Black Boxes, Student Data & Playing Moneyball for Education

black-Box_2

We’re rapidly entering a world of evidence-based decision making in public education. These decisions will be powered by vast amounts of data run through proprietary black boxes that parents will have no way of understanding. The approach is called Moneyball and the goal is to justify ration resources to students –while investors make a tidy profit.

One of the most difficult challenges I’ve had as a parent is convincing other parents that the endless collection of our kids’ data isn’t benign and technology isn’t inherently benevolent.

Big Data, Like Big Brother, Isn’t Your Friend

As adults, we’ve chosen to ignore this cold hard fact: that by using electronic devices, we are allowing ourselves to become a product. Von Shoshana Zuboff calls this evolution in big data mediated economics surveillance capitalism:

It’s now clear that this shift in the use of behavioral data was an historic turning point. Behavioral data that were once discarded or ignored were rediscovered as what I call behavioral surplus. Google’s dramatic success in “matching” ads to pages revealed the transformational value of this behavioral surplus as a means of generating revenue and ultimately turning investment into capital. Behavioral surplus was the game-changing zero-cost asset that could be diverted from service improvement toward a genuine market exchange. Key to this formula, however, is the fact that this new market exchange was not an exchange with users but rather with other companies who understood how to make money from bets on users’ future behavior. In this new context, users were no longer an end-in-themselves.  Instead they became a means to profits in  a new kind of marketplace in which users are neither buyers nor sellers nor products.  Users are the source of free raw material that feeds a new kind of manufacturing process.

As adults we’re vaguely aware that certain choices we make will impact our credit report. The inputs seem arbitrary and frankly ridiculous. Unless, there’s a problem, THEN, the unfairness of the system quickly comes into focus.

How your credit report is determined is an example of a black box. Inputs go in, something happens inside the box, and then your credit report comes out. What happens inside the box? Who knows? It’s a proprietary predictive model.

What sorts of random digital bits could impacts your credit report? Things like what operating system you use, if you do your browsing using a desktop or cellphone, even what you decided to use as your email address.

This excerpt is from New Study Shows You Can Predict Credit Rating from Your Online Tech Fingerprint.

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Making Childhood Pay: Arthur Rolnick, Steven Rothschild, and ReadyNation

Reposted with permission from Wrench in the Gears.

Pre-K Teachers Heart Tech

The push for early childhood education access is NOT being driven by a desire to meet the basic human needs of children. Rather financial interests that view children as cogs in a national workforce development program are pushing it; and they see preschoolers as lumps of human capital to be plugged into economic forecasts. This is all happening at a time when human services are being privatized in the name of scalable, outcomes-driven social entrepreneurship. The trailer for a new documentary, The Invisible Heart, on social impact bonds indicates how much capital is flowing into this new market.

This post provides additional background on the ReadyNation Global Business Summit on Early Childhood Education that will take place at the Grand Hyatt hotel in New York City November 1-2, 2018. No U.S. educators or policy advocates may attend unless they come with at least four pre-approved business sponsors. Review the draft agenda here.

This is the second in a series. Read part one here.

Where did ReadyNation come from?

The idea emerged from a conversation three men had on a conference call during the summer of 2003:

  • Arthur Rolnick, senior researcher at the Minneapolis Federal Reserve
  • Robert Dugger, financial policy analyst and venture capitalist
  • James Heckman, University of Chicago economics professor

Its first incarnation, the “Investing in Kids Working Group,” focused on researching returns on early childhood investments, developing finance mechanisms, and crafting policy recommendations. Over the past fifteen years Dugger, in consultation with Heckman and Rolnick and with support from the Pew Charitable Trusts, gradually built a structure to undergird a global investment market fueled by debt associated with provision of early childhood education services.

The push for early childhood education access is NOT being driven by a desire to meet the basic human needs of children. Rather financial interests that view children as cogs in a national workforce development program are pushing it; and they see preschoolers as lumps of human capital to be plugged into economic forecasts. This is all happening at a time when human services are being privatized in the name of scalable, outcomes-driven social entrepreneurship. The trailer for a new documentary, The Invisible Heart, on social impact bonds indicates how much capital is flowing into this new market.

