Artificial intelligence could identify gang crimes—and ignite an ethical firestorm

Curated on Posted on by Stefaan Verhulst

Matthew Hutson at Science: “When someone roughs up a pedestrian, robs a store, or kills in cold blood, police want to know whether the perpetrator was a gang member: Do they need to send in a special enforcement team? Should they expect a crime in retaliation? Now, a new algorithm is trying to automate the process of identifying gang crimes. But some scientists warn that far from reducing gang violence, the program could do the opposite by eroding trust in communities, or it could brand innocent people as gang members.

That has created some tensions. At a presentation of the new program this month, one audience member grew so upset he stormed out of the talk, and some of the creators of the program have been tight-lipped about how it could be used….

For years, scientists have been using computer algorithms to map criminal networks, or to guess where and when future crimes might take place, a practice known as predictive policing. But little work has been done on labeling past crimes as gang-related.

In the new work, researchers developed a system that can identify a crime as gang-related based on only four pieces of information: the primary weapon, the number of suspects, and the neighborhood and location (such as an alley or street corner) where the crime took place. Such analytics, which can help characterize crimes before they’re fully investigated, could change how police respond, says Doug Haubert, city prosecutor for Long Beach, California, who has authored strategies on gang prevention.

To classify crimes, the researchers invented something called a partially generative neural network. A neural network is made of layers of small computing elements that process data in a way reminiscent of the brain’s neurons. A form of machine learning, it improves based on feedback—whether its judgments were right. In this case, researchers trained their algorithm using data from the Los Angeles Police Department (LAPD) in California from 2014 to 2016 on more than 50,000 gang-related and non–gang-related homicides, aggravated assaults, and robberies.

The researchers then tested their algorithm on another set of LAPD data. The network was “partially generative,” because even when it did not receive an officer’s narrative summary of a crime, it could use the four factors noted above to fill in that missing information and then use all the pieces to infer whether a crime was gang-related. Compared with a stripped-down version of the network that didn’t use this novel approach, the partially generative algorithm reduced errors by close to 30%, the team reported at the Artificial Intelligence, Ethics, and Society (AIES) conference this month in New Orleans, Louisiana. The researchers have not yet tested their algorithm’s accuracy against trained officers.

It’s an “interesting paper,” says Pete Burnap, a computer scientist at Cardiff University who has studied crime data. But although the predictions could be useful, it’s possible they would be no better than officers’ intuitions, he says. Haubert agrees, but he says that having the assistance of data modeling could sometimes produce “better and faster results.” Such analytics, he says, “would be especially useful in large urban areas where a lot of data is available.”…(More).

Infection forecasts powered by big data

Curated on Posted on by Stefaan Verhulst

Michael Eisenstein at Nature: “…The good news is that the present era of widespread access to the Internet and digital health has created a rich reservoir of valuable data for researchers to dive into….By harvesting and combining these streams of big data with conventional ways of monitoring infectious diseases, the public-health community could gain fresh powers to catch and curb emerging outbreaks before they rage out of control.

Going viral

Data scientists at Google were the first to make a major splash using data gathered online to track infectious diseases. The Google Flu Trends algorithm, launched in November 2008, combed through hundreds of billions of users’ queries on the popular search engine to look for small increases in flu-related terms such as symptoms or vaccine availability. Initial data suggested that Google Flu Trends could accurately map the incidence of flu with a lag of roughly one day. “It was a very exciting use of these data for the purpose of public health,” says Brownstein. “It really did start a whole revolution and new field of work in query data.”

Unfortunately, Google Flu Trends faltered when it mattered the most, completely missing the onset in April 2009 of the H1N1 pandemic. The algorithm also ran into trouble later on in the pandemic. It had been trained against seasonal fluctuations of flu, says Viboud, but people’s behaviour changed in the wake of panic fuelled by media reports — and that threw off Google’s data. …

Nevertheless, its work with Internet usage data was inspirational for infectious-disease researchers. A subsequent study from a team led by Cecilia Marques-Toledo at the Federal University of Minas Gerais in Belo Horizonte, Brazil, used Twitter to get high-resolution data on the spread of dengue fever in the country. The researchers could quickly map new cases to specific cities and even predict where the disease might spread to next (C. A. Marques-Toledo et al. PLoS Negl. Trop. Dis. 11, e0005729; 2017). Similarly, Brownstein and his colleagues were able to use search data from Google and Twitter to project the spread of Zika virus in Latin America several weeks before formal outbreak declarations were made by public-health officials. Both Internet services are used widely, which makes them data-rich resources. But they are also proprietary systems for which access to data is controlled by a third party; for that reason, Generous and his colleagues have opted instead to make use of search data from Wikipedia, which is open source. “You can get the access logs, and how many people are viewing articles, which serves as a pretty good proxy for search interest,” he says.

