Paper by Julia M. Puaschunder: “The classic principal-agent problem in political science and economics describes agency dilemmas or problems when one person, the agent, is put in a situation to make decisions on behalf of another entity, the principal. A dilemma occurs in situations when individual profit maximization or principal and agent are pitted against each other. This so-called moral hazard is nowadays emerging in the artificial big data age, when big data reaping entities have to act on behalf of agents, who provide their data with trust in the principal’s integrity and responsible big data conduct. Yet to this day, no data fiduciary has been clearly described and established to protect the agent from misuse of data. This article introduces the agent’s predicament between utility derived from information sharing and dignity in privacy as well as hyper-hyperbolic discounting fallibilities to not clearly foresee what consequences information sharing can have over time and in groups. The principal’s predicament between secrecy and selling big data insights or using big data for manipulative purposes will be outlined. Finally, the article draws a clear distinction between manipulation and nudging in relation to the potential social class division of those who nudge and those who are nudged…(More)”.
Andrew Yang proposes that your digital data be considered personal property
Michael Grothaus at Fast Company: “2020 Democratic presidential candidate Andrew Yang may not be at the top of the race when it comes to polling (Politico currently has him ranked as the 7th most-popular Democratic contender), but his policies, including support for universal basic income, have made him popular among a subset of young, liberal-leaning, tech-savvy voters. Yang’s latest proposal, too, is sure to strike a chord with them.
The presidential candidate published his latest policy proposal today: to treat data as a property right. Announcing the proposal on his website, Yang lamented how our data is collected, used, and abused by companies, often with little awareness or consent from us. “This needs to stop,” Yang says. “Data generated by each individual needs to be owned by them, with certain rights conveyed that will allow them to know how it’s used and protect it.”
The rights Yang is proposing:
- The right to be informed as to what data will be collected, and how it will be used
- The right to opt out of data collection or sharing
- The right to be told if a website has data on you, and what that data is
- The right to be forgotten; to have all data related to you deleted upon request
- The right to be informed if ownership of your data changes hands
- The right to be informed of any data breaches including your information in a timely manner
- The right to download all data in a standardized format to port to another platform…(More)”.
A fairer way forward for AI in health care
Linda Nordling at Nature: “When data scientists in Chicago, Illinois, set out to test whether a machine-learning algorithm could predict how long people would stay in hospital, they thought that they were doing everyone a favour. Keeping people in hospital is expensive, and if managers knew which patients were most likely to be eligible for discharge, they could move them to the top of doctors’ priority lists to avoid unnecessary delays. It would be a win–win situation: the hospital would save money and people could leave as soon as possible.
Starting their work at the end of 2017, the scientists trained their algorithm on patient data from the University of Chicago academic hospital system. Taking data from the previous three years, they crunched the numbers to see what combination of factors best predicted length of stay. At first they only looked at clinical data. But when they expanded their analysis to other patient information, they discovered that one of the best predictors for length of stay was the person’s postal code. This was puzzling. What did the duration of a person’s stay in hospital have to do with where they lived?
As the researchers dug deeper, they became increasingly concerned. The postal codes that correlated to longer hospital stays were in poor and predominantly African American neighbourhoods. People from these areas stayed in hospitals longer than did those from more affluent, predominantly white areas. The reason for this disparity evaded the team. Perhaps people from the poorer areas were admitted with more severe conditions. Or perhaps they were less likely to be prescribed the drugs they needed.
The finding threw up an ethical conundrum. If optimizing hospital resources was the sole aim of their programme, people’s postal codes would clearly be a powerful predictor for length of hospital stay. But using them would, in practice, divert hospital resources away from poor, black people towards wealthy white people, exacerbating existing biases in the system.
“The initial goal was efficiency, which in isolation is a worthy goal,” says Marshall Chin, who studies health-care ethics at University of Chicago Medicine and was one of the scientists who worked on the project. But fairness is also important, he says, and this was not explicitly considered in the algorithm’s design….(More)”.
How cities can leverage citizen data while protecting privacy
MIT News: “India is on a path with dual — and potentially conflicting — goals related to the use of citizen data.
To improve the efficiency their municipal services, many Indian cities have started enabling government-service requests, which involves collecting and sharing citizen data with government officials and, potentially, the public. But there’s also a national push to protect citizen privacy, potentially restricting data usage. Cities are now beginning to question how much citizen data, if any, they can use to track government operations.
In a new study, MIT researchers find that there is, in fact, a way for Indian cities to preserve citizen privacy while using their data to improve efficiency.
