The Emergence of a Post-Fact World

Curated on Posted on by Stefaan Verhulst

Francis Fukuyama in Project Syndicate: “One of the more striking developments of 2016 and its highly unusual politics was the emergence of a “post-fact” world, in which virtually all authoritative information sources were called into question and challenged by contrary facts of dubious quality and provenance.

The emergence of the Internet and the World Wide Web in the 1990s was greeted as a moment of liberation and a boon for democracy worldwide. Information constitutes a form of power, and to the extent that information was becoming cheaper and more accessible, democratic publics would be able to participate in domains from which they had been hitherto excluded.

The development of social media in the early 2000s appeared to accelerate this trend, permitting the mass mobilization that fueled various democratic “color revolutions” around the world, from Ukraine to Burma (Myanmar) to Egypt. In a world of peer-to-peer communication, the old gatekeepers of information, largely seen to be oppressive authoritarian states, could now be bypassed.

While there was some truth to this positive narrative, another, darker one was also taking shape. Those old authoritarian forces were responding in dialectical fashion, learning to control the Internet, as in China, with its tens of thousands of censors, or, as in Russia, by recruiting legions of trolls and unleashing bots to flood social media with bad information. These trends all came together in a hugely visible way during 2016, in ways that bridged foreign and domestic politics….

The traditional remedy for bad information, according to freedom-of-information advocates, is simply to put out good information, which in a marketplace of ideas will rise to the top. This solution, unfortunately, works much less well in a social-media world of trolls and bots. There are estimates that as many as a third to a quarter of Twitter users fall into this category. The Internet was supposed to liberate us from gatekeepers; and, indeed, information now comes at us from all possible sources, all with equal credibility. There is no reason to think that good information will win out over bad information….

The inability to agree on the most basic facts is the direct product of an across-the-board assault on democratic institutions – in the US, in Britain, and around the world. And this is where the democracies are headed for trouble. In the US, there has in fact been real institutional decay, whereby powerful interest groups have been able to protect themselves through a system of unlimited campaign finance. The primary locus of this decay is Congress, and the bad behavior is for the most part as legal as it is widespread. So ordinary people are right to be upset.

And yet, the US election campaign has shifted the ground to a general belief that everything has been rigged or politicized, and that outright bribery is rampant. If the election authorities certify that your favored candidate is not the victor, or if the other candidate seemed to perform better in a debate, it must be the result of an elaborate conspiracy by the other side to corrupt the outcome. The belief in the corruptibility of all institutions leads to a dead end of universal distrust. American democracy, all democracy, will not survive a lack of belief in the possibility of impartial institutions; instead, partisan political combat will come to pervade every aspect of life….(More)”

The social data revolution will be crowdsourced

Curated on Posted on by Stefaan Verhulst

Nicholas B. Adams at SSRC Parameters: “It is now abundantly clear to librarians, archivists, computer scientists, and many social scientists that we are in a transformational age. If we can understand and measure meaning from all of these data describing so much of human activity, we will finally be able to test and revise our most intricate theories of how the world is socially constructed through our symbolic interactions….

We cannot write enough rules to teach a computer to read like us. And because the social world is not a game per se, we can’t design a reinforcement-learning scenario teaching a computer to “score points” and just ‘win.’ But AlphaGo’s example does show a path forward. Recall that much of AlphaGo’s training came in the form of supervised machine learning, where humans taught it to play like them by showing the machine how human experts played the game. Already, humans have used this same supervised learning approach to teach computers to classify images, identify parts of speech in text, or categorize inventories into various bins. Without writing any rules, simply by letting the computer guess, then giving it human-generated feedback about whether it guessed right or wrong, humans can teach computers to label data as we do. The problem is (or has been): humans label textual data slowly—very, very slowly. So, we have generated precious little data with which to teach computers to understand natural language as we do. But that is going to change….

