How Tech Utopia Fostered Tyranny

Curated on Posted on by Stefaan Verhulst

Jon Askonas at The New Atlantis: “The rumors spread like wildfire: Muslims were secretly lacing a Sri Lankan village’s food with sterilization drugs. Soon, a video circulated that appeared to show a Muslim shopkeeper admitting to drugging his customers — he had misunderstood the question that was angrily put to him. Then all hell broke loose. Over a several-day span, dozens of mosques and Muslim-owned shops and homes were burned down across multiple towns. In one home, a young journalist was trapped, and perished.

Mob violence is an old phenomenon, but the tools encouraging it, in this case, were not. As the New York Times reported in April, the rumors were spread via Facebook, whose newsfeed algorithm prioritized high-engagement content, especially videos. “Designed to maximize user time on site,” as the Times article describes, the newsfeed algorithm “promotes whatever wins the most attention. Posts that tap into negative, primal emotions like anger or fear, studies have found, produce the highest engagement, and so proliferate.” On Facebook in Sri Lanka, posts with incendiary rumors had among the highest engagement rates, and so were among the most highly promoted content on the platform. Similar cases of mob violence have taken place in India, Myanmar, Mexico, and elsewhere, with misinformation spread mainly through Facebook and the messaging tool WhatsApp.

Follow The New AtlantisThis is in spite of Facebook’s decision in January 2018 to tweak its algorithm, apparently to prevent the kind of manipulation we saw in the 2016 U.S. election, when posts and election ads originating from Russia reportedly showed up in newsfeeds of up to 126 million American Facebook users. The company explained that the changes to its algorithm will mean that newsfeeds will be “showing more posts from friends and family and updates that spark conversation,” and “less public content, including videos and other posts from publishers or businesses.” But these changes, which Facebook had tested out in countries like Sri Lanka in the previous year, may actually have exacerbated the problem — which is that incendiary content, when posted by friends and family, is guaranteed to “spark conversation” and therefore to be prioritized in newsfeeds. This is because “misinformation is almost always more interesting than the truth,” as Mathew Ingram provocatively put it in the Columbia Journalism Review.

How did we get here, from Facebook’s mission to “give people the power to build community and bring the world closer together”? Riot-inducing “fake news” and election meddling are obviously far from what its founders intended for the platform. Likewise, Google’s founders surely did not build their search engine with the intention of its being censored in China to suppress free speech, and yet, after years of refusing this demand from Chinese leadership, Google has recently relented rather than pull their search engine from China entirely. And YouTube’s creators surely did not intend their feature that promotes “trending” content to help clickbait conspiracy-theory videos go viral.

These outcomes — not merely unanticipated by the companies’ founders but outright opposed to their intentions — are not limited to social media. So far, Big Tech companies have presented issues of incitement, algorithmic radicalization, and “fake news” as merely bumps on the road of progress, glitches and bugs to be patched over. In fact, the problem goes deeper, to fundamental questions of human nature. Tools based on the premise that access to information will only enlighten us and social connectivity will only make us more humane have instead fanned conspiracy theories, information bubbles, and social fracture. A tech movement spurred by visions of libertarian empowerment and progressive uplift has instead fanned a global resurgence of populism and authoritarianism.

Despite the storm of criticism, Silicon Valley has still failed to recognize in these abuses a sharp rebuke of its sunny view of human nature. It remains naïvely blind to how its own aspirations for social engineering are on a spectrum with the tools’ “unintended” uses by authoritarian regimes and nefarious actors….(More)”.

Index: Trust in Institutions 2019

Curated on Posted on by Michelle Winowatan

By Michelle Winowatan, Andrew J. Zahuranec, Andrew Young, Stefaan Verhulst

The Living Library Index – inspired by the Harper’s Index – provides important statistics and highlights global trends in governance innovation. This installment focuses on trust in institutions.

