Category Archives: Ethical Data Use

Aeon: AI, virtual assistants, and emotional intelligence

We’ve talked a lot in Data Literacy in the Real World: Conversations and Case Studiesand in our 2017 and 2018 conferences. Digital assistants like Amazon’s Alexa offer a cool device at an accessible price, but there’s so much more to unpack behind those high-tech cylinders.

Do you want to bare it all to a digital assistant? What happens when we outsource our emotional soothing to a machine? How are today’s devices being coded to reflect the culture of their users? These are some of the questions referenced in The Quantified Heart,” an essay on Aeon by Polina Aronson and Judith Duportail. Here are a few excerpts to whet your appetite for the entire essay:

[A]n increasing number of people are directing such affective statements, good and bad, to their digital helpmeets. According to Amazon, half of the conversations with the company’s smart-home device Alexa are of non-utilitarian nature – groans about life, jokes, existential questions. ‘People talk to Siri about all kinds of things, including when they’re having a stressful day or have something serious on their mind,’ an Apple job ad declared in late 2017, when the company was recruiting an engineer to help make its virtual assistant more emotionally attuned. ‘They turn to Siri in emergencies or when they want guidance on living a healthier life.’

Some people might be more comfortable disclosing their innermost feelings to an AI. A study conducted by the Institute for Creative Technologies in Los Angeles in 2014 suggests that people display their sadness more intensely, and are less scared about self-disclosure, when they believe they’re interacting with a virtual person, instead of a real one. As when we write a diary, screens can serve as a kind of shield from outside judgment.

Soon enough, we might not even need to confide our secrets to our phones. Several universities and companies are exploring how mental illness and mood swings could be diagnosed just by analysing the tone or speed of your voice … By 2022, it’s possible that ‘your personal device will know more about your emotional state than your own family,’ said Annette Zimmermann, research vice-president at the consulting company Gartner, in a company blog post …

[N]either Siri or Alexa, nor Google Assistant or Russian Alisa, are detached higher minds, untainted by human pettiness. Instead, they’re somewhat grotesque but still recognisable embodiments of certain emotional regimes – rules that regulate the ways in which we conceive of and express our feelings.

These norms of emotional self-governance vary from one society to the next … Google Assistant, developed in Mountain View, California looks like nothing so much as a patchouli-smelling, flip-flop-wearing, talking-circle groupie. It’s a product of what the sociologist Eva Illouz calls emotional capitalism – a regime that considers feelings to be rationally manageable and subdued to the logic of marketed self-interest. Relationships are things into which we must ‘invest’; partnerships involve a ‘trade-off’ of emotional ‘needs’; and the primacy of individual happiness, a kind of affective profit, is key. Sure, Google Assistant will give you a hug, but only because its creators believe that hugging is a productive way to eliminate the ‘negativity’ preventing you from being the best version of yourself …

By contrast, Alisa [a Russian-language assistant] is a dispenser of hard truths and tough love; she encapsulates the Russian ideal: a woman who is capable of halting a galloping horse and entering a burning hut (to cite the 19th-century poet Nikolai Nekrasov). Alisa is a product of emotional socialism, a regime that, according to the sociologist Julia Lerner, accepts suffering as unavoidable, and thus better taken with a clenched jaw rather than with a soft embrace. Anchored in the 19th-century Russian literary tradition, emotional socialism doesn’t rate individual happiness terribly highly, but prizes one’s ability to live with atrocity.

Alisa’s developers understood the need to make her character fit for purpose, culturally speaking. ‘Alisa couldn’t be too sweet, too nice,’ Ilya Subbotin, the Alisa product manager at Yandex, told us. ‘We live in a country where people tick differently than in the West. They will rather appreciate a bit of irony, a bit of dark humour, nothing offensive of course, but also not too sweet’ …

Every answer from a conversational agent is a sign that algorithms are becoming a tool of soft power, a method for inculcating particular cultural values. Gadgets and algorithms give a robotic materiality to what the ancient Greeks called doxa: ‘the common opinion, commonsense repeated over and over, a Medusa that petrifies anyone who watches it,’ as the cultural theorist Roland Barthes defined the term in 1975. Unless users attend to the politics of AI, the emotional regimes that shape our lives risk ossifying into unquestioned doxa …