The researchers obtained and analyzed data from more than 380,000 government service requests by citizens across 112 cities in one Indian state for an entire year. They used the dataset to measure each city government’s efficiency based on how quickly they completed each service request. Based on field research in three of these cities, they also identified the citizen data that’s necessary, useful (but not critical), or unnecessary for improving efficiency when delivering the requested service.
In doing so, they identified “model” cities that performed very well in both categories, meaning they maximized privacy and efficiency. Cities worldwide could use similar methodologies to evaluate their own government services, the researchers say. …(More)”.
Big Data, Political Campaigning and the Law
Book edited by Normann Witzleb, Moira Paterson, and Janice Richardson on “Democracy and Privacy in the Age of Micro-Targeting”…: “In this multidisciplinary book, experts from around the globe examine how data-driven political campaigning works, what challenges it poses for personal privacy and democracy, and how emerging practices should be regulated.
The rise of big data analytics in the political process has triggered official investigations in many countries around the world, and become the subject of broad and intense debate. Political parties increasingly rely on data analytics to profile the electorate and to target specific voter groups with individualised messages based on their demographic attributes. Political micro-targeting has become a major factor in modern campaigning, because of its potential to influence opinions, to mobilise supporters and to get out votes. The book explores the legal, philosophical and political dimensions of big data analytics in the electoral process. It demonstrates that the unregulated use of big personal data for political purposes not only infringes voters’ privacy rights, but also has the potential to jeopardise the future of the democratic process, and proposes reforms to address the key regulatory and ethical questions arising from the mining, use and storage of massive amounts of voter data.
Providing an interdisciplinary assessment of the use and regulation of big data in the political process, this book will appeal to scholars from law, political science, political philosophy, and media studies, policy makers and anyone who cares about democracy in the age of data-driven political campaigning….(More)”.
AI Global Surveillance Technology
Carnegie Endowment: “Artificial intelligence (AI) technology is rapidly proliferating around the world. A growing number of states are deploying advanced AI surveillance tools to monitor, track, and surveil citizens to accomplish a range of policy objectives—some lawful, others that violate human rights, and many of which fall into a murky middle ground.
In order to appropriately address the effects of this technology, it is important to first understand where these tools are being deployed and how they are being used.
To provide greater clarity, Carnegie presents an AI Global Surveillance (AIGS) Index—representing one of the first research efforts of its kind. The index compiles empirical data on AI surveillance use for 176 countries around the world. It does not distinguish between legitimate and unlawful uses of AI surveillance. Rather, the purpose of the research is to show how new surveillance capabilities are transforming the ability of governments to monitor and track individuals or systems. It specifically asks:
- Which countries are adopting AI surveillance technology?
- What specific types of AI surveillance are governments deploying?
- Which countries and companies are supplying this technology?
Learn more about our findings and how AI surveillance technology is spreading rapidly around the globe….(More)”.
How big data can affect your bank account – and life
Alena Buyx, Barbara Prainsack and Aisling McMahon at The Conversation: “Mustafa loves good coffee. In his free time, he often browses high-end coffee machines that he cannot currently afford but is saving for. One day, travelling to a friend’s wedding abroad, he gets to sit next to another friend on the plane. When Mustafa complains about how much he paid for his ticket, it turns out that his friend paid less than half of what he paid, even though they booked around the same time.
He looks into possible reasons for this and concludes that it must be related to his browsing of expensive coffee machines and equipment. He is very angry about this and complains to the airline, who send him a lukewarm apology that refers to personalised pricing models. Mustafa feels that this is unfair but does not challenge it. Pursuing it any further would cost him time and money.
This story – which is hypothetical, but can and does occur – demonstrates the potential for people to be harmed by data use in the current “big data” era. Big data analytics involves using large amounts of data from many sources which are linked and analysed to find patterns that help to predict human behaviour. Such analysis, even when perfectly legal, can harm people.
Mustafa, for example, has likely been affected by personalised pricing practices whereby his search for high-end coffee machines has been used to make certain assumptions about his willingness to pay or buying power. This in turn may have led to his higher priced airfare. While this has not resulted in serious harm in Mustafa’s case, instances of serious emotional and financial harm are, unfortunately, not rare, including the denial of mortgages for individuals and risks to a person’s general credit worthiness based on associations with other individuals. This might happen if an individual shares some similar characteristics to other individuals who have poor repayment histories….(More)”.