The single greatest factor dilating the duration of such large-scale text-labeling projects has been workforce training and turnover. ….The key to organizing work for the crowd, I had learned from talking to computer scientists, was task decomposition. The work had to be broken down into simple pieces that any (moderately intelligent) person could do through a web interface without requiring face-to-face training. I knew from previous experiments with my team that I could not expect a crowd worker to read a whole article, or to know our whole conceptual scheme defining everything of potential interest in those articles. Requiring either or both would be asking too much. But when I realized that my conceptual scheme could actually be treated as multiple smaller conceptual schemes, the idea came to me: Why not have my RAs identify units of text that corresponded with the units of analysis of my conceptual scheme? Then, crowd workers reading those much smaller units of text could just label them according to a smaller sub-scheme. Moreover, I came to realize, we could ask them leading questions about the text to elicit information about the variables and attributes in the scheme, so they wouldn’t have to memorize the scheme either. By having them highlight the words justifying their answers, they would be labeling text according to our scheme without any face-to-face training. Bingo….

This approach promises more, too. The databases generated by crowd workers, citizen scientists, and students can also be used to train machines to see in social data what we humans see comparatively easily. Just as AlphaGo learned from humans how to play a strategy game, our supervision can also help it learn to see the social world in textual or video data. The final products of social data analysis assembly lines, therefore, are not merely rich and massive databases allowing us to refine our most intricate, elaborate, and heretofore data-starved theories; they are also computer algorithms that will do most or all social data labeling in the future. In other words, whether we know it or not, we social scientists hold the key to developing artificial intelligences capable of understanding our social world….

At stake is a social science with the capacity to quantify and qualify so many of our human practices, from the quotidian to mythic, and to lead efforts to improve them. In decades to come, we may even be able to follow the path of other mature sciences (including physics, biology, and chemistry) and shift our focus toward engineering better forms of sociality. All the more so because it engages the public, a crowd-supported social science could enlist a new generation in the confident and competent re-construction of society….(More)”

The Power of Networks: Six Principles That Connect Our Lives

Curated on Posted on by Stefaan Verhulst

Book by Christopher Brinton and Mung Chiang: “What makes WiFi faster at home than at a coffee shop? How does Google order search results? Why do Amazon, Netflix, and YouTube use fundamentally different rating and recommendation methods—and why does it matter? Is it really true that everyone on Facebook is connected in six steps or less? And how do cat videos—or anything else—go viral? The Power of Networks answers questions like these for the first time in a way that all of us can understand and use, whether at home, the office, or school. Using simple language, analogies, stories, hundreds of illustrations, and no more math than simple addition and multiplication, Christopher Brinton and Mung Chiang provide a smart but accessible introduction to the handful of big ideas that drive the technical and social networks we use every day—from cellular phone networks and cloud computing to the Internet and social media platforms.

The Power of Networks unifies these ideas through six fundamental principles of networking, which explain the difficulties in sharing network resources efficiently, how crowds can be wise or not so wise depending on the nature of their connections, how there are many building-blocks of layers in a network, and more. Understanding these simple ideas unlocks the workings of everything from the connections we make on Facebook to the technology that runs such platforms. Along the way, the authors also talk with and share the special insights of renowned experts such as Google’s Eric Schmidt, former Verizon Wireless CEO Dennis Strigl, and “fathers of the Internet” Vint Cerf and Bob Kahn….(More)”

Governing with Collective Intelligence

Curated on Posted on by Stefaan Verhulst

Tom Saunders and Geoff Mulgan at Nesta: “This paper provides an introduction to collective intelligence in government. It aims to be useful and relevant to governments of countries at very different levels of development. It highlights the ways in which governments are better understanding the world around them, drawing on ideas and expertise from their citizens, and encouraging greater scrutiny of their actions.

Collective intelligence is a new term to describe something which is in some respects old, but in other respects changing dramatically thanks to advances in digital technologies. It refers to the ability of large groups – a community, region, city or nation – to think and act intelligently in a way that amounts to more than the sum of their parts.

Key findings

Our analysis of government use of collective intelligence initiatives around the world finds that activities fall into four broad categories:

1. Better understanding facts and experiences: using new digital tools to gather data from many more sources.

2. Better development of options and ideas: tapping into the collective brainpower of citizens to come up with better ideas and options for action.

3. Better, more inclusive decision-making: involving citizens in decision making, from policymaking to planning and budgeting.

4. Better oversight of what is done: encouraging broader involvement in the oversight of government activity, from monitoring corruption to scrutinising budgets, helping to increase accountability and transparency….(More)”

#Republic: Divided Democracy in the Age of Social Media

Curated on Posted on by Stefaan Verhulst

Book by Cass Sunstein: “As the Internet grows more sophisticated, it is creating new threats to democracy. Social media companies such as Facebook can sort us ever more efficiently into groups of the like-minded, creating echo chambers that amplify our views. It’s no accident that on some occasions, people of different political views cannot even understand each other. It’s also no surprise that terrorist groups have been able to exploit social media to deadly effect.