So what could go wrong? Despite their upsides, emotional-management devices exacerbate emotional capitalism …These apps promote the ideal of the ‘managed heart’, to use an expression from the American sociologist Arlie Russell Hochschild …

Instead of questioning the system of values that sets the bar so high, individuals become increasingly responsible for their own inability to feel better. Just as Amazon’s new virtual stylist, the ‘Echo Look’, rates the outfit you’re wearing, technology has become both the problem and the solution. It acts as both carrot and stick, creating enough self-doubt and stress to make you dislike yourself, while offering you the option of buying your way out of unpleasantness . . .

[I]t’s worth reflecting on what could happen once we offload these skills on to our gadgets.



Sharing Bear Locations with Tourists … On a Delay

Photo of black bear standing in grass

Here’s a snip of a cool article from the Smithsonian that reminds us that while data collection and sharing can be great, sometimes data’s immediacy can cause new problems and it’s important to put the brakes on. Sure, park rangers at Yosemite want to help visitors learn what bears do and how they move, so why not share the GPS data of some bears? At the same time, some tourists to the park, armed with real-time data, might use it to find bears … and that disrupts things. From the article:

Hundreds of black bears amble through … Yosemite National Park in California … [N]ow, thanks to a new tracking system, fans of the furry animals can follow the creatures’ meandering paths—from the safety of their couch.

As Scott Smith of the Associated Press reports, the park recently launched a website called Keep Bears Wild. One of the site’s main features is the aptly-named “Bear Tracker,” which traces the steps of bears that have been fitted with GPS collars. But the animals’ locations are delayed, Ryan F. Mandelbaum reports for Gizmodo, so curious humans aren’t tempted to scout the bears out. Rangers can turn the data on and off, and tracks will be removed during fall and winter to ensure that the bears can hibernate peacefully.

The goal of the project is to educate the public and whet the appetite of bear enthusiasts, without putting anyone in danger …

These may seem like intuitive precautions, but bears are repeatedly threatened by their interactions with humans. More than 400 of Yosemite’s bears have been hit by cars since 1995, according to the Keep Bears Wild site. And bears that feast on human food can become aggressive, forcing rangers to kill them “in the interest of public safety,” the site explains.

While the Bear Tracker provides limited data to the general public, it is also useful to park rangers, who can view the bears’ steps in real time. For the past year, a team led by wildlife biologist Ryan Leahy has been using the technology to track bears on iPads and computers, according to Ezra David Romero of Valley Public Radio News. And as Smith reports, rangers can follow GPS signals and block bears before they reach campsites.

The tracking devices also help rangers learn more about black bears’ behavior. The animals can traverse more than 30 miles in two days, the data suggests, and easily scale the 5,000-foot walls of Yosemite’s canyons. The trackers have revealed that the bears begin mating in May—one month earlier than previously thought.

An interesting ethics reminder that there are times when better access data could be unintentionally harmful …

Image: Public domain from

2017 Conference dates chosen!

Decorative - 4T Data Literacy conference logo

We’re excited to announce that the 2017 4T Data Literacy Virtual Conference dates have been announced! We’ll meet virtually on July 20-21, 2017. This year, we’re focusing our presentations on three (and a half) themes:

  1. Big Data, including citizen science
  2. Ethical data use
  3. Personal data management

Registration and more details will be forthcoming soon. If you registered last year, you’re already on our list and will let you know when it’s time to sign up!

Reading Recommendation: Predictive Analytics

When used to make predictions, data can be quite powerful! A common example is the story of the retailer Target’s prediction of a customer’s pregnancy. When the company sent coupons for baby products to a teen, her father complained. However, it turned out that she was indeed pregnant. Such stories can be impressive and concerning. In addition to learning trends and patterns from data, data can lead to new information. In the case of Target and the teen, the store did not just know what the teen bought. Those data suggested more information: her pregnancy. As Eric Siegel writes:

[t]his isn’t a case of mishandling, leaking, or stealing data. Rather, it is the generation of new data, the indirect discovery of unvolunteered truths about people. Organizations predict these powerful insights from existing innocuous data, as if creating them out of thin air.

