Pricing Lives: Guideposts for a Safer Society

Curated on Posted on by Stefaan Verhulst

Book by W. Kip Viscusi: “Like it or not, sometimes we need to put a monetary value on people’s lives. In the past, government agencies used the financial “cost of death” to monetize the mortality risks of regulatory policies, but this method vastly undervalued life. Pricing Lives tells the story of how the government came to adopt an altogether different approach–the value of a statistical life, or VSL—and persuasively shows how its more widespread use could create a safer and more equitable society for everyone.

In the 1980s, W. Kip Viscusi used the method to demonstrate that the benefits of requiring businesses to label hazardous chemicals immensely outweighed the costs. VSL is the risk-reward trade-off that people make about their health when considering risky job choices. With it, Viscusi calculated how much more money workers would demand to take on hazardous jobs, boosting calculated benefits by an order of magnitude. His current estimate of the value of a statistical life is $10 million. In this book, Viscusi provides a comprehensive look at all aspects of economic and policy efforts to price lives, including controversial topics such as whether older people’s lives are worth less and richer people’s lives are worth more. He explains why corporations need to abandon the misguided cost-of-death approach, how the courts can profit from increased application of VSL in assessing liability and setting damages, and how other countries consistently undervalue risks to life.

Pricing Lives proposes sensible economic guideposts to foster more protective policies and greater levels of safety in the United States and throughout the world….(More)”.

Houston’s $6 Billion Census Problem: Frightened Immigrants

Curated on Posted on by Stefaan Verhulst

Natasha Rausch at Bloomberg: “At Houston’s City Hall last week, Mayor Sylvester Turner gathered with company CEOs, university professors, police officers, politicians and local judges to discuss a $6 billion problem they all have in common: the 2020 census.

City officials and business leaders are worried about people like 21-year-old Ana Espinoza, a U.S. citizen by birth who lives with undocumented relatives. Espinoza has no intention of answering the census because she worries it could expose her family and get them deported….

Getting an accurate count has broad economic implications across the city, said Laura Murillo, chief executive officer of the Hispanic Chamber. “For everyone, the census is important. It doesn’t matter if you’re a Republican or Democrat, black or white or green.”…

For growing businesses, the census is crucial for understanding the population they’re serving in different regions. Enterprise Rent-A-Car used the 2010 census to help diversify the company’s employee base. The data prompted Enterprise to staff a new location in Houston with Spanish-speaking employees to better serve area customers, said the company’s human resources manager Phil Dyson.

“It’s been one of our top locations,” he said.

Doing the Math

Texas stands to lose at least $1,161 in federal funding for each person not counted, according to a March report by Andrew Reamer, a research professor at the George Washington Institute of Public Policy. Multiplied by the estimated 506,000 unathorized immigrants who live in the nation’s fourth-largest city, that puts at stake about $6 billion for Houston over the 10 years the census applies.

That’s just for programs such as Medicare and Medicaid. The potential loss is even larger when grants are taken into account for items like highways and community development, he said…(More)”.

How Big Tech Is Working With Nonprofits and Governments to Turn Data Into Solutions During Disasters

Curated on Posted on by Stefaan Verhulst

Kelsey Sutton at Adweek: “As Hurricane Michael approached the Florida Panhandle, the Florida Division of Emergency Management tapped a tech company for help.

Over the past year, Florida’s DEM has worked closely with GasBuddy, a Boston-based app that uses crowdsourced data to identify fuel prices and inform first responders and the public about fuel availability or power outages at gas stations during storms. Since Hurricane Irma in 2017, GasBuddy and DEM have worked together to survey affected areas, helping Florida first responders identify how best to respond to petroleum shortages. With help from the location intelligence company Cuebiq, GasBuddy also provides estimated wait times at gas stations during emergencies.

DEM first noticed GasBuddy’s potential in 2016, when the app was collecting and providing data about fuel availability following a pipeline leak.

“DEM staff recognized how useful such information would be to Florida during any potential future disasters, and reached out to GasBuddy staff to begin a relationship,” a spokesperson for the Florida State Emergency Operations Center explained….

