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Blockchain Ethical Design Framework

Curated on June 23, 2018August 3, 2018 by Stefaan Verhulst

Report by Cara LaPointe and Lara Fishbane: “There are dramatic predictions about the potential of blockchain to “revolutionize” everything from worldwide financial markets and the distribution of humanitarian assistance to the very way that we outright recognize human identity for billions of people around the globe. Some dismiss these claims as excessive technology hype by citing flaws in the technology or robustness of incumbent solutions and infrastructure.

The reality will likely fall somewhere between these two extremes across multiple sectors. Where initial applications of blockchain were focused on the financial industry, current applications have rapidly expanded to address a wide array of sectors with major implications for social impact.

This paper aims to demonstrate the capacity of blockchain to create scalable social impact and to identify the elements that need to be addressed to mitigate challenges in its application. We are at a moment when technology is enabling society to experiment with new solutions and business models. Ubiquity and global reach, increased capabilities, and affordability have made technology a critical tool for solving problems, making this an exciting time to think about achieving greater social impact. We can address issues for underserved or marginalized people in ways that were previously unimaginable.

Blockchain is a technology that holds real promise for dealing with key inefficiencies and transforming operations in the social sector and for improving lives. Because of its immutability and decentralization, blockchain has the potential to create transparency, provide distributed verification, and build trust across multiple systems. For instance, blockchain applications could provide the means for establishing identities for individuals without identification papers, improving access to finance and banking services for underserved populations, and distributing aid to refugees in a more transparent and efficient manner. Similarly, national and subnational governments are putting land registry information onto blockchains to create greater transparency and avoid corruption and manipulation by third parties.

From increasing access to capital, to tracking health and education data across multiple generations, to improving voter records and voting systems, blockchain has countless potential applications for social impact. As developers take on building these types of solutions, the social effects of blockchain can be powerful and lasting. With the potential for such a powerful impact, the design, application, and approach to the development and implementation of blockchain technologies have long-term implications for society and individuals.

This paper outlines why intentionality of design, which is important with any technology, is particularly crucial with blockchain, and offers a framework to guide policymakers and social impact organizations. As social media, cryptocurrencies, and algorithms have shown, technology is not neutral. Values are embedded in the code. How the problem is defined and by whom, who is building the solution, how it gets programmed and implemented, who has access, and what rules are created have consequences, in intentional and unintentional ways. In the applications and implementation of blockchain, it is critical to understand that seemingly innocuous design choices have resounding ethical implications on people’s lives.

This white paper addresses why intentionality of design matters, identifies the key questions that should be asked, and provides a framework to approach use of blockchain, especially as it relates to social impact. It examines the key attributes of blockchain, its broad applicability as well as its particular potential for social impact, and the challenges in fully realizing that potential. Social impact organizations and policymakers have an obligation to understand the ethical approaches used in designing blockchain technology, especially how they affect marginalized and vulnerable populations….(More)”

Balancing Act: Innovation vs. Privacy in the Age of Data Portability

Curated on June 22, 2018November 15, 2018 by admin

Thursday, July 12, 2018 @ 2 MetroTech Center, Brooklyn, NY 11201

RSVP here.

The ability of people to move or copy data about themselves from one service to another — data portability — has been hailed as a way of increasing competition and driving innovation. In many areas, such as through the Open Banking initiative in the United Kingdom, the practice of data portability is fully underway and propagating. The launch of GDPR in Europe has also elevated the issue among companies and individuals alike. But recent online security breaches and other experiences of personal data being transferred surreptitiously from private companies, (e.g., Cambridge Analytica’s appropriation of Facebook data), highlight how data portability can also undermine people’s privacy.

The GovLab at the NYU Tandon School of Engineering is pleased to present Jeni Tennison, CEO of the Open Data Institute, for its next Ideas Lunch, where she will discuss how data portability has been regulated in the UK and Europe, and what governments, businesses and people need to do to strike the balance between its risks and benefits.

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Jeni Tennison is the CEO of the Open Data Institute. She gained her PhD from the University of Nottingham then worked as an independent consultant, specialising in open data publishing and consumption, before joining the ODI in 2012. Jeni was awarded an OBE for services to technology and open data in the 2014 New Year Honours.

