’ as international human rights law and maintaining the distinctions between binding legal obligations on governments and broader issues of ethics, politics, and social change. Resolving complex social problems requires more than simplistic appeals to rights, and adopting a ‘radically moderate’ approach that recognizes both the potential and the limits of international human rights law, offers the best hope of preserving the principle that we all have rights, simply because we are human….(More)”.

Shutting down the internet doesn’t work – but governments keep doing it

Curated on Posted on by Stefaan Verhulst

George Ogola in The Conversation: “As the internet continues to gain considerable power and agency around the world, many governments have moved to regulate it. And where regulation fails, some states resort to internet shutdowns or deliberate disruptions.

The statistics are staggering. In India alone, there were 154 internet shutdowns between January 2016 and May 2018. This is the most of any country in the world.

But similar shutdowns are becoming common on the African continent. Already in 2019 there have been shutdowns in Cameroon, the Democratic Republic of Congo, Republic of Congo, Chad, Sudan and Zimbabwe. Last year there were 21 such shutdowns on the continent. This was the case in Togo, Sierra Leone, Sudan and Ethiopia, among others.

The justifications for such shutdowns are usually relatively predictable. Governments often claim that internet access is blocked in the interest of public security and order. In some instances, however, their reasoning borders on the curious if not downright absurd, like the case of Ethiopia in 2017 and Algeria in 2018 when the internet was shut down apparently to curb cheating in national examinations.

Whatever their reasons, governments have three general approaches to controlling citzens’ access to the web.

How they do it

Internet shutdowns or disruptions usually take three forms. The first and probably the most serious is where the state completely blocks access to the internet on all platforms. It’s arguably the most punitive, with significant social, economic and political costs.

The financial costs can run into millions of dollars for each day the internet is blocked. A Deloitte report on the issue estimates that a country with average connectivity could lose at least 1.9% of its daily GDP for each day all internet services are shut down.

For countries with average to medium level connectivity the loss is 1% of daily GDP, and for countries with average to low connectivity it’s 0.4%. It’s estimated that Ethiopia, for example, could lose up to US$500,000 a day whenever there is a shutdown. These shutdowns, then, damage businesses, discourage investments, and hinder economic growth.

The second way that governments restrict internet access is by applying content blocking techniques. They restrict access to particular sites or applications. This is the most common strategy and it’s usually targeted at social media platforms. The idea is to stop or limit conversations on these platforms.

Online spaces have become the platform for various forms of political expression that many states especially those with authoritarian leanings consider subversive. Governments argue, for example, that social media platforms encourage the spread of rumours which can trigger public unrest.

This was the case in 2016 in Uganda during the country’s presidential elections. The government restricted access to social media, describing the shutdown as a “security measure to avert lies … intended to incite violence and illegal declaration of election results”.

In Zimbabwe, the government blocked social media following demonstrations over an increase in fuel prices. It argued that the January 2019 ban was because the platforms were being “used to coordinate the violence”.

The third strategy, done almost by stealth, is the use of what is generally known as “bandwidth throttling”. In this case telecom operators or internet service providers are forced to lower the quality of their cell signals or internet speed. This makes the internet too slow to use. “Throttling” can also target particular online destinations such as social media sites….(More)”

Responsible AI for conservation

Curated on Posted on by Stefaan Verhulst

Oliver Wearn, RobinFreeman and David Jacoby in Nature: “Machine learning (ML) is revolutionizing efforts to conserve nature. ML algorithms are being applied to predict the extinction risk of thousands of species, assess the global footprint of fisheries, and identify animals and humans in wildlife sensor data recorded in the field. These efforts have recently been given a huge boost with support from the commercial sector. New initiatives, such as Microsoft’s AI for Earth and Google’s AI for Social Good, are bringing new resources and new ML tools to bear on some of the biggest challenges in conservation. In parallel to this, the open data revolution means that global-scale, conservation-relevant datasets can be fed directly to ML algorithms from open data repositories, such as Google Earth Engine for satellite data or Movebank for animal tracking data. Added to these will be Wildlife Insights, a Google-supported platform for hosting and analysing wildlife sensor data that launches this year. With new tools and a proliferation of data comes a bounty of new opportunities, but also new responsibilities….(More)”

Weather Service prepares to launch prediction model many forecasters don’t trust

Curated on Posted on by Stefaan Verhulst

Jason Samenow in the Washington Post: “In a month, the National Weather Service plans to launch its “next generation” weather prediction model with the aim of “better, more timely forecasts.” But many meteorologists familiar with the model fear it is unreliable.