Arthur Rolnick, Steven Rothschild, and Pay for Performance

Much of my research has focused on the Boston area (global finance), the Bay Area (tech), Chicago (blockchain), and New York (urban policy). So I was surprised to find what may be a key piece of this puzzle actually comes out of Minneapolis Minnesota. Though perhaps the fact that Minnesota is home to the nation’s first charter school, City Academy that opened in St. Paul in 1992, indicates local conditions favor neoliberal reforms.

Arthur (Art) Rolnick spent his 40-year career as a senior economic researcher at the Minneapolis Federal Reserve Bank. During that time he also served as an associate professor in the economics department of the University of Minnesota and was co-director of the Human Capital Research Collaborative in the Humphrey School of Public Affairs. The Collaborative houses the Chicago Longitudinal Study whose researchers are tracking the short and long term effects of early intervention on 1,000 students who attended Chicago’s Child-Parent Centers in 1984-85.

The Chicago Child-Parent Centers were service providers for one of the nation’s first two early childhood social impact bonds, begun in December 2014. The Chicago SIB included payout metrics tied to third grade literacy scores. Thus far the program has issued maximum payments to investors including Pritzker, Goldman-Sachs and Northern Trust. According to this report from the Institute for Child Success, it is possible that over the seventeen-year time horizon for the SIB, $34 million could be paid out on the initial $16.9 investment.

Click here for the interactive version of this map.

Rolnick connected with Steven Rothschild, a former vice president at General Mills who left the corporate sector and launched Twin Cities RISE!, an “innovative anti-poverty” program that provided workforce training for low income adults, in the mid 1990s. Rothschild arranged with the state of Minnesota to provide services via an outcomes-based contracting arrangement where the organization was only paid when the “economic value” they provided to the state by increasing taxes (paid by those placed in jobs) and decreasing state expenditures (reduced costs for social services or incarceration) met approved targets.

Arthur Rolnick and Gary Stern of the Minneapolis Federal Reserve worked with Rothschild and Twin Cities Rise! to develop the economic analysis in support of the outcomes-based contracting initiative. Rolnick’s work with Rothschild eventually led him to examine the economic implications of early childhood interventions using data from the High/Scope Perry Preschool Study. In 2003, the year Rolnick had that auspicious phone call with Robert Dugger and James Heckman, he and and Rob Grunewald, regional economic analyst, put out the following report for the Minneapolis Federal Reserve: Early Childhood Development: Economic Development with a High Public Return.

In a 2006 profile of Rolnick, Minnesota journalist and blogger Kevin Featherly notes that report catalyzed $1 million in seed money for the Minnesota Early Learning Foundation, a project of the Minnesota Business for Early Learning. It also put Rolnick and Grunewald on the lecture circuit for the next several years where they touted early childhood education as a prudent economic investment. Weatherly likened Rolnick’s schedule after the release of the report to that of a presidential candidate, sharing the stage with Jeb Bush at the National Governor’s Convention, the head of the Gates Foundation at the National Council of State Legislatures, and presenting to a global audience at the World Bank.

Rothschild who served on the boards of the Greater Twin Cities United Way and Minneapolis Foundation, went on to found the consulting firm Invest in Outcomes and write the Non Non-Profit, a book that exhorted non-profits to focus on the Return on Investment (ROI) and measurable economic outcomes of the services they provide. These ideas eventually led the Minnesota legislature to adopt the “Pay for Performance Act” in 2011 that appropriated $10 million for a pilot program to develop Human Capital Performance Bonds or HuCaps.

Rothschild provides a detailed explanation of how HuCaps function in a 2013 article for the San Francisco Federal Reserve’s publication Community Development Investment Review. HuCaps differ from social impact bonds in that they are true bonds and tap into the state bond markets; which, in theory, could give them access to significantly more capital-trillions of dollars rather than millions. In this podcast with the St. Louis Federal Reserve, Rothschild describes the model developed by Twin Cities RISE! as the basis for much of the social impact investing activities that have emerged over the past decade.

Source for this slide.