Stefaan Verhulst, co-founder and chief research and development officer at the Governance Laboratory at New York University, advocates for private corporations to partner with public institutions and NGOs. Private data collected by corporations is richer, more granular and more up-to-date than data collected through traditional social science methods, making that data useful for noncorporate purposes like research, Verhulst said. “Those characteristics are extremely valuable if you are trying to understand how society works,” Verhulst said….(More)”.

When AI Misjudgment Is Not an Accident

Curated on Posted on by Stefaan Verhulst

Douglas Yeung at Scientific American: “The conversation about unconscious bias in artificial intelligence often focuses on algorithms that unintentionally cause disproportionate harm to entire swaths of society—those that wrongly predict black defendants will commit future crimes, for example, or facial-recognition technologies developed mainly by using photos of white men that do a poor job of identifying women and people with darker skin.

But the problem could run much deeper than that. Society should be on guard for another twist: the possibility that nefarious actors could seek to attack artificial intelligence systems by deliberately introducing bias into them, smuggled inside the data that helps those systems learn. This could introduce a worrisome new dimension to cyberattacks, disinformation campaigns or the proliferation of fake news.

According to a U.S. government study on big data and privacy, biased algorithms could make it easier to mask discriminatory lending, hiring or other unsavory business practices. Algorithms could be designed to take advantage of seemingly innocuous factors that can be discriminatory. Employing existing techniques, but with biased data or algorithms, could make it easier to hide nefarious intent. Commercial data brokers collect and hold onto all kinds of information, such as online browsing or shopping habits, that could be used in this way.

Biased data could also serve as bait. Corporations could release biased data with the hope competitors would use it to train artificial intelligence algorithms, causing competitors to diminish the quality of their own products and consumer confidence in them.

Algorithmic bias attacks could also be used to more easily advance ideological agendas. If hate groups or political advocacy organizations want to target or exclude people on the basis of race, gender, religion or other characteristics, biased algorithms could give them either the justification or more advanced means to directly do so. Biased data also could come into play in redistricting efforts that entrench racial segregation (“redlining”) or restrict voting rights.

Finally, national security threats from foreign actors could use deliberate bias attacks to destabilize societies by undermining government legitimacy or sharpening public polarization. This would fit naturally with tactics that reportedly seek to exploit ideological divides by creating social media posts and buying online ads designed to inflame racial tensions….(More)”.

Lean Impact: How to Innovate for Radically Greater Social Good,

Curated on Posted on by Stefaan Verhulst

Book by Ann Mei Chang: “As we know all too well, the pace of progress is falling far short of both the desperate needs in the world and the ambitions of the Sustainable Development Goals. Today, it’s hard to find anyone who disputes the need for innovation for global development.

So, why does innovation still seem to be largely relegated to scrappy social enterprises and special labs at larger NGOs and funders while the bulk of the development industry churns on with business as usual?

We need to move more quickly to bring best practices such as the G7 Principles to Accelerate Innovation and Impact and the Principles for Digital Development into the mainstream. We know we can drive greater impact at scale by taking measured risks, designing with users, building for scale and sustainability, and using data to drive faster feedback loops.

In Lean Impact: How to Innovate for Radically Greater Social Good, I detail practical tips for how to put innovation principles into practice…(More)”.

The Big Blockchain Lie

Curated on Posted on by Stefaan Verhulst

Nouriel Roubini at Project Syndicate: “Blockchain has been heralded as a potential panacea for everything from poverty and famine to cancer. In fact, it is the most overhyped – and least useful – technology in human history.

In practice, blockchain is nothing more than a glorified spreadsheet. But it has also become the byword for a libertarian ideology that treats all governments, central banks, traditional financial institutions, and real-world currencies as evil concentrations of power that must be destroyed. Blockchain fundamentalists’ ideal world is one in which all economic activity and human interactions are subject to anarchist or libertarian decentralization. They would like the entirety of social and political life to end up on public ledgers that are supposedly “permissionless” (accessible to everyone) and “trustless” (not reliant on a credible intermediary such as a bank).