To understand how predictive analytics work, Siegel provides a wealth of examples and in-depth explanations in Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die. Understanding how organizations glean information from data and use that information helps us understand marketing and decisionmaking today. It also helps us manage our personal data.


Source: Siegel, Eric. Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die. Hoboken, New Jersey: John Wiley & Sons, 2013.

Image: “Women Grocery Shopping.jpg” by Bill Branson (Photographer), on Wikimedia Commons. Public Domain. 

Reading Recommendation: What Stays in Vegas

One industry that uses personal data from customers is gaming. Through loyalty programs, casinos can glean information about people to customize advertising and services. Adam Tanner describes this practice in What Stays in Vegas: The World of Personal Data–Lifeblood of Big Bussiness–and the End of Privacy as We Know It:

Boosted by vast banks of computers, Caesars today know the names of the vast majority of their clients, exactly how much they spend, where they like to spend it, how often they come, and many other characteristics. They even know exactly where many of their customers are at a given moment–whether they are sitting at a specific Wheel of Fortune slot machine or playing blackjack in the wee hours of the morning. They gather all these details with the consent of those who choose to participate in their loyalty program.

Loyalty programs supply your personal data to the companies with which you sign up for them. This book made me think twice about signing up for and using loyalty programs, despite their benefits, because they require giving up so much information about my habits. I had no idea!

In What Stays in Vegas, Tanner also brings up ethical issues, such as the justifications that commercial companies have for tracking people. He questions where the line between creepy and useful is. Tanner proposes that consumers should be able to see what data that private companies have and that privacy policies should be provided consistently and recognizably. Check out his appendix for actionable ways to control your personal data, such as using an email address that does not identify you by name for communications from commercial companies and signing up for the Do Not Call Registry.

What are ways that you limit your personal data sharing? Do you participate in loyalty programs?


Source: Tanner, Adam. What Stays in Vegas: The World of Personal Data–Lifeblood of Big Bussiness–and the End of Privacy as We Know It. New York: PublicAffairs, a Member of the Perseus Book Group, 2014.

Image: “A view of the card tables inside the casino” by Kym Koch Thompson, on Wikipedia. CC BY 2.0. 

Reading Recommendation: Data and Goliath

Where are your data stored, and who has control of your data?

The answer to this question is not always straightforward. We don’t always know whose eyes are on our data. For example, cell phone data reside on servers of private companies. A lot of information can be gleaned from data, from your location to your relationships.

Bruce Schneier writes about surveillance via data in Data and Goliath: The Hidden Battles to Collect Your Data and Control Your World. For anyone curious about what data that companies and the government keep and monitor, it is a fascinating read.

One of Schneier’s points is about security and privacy, which pertain to data. Access to data, like cell phone logs, can reduce privacy but support security. He writes:   

[o]ften the debate is characterized as “security versus privacy.” This simplistic view requires us to make some kind of fundamental trade-off between the two: in order to become secure, we must sacrifice our privacy and subject ourselves to surveillance. And if we want some level of privacy, we must recognize that we must sacrifice some security in order to get it.

However, this contrast between security and privacy might not be necessary. Schneier goes on to point out that:

[i]t’s a false trade-off. First, some security measures require people to give up privacy, but others don’t impinge on privacy at all: door locks, tall fences, guards, reinforced cockpit doors on airplanes. When we have no privacy, we feel exposed and vulnerable; we feel less secure. Similarly, if our personal spaces and records are not secure, we have less privacy. The Fourth Amendment of the US Constitution talks about ‘the right of the people to be secure in the persons, houses, papers, and effects’… . Its authors recognized that privacy is fundamental to the security of the individual.

More generally, our goal shouldn’t be to find an acceptable trade-off between security and privacy, because we can and should maintain both together.

Schneier’s book is illuminating for considering personal data management (one of the themes for the upcoming second year of our project in 2016-2017!) in light of data use by commercial companies and government. Schneier takes a philosophical approach to discussing data, security, and privacy. He concludes with useful tips for protecting your data. Read Data and Goliath for some great food for thought!