Before joining the ODI, Jeni was the technical architect and lead developer for legislation.gov.uk. She worked on the early linked data work on data.gov.uk, including helping to engineer new standards for publishing statistics as linked data. She continues her work within the UK’s public sector as a member of the Open Standards Board.

Jeni also works on international web standards. She was appointed to serve on the W3C’s Technical Architecture Group from 2011 to 2015 and in 2014 she started to co-chair the W3C’s CSV on the Web Working Group. She also sits on the Advisory Boards for Open Contracting Partnership and the Data Transparency Lab.

Twitter handle: @JeniT

We Need to Save Ignorance From AI

Curated on June 22, 2018August 3, 2018 by Stefaan Verhulst

Christina Leuker and Wouter van den Bos in Nautilus: “After the fall of the Berlin Wall, East German citizens were offered the chance to read the files kept on them by the Stasi, the much-feared Communist-era secret police service. To date, it is estimated that only 10 percent have taken the opportunity.

In 2007, James Watson, the co-discoverer of the structure of DNA, asked that he not be given any information about his APOE gene, one allele of which is a known risk factor for Alzheimer’s disease.

Most people tell pollsters that, given the choice, they would prefer not to know the date of their own death—or even the future dates of happy events.

Each of these is an example of willful ignorance. Socrates may have made the case that the unexamined life is not worth living, and Hobbes may have argued that curiosity is mankind’s primary passion, but many of our oldest stories actually describe the dangers of knowing too much. From Adam and Eve and the tree of knowledge to Prometheus stealing the secret of fire, they teach us that real-life decisions need to strike a delicate balance between choosing to know, and choosing not to.

But what if a technology came along that shifted this balance unpredictably, complicating how we make decisions about when to remain ignorant? That technology is here: It’s called artificial intelligence.

AI can find patterns and make inferences using relatively little data. Only a handful of Facebook likes are necessary to predict your personality, race, and gender, for example. Another computer algorithm claims it can distinguish between homosexual and heterosexual men with 81 percent accuracy, and homosexual and heterosexual women with 71 percent accuracy, based on their picture alone. An algorithm named COMPAS (Correctional Offender Management Profiling for Alternative Sanctions) can predict criminal recidivism from data like juvenile arrests, criminal records in the family, education, social isolation, and leisure activities with 65 percent accuracy….

Recently, though, the psychologist Ralph Hertwig and legal scholar Christoph Engel have published an extensive taxonomy of motives for deliberate ignorance. They identified two sets of motives, in particular, that have a particular relevance to the need for ignorance in the face of AI.

The first set of motives revolves around impartiality and fairness. Simply put, knowledge can sometimes corrupt judgment, and we often choose to remain deliberately ignorant in response. For example, peer reviews of academic papers are usually anonymous. Insurance companies in most countries are not permitted to know all the details of their client’s health before they enroll; they only know general risk factors. This type of consideration is particularly relevant to AI, because AI can produce highly prejudicial information….(More)”.

Ghost Cities: Built but Never Inhabited

Curated on June 21, 2018August 3, 2018 by Stefaan Verhulst

Civic Data Design Lab at UrbanNext: “Ghost Cities are vacant neighborhoods and sometimes whole cities that were built but were never inhabited. Their existence is a physical manifestation of Chinese overdevelopment in real estate and the dependence on housing as an investment strategy. Little data exists which establishes the location and extent of these Ghost Cities in China. MIT’s Civic Data Design Lab developed a model using data scraped from Chinese social media sites and Baidu (Chinese Google Maps) to create one of the first maps identifying the locations of Chinese Ghost Cities….

Quantifying the extent and location of Ghost Cities is complicated by the fact that the Chinese government keeps a tight hold on data about sales and occupancy of buildings. Even local planners may have a hard time acquiring it. The Civic Data Design Lab developed a model to identify Ghost Cities based on the idea that amenities (grocery stores, hair salons, restaurants, schools, retail, etc.) are the mark of a healthy community and the lack of amenities might indicate locations where no one lives. Given the lack of openly available data in China, data was scraped from Chinese social media and websites, including Dianping (Chinese Yelp), Amap (Chinese Map Quest), Fang (Chinese Zillow), and Baidu (Chinese Google Maps) using openly accessible Application Programming Interfaces(APIs).