Yet far from ushering in a utopia, blockchain has given rise to a familiar form of economic hell. A few self-serving white men (there are hardly any women or minorities in the blockchain universe) pretending to be messiahs for the world’s impoverished, marginalized, and unbanked masses claim to have created billions of dollars of wealth out of nothing. But one need only consider the massive centralization of power among cryptocurrency “miners,” exchanges, developers, and wealth holders to see that blockchain is not about decentralization and democracy; it is about greed….

As for blockchain itself, there is no institution under the sun – bank, corporation, non-governmental organization, or government agency – that would put its balance sheet or register of transactions, trades, and interactions with clients and suppliers on public decentralized peer-to-peer permissionless ledgers. There is no good reason why such proprietary and highly valuable information should be recorded publicly.

Moreover, in cases where distributed-ledger technologies – so-called enterprise DLT – are actually being used, they have nothing to do with blockchain. They are private, centralized, and recorded on just a few controlled ledgers. They require permission for access, which is granted to qualified individuals. And, perhaps most important, they are based on trusted authorities that have established their credibility over time. All of which is to say, these are “blockchains” in name only.

It is telling that all “decentralized” blockchains end up being centralized, permissioned databases when they are actually put into use. As such, blockchain has not even improved upon the standard electronic spreadsheet, which was invented in 1979.1

No serious institution would ever allow its transactions to be verified by an anonymous cartel operating from the shadows of the world’s authoritarian kleptocracies. So it is no surprise that whenever “blockchain” has been piloted in a traditional setting, it has either been thrown in the trash bin or turned into a private permissioned database that is nothing more than an Excel spreadsheet or a database with a misleading name….(More)”.

Who represents the human in the digital age?

Curated on Posted on by Stefaan Verhulst

Anni Rowland-Campbell at NPC: “In his book The Code Economy Philip E. Auerswald talks about the long history of humans developing codeas a mechanism by which to create and regulate activities and markets.[1] We have Codes of Practice, Ethical Codes, Building Codes, and Legal Codes, just to name a few.

Each and every one of these is based on the data of human behaviour, and that data can now be collected, analysed, harvested and repurposed as never before through the application of intelligent machines that operate and are instructed by algorithms. Anything that can be articulated as an algorithm—a self-contained sequence of actions to be performed—is now fertile ground for machine analysis, and increasingly machine activity.

So, what does this mean for us humans who, are ourselves a conglomeration of DNA code? I have spent many years thinking about this. Not that long ago my friends and family tolerated my speculations with good humour, but a fair degree of scepticism. Now I run workshops for boards and even my children are listening far more intently. Because people are sensing that the invasion of the ‘Social Machine’ is changing our relationship with such things as privacy, as well as with both ourselves and each other. It is changing how we understand our role as humans.

The Social Machine is the name given to the systems we have created that blur the lines between computational processes and human input, of which the World Wide Web is the largest and best known example. These ‘smart machines’ are increasingly pervading almost every aspect of human existenceand, in many ways, getting to know us better than we know ourselves.

So who stands up for us humans? Who determines how society will harness and utilise the power of information technologies whilst ensuring that the human remain both relevant and important?…

Philanthropists must equip themselves with the knowledge they need in order to do good with digital

Consider the Luddites as they smashed the looms in the early 1800s. Their struggle is instructive because they were amongst the first to experience technological displacement. They sensed the degradation of human kind and they fought for social equality and fairness in the distribution of the benefits of science and technology to all. If knowledge is power, philanthropy must arm itself with knowledge of digital to ensure the power of digital lies with the many and not the few.

The best place to start in understanding the digital world as it stands now is to begin to see the world, and all human activities, through the lens of data and as a form of digital currency. This links back to the earlier idea of codes. Our activities, up until recently, were tacit and experiential, but now they are becoming increasingly explicit and quantified. Where we go, who we meet, what we say, what we do is all being registered, monitored and measured as long as we are connected to the digital infrastructure.

A new currency is emerging that is based on the world’s most valuable resource: data. It is this currency that connects the arteries and capillaries, and reaches across all disciplines and fields of expertise. The kind of education that is required now is to be able to make connections and to see the opportunities in the interstice between policy and day-to-day reality.