Source: Schneier, Bruce. Data and Goliath: The Hidden Battles to Collect Your Data and Control Your World. New York: W.W. Norton & Company, 2015.

Image: “People Lens White Eye Large” by, on Pexels. CC0 Public Domain. 

Team member Debbie Abilock on online youth privacy and big data

This post is Part 2 in a two-part series highlighting our team members’ work with Choose Privacy Week. This initiative of the American Library Association puts a spotlight on issues of privacy in today’s digital world, such as tracking in online searches. Knowing how your data are used is a component of data literacy, and we are excited to feature our team members’ blog posts on these topics.

Debbie wrote with Rigele Abilock about online privacy policies and data collection on the Choose Privacy Week blog. Data collection by vendors can affect students, as they explain:

Reconciling big data opportunities with healthcare privacy concerns is the same dilemma we face in education. Instructors want to support personalized learning, instruction, and classroom management with online offerings – but the data of underage patrons hangs in the balance. Just as health profiling based on longitudinal data collection raises red flags, so does educational performance profiling. Ethically and practically, youth will always be our Achilles Heel.

Knowing what data vendors are collecting can be difficult to discern. Debbie and Rigele advise a close examination of their Terms of Service and Privacy Policy:

The Privacy Policy is an on-the-ground description of how the vendor operates its site, and should be read in conjunction with the Terms of Service.  A link to the Privacy Policy must be placed on the vendor’s homepage and/or product page.  The Privacy Policy is a working picture of the company’s current and expected practices related to data use, collection, and sharing, as well as marketing, advertising, access, and security control. While a Privacy Policy lacks the contractual element of a click-through signature, it remains the primary declaration of the company’s privacy practices, and thus may be enforceable against a vendor that breaches those standard practices. Through a close reading of the Privacy Policy, you should be able to learn a great deal about a vendor’s privacy standards; if the language is overly complex or contorted, treat that as indicative of what a vendor may want you to know, or not.

And so we come to intention. Close reading of a Terms of Service and Privacy Policy must be augmented by your common-sense evaluation of a vendor’s corporate intention. Both for-profit and non-profit entities may choose to embed trackers into Web pages to collect information such as navigation patterns and preferences. Certain trackers, such as Facebook’s “like” thumb and Twitter’s blue bird, are visible, but most are hidden.  Sometimes these trackers follow the user to other sites to gain additional insight, in order to create a better user experience. Specifically, trackers may run tests on differences in language and image use, look for ways to improve navigation, and fix technical problems.

Check out their post for some practical tips on monitoring what information vendors collect!

Image: “Freedom from Surveillance — Choose Privacy Week 2012,” American Library Association, on Choose Privacy Week

Team member Connie Williams on privacy and teens

This post is Part 1 in a two-part series highlighting our team members’ work with Choose Privacy Week. This initiative of the American Library Association puts a spotlight on issues of privacy in today’s digital world, such as tracking in online searches. Knowing how your data are used is a component of data literacy, and we are excited to feature our team members’ blog posts on these topics.

Connie wrote about the traces that online actions leave and how they affect teens on the Choose Privacy Week blog. Here is an excerpt from her piece:

…there are universal norms that our students must know about their online presence: what you post can describe you, once a post leaves your device it is no longer in your control, and there is indeed, a digital footprint that gets left behind.

What this means for children and teens is that their online lives can follow them through their offline lives. If they post provocative things or mean things or negative things, they will be perceived by their online friends as those things; even if they are none of those things in their offline lives. One of the hardest ideas for teens to grasp sometimes is the idea that they are often creating a ‘body of work’ that can define them to others.

Online work can certainly have broad implications. Being active online, and managing privacy at the same time, are not always easy, though. Connie suggests establishing norms:

…it is important that we begin thinking about how we will allow our growing children online access while still keeping them protected. While online security is not a typical survival necessity, it is one that can impact our children. As adults, the information we share about our children with our own friends and families is the first step to modeling positive online behavior. Setting up norms that children learn to follow and understand – ‘hand holding’ –  will allow parents and educators to loosen that grip, enabling them to expand their access as they grow and demonstrate their abilities to participate positively.