Please share any additional, illustrative statistics on open data, or other issues at the nexus of technology and governance, with us at [email protected]

Global Trust in Public Institutions

Trust in Government

United States

  • Americans who say their democracy is working at least “somewhat well:” 58% – 2018
  • Number who believe sweeping changes to their government are needed: 61% – 2018
  • Percentage of Americans expressing faith in election system security: 45% – 2018
  • Percentage of Americans expressing an overarching trust in government: 40% – 2019
  • How Americans would rate the trustworthiness of Congress: 4.1 out of 10 – 2017
  • Number who have confidence elected officials act in the best interests of the public: 25% – 2018
  • Amount who trust the federal government to do what is right “just about always or most of the time”: 18% – 2017
  • Americans with trust and confidence in the federal government to handle domestic problems: 2 in 5 – 2018
    • International problems: 1 in 2 – 2018
  • US institution with highest amount of confidence to act in the best interests of the public: The Military (80%) – 2018
  • Most favorably viewed level of government: Local (67%) – 2018
  • Most favorably viewed federal agency: National Park Service (83% favorable) – 2018
  • Least favorable federal agency: Immigration and Customs Enforcement (47% unfavorable) – 2018

United Kingdom

  • Overall trust in government: 42% – 2019
    • Number who think the country is headed in the “wrong direction:” 7 in 10 – 2018
    • Those who have trust in politicians: 17% – 2018
    • Amount who feel unrepresented in politics: 61% – 2019
    • Amount who feel that their standard of living will get worse over the next year: Nearly 4 in 10 – 2019
  • Trust the national government handling of personal data:

European Union

Africa

Latin America

Other

Trust in Media

  • Percentage of people around the world who trust the media: 47% – 2019
    • In the United Kingdom: 37% – 2019
    • In the United States: 48% – 2019
    • In China: 76% – 2019
  • Rating of news trustworthiness in the United States: 4.5 out of 10 – 2017
  • Number of citizens who trust the press across the European Union: Almost 1 in 2 – 2019
  • France: 3.9 out of 10 – 2019
  • Germany: 4.8 out of 10 – 2019
  • Italy: 3.8 out of 10 – 2019
  • Slovenia: 3.9 out of 10 – 2019
  • Percentage of European Union citizens who trust the radio: 59% – 2017
    • Television: 51% – 2017
    • The internet: 34% – 2017
    • Online social networks: 20% – 2017
  • EU citizens who do not actively participate in political discussions on social networks because they don’t trust online social networks: 3 in 10 – 2018
  • Those who are confident that the average person in the United Kingdom can tell real news from ‘fake news’: 3 in 10 – 2018

Trust in Business

Sources

Artificial Intelligence and National Security

Curated on Posted on by Stefaan Verhulst

Report by Congressional Research Service: “Artificial intelligence (AI) is a rapidly growing field of technology with potentially significant implications for national security. As such, the U.S. Department of Defense (DOD) and other nations are developing AI applications for a range of military functions. AI research is underway in the fields of intelligence collection and analysis, logistics, cyber operations, information operations, command and control, and in a variety of semi-autonomous and autonomous vehicles.

Already, AI has been incorporated into military operations in Iraq and Syria. Congressional action has the potential to shape the technology’s development further, with budgetary and legislative decisions influencing the growth of military applications as well as the pace of their adoption.

AI technologies present unique challenges for military integration, particularly because the bulk of AI development is happening in the commercial sector. Although AI is not unique in this regard, the defense acquisition process may need to be adapted for acquiring emerging technologies like AI.

In addition, many commercial AI applications must undergo significant modification prior to being functional for the military. A number of cultural issues also challenge AI acquisition, as some commercial AI companies are averse to partnering with DOD due to ethical concerns, and even within the department, there can be resistance to incorporating AI technology into existing weapons systems and processes.

Potential international rivals in the AI market are creating pressure for the United States to compete for innovative military AI applications. China is a leading competitor in this regard, releasing a plan in 2017 to capture the global lead in AI development by 2030. Currently, China is primarily focused on using AI to make faster and more well-informed decisions, as well as on developing a variety of autonomous military vehicles. Russia is also active in military AI development, with a primary focus on robotics. Although AI has the potential to impart a number of advantages in the military context, it may also introduce distinct challenges.

AI technology could, for example, facilitate autonomous operations, lead to more informed military decisionmaking, and increase the speed and scale of military action. However, it may also be unpredictable or vulnerable to unique forms of manipulation. As a result of these factors, analysts hold a broad range of opinions on how influential AI will be in future combat operations.

While a small number of analysts believe that the technology will have minimal impact, most believe that AI will have at least an evolutionary—if not revolutionary—effect….(More)”.

The Think-Tank Dilemma

Curated on Posted on by Stefaan Verhulst

Blog by Yoichi Funabashi: “Without the high-quality research that independent think tanks provide, there can be no effective policymaking, nor even a credible basis for debating major issues. Insofar as funding challenges, foreign influence-peddling, and populist attacks on truth pose a threat to such institutions tanks, they threaten democracy itself….