The dominant players in this space thus far have been the large corporations and governments that have harnessed and exploited digital currencies for their own benefit. Shoshana Zuboff describes this as the ‘surveillance economy’. But this data actually belongs to each and every human who generates it. As people begin to wake up to this we are gradually realising that this is what fuels the social currency of entrepreneurship, leadership and innovation, and provides the legitimacy upon which trust is based.

Trust is an outcome of experiences and interactions, but governments and corporations have transactionalised their interactions with citizens and consumer through exploiting data. As a consequence they have eroded the esteem with which they are held. The more they try to garner greater insights through data and surveillance, the more they alienate the people they seek to reach.

If we are smart what we need to do, as philanthropists, is to understand the fundamentals of data as a currency and integrate this in to each and every interaction we have. This will enable us to create relationships with the people that are based on the authenticity of purpose, supported by the data of proof. Yes, there have been some instances where the sector has not done as well as it could and betrayed that trust. But this only serves as a lesson as to how fragile the world of trust and legitimacy are. It shows how crucial it is that we define all that we do in terms of social outcomes and impact, however that is defined….(More)”

Getting the Work Done: What Government Innovation Really Looks Like

Curated on Posted on by Stefaan Verhulst

Report by Hana Schank and Sara Hudson: “…In 2017 and 2018, we interviewed problem-solvers working across federal, state, and local government in the United States on improving the state of government services. This movement is small compared to the number of government agencies running business as usual, but it is growing. Innovation teams, digital service teams, technologists, researchers, policymakers, lawyers, funders, and service designers are rethinking how government functions, reshaping how people solve problems, and helping to restore citizens’ faith in governing bodies.

We had both worked on these types of teams at the city and federal level, and wanted a holistic view of the work, its successes, and its challenges. We knew there were efforts across the country focused on making government work, but less work connecting the field. We had a hunch that these teams knew a lot. They had tested out strategies, saw what worked and what didn’t. We wanted to understand what all of that knowledge added up to when taken together.

Our original plan was simple: interview people “in the field” doing the work of making government work. Or work better. (We were flexible.) Ideally, find great success stories. Aggregate and distill them into lessons learned. Maybe make a playbook. Maybe make a report like this. Definitely write some pieces for national publications, because this kind of work inspires and expands through storytelling.

We focused on people improving government services through technology and citizen-centered thinking. We interviewed people from major cities to smaller locales; chief innovation officers and city managers to service designers, product managers, and engineers.

But after we started to do interviews and synthesis, we realized we had been asking the wrong questions. We wanted tactics on how to get the work done from people who had everything figured out. As it turns out, no one has it all figured out. As a community, we are still trying to answer the most basic questions. What do we call ourselves? This work? Is this a field? What do we really mean by innovation? With so much work to be done, where do we start? What’s the best way to hire people? What’s the best way to keep them once they’ve been hired? How do we affect culture change? How do we get the work done? How do we know when we’ve succeeded? How do we know when it’s time to quit?

What we have compiled in this report is neither a playbook nor a document with all the answers. Instead, this report reflects many of the things people often wonder about at work, whisper in corners at conferences, save in browser tabs, or jot in the margins at meetings to think over later: Where are we seeing solutions? Where are we seeing pain points? Who else is doing this? How are they approaching it? How do I find them?…One of the most important themes, which weaves into every piece of this report’s findings, is that people in government care. They want to make a difference, but often aren’t sure how. When given the chance to learn more, and to do better, they jump at it. We’re sharing this to lift up what many such people have learned about how to make change. We hope it inspires more people, cities, and government workers to follow suit….(More)”

Here’s What the USMCA Does for Data Innovation

Curated on Posted on by Stefaan Verhulst

Joshua New at the Center for Data Innovation: “…the Trump administration announced the United States-Mexico-Canada Agreement (USMCA), the trade deal it intends to replace NAFTA with. The parties—Canada, Mexico, and the United States—still have to adopt the deal, and if they do, they will enjoy several welcome provisions that can give a boost to data-driven innovation in all three countries.