As structured in the Minnesota legislation, the service provider is the one that takes the risk rather than the investor. If the provider is not able to meet the target metrics they are the ones who will not be paid. As a consequence, HuCaps have not yet taken off; see Propel Nonprofit’s analysis here.

Source for this slide.

Nevertheless, there are those who have not given up on the Human Capital Performance Bond approach. Arnold Packer, former director of the education reform and workforce development SCANS 2000 Center based out of Johns Hopkins University, wrote about HuCaps for the Brookings Institution in 2015 (the co-chair of the Commission on Evidence-Based Policy Making is Bruce Haskins also of Brookings). He noted that Milton Friedman was among the first to float the idea of leveraging private investment in human capital development. Take a minute to watch this one-minute video, from Institute for the Future, that portrays a college student contemplating entering into an income-sharing arrangement in exchange for tuition.

The idea that states could issue bonds for human capital in the same way they do for infrastructure like bridges, and that future savings will be created as people attain higher paying jobs due to their improved human capital, is central to the HuCap premise. In order to justify future cost savings, those receiving services must be tracked, so their “outcomes” can be measured over time. According to Arnold:

“This reform requires a shift in thinking on all sides, investors in human resources (early childhood education falls into this category) will have to consider statistically estimated benefits in terms of future cost savings and revenue as equivalent to projected revenue from a toll road. Government agencies will have to coordinate in order to structure attractive Human Resource bonds, since different agencies at different levels of government, benefit from the savings resulting from earlier investments.” Source

This model of finance, if ever widely adopted, would demand all recipients of public services (including education) be part of the government’s statistical estimate. Because many early-intervention services are directed at families, a person’s predictive profile would likely start to be amassed prenatally; babies assigned a Decentralized Identifier (DID), before they are even born. Estimates would be made about the likelihood a person would need to access services in the future, what those services would be, and what they would cost. Assessments would be made about the anticipated tax revenue a person would in turn generate over their lifetime. All of this data would need to be calculated in order to determine the impact metrics for the investors and structure “attractive human resource bonds.”

Before the rise of cloud-based computing, such a level of tracking would have been impossible. Having access to data to make those predictions would have been difficult to obtain. But that is rapidly changing in this world of Big Data, digital identity and “moneyball for kids.” The bi-partisan Commission on Evidence-Based Policy Making concluded public hearings in February 2017, and the vast majority of those providing testimony favored creating enormous pools of data to inform public policy decisions.

Evidence Based Policy Making

Read the report.

Responsibilities of the Commission on Evidence Based Policy Making:

Things seem to be on hold for the moment with Human Capital Performance Bonds, but I feel strongly they may be simply waiting in the wings until Blockchain sovereign identity is normalized. An Illinois state Blockchain task force (note Pritzker, backer of early childhood SIBs is running a well-funded campaign for governor of Illinois now) has developed preliminary recommendations linking public service benefits to citizens using Blockchain technology. They even envision building in behavioral incentives tied to the provision of services through digital economic platforms. See the diagram below for an illustration of how they might incentivize food purchases.

Read the report.

Of course the implications of this type of manipulation for people who live in food deserts with limited access to fresh produce remains unaddressed. And it doesn’t take a stretch of the imagination to see how other choices might be economically incentivized: which online course to take (the evidence-based one); which training program (the evidence-based one); which therapy provider (the evidence-based one); which medical treatment (the evidence-based one). But by whose measure? Who sets the metrics? Who profits when “evidence-based” standards are imposed?

How will independently-owned, neighborhood-based child care centers fare in this new landscape? If they are shuttered, what will the economic impacts be for communities, especially in economically distressed neighborhoods where such businesses are important sources of employment? Will small-scale providers be willing to collect the “human capital” data required to take advantage of pay for success investments? If they are willing, would they even have the money to purchase the technology (smart tables, anyone?) required to gather their “impact” evidence?

Rob Grunewald, Rolnick’s collaborater on the Federal Reserve Early Childhood paper, is on the ReadyNation Summit planning committee. Rolnick is part of a workshop, “Scalable Success Stories in Early Childhood Programs,” at 11:45 on Friday, November 2nd.