Instruction on best practices for students can take a variety of forms, and Connie goes on to provide examples. Thanks, Connie!

Image: “Choose Privacy Week 2013,” American Library Association, on Choose Privacy Week

In the News: Internet privacy

In what ways do you limit your data sharing? Do you join or avoid loyalty rewards programs that track your habits? Do you block or regularly clean out cookies in your browser? Those steps are some areas where you have control over your information. Yet, data sharing to third parties is sometimes out of your hands or buried in the fine print of services that you use.

This last week, the Federal Communications Commission proposed new rules to give you a choice to opt out of data sharing to third parties by your Internet service provider. While this rule does not apply to sharing by websites, as critics point out, it does take a step toward consumer control of data sharing in the United States. It will be interesting to see what comes of this possibility!

Image: “Binary Map Internet Technology World Digital” by Pete Linforth on Pixabay. CC0 Public Domain.

The Polling Rodeo: Predicting Election Results and Democracy

By Billy Hathorn (Own work) [CC BY 3.0 (], via Wikimedia Commons

“While Mr. Sanders led New Hampshire polls for the last month, and Mr. Trump was ahead here since July, the wave of support for both men was nonetheless stunning to leaders of both parties who believed that in the end, voters would embrace more experienced candidates like Mrs. Clinton or one of the Republican governors in the race.”  — New York Times, 2/9/2016

“Donald Trump was at the top of each of the last 10 polls in Iowa, but his lead failed to hold up on caucus night Monday. In the end, his seven-point lead in polling averages amounted to a three-point loss to Ted Cruz.” — New York Times, 2/2/2016,

“Imagine that you’re a member of Congress, I said, and you’re about to head into the House to vote on an act—let’s call it the Smeadwell-Nutley Act. As you do, you use an app called iThePublic to learn the opinions of your constituents. You oppose Smeadwell-Nutley; your constituents are seventy-nine per cent in favor of it. Your constituents will instantly know how you’ve voted, and many have set up an account with Crowdpac to make automatic campaign donations. If you vote against the proposed legislation, your constituents will stop giving money to your reëlection campaign. If, contrary to your convictions but in line with your iThePublic, you vote for Smeadwell-Nutley, would that be democracy?” — The New Yorker, 11/16/2015,

So … It’s been an interesting week (or year!) for polling and predicting who will be President.  One of the reasons that the grant team felt like the time was right for providing data literacy, professional development to librarians was because of the election in the not-too-distant future.  Interpreting polling data is vital to helping our students become informed citizens.

Why do polls “get it wrong” or surprise people?  Charles Wheelan In Naked Statistics (one of our “homework books” ) does a great job explaining where things can go wrong in polling.  In addition to the points made by Nate Cohn  from the New York Times regarding who is taking the polls — flawed voter models, unrepresentative samples, the influence of late-breaking events — Wheelan encourages us to look closer at the questions and answers in these surveys …

  • Have the questions been posed in a way that elicits accurate information on the topic of interest?
  • Are respondents telling the truth?

When so much seems to be riding on perception in this election (look at what happened in the Midterm election and how people’s perception of the economy informed how they voted), opinion polls matter.  Jill Lepore writes in the New Yorker that “Polling may never have been less reliable, or more influential, than it is now.”  The public relies on the media to provide them with a good sense of what’s going on in the world.  Data science paired with data literacy skills can do that.  Misinterpreted survey data or polls conducted unethically leads people to draw conclusions that may just reinforce partisan beliefs (again, see what happened in the Midterms).

Yes … I know … There are whole graduate programs devoted to the methodology of conducting surveys — Programs that might cover how to conduct good opinion polls!  But in this wild rodeo of an election where BOTH sides have voters who are bull-headed, I think teaching high schoolers to ask basic questions like “Who is answering the questions in this survey?” and “How might  the format of this question influence the answer?” are good strategies as they move forward to become informed citizens and not just partisan, rodeo clowns.

Image:  File:Post, TX, Stampede Rodeo stadium IMG 1722.JPG by Billy Hathorn on Wikimedia Commons.  CC BY 3.0.