The introduction of a model that forecasters lack confidence in matters, considering the enormous impact that weather has on the economy, valued at around $485 billion annually.

The Weather Service announced Wednesday that the model, known as the GFS-FV3 (FV3 stands for Finite­ Volume Cubed-Sphere dynamical core), is “tentatively” set to become the United States’ primary forecast model on March 20, pending tests. It is an update to the current version of the GFS (Global Forecast System), popularly known as the American model, which has existed in various forms for more than 30 years….

A concern is that if forecasters cannot rely on the FV3, they will be left to rely only on the European model for their predictions without a credible alternative for comparisons. And they’ll also have to pay large fees for the European model data. Whereas model data from the Weather Service is free, the European Center for Medium-Range Weather Forecasts, which produces the European model, charges for access.

But there is an alternative perspective, which is that forecasters will just need to adjust to the new model and learn to account for its biases. That is, a little short-term pain is worth the long-term potential benefits as the model improves….

The Weather Service’s parent agency, the National Oceanic and Atmospheric Administration, recently entered an agreement with the National Center for Atmospheric Research to increase collaboration between forecasters and researchers in improving forecast modeling.

In addition, President Trump recently signed into law the Weather Research and Forecast Innovation Act Reauthorization, which establishes the NOAA Earth Prediction Innovation Center, aimed at further enhancing prediction capabilities. But even while NOAA develops relationships and infrastructure to improve the Weather Service’s modeling, the question remains whether the FV3 can meet the forecasting needs of the moment. Until the problems identified are addressed, its introduction could represent a step back in U.S. weather prediction despite a well-intended effort to leap forward….(More).

Dirty Data, Bad Predictions: How Civil Rights Violations Impact Police Data, Predictive Policing Systems, and Justice

Curated on Posted on by Stefaan Verhulst

Paper by Rashida Richardson, Jason Schultz, and Kate Crawford: “Law enforcement agencies are increasingly using algorithmic predictive policing systems to forecast criminal activity and allocate police resources. Yet in numerous jurisdictions, these systems are built on data produced within the context of flawed, racially fraught and sometimes unlawful practices (‘dirty policing’). This can include systemic data manipulation, falsifying police reports, unlawful use of force, planted evidence, and unconstitutional searches. These policing practices shape the environment and the methodology by which data is created, which leads to inaccuracies, skews, and forms of systemic bias embedded in the data (‘dirty data’). Predictive policing systems informed by such data cannot escape the legacy of unlawful or biased policing practices that they are built on. Nor do claims by predictive policing vendors that these systems provide greater objectivity, transparency, or accountability hold up. While some systems offer the ability to see the algorithms used and even occasionally access to the data itself, there is no evidence to suggest that vendors independently or adequately assess the impact that unlawful and bias policing practices have on their systems, or otherwise assess how broader societal biases may affect their systems.

In our research, we examine the implications of using dirty data with predictive policing, and look at jurisdictions that (1) have utilized predictive policing systems and (2) have done so while under government commission investigations or federal court monitored settlements, consent decrees, or memoranda of agreement stemming from corrupt, racially biased, or otherwise illegal policing practices. In particular, we examine the link between unlawful and biased police practices and the data used to train or implement these systems across thirteen case studies. We highlight three of these: (1) Chicago, an example of where dirty data was ingested directly into the city’s predictive system; (2) New Orleans, an example where the extensive evidence of dirty policing practices suggests an extremely high risk that dirty data was or will be used in any predictive policing application, and (3) Maricopa County where despite extensive evidence of dirty policing practices, lack of transparency and public accountability surrounding predictive policing inhibits the public from assessing the risks of dirty data within such systems. The implications of these findings have widespread ramifications for predictive policing writ large. Deploying predictive policing systems in jurisdictions with extensive histories of unlawful police practices presents elevated risks that dirty data will lead to flawed, biased, and unlawful predictions which in turn risk perpetuating additional harm via feedback loops throughout the criminal justice system. Thus, for any jurisdiction where police have been found to engage in such practices, the use of predictive policing in any context must be treated with skepticism and mechanisms for the public to examine and reject such systems are imperative….(More)”.

Democracy Beyond Voting and Protests

Curated on Posted on by Stefaan Verhulst

Sasha Fisher at Project Syndicate: “For over a decade now, we have witnessed more elections and, simultaneously, less democracy. According to Bloomberg, elections have been occurring more frequently around the world. Yet Freedom House finds that some 110 countries have experienced declines in political and civil rights over the past 13 years.

As democracy declines, so does our sense of community. In the United States, this is evidenced by a looming loneliness epidemicand the rapid disappearance of civic institutions such as churches, eight of which close every day. And though these trends are global in nature, the US exemplifies them in the extreme.