The “pay for performance” finance mechanism dreamed up by Rothschild and Rolnick in the 1990s is particularly well-suited to this age of Internet of Things data collection, surveillance, predictive analytics, financialization, and economic precocity. This is why we should all be very concerned about ReadyNation’s Global Business Summit on Early Childhood; especially because it so clearly discourages early childhood educators and policy advocates from attending.

Next up, Dr. James Heckman and the Institute for New Economic Thinking.

-Alison McDowell

 

“Smart and Surveilled:” Building Sanctuary Part 3

Reposted with permission from Wrench in the Gears.

smart and surveilled

The future is uncertain and unlikely to play out exactly as described. Nevertheless, we must begin to comprehend how technological developments combined with concentrated power and extreme income inequality are leading us to increasingly automated forms of oppression. My hope is that communities will begin to incorporate an understanding of this bigger picture into resistance efforts for public education and beyond. Let us join together, embracing our humanity, to fight the forces that would bring us to “lockdown.” How can we preserve our lives and those of our loved ones outside the data stream? How can we nurture community in a world where alienation is becoming normalized? What do we owe one another? What are we willing to risk? I have divided my story into seven parts. I hope you’ll read along and consider sharing it with others.

This installment highlights  smart city surveillance and the Internet of Things. Cam and Li’s lives, including their educational experiences, are shaped by ubiquitous algorithms that align their behaviors to the economic and social expectations put in place by the Solutionists. This is the third installment in the series. If you want to read from the beginning use this link to access the introduction and Part 1: Plugging In. The whole series can be accessed here: Link

Cam and Li have grown up in a world controlled by sensors and data. All day, every day sensors watch, track and transmit information. The devices that make up the vast web of Internet of Things are tiny, but their combined power is incalculable. The most common IoT sensor in the pre-lockdown years was the smart phone. Practically anyone over the age of ten had one. Acting as a sensor, people’s phones were a primary means of data collection, logging information about how people interacted with each other, with systems, and their physical world.

The first sensors were created to monitor global supply chain shipments. Then, corporate, government and academic researchers devised a dizzying array of sensors to transmit data about most aspects of the physical world and how people live their lives in it. Instead of tracking pallets on cargo ships, they now track people, buses, energy, animals, art, storm water runoff, even sounds and footsteps. Each processor gathers a particular type of information that can be merged into the data stream for analysis. Predictive analytics algorithms, complex mathematical equations that anticipate future outcomes, tap into the data stream. Such algorithms can be used to predict when the bulb in a streetlight will fail, when a storm sewer will overflow, or even where a crime will happen.

For years authorities quietly built datasets that digitally documented community life using police body cameras and later cameras embedded into robot patrols. It showed incredible hubris to roll out such a program under the guise of citizen protection. The cameras, of course, were always looking out at the people, not at the police. Even with footage, police were rarely held accountable for crimes committed. Meanwhile, all aspects of people’s daily lives were taken in; faces, routines, social connections; anything within the field of view of the camera was absorbed by Oracle.

That such data would be turned against citizens in times of civil unrest should have been anticipated. Some who lived in communities that had experienced the evolution of brutal policing were indeed skeptical, but many held on to the idea that the cameras were well intentioned. Cam’s mother vividly remembers the week of the lockdown, how teams were deployed strategically throughout the city in ways that made resistance futile. All those years, the police state’s neural networks had been “learning” their neighborhoods and their faces all in the name of public safety.

Post lockdown, sensors and technology have been integrated into more and more aspects of daily life, pressuring people to make “good decisions.” Strivers feel less and less in control of their daily activities. They await the next haptic pulse that will direct their attention and actions. Cam might crave a pint of chocolate ice cream, but her minder is watching the refrigerator and uses guilt to pressure her into choosing carrots and celery instead. If she doesn’t comply, it will most certainly go into her health data log. Maybe Li wants to sleep late. Well, the sleep monitor strives to keep her on a productive R.E.M. cycle, so it raises the shades in her bedroom and turns on the shower down the hall at the appropriate hour. Is Talia driving to the corner store when she should be walking? Well, her auto tracker knows, as does her step counter, which means her insurance providers know, too. Maybe she can get away with it early in the month, if she has time to make up her activity quota before the 31st. Resources for healthcare are so constrained that people must demonstrate through data that their personal routines and lifestyle choices optimize preventative health protocols.