Sharenthood: Why We Should Think before We Talk about Our Kids Online
Book by Leah Plunkett: “Our children’s first digital footprints are made before they can walk—even before they are born—as parents use fertility apps to aid conception, post ultrasound images, and share their baby’s hospital mug shot. Then, in rapid succession come terabytes of baby pictures stored in the cloud, digital baby monitors with built-in artificial intelligence, and real-time updates from daycare. When school starts, there are cafeteria cards that catalog food purchases, bus passes that track when kids are on and off the bus, electronic health records in the nurse’s office, and a school surveillance system that has eyes everywhere. Unwittingly, parents, teachers, and other trusted adults are compiling digital dossiers for children that could be available to everyone—friends, employers, law enforcement—forever. In this incisive book, Leah Plunkett examines the implications of “sharenthood”—adults’ excessive digital sharing of children’s data. She outlines the mistakes adults make with kids’ private information, the risks that result, and the legal system that enables “sharenting.”
Plunkett describes various modes of sharenting—including “commercial sharenting,” efforts by parents to use their families’ private experiences to make money—and unpacks the faulty assumptions made by our legal system about children, parents, and privacy. She proposes a “thought compass” to guide adults in their decision making about children’s digital data: play, forget, connect, and respect. Enshrining every false step and bad choice, Plunkett argues, can rob children of their chance to explore and learn lessons. The Internet needs to forget. We need to remember….(More)”.
Study finds Big Data eliminates confidentiality in court judgements
Swissinfo: “Swiss researchers have found that algorithms that mine large swaths of data can eliminate anonymity in federal court rulings. This could have major ramifications for transparency and privacy protection.
This is the result of a study by the University of Zurich’s Institute of Law, published in the legal journal “Jusletter” and shared by Swiss public television SRF on Monday.
The study relied on a “web scraping technique” or mining of large swaths of data. The researchers created a database of all decisions of the Supreme Court available online from 2000 to 2018 – a total of 122,218 decisions. Additional decisions from the Federal Administrative Court and the Federal Office of Public Health were also added.
Using an algorithm and manual searches for connections between data, the researchers were able to de-anonymise, in other words reveal identities, in 84% of the judgments in less than an hour.
In this specific study, the researchers were able to identify the pharma companies and medicines hidden in the documents of the complaints filed in court.
Study authors say that this could have far-reaching consequences for transparency and privacy. One of the study’s co-authors Kerstin Noëlle Vokinger, professor of law at the University of Zurich explains that, “With today’s technological possibilities, anonymisation is no longer guaranteed in certain areas”. The researchers say the technique could be applied to any publicly available database.
Vokinger added there is a need to balance necessary transparency while safeguarding the personal rights of individuals.
Adrian Lobsiger, the Swiss Federal Data Protection Commissioner, told SRF that this confirms his view that facts may need to be treated as personal data in the age of technology….(More)”.
Government wants access to personal data while it pushes privacy
Sara Fischer and Scott Rosenberg at Axios: “Over the past two years, the U.S. government has tried to rein in how major tech companies use the personal data they’ve gathered on their customers. At the same time, government agencies are themselves seeking to harness those troves of data.
Why it matters: Tech platforms use personal information to target ads, whereas the government can use it to prevent and solve crimes, deliver benefits to citizens — or (illegally) target political dissent.
Driving the news: A new report from the Wall Street Journal details the ways in which family DNA testing sites like FamilyTreeDNA are pressured by the FBI to hand over customer data to help solve criminal cases using DNA.
- The trend has privacy experts worried about the potential implications of the government having access to large pools of genetic data, even though many people whose data is included never agreed to its use for that purpose.
The FBI has particular interest in data from genetic and social media sites, because it could help solve crimes and protect the public.
- For example, the FBI is “soliciting proposals from outside vendors for a contract to pull vast quantities of public data” from Facebook, Twitter Inc. and other social media companies,“ the Wall Street Journal reports.
- The request is meant to help the agency surveil social behavior to “mitigate multifaceted threats, while ensuring all privacy and civil liberties compliance requirements are met.”
- Meanwhile, the Trump administration has also urged social media platforms to cooperate with the governmentin efforts to flag individual users as potential mass shooters.
Other agencies have their eyes on big data troves as well.
- Earlier this year, settlement talks between Facebook and the Department of Housing and Urban Development broke down over an advertising discrimination lawsuit when, according to a Facebook spokesperson, HUD “insisted on access to sensitive information — like user data — without adequate safeguards.”
- HUD presumably wanted access to the data to ensure advertising discrimination wasn’t occurring on the platform, but it’s unclear whether the agency needed user data to be able to support that investigation….(More)”.