Welcome to the age of #Republic.

In this revealing book, Cass Sunstein, the New York Times bestselling author of Nudge and The World According to Star Wars, shows how today’s Internet is driving political fragmentation, polarization, and even extremism—and what can be done about it.

Thoroughly rethinking the critical relationship between democracy and the Internet, Sunstein describes how the online world creates “cybercascades,” exploits “confirmation bias,” and assists “polarization entrepreneurs.” And he explains why online fragmentation endangers the shared conversations, experiences, and understandings that are the lifeblood of democracy.

In response, Sunstein proposes practical and legal changes to make the Internet friendlier to democratic deliberation. These changes would get us out of our information cocoons by increasing the frequency of unchosen, unplanned encounters and exposing us to people, places, things, and ideas that we would never have picked for our Twitter feed.

#Republic need not be an ironic term. As Sunstein shows, it can be a rallying cry for the kind of democracy that citizens of diverse societies most need….(More)”

The Signal Code

Curated on Posted on by Stefaan Verhulst

The Signal Code: “Humanitarian action adheres to the core humanitarian principles of impartiality, neutrality, independence, and humanity, as well as respect for international humanitarian and human rights law. These foundational principles are enshrined within core humanitarian doctrine, particularly the Red Cross/NGO Code of Conduct5 and the Humanitarian Charter.6 Together, these principles establish a duty of care for populations affected by the actions of humanitarian actors and impose adherence to a standard of reasonable care for those engaged in humanitarian action.

Engagement in HIAs, including the use of data and ICTs, must be consistent with these foundational principles and respect the human rights of crisis-affected people to be considered “humanitarian.” In addition to offering potential benefits to those affected by crisis, HIAs, including the use of ICTs, can cause harm to the safety, wellbeing, and the realization of the human rights of crisis-affected people. Absent a clear understanding of which rights apply to this context, the utilization of new technologies, and in particular experimental applications of these technologies, may be more likely to harm communities and violate the fundamental human rights of individuals.

The Signal Code is based on the application of the UDHR, the Nuremberg Code, the Geneva Convention, and other instruments of customary international law related to HIAs and the use of ICTs by crisis affected-populations and by humanitarians on their behalf. The fundamental human rights undergirding this Code are the rights to life, liberty, and security; the protection of privacy; freedom of expression; and the right to share in scientific advancement and its benefits as expressed in Articles 3, 12, 19, and 27 of the UDHR.7

The Signal Code asserts that all people have fundamental rights to access, transmit, and benefit from information as a basic humanitarian need; to be protected from harms that may result from the provision of information during crisis; to have a reasonable expectation of privacy and data security; to have agency over how their data is collected and used; and to seek redress and rectification when data pertaining to them causes harm or is inaccurate.

These rights are found to apply specifically to the access, collection, generation, processing, use, treatment, and transmission of information, including data, during humanitarian crises. These rights are also found herein to be interrelated and interdependent. To realize any of these rights individually requires realization of all of these rights in concert.

These rights are found to apply to all phases of the data lifecycle—before, during, and after the collection, processing, transmission, storage, or release of data. These rights are also found to be elastic, meaning that they apply to new technologies and scenarios that have not yet been identified or encountered by current practice and theory.

Data is, formally, a collection of symbols which function as a representation of information or knowledge. The term raw data is often used with two different meanings, the first being uncleaned data, that is, data that has been collected in an uncontrolled environment, and unprocessed data, which is collected data that has not been processed in such a way as to make it suitable for decision making. Colloquially, and in the humanitarian context, data is usually thought of solely in the machine readable or digital sense. For the purposes of the Signal Code, we use the term data to encompass information both in its analog and digital representations. Where it is necessary to address data solely in its digital representation, we refer to it as digital data.

No right herein may be used to abridge any other right. Nothing in this code may be interpreted as giving any state, group, or person the right to engage in any activity or perform any act that destroys the rights described herein.