The Nudge Unit is constantly looking for new ways to incorporate behavioral triggers and feedback loops into online education and VR platforms, too. Buzz, buzz, a text appears. “Cam needs more points on Skyward Skills. It’s time to log on.” Or the pulse monitor indicates Li is too tense. Buzz, buzz, “Take a mindfulness break kid,” breathe and reflect. Buzz, buzz, “Talia step away from the screen and walk around the block to avoid blood clots.” Action triggered, data logged, repeat has turned life into one unending Pavlovian experiment.

Existence has subtly shifted to align to the Solutionist outlook. Economic forecasters rely on people being rational actors as they develop financial projections, and if technology can be used as a tool to shape human behaviors and enforce “rationality,” it is all the better for the global financiers who generate their wealth by speculating on the lives of everyday people. For the strivers, optimization has erased freedom and personal agency.

In the post-labor era, people have become more valuable for the data they produce than for their capacity to do physical work. Thus all but the off-liners have been integrated into the global corporate value chain as commodities. With biometrically-enabled Citi Badges, Cam and Li are not unlike tagged calves or farmed salmon, managed and processed without agency or recourse; lives controlled for the profit of others. The bio capitalist economic model values them only to the extent that they contribute their digital labor to the Solutionists’ data-driven system of outcomes-based results.

Algorithms hold tremendous power over Cam and Li. Using data generated through the Internet of Things, Oracle can make predictions about the type of adults the children are likely to become. What their cost to society will be. What they might contribute as human capital. Should their family should fall into poverty, Oracle can evaluate how much profit there could be made providing services to “impact” their situation through Pay for Success contracts. Would the predicted rate of return on their lives justify expending the Global Coin required? The Solutionists say, “Just run the data; the data will tell us.”

Talia tries to shelter the family from the data stream as much as possible, but that is has proven difficult. Accessing any public services demands data. Walking outside means you are under surveillance. Even at home devices keep tabs. Data has also become a currency people use to supplement their insufficient Global Coin stipends. The pretense that a person “owns” their own data and can monetize it is supposed to make them feel better about their situation. It doesn’t. Each data transaction puts another piece of one’s soul on the auction block, scrutinized by a predatory system that thrives on want and suffering. And it’s always a buyer’s market. No person in need is going to get ahead selling bits of data. These transactions are just stopgaps until the next Citi Badge stipend hits, a release valve that has thus far kept rebellion at bay.

At first the sensors seemed innocuous, uploading information about when a trashcan was full or telling people where parking spots were available. There were sensors that monitored air quality and ones that made sure streetlights were efficiently managed. People were enthusiastic. But then came the noise sniffers, and the motion sensors, and the drones. Parks and recreation officials were brought on board and encouraged to incorporate cyborg roses into public landscape projects. When first introduced, people were astonished at Eleni Stavrinidou’s work transforming plants into transistors, and now there were rumors of computational forests being grown in remote outposts. Once plants had sensors, people started to get really worried.

Teachers never imagined how sensors would alter classrooms and eventually eliminate them altogether. Adoption of 1:1 devices eroded teacher autonomy until students were spending most of their day with volunteer aides, eyes glued to screens. The teachers that remained were left evaluating student data. In classes where teachers were still allowed to lecture, movement, vibrations and sounds were monitored through sensors embedded in seats. The aim? Supposedly to provide continual feedback regarding student engagement and quality of instruction, but everyone knew it was really to keep track of the content delivered and how students responded. It was chilling.