However, the problems that sank Google Flu Trends still exist….Additionally, online activity differs for infectious conditions with a social stigma such as syphilis or AIDS, because people who are or might be affected are more likely to be concerned about privacy. Appropriate search-term selection is essential: Generous notes that initial attempts to track flu on Twitter were confounded by irrelevant tweets about ‘Bieber fever’ — a decidedly non-fatal condition affecting fans of Canadian pop star Justin Bieber.

Alternatively, researchers can go straight to the source — by using smartphone apps to ask people directly about their health. Brownstein’s team has partnered with the Skoll Global Threats Fund to develop an app called Flu Near You, through which users can voluntarily report symptoms of infection and other information. “You get more detailed demographics about age and gender and vaccination status — things that you can’t get from other sources,” says Brownstein. Ten European Union member states are involved in a similar surveillance programme known as Influenzanet, which has generally maintained 30,000–40,000 active users for seven consecutive flu seasons. These voluntary reporting systems are particularly useful for diseases such as flu, for which many people do not bother going to the doctor — although it can be hard to persuade people to participate for no immediate benefit, says Brownstein. “But we still get a good signal from the people that are willing to be a part of this.”…(More)”.

Your Data Is Crucial to a Robotic Age. Shouldn’t You Be Paid for It?

Curated on Posted on by Stefaan Verhulst

Eduardo Porter at The New York Times: “The idea has been around for a bit. Jaron Lanier, the tech philosopher and virtual-reality pioneer who now works for Microsoft Research, proposed it in his 2013 book, “Who Owns the Future?,” as a needed corrective to an online economy mostly financed by advertisers’ covert manipulation of users’ consumer choices.

It is being picked up in “Radical Markets,” a book due out shortly from Eric A. Posner of the University of Chicago Law School and E. Glen Weyl, principal researcher at Microsoft. And it is playing into European efforts to collect tax revenue from American internet giants.

In a report obtained last month by Politico, the European Commission proposes to impose a tax on the revenue of digital companies based on their users’ location, on the grounds that “a significant part of the value of a business is created where the users are based and data is collected and processed.”

Users’ data is a valuable commodity. Facebook offers advertisers precisely targeted audiences based on user profiles. YouTube, too, uses users’ preferences to tailor its feed. Still, this pales in comparison with how valuable data is about to become, as the footprint of artificial intelligence extends across the economy.

Data is the crucial ingredient of the A.I. revolution. Training systems to perform even relatively straightforward tasks like voice translation, voice transcription or image recognition requires vast amounts of data — like tagged photos, to identify their content, or recordings with transcriptions.

“Among leading A.I. teams, many can likely replicate others’ software in, at most, one to two years,” notes the technologist Andrew Ng. “But it is exceedingly difficult to get access to someone else’s data. Thus data, rather than software, is the defensible barrier for many businesses.”

We may think we get a fair deal, offering our data as the price of sharing puppy pictures. By other metrics, we are being victimized: In the largest technology companies, the share of income going to labor is only about 5 to 15 percent, Mr. Posner and Mr. Weyl write. That’s way below Walmart’s 80 percent. Consumer data amounts to work they get free….

The big question, of course, is how we get there from here. My guess is that it would be naïve to expect Google and Facebook to start paying for user data of their own accord, even if that improved the quality of the information. Could policymakers step in, somewhat the way the European Commission did, demanding that technology companies compute the value of consumer data?…(More)”.