This is no coincidence. As Alexis de Tocqueville pointed out in the 1830s, America’s founders envisioned a country governed not by shared values, but by self-interest. That vision has since defined America’s institutions, and fostered a hyper-individualistic society.

Growing distrust in governing institutions has fueled a rise in authoritarian populist movements around the world. Citizens are demanding individual economic security and retreating into an isolationist mentality. ...

And yet we know that “user engagement” works, as shown by countless studies and human experiences. For example, an evaluation conducted in Uganda found that the more citizens participated in the design of health programs, the more the perception of the health-care system improved. And in Indonesia, direct citizen involvement in government decision-making has led to higher satisfaction with government services....

While the Western world suffers from over-individualization, the most notable governance and economic innovations are taking place in the Global South. In Rwanda, for example, the government has introduced policies to encourage grassroots solutions that strengthen citizens’ sense of community and shared accountability. Through monthly community-service meetings, families and individuals work together to build homes for the needy, fix roads, and pool funds to invest in better farming practices and equipment.

Imagine if over 300 million Americans convened every month for a similar purpose. There would suddenly be billions more citizen hours invested in neighbor-to-neighbor interaction and citizen action.

This was one of the main effects of the Village Savings and Loan Associations that originated in the Democratic Republic of Congo. Within communities, members have access to loans to start small businesses and save for a rainy day. The model works because it leverages neighbor-to-neighbor accountability. Likewise, from Haiti to Liberia to Burundi and beyond, community-based health systems have proven effective precisely because health workers know their neighbors and their needs. Community health workers go from home to home, checking in on pregnant mothers and making sure they are cared for. Each of these solutions uses and strengthens communal accountability through shared engagement – not traditional vertical accountability lines.

If we believe in the democratic principle that governments must be accountable to citizens, we should build systems that hold us accountable to each other – and we must engage beyond elections and protests. We must usher in a new era of community-driven democracy – power must be decentralized and placed in the hands of families and communities.

When we achieve community-driven democracy, we will engage with one another and with our governments – not just on special occasions, but continuously, because our democracy and freedom depend on us….(More)” (See also Index on Trust in Institutions)

Technology and National Security

Curated on Posted on by Stefaan Verhulst

Book from the Aspen Strategy Group: “This edition is a collection of papers commissioned for the 2018 Aspen Strategy Group Summer Workshop, a bipartisan meeting of national security experts, academics, private sector leaders, and technologists. The chapters in this volume evaluate the disruptive nature of technological change on the US military, economic power, and democratic governance. They highlight possible avenues for US defense modernization, the impact of disinformation tactics and hybrid warfare on democratic institutions, and the need for a reinvigorated innovation triangle comprised of the US government, academia, and private corporations. The executive summary offers practical recommendations to meet the daunting challenges this technological era imposes….(More)”.

Congress needs your input (but don’t call it crowdsourcing)

Curated on Posted on by Stefaan Verhulst

Lorelei Kelly at TechCrunch: “As it stands, Congress does not have the technical infrastructure to ingest all this new input in any systematic way. Individual members lack a method to sort and filter signal from noise or trusted credible knowledge from malicious falsehood and hype.

What Congress needs is curation, not just more information

Curation means discovering, gathering and presenting content. This word is commonly thought of as the job of librarians and museums, places we go to find authentic and authoritative knowledge. Similarly, Congress needs methods to sort and filter information as required within the workflow of lawmaking. From personal offices to committees, members and their staff need context and informed judgement based on broadly defined expertise. The input can come from individuals or institutions. It can come from the wisdom of colleagues in Congress or across the federal government. Most importantly, it needs to be rooted in local constituents and it needs to be trusted.

It is not to say that crowdsourcing is unimportant for our governing system. But input methods that include digital must demonstrate informed and accountable deliberative methods over time. Governing is the curation part of democracy. Governing requires public review, understanding of context, explanation and measurements of value for the nation as a whole. We are already thinking about how to create an ethical blockchain. Why not the same attention for our most important democratic institution?

Governing requires trade-offs that elicit emotion and sometimes anger. But as in life, emotions require self-regulation. In Congress, this means compromise and negotiation. In fact, one of the reasons Congress is so stuck is that its own deliberative process has declined at every level. Besides the official committee process stalling out, members have few opportunities to be together as colleagues, and public space is increasingly antagonistic and dangerous.

With so few options, members are left with blunt communications objects like clunky mail management systems and partisan talking points. This means that lawmakers don’t use public input for policy formation as much as to surveil public opinion.