By that point, the last remaining veteran teachers abandoned the profession. Eventually teacher shortages, austerity budgets, and the corporate education lobby’s campaign for “anytime, anywhere” learning ushered in IoT-enabled learning ecosystems. No one had invested in public education infrastructure for years. Sending everyone home with a device meant there was no longer the expense of feeding poor children. Students too young to stay at home and whose parents were working strivers were packed off to community partners. These partners had been carefully prepared for their role providing standards-aligned summer and out of school time programs. Plus this approach brought education completely under the umbrella of social impact investing, which pleased the financiers. All in all it was a pretty seamless transition. Given how punitive the instruction had become, most felt a sense of relief when the time came to phase out schools entirely.

Ten years out Cam and Li, like the characters in Isaac Asimov’s short story The Fun They Had, have no idea what “going to school” means. Some nights before turning out the lights, Talia tells the girls stories that give them a glimpse into that past. Yet, it is so far removed from their reality that neither can imagine what it must have been like to learn with a group of other kids. To have a human teacher and books, and go to a school building and spend the day there is a frightening prospect. People live isolated lives. Encounters with others are carefully managed. To spend a full day as part of a group, talking no less, seems a perilous and fraught enterprise.

Now everyone is assigned an Artificial Intelligence (AI) “assistant,” a lifelong learning guide when they receive their first education voucher. Cam tolerates hers, but Li is another story. They have quite the adversarial relationship. Li accuses her AI of giving her assessments that underestimate her actual ability, so she has to spend days and days going over material she already knows. Her games are always shorting out at a critical moment, right before her points are logged. The algorithm gives her essays failing marks, even though her mom and Grandpa Rex both say she has a gift for creative writing. Cam says that because the companies are rolling out so many new programs, glitches just going to happen and to not take it personally. People have always had frustrations with their devices, from autocorrect fails to systems freezing unexpectedly, but now that devices control so much more of people’s lives their faults are harder to tolerate. Talia often finds herself having to get up from her work and do a hard shutdown of Li’s tablet to give them both a time out.

The AI conversational agents and the platforms that host them employ a variety of tactics to ensure that Cam, Li, and all the children remain on task. Devices record ISPs and timestamps for logins. Keystroke and facial recognition data is stored, too. Wearable and biometrics are part of the equation. The early headbands and wristbands were incredibly clunky, but five years in they switched to IoT temporary tattoos with sleek designs that prominently identify each child’s designated pathway and rank.

It’s a major milestone when a student attains enough credentials in their portfolio to upload and claim a pathway. The tattoos, not unlike military insignia, help communicate social order and expected etiquette when new people meet. A picture is worth a thousand words, and in a culture that is increasingly non-verbal, a pathway tattoo is an important tool.

To maintain order, the Solutionists knew behavioral engineering had to become central to the educational system. With little meaningful work, systematic mental health training was needed. They wanted people neither too depressed nor too rebellious. Resilience, and grit were traits instilled through apps and gamification; children’s mindsets tracked as closely as the knowledge they acquired. The system was calibrated to identify mental disorders and dissidents early, flagging them for intervention. Both Cam and Li knew kids who had been forcibly plugged into remediation, but it wasn’t discussed openly.

The isolation that resulted from cyber education took a toll on many. Social networks withered. Kids rarely spent time with friends face-to-face. Text-support only went so far in beating back the darkness. Suicide rates climbed, affecting younger and young children. Programmers scrambled to develop new monitoring procedures. The Global Well Being Program was a leader in the field, their cutting-edge algorithms effective, but expensive.

Despite the high cost, sector education officials from all but the poorest communities debited funds for the monitoring service directly from student vouchers to cover the cost. Timely intervention was a matter of life or death, and people were willing to pay. In the post-labor world, monitoring and treating depression was a growth market. Before long tele-therapy and mental-health VR surged past bio-pharmaceuticals as darlings of the venture capital investment crowd.

By 2025 most major and mid-size cities had become “smart cities,” integrating IoT sensors into a wide variety of infrastructure projects. In doing so, officials created a ubiquitous layer of surveillance across the public sphere. Now, in order to access communal spaces, residents had to acquiesce to being watched. Management of the complex IoT systems required expertise far beyond the in-house capacity of most cities; as a result, outsourcing to global corporations became commonplace.