Building Democratic Infrastructure

Curated on Posted on by Stefaan Verhulst

Hollie Russon Gilman, K. Sabeel Rahman, & Elena Souris in Stanford Social Innovation Review: “How can civic engagement be effective in fostering an accountable, inclusive, and responsive American democracy? This question has gained new relevance under the Trump administration, where a sense of escalating democratic crises risks obscuring any nascent grassroots activism. Since the 2016 election, the twin problems of authoritarianism and insufficient political accountability have attracted much attention, as has the need to mobilize for near-future elections. These things are critical for the long-term health of American democracy, but at the same time, it’s not enough to focus solely on Washington or to rely on electoral campaigns to salvage our democracy.

Conventional civic-engagement activities such as canvassing, registering voters, signing petitions, and voting are largely transient experiences, offering little opportunity for civic participation once the election is over. And such tactics often do little to address the background conditions that make participation more difficult for marginalized communities.

To address these issues, civil society organization and local governments should build more long-term and durable democratic infrastructure, with the aim of empowering constituencies to participate in meaningful and concrete ways, overcoming division within our societies, and addressing a general distrust of government by enhancing accountability.

In our work with groups like the Center for Rural Strategies in Appalachia and the Chicago-based Inner-City Muslim Action Network, as well as with local government officials in Eau Claire, Wis. and Boston, Mass., we identify two areas where can help build a broader democratic infrastructure for the long haul. First, we need to support and radically expand efforts by local-level government officials to innovate more participatory and accountable forms of policymaking. And then we need to continue developing new methods of diverse, cross-constituency organizing that can help build more inclusive identities and narratives. Achieving this more-robust form of democracy will require that many different communities—including organizers and advocacy groups, policymakers and public officials, technologists, and funders—combine their efforts….(More)”.

When Fighting Fake News Aids Censorship

Curated on Posted on by Stefaan Verhulst

Courtney C. Radsch at Project Syndicate: “Many media analysts have rightly identified the dangers posed by “fake news,” but often overlook what the phenomenon means for journalists themselves. Not only has the term become a shorthand way to malign an entire industry; autocrats are invoking it as an excuse to jail reporters and justify censorship, often on trumped-up charges of supporting terrorism.

Around the world, the number of honest journalists jailed for publishing fake or fictitious news is at an all-time high of at least 21. As non-democratic leaders increasingly use the “fake news” backlash to clamp down on independent media, that number is likely to climb.

The United States, once a world leader in defending free speech, has retreated from this role. President Donald Trump’s Twitter tirades about “fake news” have given autocratic regimes an example by which to justify their own media crackdowns. In December, China’s state-run People’s Daily newspaper posted tweets and a Facebook post welcoming Trump’s fake news mantra, noting that it “speaks to a larger truth about Western media.” This followed the Egyptian government’s praise for the Trump administration in February 2017, when the country’s foreign ministry criticized Western journalists for their coverage of global terrorism.

And in January 2017, Turkish President Recep Tayyip Erdoğan praised Trump for berating a CNN reporter during a live news conference. Erdoğan, who criticized the network for its coverage of pro-democracy protests in Turkey in 2013, said that Trump had put the journalist “in his place.” Trump returned the compliment when he met Erdoğan a few months later. Praising his counterpart for being an ally in the fight against terrorism, Trump made no mention of Erdoğan’s own dismal record on press freedom.

It is no accident that these three countries have been quickest to embrace Trump’s “fake news” trope. China, Egypt, and Turkey jailed more than half of the world’s journalists in 2017, continuing a trend from the previous year. The international community’s silence in the face of these governments’ attacks on independent media seems to have been interpreted as consent….(More)”.

Global Fishing Watch And The Power Of Data To Understand Our Natural World

Curated on Posted on by Stefaan Verhulst

Kalev Leetaru at Forbes: “A year and a half ago I wrote about the public debut of the Global Fishing Watch project as a showcase of what becomes possible when massive datasets are made accessible to the general public through easy-to-use interfaces that allow them to explore the planet they inhabit. At the time I noted how the project drove home the divide between the “glittering technological innovation of Silicon Valley and the technological dark ages of the development community” and what becomes possible when technologists and development organizations come together to apply incredible technology not for commercial gain, but rather to save the world itself. Continuing those efforts, last week Global Fishing Watch launched what it describes as the “the first ever dataset of global industrial fishing activities (all countries, all gears),” making the entire dataset freely accessible to seed new scientific, activist, governmental, journalistic and citizen understanding of the state of global fishing.