Using data scraped from social media sites in Chengdu and Shenyang, the model was tested using 300 m x 300 m grid cells marking residential locations. Each grid cell was given an amenity accessibility score based on the distance and clustering of amenities nearby. Residential areas that had a cluster of low scores were marked as Ghost Cities. The results were ground-truthed through site visits documenting the location using aerial photography from drones and interviews with local stakeholders.

The model worked well at documenting under-utilized residential locations in these Chinese cities, picking up everything from vacant housing and stalled construction to abandoned older residential locations, creating the first data set that marks risk in the Chinese real estate market. The research shows that data available through social media can help locate and estimate risk in the Chinese real estate market. Perhaps more importantly, however, identifying where these areas are concentrated can help city planners, developers and local citizens make better investment decisions and address the risk created by these under-utilized developments….(More)”.

When Technology Gets Ahead of Society

Curated on June 20, 2018August 3, 2018 by Stefaan Verhulst

Tarun Khanna at Harvard Business Review: “Drones, originally developed for military purposes, weren’t approved for commercial use in the United States until 2013. When that happened, it was immediately clear that they could be hugely useful to a whole host of industries—and almost as quickly, it became clear that regulation would be a problem. The new technology raised multiple safety and security issues, there was no consensus on who should write rules to mitigate those concerns, and the knowledge needed to develop the rules didn’t yet exist in many cases. In addition, the little flying robots made a lot of people nervous.

Such regulatory, logistical, and social barriers to adopting novel products and services are very common. In fact, technology routinely outstrips society’s ability to deal with it. That’s partly because tech entrepreneurs are often insouciant about the legal and social issues their innovations birth. Although electric cars are subsidized by the federal government, Tesla has run afoul of state and local regulations because it bypasses conventional dealers to sell directly to consumers. Facebook is only now facing up to major regulatory concerns about its use of data, despite being massively successful with users and advertisers.

It’s clear that even as innovations bring unprecedented comfort and convenience, they also threaten old ways of regulating industries, running a business, and making a living. This has always been true. Thus early cars weren’t allowed to go faster than horses, and some 19th-century textile workers used sledgehammers to attack the industrial machinery they feared would displace them. New technology can even upend social norms: Consider how dating apps have transformed the way people meet.

Entrepreneurs, of course, don’t really care that the problems they’re running into are part of a historical pattern. They want to know how they can manage—and shorten—the period between the advent of a technology and the emergence of the rules and new behaviors that allow society to embrace its possibilities.

Interestingly, the same institutional murkiness that pervades nascent industries such as drones and driverless cars is something I’ve also seen in developing countries. And strange though this may sound, I believe that tech entrepreneurs can learn a lot from businesspeople who have succeeded in the world’s emerging markets.

Entrepreneurs in Brazil or Nigeria know that it’s pointless to wait for the government to provide the institutional and market infrastructure their businesses need, because that will simply take too long. They themselves must build support structures to compensate for what Krishna Palepu and I have referred to in earlier writings as “institutional voids.” They must create the conditions that will allow them to create successful products or services.

Tech-forward entrepreneurs in developed economies may want to believe that it’s not their job to guide policy makers and the public—but the truth is that nobody else can play that role. They may favor hardball tactics, getting ahead by evading rules, co-opting regulators, or threatening to move overseas. But in the long term, they’d be wiser to use soft power, working with a range of partners to co-create the social and institutional fabric that will support their growth—as entrepreneurs in emerging markets have done.…(More)”.

Wikipedia vandalism could thwart hoax-busting on Google, YouTube and Facebook

Curated on June 19, 2018August 3, 2018 by Stefaan Verhulst

Daniel Funke at Poynter: “For a brief moment, the California Republican Party supported Nazism. At least, that’s what Google said.

That’s because someone vandalized the Wikipedia page for the party on May 31 to list “Nazism” alongside ideologies like “Conservatism,” “Market liberalism” and “Fiscal conservatism.” The mistake was removed from search results, with Google clarifying to Vice News that the search engine had failed to catch the vandalism in the Wikipedia entry….

Google has long drawn upon the online encyclopedia for appending basic information to search results. According to the edit log for the California GOP page, someone added “Nazism” to the party’s ideology section around 7:40 UTC on May 31. The edit was removed within a minute, but it appears Google’s algorithm scraped the page just in time for the fake.