The Brookings Institution in Washington, DC – perhaps the world’s top think tank – is under scrutiny for receiving six-figure donations from Chinese telecommunications giant Huawei, which many consider to be a security threat. And since the barbaric murder of Saudi journalist Jamal Khashoggi last October, many other Washington-based think tanks have come under pressure to stop accepting donations from Saudi Arabia.

These recent controversies have given rise to a narrative that Washington-based think tanks are facing a funding crisis. In fact, traditional think tanks are confronting three major challenges that have put them in a uniquely difficult situation. Not only are they facing increased competition from for-profit think tanks such as the McKinsey Global Institute and the Eurasia Group; they also must negotiate rising geopolitical tensions, especially between the United States and China.And complicating matters further, many citizens, goaded by populist harangues, have become dismissive of “experts” and the fact-based analyses that think tanks produce (or at least should produce).

With respect to the first challenge, Daniel Drezner of Tufts University argues in The Ideas Industry: How Pessimists, Partisans, and Plutocrats are Transforming the Marketplace of Ideas that for-profit think tanks have engaged in thought leadership by operating as platforms for provocative thinkers who push big ideas. Whereas many non-profit think tanks – as well as universities and non-governmental organizations – remain “old-fashioned” in their approach to data, their for-profit counterparts thrive by finding the one statistic that captures public attention in the digital age. Given their access to both public and proprietary information, for-profit think tanks are also able to maximize the potential of big data in ways that traditional think tanks cannot.

Moreover, with the space for balanced foreign-policy arguments narrowing, think tanks are at risk of becoming tools of geopolitical statecraft. This is especially true now that US-China relations are deteriorating and becoming more ideologically tinged.

Over time, foreign governments of all stripes have cleverly sought to influence policymaking not only in Washington, but also in London, Brussels, Berlin, and elsewhere, by becoming significant donors to think tanks. Governments realize that the well-connected think tanks that act as “power brokers” vis-à-vis the political establishment have been facing fundraising challenges since the 2008 financial crisis. In some cases, locally based think tanks have even been accused of becoming fronts for foreign authoritarian governments….(More)”.


The 2019 Edelman Trust Barometer

Curated on Posted on by Stefaan Verhulst

Press Release: “The 2019 Edelman Trust Barometer reveals that trust has changed profoundly in the past year—people have shifted their trust to the relationships within their control, most notably their employers. Globally, 75 percent of people trust “my employer” to do what is right, significantly more than NGOs (57 percent), business (56 percent) and media (47 percent).

Divided by Trust

There is a 16-point gap between the more trusting informed public and the far-more-skeptical mass population, marking a return to record highs of trust inequality. The phenomenon fueling this divide was a pronounced rise in trust among the informed public. Markets such as the U.S., UK, Canada, South Korea and Hong Kong saw trust gains of 12 points or more among the informed public. In 18 markets, there is now a double-digit trust gap between the informed public and the mass population.

2019 Edelman Trust Barometer - Trust Inequality

An Urgent Desire for Change

Despite the divergence in trust between the informed public and mass population the world is united on one front—all share an urgent desire for change. Only one in five feels that the system is working for them, with nearly half of the mass population believing that the system is failing them.

In conjunction with pessimism and worry, there is a growing move toward engagement and action. In 2019, engagement with the news surged by 22 points; 40 percent not only consume news once a week or more, but they also routinely amplify it. But people are encountering roadblocks in their quest for facts, with 73 percent worried about fake news being used as a weapon.

Trust Barometer - News Engagement

The New Employer-Employee Contract

Despite a high lack of faith in the system, there is one relationship that remains strong: “my employer.” Fifty-eight percent of general population employees say they look to their employer to be a trustworthy source of information about contentious societal issues.

Employees are ready and willing to trust their employers, but the trust must be earned through more than “business as usual.” Employees’ expectation that prospective employers will join them in taking action on societal issues (67 percent) is nearly as high as their expectations of personal empowerment (74 percent) and job opportunity (80 percent)….(More)”.

China will now officially try to extend its Great Firewall to blockchains

Curated on Posted on by Stefaan Verhulst

Mike Orcutt at Technology Review: “China’s crackdown on blockchain technology has taken another step: the country’s internet censorship agency has just approved new regulations aimed at blockchain companies. 

Hand over the data: The Cyberspace Administration of China (CAC) will require any “entities or nodes” that provide “blockchain information services” to collect users’ real names and national ID or telephone numbers, and allow government officials to access that data.

It will ban companies from using blockchain technology to “produce, duplicate, publish, or disseminate” any content that Chinese law prohibits. Last year, internet users evaded censors by recording the content of two banned articles on the Ethereum blockchain. The rules, first proposed in October, will go into effect next month.