The five human rights that exist specific to information and HIAs during humanitarian crises are the following:

The Right to Information
The Right to Protection
The Right to Data Security and Privacy
The Right to Data Agency
The Right to Redress and Rectification…(More)”

Artificial Intelligence “Jolted by Success”

Curated on Posted on by Stefaan Verhulst

Steven Aftergood in SecrecyNews: “Since 2010, the field of artificial intelligence (AI) has been “jolted” by the “broad and unforeseen successes” of one of its component technologies, known as multi-layer neural networks, leading to rapid developments and new applications, according to a new study from the JASON scientific advisory panel.

The JASON panel reviewed the current state of AI research and its potential use by the Department of Defense. See Perspectives on Research in Artificial Intelligence and Artificial General Intelligence Relevant to DoD, JSR-16-Task-003, January 2017….

The JASON report distinguishes between artificial intelligence — referring to the ability of computers to perform particular tasks that humans do with their brains — and artificial general intelligence (AGI) — meaning a human-like ability to pursue long-term goals and exercise purposive behavior.

“Where AI is oriented around specific tasks, AGI seeks general cognitive abilities.” Recent progress in AI has not been matched by comparable advances in AGI. Sentient machines, let alone a revolt of robots against their creators, are still somewhere far over the horizon, and may be permanently in the realm of fiction.

While many existing DoD weapon systems “have some degree of ‘autonomy’ relying on the technologies of AI, they are in no sense a step–not even a small step–towards ‘autonomy’ in the sense of AGI, that is, the ability to set independent goals or intent,” the JASONs said.

“Indeed, the word ‘autonomy’ conflates two quite different meanings, one relating to ‘freedom of will or action’ (like humans, or as in AGI), and the other the much more prosaic ability to act in accordance with a possibly complex rule set based on possibly complex sensor input, as in the word ‘automatic’. In using a terminology like ‘autonomous weapons’, the DoD may, as an unintended consequence, enhance the public’s confusion on this point.”…

This week the Department of Defense announced the demonstration of swarms of “autonomous” micro-drones. “The micro-drones demonstrated advanced swarm behaviors such as collective decision-making, adaptive formation flying, and self-healing,” according to a January 9 news release.

A journalistic account of recent breakthroughs in the use of artificial intelligence for machine translation appeared in the New York Times Magazine last month. See “The Great A.I. Awakening” by Gideon Lewis-Kraus, December 14, 2016…(More)”

Crowdsourcing, Citizen Science, and Data-sharing

Curated on Posted on by Stefaan Verhulst

Sapien Labs: “The future of human neuroscience lies in crowdsourcing, citizen science and data sharing but it is not without its minefields.

A recent Scientific American article by Daniel Goodwin, “Why Neuroscience Needs Hackers,” makes the case that neuroscience, like many fields today, is drowning in data, begging for application of advances in computer science like machine learning. Neuroscientists are able to gather realms of neural data, but often without big data mechanisms and frameworks to synthesize them.

The SA article describes the work of Sebastian Seung, a Princeton neuroscientist, who recently mapped the neural connections of the human retina from an “overwhelming mass” of electron microscopy data using state of the art A.I. and massive crowd-sourcing. Seung incorporated the A.I. into a game called “Eyewire” where 1,000s of volunteers scored points while improving the neural map.   Although the article’s title emphasizes advanced A.I., Dr. Seung’s experiment points even more to crowdsourcing and open science, avenues for improving research that have suddenly become easy and powerful with today’s internet. Eyewire perhaps epitomizes successful crowdsourcing — using an application that gathers, represents, and analyzes data uniformly according to researchers’ needs.

Crowdsourcing is seductive in its potential but risky for those who aren’t sure how to control it to get what they want. For researchers who don’t want to become hackers themselves, trying to turn the diversity of data produced by a crowd into conclusive results might seem too much of a headache to make it worthwhile. This is probably why the SA article title says we need hackers. The crowd is there but using it depends on innovative software engineering. A lot of researchers could really use software designed to flexibly support a diversity of crowdsourcing, some AI to enable things like crowd validation and big data tools.