“Sometimes people vandalize public information sources, like Wikipedia, which can impact the information that appears in search,” a Google spokesperson told Poynter in an email. “We have systems in place that catch vandalism before it impacts search results, but occasionally errors get through, and that’s what happened here.”…

According to Google, more than 99.9 percent of Wikipedia edits that show up in Knowledge Panels, which display basic information about searchable keywords at the top of results, aren’t vandalism. The user who authored the original edit to the California GOP’s page did not use a user profile, making them hard to track down.

That’s a common tactic among people who vandalize Wikipedia pages, a practice the nonprofit has documented extensively. But given the volume of edits that are made on Wikipedia — about 10 per second, with 600 new pages per day — and the fact that Facebook and YouTube are now pulling from them to provide more context to posts, the potential for and effect of abuse is high….(More)”.

Data Stewards: Data Leadership to Address 21st Century Challenges

Curated on June 14, 2018August 3, 2018 by Stefaan Verhulst

Post by Stefaan Verhulst: “…Over the last two years, we have focused on the opportunities (and challenges) surrounding what we call “data collaboratives.” Data collaboratives are an emerging form of public-private partnership, in which information held by companies (or other entities) is shared with the public sector, civil society groups, research institutes and international organizations. …

For all its promise, the practice of data collaboratives remains ad hoc and limited. In part, this is a result of the lack of a well-defined, professionalized concept of data stewardship within corporations that has a mandate to explore ways to harness the potential of their data towards positive public ends.

Today, each attempt to establish a cross-sector partnership built on the analysis of private-sector data requires significant and time-consuming efforts, and businesses rarely have personnel tasked with undertaking such efforts and making relevant decisions.

As a consequence, the process of establishing data collaboratives and leveraging privately held data for evidence-based policy making and service delivery is onerous, generally one-off, not informed by best practices or any shared knowledge base, and prone to dissolution when the champions involved move on to other functions.

By establishing data stewardship as a corporate function, recognized and trusted within corporations as a valued responsibility, and by creating the methods and tools needed for responsible data-sharing, the practice of data collaboratives can become regularized, predictable, and de-risked….

To take stock of current practice and scope needs and opportunities we held a small yet in-depth kick-off event at the offices of the Cloudera Foundation in San Francisco on May 8th 2018 that was attended by representatives from Linkedin, Facebook, Uber, Mastercard, DigitalGlobe, Cognizant, Streetlight Data, the World Economic Forum, and Nethope — among others.

Four Key Take Aways

The discussions were varied and wide-ranging.

Several reflected on the risks involved — including the risks of NOT sharing or collaborating on privately held data that could improve people’s lives (and in some occasions save lives).

Others warned that the window of opportunity to increase the practice of data collaboratives may be closing — given new regulatory requirements and other barriers that may disincentivize corporations from engaging with third parties around their data.

Ultimately four key take aways emerged. These areas — at the nexus of opportunities and challenges — are worth considering further, because they help us better understand both the potential and limitations of data collaboratives….(More)”

I want your (anonymized) social media data

Curated on June 13, 2018May 29, 2019 by Stefaan Verhulst

Anthony Sanford at The Conversation: “Social media sites’ responses to the Facebook-Cambridge Analytica scandal and new European privacy regulations have given users much more control over who can access their data, and for what purposes. To me, as a social media user, these are positive developments: It’s scary to think what these platforms could do with the troves of data available about me. But as a researcher, increased restrictions on data sharing worry me.

I am among the many scholars who depend on data from social media to gain insights into people’s actions. In a rush to protect individuals’ privacy, I worry that an unintended casualty could be knowledge about human nature. My most recent work, for example, analyzes feelings people express on Twitter to explain why the stock market fluctuates so much over the course of a single day. There are applications well beyond finance. Other scholars have studied mass transit rider satisfaction, emergency alert systems’ function during natural disasters and how online interactions influence people’s desire to lead healthy lifestyles.

This poses a dilemma – not just for me personally, but for society as a whole. Most people don’t want social media platforms to share or sell their personal information, unless specifically authorized by the individual user. But as members of a collective society, it’s useful to understand the social forces at work influencing everyday life and long-term trends. Before the recent crises, Facebook and other companies had already been making it hard for legitimate researchers to use their data, including by making it more difficult and more expensive to download and access data for analysis. The renewed public pressure for privacy means it’s likely to get even tougher….

It’s true – and concerning – that some presumably unethical people have tried to use social media data for their own benefit. But the data are not the actual problem, and cutting researchers’ access to data is not the solution. Doing so would also deprive society of the benefits of social media analysis.