Any path forward to the 21st century must include new methods to (1) curate and hear from the public in a way that informs policy AND (2) incorporate real data into a results-driven process.

While our democracy is facing unprecedented stress, there are bright spots. Congress is again dedicating resources to an in-house technologyassessment capacity. Earlier this month, the new 116th Congress created a Select Committee on the Modernization of Congress. It will be chaired by Rep. Derek Kilmer (D-WA). Then the Open Government Data Actbecame law. This law will potentially scale the level of access to government data to unprecedented levels. It will require that all public-facing federal data must be machine-readable and reusable. This is a move in the right direction, and now comes the hard part.

Marci Harris, the CEO of civic startup Popvox, put it well, “The Foundations for Evidence-Based Policymaking (FEBP) Act, which includes the OPEN Government Data Act, lays groundwork for a more effective, accountable government. To realize the potential of these new resources, Congress will need to hire tech literate staff and incorporate real data and evidence into its oversight and legislative functions.”

In forsaking its own capacity for complex problem solving, Congress has become non-competitive in the creative process that moves society forward. During this same time period, all eyes turned toward Silicon Valley to fill the vacuum. With mass connection platforms and unlimited personal freedom, it seemed direct democracy had arrived. But that’s proved a bust. If we go by current trends, entrusting democracy to Silicon Valley will give us perfect laundry and fewer voting rights. Fixing democracy is a whole-of-nation challenge that Congress must lead.

Finally, we “the crowd” want a more effective governing body that incorporates our experience and perspective into the lawmaking process, not just feel-good form letters thanking us for our input. We also want a political discourse grounded in facts. A “modern” Congress will provide both, and now we have the institutional foundation in place to make it happen….(More)”.

Achieving Digital Permanence

Curated on Posted on by Stefaan Verhulst

Raymond Blum with Betsy Beyer at ACM Queu: “Digital permanence has become a prevalent issue in society. This article focuses on the forces behind it and some of the techniques to achieve a desired state in which “what you read is what was written.” While techniques that can be imposed as layers above basic data stores—blockchains, for example—are valid approaches to achieving a system’s information assurance guarantees, this article won’t discuss them.

First, let’s define digital permanence and the more basic concept of data integrity.

Data integrity is the maintenance of the accuracy and consistency of stored information. Accuracy means that the data is stored as the set of values that were intended. Consistency means that these stored values remain the same over time—they do not unintentionally waver or morph as time passes.

Digital permanence refers to the techniques used to anticipate and then meet the expected lifetime of data stored in digital media. Digital permanence not only considers data integrity, but also targets guarantees of relevance and accessibility: the ability to recall stored data and to recall it with predicted latency and at a rate acceptable to the applications that require that information.

To illustrate the aspects of relevance and accessibility, consider two counterexamples: journals that were safely stored redundantly on Zip drives or punch cards may as well not exist if the hardware required to read the media into a current computing system isn’t available. Nor is it very useful to have receipts and ledgers stored on a tape medium that will take eight days to read in when you need the information for an audit on Thursday.

The Multiple Facets of Digital Permanence

Human memory is the most subjective record imaginable. Common adages and clichés such as “He said, she said,” “IIRC (If I remember correctly),” and “You might recall” recognize the truth of memories—that they are based only on fragments of the one-time subjective perception of any objective state of affairs. What’s more, research indicates that people alter their memories over time. Over the years, as the need to provide a common ground for actions based on past transactions arises, so does the need for an objective record of fact—an independent “true” past. These records must be both immutable to a reasonable degree and durable. Media such as clay tablets, parchment, photographic prints, and microfiche became popular because they satisfied the “write once, read many” requirement of society’s record keepers.

Information storage in the digital age has evolved to fit the scale of access (frequent) and volume (high) by moving to storage media that record and deliver information in an almost intangible state. Such media have distinct advantages: electrical impulses and the polarity of magnetized ferric compounds can be moved around at great speed and density. These media, unfortunately, also score higher in another measure: fragility. Paper and clay can survive large amounts of neglect and punishment, but a stray electromagnetic discharge or microscopic rupture can render a digital library inaccessible or unrecognizable.

It stands to reason that storing permanent records in some immutable and indestructible medium would be ideal—something that, once altered to encode information, could never be altered again, either by an overwrite or destruction. Experience shows that such ideals are rarely realized; with enough force and will, the hardest stone can be broken and the most permanent markings defaced.

In considering and ensuring digital permanence, you want to guard against two different failures: the destruction of the storage medium, and a loss of the integrity or “truthfulness” of the records….(More)”.