How Being Watched Changes How You Think


Article by Simon Makin: “In 1785 English philosopher Jeremy Bentham designed the perfect prison: Cells circle a tower from which an unseen guard can observe any inmate at will. As far as a prisoner knows, at any given time, the guard may be watching—or may not be. Inmates have to assume they’re constantly observed and behave accordingly. Welcome to the Panopticon.

Many of us will recognize this feeling of relentless surveillance. Information about who we are, what we do and buy and where we go is increasingly available to completely anonymous third parties. We’re expected to present much of our lives to online audiences and, in some social circles, to share our location with friends. Millions of effectively invisible closed-circuit television (CCTV) cameras and smart doorbells watch us in public, and we know facial recognition with artificial intelligence can put names to faces.

So how does being watched affect us? “It’s one of the first topics to have been studied in psychology,” says Clément Belletier, a psychologist at University of Clermont Auvergne in France. In 1898 psychologist Norman Triplett showed that cyclists raced harder in the presence of others. From the 1970s onward, studies showed how we change our overt behavior when we are watched to manage our reputation and social consequences.

But being watched doesn’t just change our behavior; decades of research show it also infiltrates our mind to impact how we think. And now a new study reveals how being watched affects unconscious processing in our brain. In this era of surveillance, researchers say, the findings raise concerns about our collective mental health…(More)”.

How we think about protecting data


Article by Peter Dizikes: “How should personal data be protected? What are the best uses of it? In our networked world, questions about data privacy are ubiquitous and matter for companies, policymakers, and the public.

A new study by MIT researchers adds depth to the subject by suggesting that people’s views about privacy are not firmly fixed and can shift significantly, based on different circumstances and different uses of data.

“There is no absolute value in privacy,” says Fabio Duarte, principal research scientist in MIT’s Senseable City Lab and co-author of a new paper outlining the results. “Depending on the application, people might feel use of their data is more or less invasive.”

The study is based on an experiment the researchers conducted in multiple countries using a newly developed game that elicits public valuations of data privacy relating to different topics and domains of life.

“We show that values attributed to data are combinatorial, situational, transactional, and contextual,” the researchers write.

The open-access paper, “Data Slots: tradeoffs between privacy concerns and benefits of data-driven solutions,” is published today in Nature: Humanities and Social Sciences Communications. The authors are Martina Mazzarello, a postdoc in the Senseable City Lab; Duarte; Simone Mora, a research scientist at Senseable City Lab; Cate Heine PhD ’24 of University College London; and Carlo Ratti, director of the Senseable City Lab.

The study is based around a card game with poker-type chips the researchers created to study the issue, called Data Slots. In it, players hold hands of cards with 12 types of data — such as a personal profile, health data, vehicle location information, and more — that relate to three types of domains where data are collected: home life, work, and public spaces. After exchanging cards, the players generate ideas for data uses, then assess and invest in some of those concepts. The game has been played in-person in 18 different countries, with people from another 74 countries playing it online; over 2,000 individual player-rounds were included in the study…(More)”.

DOGE’s Growing Reach into Personal Data: What it Means for Human Rights


Article by Deborah Brown: “Expansive interagency sharing of personal data could fuel abuses against vulnerable people and communities who are already being targeted by Trump administration policies, like immigrants, lesbian, gay, bisexual, and transgender (LGBT) people, and student protesters. The personal data held by the government reveals deeply sensitive information, such as people’s immigration status, race, gender identity, sexual orientation, and economic status.

A massive centralized government database could easily be used for a range of abusive purposes, like to discriminate against current federal employees and future job applicants on the basis of their sexual orientation or gender identity, or to facilitate the deportation of immigrants. It could result in people forgoing public services out of fear that their data will be weaponized against them by another federal agency.

But the danger doesn’t stop with those already in the administration’s crosshairs. The removal of barriers keeping private data siloed could allow the government or DOGE to deny federal loans for education or Medicaid benefits based on unrelated or even inaccurate data. It could also facilitate the creation of profiles containing all of the information various agencies hold on every person in the country. Such profiles, combined with social media activity, could facilitate the identification and targeting of people for political reasons, including in the context of elections.