The Global Fishing Watch project stands as a powerful model for data-driven development work done right and hopefully, the rise of notable efforts like it will eventually catalyze the broader development community to emerge from the stone age of technology and more openly embrace the technological revolution. While it has a very long way to go, there are signs of hope for the development community as pockets of innovation begin to infuse the power of data-driven decision making and situational awareness into everything from disaster response to proactive planning to shaping legislative action.

Bringing technologists and development organizations together is not always that easy and the most creative solutions aren’t always to be found among the “usual suspects.” Open data and open challenges built upon them offer the potential for organizations to reach beyond the usual communities they interact with and identify innovative new approaches to the grand challenges of their fields. Just last month a collaboration of the World Bank, WeRobotics and OpenAerialMap launched a data challenge to apply deep learning to assess aerial imagery in the immediate aftermath of disasters to determine the impact to food producing trees and to road networks. By launching the effort as an open AI challenge, the goal is to reach the broader AI and open development communities at the forefront of creative and novel algorithmic approaches….(More)”.

Liquid democracy uses blockchain to fix politics, and now you can vote for it

Curated on Posted on by Stefaan Verhulst

Danny Crichton at TechCrunch: “…Confidence in Congress remains pitifully low, driven by perceived low ethical standards and an increasing awareness that politics is bought by the highest bidder.

Now, a group of technologists and blockchain enthusiasts are asking whether a new approach could reform the system, bringing citizens closer to their representatives and holding congressmen accountable to their voters in a public, verifiable way. And if you live in western San Francisco, you can actually vote to put this system into office.

The concept is known as liquid democracy, and it’s a solid choice for fixing a broken system. The idea is that every person should have the right to give feedback on a policy issue or a piece of new legislation, but often people don’t have the time to do so. Using a liquid democracy platform, however, that voter can select a personal representative who has the authority to be a proxy for their vote. That proxy can be changed at will as a voter’s interests change.

Here is where the magic happens. Those proxies can themselves proxy their votes to other people, creating a directed network graph, ideally connecting every voter to politicians and all publicly verified on a blockchain. While there may be 700,000 people in a congressional district, potentially only a few hundred of a few thousand “super proxies” would need to be deeply engaged in the system for better representation to take place.

David Ernst is a leader of the liquid democracy movement and now a candidate for California Assembly District 19, which centers on the western half of San Francisco. He is ardently committed to the concept, and despite its novelty, believes that this is the path forward for improving governance….

Following college (which he began at age 16) and a few startup jobs, Ernst began working as CTO of a startup called Numerai, a crypto-backed decentralized hedge fund that allows data scientists to earn money when they solve data challenges. “The idea was that we can include many more people to participate in the system who weren’t able to before,” Ernst explained. That’s when it hit him that the decentralized nature of blockchain could allow for more participation in politics, fusing his two passions.

Ernst followed the campaign of the Flux Party in Australia in 2016, which is trying to implement what it calls “issue-based direct democracy” in that country’s legislature. “That was when something clicked,” he said. A congressman for example could commit to voting the calculated liquid democracy position, and “We could elect these sort of remote-controlled politicians as a way to graft this new system onto the old system.”

He built a platform called United.vote to handle the logistics of selecting personal representatives and voting on issues. More importantly, the app then tracks how those votes compare to the votes of congressmen and provides a scorecard….(More)”.

No One Owns Data

Curated on Posted on by Stefaan Verhulst

Paper by Lothar Determann: “Businesses, policy makers, and scholars are calling for property rights in data. They currently focus particularly on the vast amounts of data generated by connected cars, industrial machines, artificial intelligence, toys and other devices on the Internet of Things (IoT). This data is personal to numerous parties who are associated with a connected device, for example, the driver of a connected car, its owner and passengers, as well as other traffic participants. Manufacturers, dealers, independent providers of auto parts and services, insurance companies, law enforcement agencies and many others are also interested in this data. Various parties are actively staking their claims to data on the Internet of Things, as they are mining data, the fuel of the digital economy.

Stakeholders in digital markets often frame claims, negotiations and controversies regarding data access as one of ownership. Businesses regularly assert and demand that they own data. Individual data subjects also assume that they own data about themselves. Policy makers and scholars focus on how to redistribute ownership rights to data. Yet, upon closer review, it is very questionable whether data is—or should be—subject to any property rights. This article unambiguously answers the question in the negative, both with respect to existing law and future lawmaking, in the United States as in the European Union, jurisdictions with notably divergent attitudes to privacy, property and individual freedoms….