Defeating the purpose? For more than a year, China has been cracking down on cryptocurrency trading and its surrounding industry while also singing the praises of blockchain. It appears its goal is to take advantage of the resiliency and tamper-proof nature of blockchains while canceling out their most most radical attribute: censorship resistance….(More)”.

Gradually, Then Suddenly

Curated on Posted on by Stefaan Verhulst

Blogpost by Tim O’Reilly: “There’s a passage in Ernest Hemingway’s novel The Sun Also Rises in which a character named Mike is asked how he went bankrupt. “Two ways,” he answers. “Gradually, then suddenly.”

Technological change happens in much the same way. Small changes accumulate, and suddenly the world is a different place. Throughout my career at O’Reilly Media, we’ve tracked and fostered a lot of “gradually, then suddenly” movements: the World Wide Web, open source software, big data, cloud computing, sensors and ubiquitous computing, and now the pervasive effects of AI and algorithmic systems on society and the economy.

What are some of the things that are in the middle of their “gradually, then suddenly” transition right now? The list is long; here are a few of the areas that are on my mind.

1) AI and algorithms are everywhere

The most important trend for readers of this newsletter to focus on is the development of new kinds of partnership between human and machine. We take for granted that algorithmic systems do much of the work at online sites like Google, Facebook, Amazon, and Twitter, but we haven’t fully grasped the implications. These systems are hybrids of human and machine. Uber, Lyft, and Amazon Robotics brought this pattern to the physical world, reframing the corporation as a vast, buzzing network of humans both guiding and guided by machines. In these systems, the algorithms decide who gets what and why; they’re changing the fundamentals of market coordination in ways that gradually, then suddenly, will become apparent.

2) The rest of the world is leapfrogging the US

The volume of mobile payments in China is $13 trillion versus the US’s $50 billion, while credit cards never took hold. Already Zipline’s on-demand drones are delivering 20% of all blood supplies in Rwanda and will be coming soon to other countries (including the US). In each case, the lack of existing infrastructure turned out to be an advantage in adopting a radically new model. Expect to see this pattern recur, as incumbents and old thinking hold back the adoption of new models..…

9) The crisis of faith in government

Ever since Jennifer Pahlka and I began working on the Gov 2.0 Summit back in 2008, we’ve been concerned that if we can’t get government up to speed on 21st century technology, a critical pillar of the good society will crumble. When we started that effort, we were focused primarily on government innovation; over time, through Jen’s work at Code for America and the United States Digital Service, that shifted to a focus on making sure that government services actually work for those who need them most. Michael Lewis’s latest book, The Fifth Risk, highlights just how bad things might get if we continue to neglect and undermine the machinery of government. It’s not just the political fracturing of our country that should concern us; it’s the fact that government plays a critical role in infrastructure, in innovation, and in the safety net. That role has gradually been eroded, and the cracks that are appearing in the foundation of our society are coming at the worst possible time….(More)”.

IBM aims to use crowdsourced sensor data to improve local weather forecasting globally

Curated on Posted on by Stefaan Verhulst

Larry Dignan at ZDN: “IBM is hoping that mobile barometric sensors from individuals opting in, supercomputing ,and the Internet of Things can make weather forecasting more local globally.

Big Blue, which owns The Weather Company, will outline the IBM Global High-Resolution Atmospheric Forecasting System (GRAF). GRAF incorporates IoT data in its weather models via crowdsourcing.

While hyper local weather forecasts are available in the US, Japan, and some parts of Western Europe, many regions in the world lack an accurate picture of weather.

Mary Glackin, senior vice president of The Weather Company, said the company is “trying to fill in the blanks.” She added, “In a place like India, weather stations are kilometers away. We think this can be as significant as bringing satellite data into models.”

For instance, the developing world gets forecasts based on global data that are updated every 6 hours and resolutions at 10km to 15km. By using GRAF, IBM said it can offer forecasts for the day ahead that are updated hourly on average and have a 3km resolution….(More)”.

Implementing Public Policy: Is it possible to escape the ‘Public Policy Futility’ trap?