Information silos exist for a reason. Personal data should be collected for a determined, specific, and legitimate purpose, and not used for another purpose without notice or justification, according to the key internationally recognized data protection principle, “purpose limitation.” Sharing data seamlessly across federal or even state agencies in the name of an undefined and unmeasurable goal of efficiency is incompatible with this core data protection principle…(More)”.

Trump Wants to Merge Government Data. Here Are 314 Things It Might Know About You.


Article by Emily Badger and Sheera Frenkel: “The federal government knows your mother’s maiden name and your bank account number. The student debt you hold. Your disability status. The company that employs you and the wages you earn there. And that’s just a start. It may also know your …and at least 263 more categories of data.These intimate details about the personal lives of people who live in the United States are held in disconnected data systems across the federal government — some at the Treasury, some at the Social Security Administration and some at the Department of Education, among other agencies.

The Trump administration is now trying to connect the dots of that disparate information. Last month, President Trump signed an executive order calling for the “consolidation” of these segregated records, raising the prospect of creating a kind of data trove about Americans that the government has never had before, and that members of the president’s own party have historically opposed.

The effort is being driven by Elon Musk, the world’s richest man, and his lieutenants with the Department of Government Efficiency, who have sought access to dozens of databases as they have swept through agencies across the federal government. Along the way, they have elbowed past the objections of career staff, data security protocols, national security experts and legal privacy protections…(More)”.

Privacy-Enhancing and Privacy-Preserving Technologies in AI: Enabling Data Use and Operationalizing Privacy by Design and Default


Paper by the Centre for Information Policy Leadership at Hunton (“CIPL”): “provides an in-depth exploration of how privacy-enhancing technologies (“PETs”) are being deployed to address privacy within artificial intelligence (“AI”) systems. It aims to describe how these technologies can help operationalize privacy by design and default and serve as key business enablers, allowing companies and public sector organizations to access, share and use data that would otherwise be unavailable. It also seeks to demonstrate how PETs can address challenges and provide new opportunities across the AI life cycle, from data sourcing to model deployment, and includes real-world case studies…

As further detailed in the Paper, CIPL’s recommendations for boosting the adoption of PETs for AI are as follows:

Stakeholders should adopt a holistic view of the benefits of PETs in AI. PETs deliver value beyond addressing privacy and security concerns, such as fostering trust and enabling data sharing. It is crucial that stakeholders consider all these advantages when making decisions about their use.

Regulators should issue more clear and practical guidance to reduce regulatory uncertainty in the use of PETs in AI. While regulators increasingly recognize the value of PETs, clearer and more practical guidance is needed to help organizations implement these technologies effectively.

Regulators should adopt a risk-based approach to assess how PETs can meet standards for data anonymization, providing clear guidance to eliminate uncertainty. There is uncertainty around whether various PETs meet legal standards for data anonymization. A risk-based approach to defining anonymization standards could encourage wider adoption of PETs.

Deployers should take steps to provide contextually appropriate transparency to customers and data subjects. Given the complexity of PETs, deployers should ensure customers and data subjects understand how PETs function within AI models…(More)”.

Europe’s GDPR privacy law is headed for red tape bonfire within ‘weeks’


Article by Ellen O’Regan: “Europe’s most famous technology law, the GDPR, is next on the hit list as the European Union pushes ahead with its regulatory killing spree to slash laws it reckons are weighing down its businesses.

The European Commission plans to present a proposal to cut back the General Data Protection Regulation, or GDPR for short, in the next couple of weeks. Slashing regulation is a key focus for Commission President Ursula von der Leyen, as part of an attempt to make businesses in Europe more competitive with rivals in the United States, China and elsewhere. 

The EU’s executive arm has already unveiled packages to simplify rules around sustainability reporting and accessing EU investment. The aim is for companies to waste less time and money on complying with complex legal and regulatory requirements imposed by EU laws…Seven years later, Brussels is taking out the scissors to give its (in)famous privacy law a trim.

There are “a lot of good things about GDPR, [and] privacy is completely necessary. But we don’t need to regulate in a stupid way. We need to make it easy for businesses and for companies to comply,” Danish Digital Minister Caroline Stage Olsen told reporters last week. Denmark will chair the work in the EU Council in the second half of 2025 as part of its rotating presidency.