Over time, voters found they had less and less voice in government. Officials kept up appearances for several election cycles, but it became obvious that technology companies like Sysko were really the ones in charge. People wanted to believe elections still mattered. The history modules made a point of expressing how hard people had fought for the right to vote and to fix problems like gerrymandering, but it the years leading up to lockdown it became a hollow exercise. Talia had memories as a teen of the media stirring up outrage over voting irregularities. Looking back, they should have realized something was amiss. The solution to this “problem” was to switch to voting on the Blockchain using Citi Badges. Of course that shift effectively shut all of the off-liners, those who had no badge, out of the process.

Democracy was exposed for the charade it had always been, and it became clear to all that they had been living under fascism for a very long time. The cloud-based computing, telecommunication, and global finance interests united under the Solutionist banner and ensured authoritarian control was firmly in place. Global law enforcement working through the Blockchain Collaborative backed the technocrats in their coup. Now for Cam and Li, voting was a topic touched upon briefly in history modules where it was framed as a messy process no longer suited to the well-structured, transparent society the Solutionists had devised.

As the end game neared, secure and exclusive sanctuaries modeled after billionaire and media mogul Richard Braddock’s island home began to appear. He was among the first to bring world thought leaders together to discuss ways to build and scale Blockchain applications. These thought leaders sold everyone a utopian vision of trust, transparency and collective support. Those purported values fell by the wayside, though, shortly after the lockdown.

People with knowledge of edge computing, IoT, and Blockchain deployment and who had the money constructed sensor free zones to which they could retreat. Of course kids like Cam and Li will never be able to obtain access to such sanctuaries. That world is limited to families that can afford the astronomical costs of having human teachers for their children, whose social networks are such that they don’t need citizen scores or e-portfolios to assert their value to society. Sometimes Cam and Li wonder about the sanctuary kids. Surely there aren’t many of them. Are they lonely? Do they feel isolated, too? Are they glad to be unplugged? Do they know about life on the outside, life on the ledger?

Continue to Part 4: Data Mining Life on the Ledger

Supplemental Links

Internet of Things IBM: Link

History of IoT Sensors: Link

What is Blockchain: Link

Supply Chain IoT: Link

Cash VS Digital Economy and Online Payments: Link

Sidewalk Labs: Link

Smart Cities / Noise Sniffer: Link

IoT and Predictive Policing: Link

Police Body Cameras and AI: Link and Link

Patrol Robots: Link

Street Lights and IoT: Link

IoT Parking: Link

Storm water IoT: Link

Smart Trash Cans: Link

Sensors and Smart Cities: Link

Cognitive Drones: Link

Cyborg Roses: Link

Internet of Battlefield Things: Link

Pay for Success and Big Data: Link

Blockchain Social Impact Token: Link

Human Capital Analytics: Link

Nudge Unit: Link and Link

Game Theory, Human Resources and Social Skills: Link

AI Nudge Bots: Link

Behavior Change for Good: Link

Haptic Devices: Link

Rational Choice and Behavioral Economics: Link

Education and Biocapitalism: Link

Behavioral Science and Social Impact: Link

Making Behavior Change Stick: Link

IoT Classrooms: Link

Sensors Determining Education Quality: Link

Affectiva Emotion Sensing Software: Link

Behavioral Biometrics: Link

World Well Being Project: Link

The Fun They HadLink

Device Use Behavior Tracking in Education: Link

Virtual Agents / USC Institute of Creative Technologies: Link

AI Conversational Agents / Amelia IP Soft: Link and Link

AI Teaching Assistant: Link

Conversational Agents / Articulab: Link

Applied Gaming and Mental Health: Link

Brainwave Data Collection: Link

IoT Tattoos / Duoskin: Link

Pathways to Prosperity / Jobs for the Future: Link

Characterlab / Grit: Link

CASEL / Social Emotional Learning: Link

Serious Games and Mental Health: Link

Government as Platform: Link and Link

IBM Smart Cities: Link

Cisco Smart Cities: Link

New York Smart City: Link

Blockchain Voting: Link

Neckar Island Blockchain Summit: Link

Edge Computing: Link

Blockchain Cryptoeconomics: Link

Blockchain Alliance: Link

-Alison McDowell