First, USMCA is the first trade agreement in the world to promote the publication of open government data. Article 19.18 of the agreement officially recognizes that “facilitating public access to and use of government information fosters economic and social development, competitiveness, and innovation.” Though the deal does not require parties to publish open government data, to the extent they choose to publish this data, it directs them to adhere to best practices for open data, including ensuring it is in open, machine-readable formats. Additionally, the deal directs parties to try to cooperate and identify ways they can expand access to and the use of government data, particularly for the purposes of creating economic opportunity for small and medium-sized businesses. While this is a welcome provision, the United States still needs legislation to ensure that publishing open data becomes an official responsibility of federal government agencies.

Second, Article 19.11 of USMCA prevents parties from restricting “the cross-border transfer of information, including personal information, by electronic means if this activity is for the conduct of the business of a covered person.” Additionally, Article 19.12 prevents parties from requiring people or firms “to use or locate computing facilities in that Party’s territory as a condition for conducting business in that territory.” In effect, these provisions prevent parties from enacting protectionist data localization requirements that inhibit the flow of data across borders. This is important because many countries have disingenuously argued for data localization requirements on the grounds that it protects their citizens from privacy or security harms, despite the location of data having no bearing on either privacy or security, to prop up their domestic data-driven industries….(More)”.

A Right to Reasonable Inferences: Re-Thinking Data Protection Law in the Age of Big Data and AI

Curated on Posted on by Stefaan Verhulst

Paper by Sandra Wachter and Brent Mittelstadt: “Big Data analytics and artificial intelligence (AI) draw non-intuitive and unverifiable inferences and predictions about the behaviors, preferences, and private lives of individuals. These inferences draw on highly diverse and feature-rich data of unpredictable value, and create new opportunities for discriminatory, biased, and invasive decision-making. Concerns about algorithmic accountability are often actually concerns about the way in which these technologies draw privacy invasive and non-verifiable inferences about us that we cannot predict, understand, or refute.

Data protection law is meant to protect people’s privacy, identity, reputation, and autonomy, but is currently failing to protect data subjects from the novel risks of inferential analytics. The broad concept of personal datain Europe could be interpreted to include inferences, predictions, and assumptions that refer to or impact on an individual. If seen as personal data, individuals are granted numerous rights under data protection law. However, the legal status of inferences is heavily disputed in legal scholarship, and marked by inconsistencies and contradictions within and between the views of the Article 29 Working Party and the European Court of Justice.

As we show in this paper, individuals are granted little control and oversight over how their personal data is used to draw inferences about them. Compared to other types of personal data, inferences are effectively ‘economy class’ personal data in the General Data Protection Regulation (GDPR). Data subjects’ rights to know about (Art 13-15), rectify (Art 16), delete (Art 17), object to (Art 21), or port (Art 20) personal data are significantly curtailed when it comes to inferences, often requiring a greater balance with controller’s interests (e.g. trade secrets, intellectual property) than would otherwise be the case. Similarly, the GDPR provides insufficient protection against sensitive inferences (Art 9) or remedies to challenge inferences or important decisions based on them (Art 22(3))….

In this paper we argue that a new data protection right, the ‘right to reasonable inferences’, is needed to help close the accountability gap currently posed ‘high risk inferences’ , meaning inferences that are privacy invasive or reputation damaging and have low verifiability in the sense of being predictive or opinion-based. In cases where algorithms draw ‘high risk inferences’ about individuals, this right would require ex-ante justification to be given by the data controller to establish whether an inference is reasonable. This disclosure would address (1) why certain data is a relevant basis to draw inferences; (2) why these inferences are relevant for the chosen processing purpose or type of automated decision; and (3) whether the data and methods used to draw the inferences are accurate and statistically reliable. The ex-ante justification is bolstered by an additional ex-post mechanism enabling unreasonable inferences to be challenged. A right to reasonable inferences must, however, be reconciled with EU jurisprudence and counterbalanced with IP and trade secrets law as well as freedom of expression and Article 16 of the EU Charter of Fundamental Rights: the freedom to conduct a business….(More)”.