The criticism of the GDPR echoes the views of former Italian Prime Minister Mario Draghi, who released a landmark economic report last September warning that Europe’s complex laws were preventing its economy from catching up with the United States and China. “The EU’s regulatory stance towards tech companies hampers innovation,” Draghi wrote, singling out the Artificial Intelligence Act and the GDPR…(More)”.

Differential Privacy


Open access book by  Simson L. Garfinkel: “Differential privacy (DP) is an increasingly popular, though controversial, approach to protecting personal data. DP protects confidential data by introducing carefully calibrated random numbers, called statistical noise, when the data is used. Google, Apple, and Microsoft have all integrated the technology into their software, and the US Census Bureau used DP to protect data collected in the 2020 census. In this book, Simson Garfinkel presents the underlying ideas of DP, and helps explain why DP is needed in today’s information-rich environment, why it was used as the privacy protection mechanism for the 2020 census, and why it is so controversial in some communities.

When DP is used to protect confidential data, like an advertising profile based on the web pages you have viewed with a web browser, the noise makes it impossible for someone to take that profile and reverse engineer, with absolute certainty, the underlying confidential data on which the profile was computed. The book also chronicles the history of DP and describes the key participants and its limitations. Along the way, it also presents a short history of the US Census and other approaches for data protection such as de-identification and k-anonymity…(More)”.

Conflicts over access to Americans’ personal data emerging across federal government


Article by Caitlin Andrews: “The Trump administration’s fast-moving efforts to limit the size of the U.S. federal bureaucracy, primarily through the recently minted Department of Government Efficiency, are raising privacy and data security concerns among current and former officials across the government, particularly as the administration scales back positions charged with privacy oversight. Efforts to limit the independence of a host of federal agencies through a new executive order — including the independence of the Federal Trade Commission and Securities and Exchange Commission — are also ringing alarm bells among civil society and some legal experts.

According to CNN, several staff within the Office of Personnel Management’s privacy and records keeping department were fired last week. Staff who handle communications and respond to Freedom of Information Act requests were also let go. Though the entire privacy team was not fired, according to the OPM, details about what kind of oversight will remain within the department were limited. The report also states the staff’s termination date is 15 April.

It is one of several moves the Trump administration has made in recent days reshaping how entities access and provide oversight to government agencies’ information.

The New York Times reports on a wide range of incidents within the government where DOGE’s efforts to limit fraudulent government spending by accessing sensitive agency databases have run up against staffers who are concerned about the privacy of Americans’ personal information. In one incident, Social Security Administration acting Commissioner Michelle King was fired after resisting a request from DOGE to access the agency’s database. “The episode at the Social Security Administration … has played out repeatedly across the federal government,” the Times reported…(More)”.

On Privacy and Technology


Book by Daniel J. Solove: “With the rapid rise of new digital technologies and artificial intelligence, is privacy dead? Can anything be done to save us from a dystopian world without privacy?

In this short and accessible book, internationally renowned privacy expert Daniel J. Solove draws from a range of fields, from law to philosophy to the humanities, to illustrate the profound changes technology is wreaking upon our privacy, why they matter, and what can be done about them. Solove provides incisive examinations of key concepts in the digital sphere, including control, manipulation, harm, automation, reputation, consent, prediction, inference, and many others.

Compelling and passionate, On Privacy and Technology teems with powerful insights that will transform the way you think about privacy and technology…(More)”.

Empowering open data sharing for social good: a privacy-aware approach


Paper by Tânia Carvalho et al: “The Covid-19 pandemic has affected the world at multiple levels. Data sharing was pivotal for advancing research to understand the underlying causes and implement effective containment strategies. In response, many countries have facilitated access to daily cases to support research initiatives, fostering collaboration between organisations and making such data available to the public through open data platforms. Despite the several advantages of data sharing, one of the major concerns before releasing health data is its impact on individuals’ privacy. Such a sharing process should adhere to state-of-the-art methods in Data Protection by Design and by Default. In this paper, we use a Covid-19 data set from Portugal’s second-largest hospital to show how it is feasible to ensure data privacy while improving the quality and maintaining the utility of the data. Our goal is to demonstrate how knowledge exchange in multidisciplinary teams of healthcare practitioners, data privacy, and data science experts is crucial to co-developing strategies that ensure high utility in de-identified data…(More).”