Curated on Posted on by Stefaan Verhulst

Blogpost by Matt Andrews:

Screen Shot 2018-12-06 at 6.29.15 PM

“Polls suggest that governments across the world face high levels of citizen dissatisfaction, and low levels of citizen trust. The 2017 Edelman Trust Barometer found, for instance, that only 43% of those surveyed trust Canada’s government. Only 15% of those surveyed trust government in South Africa, and levels are low in other countries too—including Brazil (at 24%), South Korea (28%), the United Kingdom (36%), Australia, Japan, and Malaysia (37%), Germany (38%), Russia (45%), and the United States (47%). Similar surveys find trust in government averaging only 40-45% across member countries of the Organization for Economic Cooperation and Development (OECD), and suggest that as few as 31% and 32% of Nigerians and Liberians trust government.

There are many reasons why trust in government is deficient in so many countries, and these reasons differ from place to place. One common factor across many contexts, however, is a lack of confidence that governments can or will address key policy challenges faced by citizens.

Studies show that this confidence deficiency stems from citizen observations or experiences with past public policy failures, which promote jaundiced views of their public officials’ capabilities to deliver. Put simply, citizens lose faith in government when they observe government failing to deliver on policy promises, or to ‘get things done’. Incidentally, studies show that public officials also often lose faith in their own capabilities (and those of their organizations) when they observe, experience or participate in repeated policy implementation failures. Put simply, again, these public officials lose confidence in themselves when they repeatedly fail to ‘get things done’.

I call the ‘public policy futility’ trap—where past public policy failure leads to a lack of confidence in the potential of future policy success, which feeds actual public policy failure, which generates more questions of confidence, in a vicious self fulfilling prophecy. I believe that many governments—and public policy practitioners working within governments—are caught in this trap, and just don’t believe that they can muster the kind of public policy responses needed by their citizens.

Along with my colleagues at the Building State Capability (BSC) program, I believe that many policy communities are caught in this trap, to some degree or another. Policymakers in these communities keep coming up with ideas, and political leaders keep making policy promises, but no one really believes the ideas will solve the problems that need solving or produce the outcomes and impacts that citizens need. Policy promises under such circumstances center on doing what policymakers are confident they can actually implement: like producing research and position papers and plans, or allocating inputs toward the problem (in a budget, for instance), or sponsoring visible activities (holding meetings or engaging high profile ‘experts’ for advice), or producing technical outputs (like new organizations, or laws). But they hold back from promising real solutions to real problems, as they know they cannot really implement them (given past political opposition, perhaps, or the experience of seemingly interactable coordination challenges, or cultural pushback, and more)….(More)”.

The global race is on to build ‘City Brains’

Curated on Posted on by Stefaan Verhulst

Prediction by Geoff Mulgan, Eva Grobbink and Vincent Straub: “The USSR’s launch of the Sputnik 1 satellite in 1958 was a major psychological blow to the United States. The US had believed it was technologically far ahead of its rival, but was confronted with proof that the USSR was pulling ahead in some fields. After a bout of soul-searching the country responded with extraordinary vigour, massively increasing investment in space technologies and promising to put a man on the Moon by the end of the 1960s.

In 2019, China’s success in smart cities could prompt a similar “Sputnik Moment” for the rest of the world. It may not be as dramatic as that of 1958. But unlike beeping satellites and Moon landings, it could be coming to a town near you….

The concept of a “smart city” has been around for several decades, often associated with hype, grandiose failures, and an overemphasis on hardware rather than people (Nesta has previously written on how we can rethink smart cities and ensure digital innovation realises the potential of technology and people). But various technologies are now coming of age which bring the vision of a smart city closer to fruition. China is in the forefront, investing heavily in sensors and infrastructures, and its ET City Brain project shows just how far the country’s thinking has progressed.

First launched in September 2016, ET City Brain is a collaboration between Chinese technology giant Alibaba and several cities. It was first trialled in Hangzhou, the hometown of Alibaba’s executive chairman, Jack Ma, but has since expanded to other Chinese cities. Earlier this year, Kuala Lumpurbecame the first city outside of China to import the ET City Brain model.

The ET City Brain system gathers large amounts of data (including logs, videos, and data stream) from sensors. These are then processed by algorithms in supercomputers and fed back into control centres around the city for administrators to act on—in some cases, automation means the system works without any human intervention at all.

So far, the project has been used to monitor congestion in Hangzhou, improve the response of emergency services in Guangzhou, and detect traffic accidents in Suzhou. In Hangzhou, Alibaba was given control of 104 traffic light junctions in the city’s Xiaoshan district and tasked with managing traffic flows. By combining mass video surveillance with live data from public transportation systems, ET City Brain was able to autonomously change traffic lights so that emergency vehicles could travel to accident scenes without interruption. As a result, arrival times for ambulances improved by 49 percent….(More)”.