Fortunately, there is a way to resolve this dilemma. Anonymization of data can keep people’s individual privacy intact, while giving researchers access to collective data that can yield important insights.

There’s even a strong model for how to strike that balance efficiently: the U.S. Census Bureau. For decades, that government agency has collected extremely personal data from households all across the country: ages, employment status, income levels, Social Security numbers and political affiliations. The results it publishes are very rich, but also not traceable to any individual.

It often is technically possible to reverse anonymity protections on data, using multiple pieces of anonymized information to identify the person they all relate to. The Census Bureau takes steps to prevent this.

For instance, when members of the public access census data, the Census Bureau restricts information that is likely to identify specific individuals, such as reporting there is just one person in a community with a particularly high- or low-income level.

For researchers the process is somewhat different, but provides significant protections both in law and in practice. Scholars have to pass the Census Bureau’s vetting process to make sure they are legitimate, and must undergo training about what they can and cannot do with the data. The penalties for violating the rules include not only being barred from using census data in the future, but also civil fines and even criminal prosecution.

Even then, what researchers get comes without a name or Social Security number. Instead, the Census Bureau uses what it calls “protected identification keys,” a random number that replaces data that would allow researchers to identify individuals.

Each person’s data is labeled with his or her own identification key, allowing researchers to link information of different types. For instance, a researcher wanting to track how long it takes people to complete a college degree could follow individuals’ education levels over time, thanks to the identification keys.

Social media platforms could implement a similar anonymization process instead of increasing hurdles – and cost – to access their data…(More)” .

Data Detectives: More data and surveillance are transforming justice systems

Curated on June 13, 2018August 3, 2018 by Stefaan Verhulst

Special issue by The Economist: “…the relationship between information and crime has changed in two ways, one absolute, one relative. In absolute terms, people generate more searchable information than they used to. Smartphones passively track and record where people go, who they talk to and for how long; their apps reveal subtler personal information, such as their political views, what they like to read and watch and how they spend their money. As more appliances and accoutrements become networked, so the amount of information people inadvertently create will continue to grow.

To track a suspect’s movements and conversations, police chiefs no longer need to allocate dozens of officers for round-the-clock stakeouts. They just need to seize the suspect’s phone and bypass its encryption. If he drives, police cars, streetlights and car parks equipped with automatic number-plate readers (ANPRs, known in America as automatic licence-plate readers or ALPRs) can track all his movements.

In relative terms, the gap between information technology and policy gapes ever wider. Most privacy laws were written for the age of postal services and fixed-line telephones. Courts give citizens protection from governments entering their homes or rifling through their personal papers. The law on people’s digital presence is less clear. In most liberal countries, police still must convince a judge to let them eavesdrop on phone calls.

But mobile-phone “metadata”—not the actual conversations, but data about who was called and when—enjoy less stringent protections. In 2006 the European Union issued a directive requiring telecom firms to retain customer metadata for up to two years for use in potential crime investigations. The European Court of Justice invalidated that law in 2014, after numerous countries challenged it in court, saying that it interfered with “the fundamental rights to respect for private life”. Today data-retention laws vary widely in Europe. Laws, and their interpretation, are changing in America, too. A case before the Supreme Court will determine whether police need a warrant to obtain metadata.

Less shoe leather

If you drive in a city anywhere in the developed world, ANPRs are almost certainly tracking you. This is not illegal. Police do not generally need a warrant to follow someone in public. However, people not suspected of committing a crime do not usually expect authorities to amass terabytes of data on every person they have met and every business visited. ANPRs offer a lot of that.

To some people, this may not matter. Toplines, an Israeli ANPR firm, wants to add voice- and facial-recognition to its Bluetooth-enabled cameras, and install them on private vehicles, turning every car on the road into a “mobile broadcast system” that collects and transmits data to a control centre that security forces can access. Its founder posits that insurance-rate discounts could incentivise drivers to become, in effect, freelance roving crime-detection units for the police, subjecting unwitting citizens to constant surveillance. In answer to a question about the implications of such data for privacy, a Toplines employee shrugs: Facebook and WhatsApp are spying on us anyway, he says. If the stream of information keeps people safer, who could object? “Privacy is dead.”

It is not. But this dangerously complacent attitude brings its demise ever closer….(More)”.