The article begins with a brief review of the current landscape of the Internet of Things notes explosive growth of data pools generated by connected devices, artificial intelligence, big data analytics tools and other information technologies. Part 1 lays the foundation for examining concrete current legal and policy challenges in the remainder of the article. Part 2 supplies conceptual differentiation and definitions with respect to “data” and “information” as the subject of rights and interests. Distinctions and definitional clarity serve as the basis for examining the purposes and reach of existing property laws in Part 3, including real property, personal property and intellectual property laws. Part 4 analyzes the effect of data-related laws that do not grant property rights. Part 5 examines how the interests of the various stakeholders are protected or impaired by the current framework of data-related laws to identify potential gaps that could warrant additional property rights. Part 6 examines policy considerations for and against property rights in data. Part 7 concludes that no one owns data and no one should own data….(More)”.

Open data sharing and the Global South—Who benefits?

Curated on Posted on by Stefaan Verhulst

David Serwadda et al in Science: “A growing number of government agencies, funding organizations, and publishers are endorsing the call for increased data sharing, especially in biomedical research, many with an ultimate goal of open data. Open data is among the least restrictive forms of data sharing, in contrast to managed access mechanisms, which typically have terms of use and in some cases oversight by the data generators themselves. But despite an ethically sound rationale and growing support for open data sharing in many parts of the world, concerns remain, particularly among researchers in low- and middle-income countries (LMICs) in Africa, Latin America, and parts of Asia and the Middle East that comprise the Global South. Drawing on our perspective as researchers and ethicists working in the Global South, we see opportunities to improve community engagement, raise awareness, and build capacity, all toward improving research and data sharing involving researchers in LMICs…African scientists have expressed concern that open data compromises national ownership and reopens the gates for “parachute-research” (i.e., Northern researchers absconding with data to their home countries). Other LMIC researchers have articulated fears over free-riding scientists using the data collected by others for their own career advancement …(More)”

The Rise of Virtual Citizenship

Curated on Posted on by Stefaan Verhulst

James Bridle in The Atlantic: “In Cyprus, Estonia, the United Arab Emirates, and elsewhere, passports can now be bought and sold….“If you believe you are a citizen of the world, you are a citizen of nowhere. You don’t understand what citizenship means,” the British prime minister, Theresa May, declared in October 2016. Not long after, at his first postelection rally, Donald Trump asserted, “There is no global anthem. No global currency. No certificate of global citizenship. We pledge allegiance to one flag and that flag is the American flag.” And in Hungary, Prime Minister Viktor Orbán has increased his national-conservative party’s popularity with statements like “all the terrorists are basically migrants” and “the best migrant is the migrant who does not come.”

Citizenship and its varying legal definition has become one of the key battlegrounds of the 21st century, as nations attempt to stake out their power in a G-Zero, globalized world, one increasingly defined by transnational, borderless trade and liquid, virtual finance. In a climate of pervasive nationalism, jingoism, xenophobia, and ever-building resentment toward those who move, it’s tempting to think that doing so would become more difficult. But alongside the rise of populist, identitarian movements across the globe, identity itself is being virtualized, too. It no longer needs to be tied to place or nation to function in the global marketplace.

Hannah Arendt called citizenship “the right to have rights.” Like any other right, it can be bestowed and withheld by those in power, but in its newer forms it can also be bought, traded, and rewritten. Virtual citizenship is a commodity that can be acquired through the purchase of real estate or financial investments, subscribed to via an online service, or assembled by peer-to-peer digital networks. And as these options become available, they’re also used, like so many technologies, to exclude those who don’t fit in.

In a world that increasingly operates online, geography and physical infrastructure still remain crucial to control and management. Undersea fiber-optic cables trace the legacy of imperial trading routes. Google and Facebook erect data centers in Scandinavia and the Pacific Northwest, close to cheap hydroelectric power and natural cooling. The trade in citizenship itself often manifests locally as architecture. From luxury apartments in the Caribbean and the Mediterranean to data centers in Europe and refugee settlements in the Middle East, a scattered geography of buildings brings a different reality into focus: one in which political decisions and national laws transform physical space into virtual territory…(More)”.