The Potential

The SA article also points to Open BCI (brain-computer interface), mentioned here in other posts, as an example of how traditional divisions between institutional and amateur (or “citizen”) science are now crumbling; Open BCI is a community of professional and citizen scientists doing principled research with cheap, portable EEG-headsets producing professional research quality data. In communities of “neuro-hackers,” like NeurotechX, professional researchers, entrepreneurs, and citizen scientists are coming together to develop all kinds of applications, such as “telepathic” machine control, prostheses, and art. Other companies, like Neurosky sell EEG headsets and biosensors for bio-/neuro-feedback training and health-monitoring at consumer affordable pricing. (Read more in Citizen Science and EEG)

Tan Le, whose company Emotiv Lifesciences, also produces portable EEG head-sets, says, in an article in National Geographic, that neuroscience needs “as much data as possible on as many brains as possible” to advance diagnosis of conditions such as epilepsy and Alzheimer’s. Human neuroscience studies have typically consisted of 20 to 50 participants, an incredibly small sampling of a 7 billion strong humanity. For a single lab to collect larger datasets is difficult but with diverse populations across the planet real understanding may require data not even from thousands of brains but millions. With cheap mobile EEG-headsets, open-source software, and online collaboration, the potential for anyone can participate in such data collection is immense; the potential for crowdsourcing unprecedented. There are, however, significant hurdles to overcome….(More)”

Prisoners use VR programme as a rehabilitation tool

Curated on Posted on by Stefaan Verhulst

Springwise: “The global prison population currently totals 10.5 million, and while many countries including the UK and US have seen a steady decline in crime rates over the past decade, the rate of reoffending prisoners has increased. About two-thirds of released prisoners in the US are rearrested within three years of release, and about three-quarters of released prisoners were rearrested within five. Virtual Rehab is a new project that seeks to rehabilitate inmates using VR technology.

Virtual Rehab’s interactive tool includes education on a broad range of themes, from family violence and sexual offences to psychological challenges including mental & emotional disorders. The programme works by placing the prisoner into interactive role play scenarios which reverse the aggressor / victim roles, propelling the prisoner into the skin of an assaulted person with the aim of developing empathy. The programme also includes formal education and vocational job training, developing professional skills to help ex-offenders thrive in the real world. …

Virtual reality has already had an impact in various areas related to rehabilitation, including in the treatment of conditions such as PTSD and anxiety. At Springwise, we recently covered two programmes (a glove and an online platform) that use online gaming to support the recovery of patients….(More)”

Rule by the lowest common denominator? It’s baked into democracy’s design

Curated on Posted on by Stefaan Verhulst

 in The Conversation: “The Trump victory, and the general disaster for Democrats this year, was the victory of ignorance, critics moan.

Writing in Foreign Policy, Georgetown’s Jason Brennan called it “the dance of the dunces” and wrote that “Trump owes his victory to the uninformed.”…

For liberals, Trump’s victory was the triumph of prejudice, bigotry and forces allied against truth and expertise in politics, science and culture at large. Trump brandishes unconcern for traditional political wisdom and protocol – much less facts – like a badge of honor, and his admirers roar with glee. His now famous rallies, the chastened media report, are often scary, sometimes giving way to violence, sometimes threatening to spark broader recriminations and social mayhem. This is a glimpse of how tyrants rise to power, some political minds worry; this is how tyrants enlist the support of rabid masses, and get them to do their bidding.

For the contemporary French philosopher Jacques Rancière, however, the Trump victory provides a useful reminder of the essential nature of democracy – a reminder of what precisely makes it vibrant. And liable to lapse into tyranny at once….

Democracy is rule by the rabble, in Plato’s view. It is the rule by the lowest common denominator. In a democracy, passions are inflamed and proliferate. Certain individuals may take advantage of and channel the storm of ignorance, Plato feared, and consolidate power out of a desire to serve their own interests.

As Rancière explains, there is a “scandal of democracy” for Plato: The best and the high born “must bow before the law of chance” and submit to the rule of the inexpert, the commoner, who knows little about politics or much else.

Merit ought to decide who rules, in Plato’s account. But democracy consigns such logic to the dustbin. The rabble may decide they want to be ruled by one of their own – and electoral conditions may favor them. Democracy makes it possible that someone who has no business ruling lands at the top. His rule may prove treacherous, and risk dooming the state. But, Rancière argues, this is a risk democracies must take. Without it, they lack legitimacy….

Rancière maintains people more happily suffer authority ascribed by chance than authority consigned by birth, merit or expertise. Liberals may be surprised about this last point. According to Rancière, expertise is no reliable, lasting or secure basis for authority. In fact, expertise soon loses authority, and with it, the legitimacy of the state. Why?…(More)”