From Bill Gates to BigQuery, From Blockchain to Hashgraph
In my recent article series, I document how the US Department of Education’s emergency COVID rules for “Distance Learning and Innovation” (85 FR 18638) have deregulated the federal requirements for “adaptive learning” and other ed-tech forms of “artificial intelligence” that are now being bankrolled by floods of stimulus money from the Coronavirus Aid, Relief, and Economic Security (CARES) Act.
I’ve also documented how such CARES-financed ed-tech, including adaptive-learning and socioemotional-feedback technologies, are set up to be data-mined through public-private partnerships that are being funded by the Bill and Melinda Gates Foundation’s campaign to “Reimagine Education.”
Through Gates-funded corporate-government partnerships, such as the Gates Foundation’s joint venture with New York Governor Andrew Cuomo and Eric Schmidt, who is a “Technical Advisor” at Google’s Alphabet Inc., the Reimagine Education initiative is building a “surveillance capitalist” infrastructure of Big Data to facilitate the tracking of students’ cognitive-behavioral and socioemotional algorithms into “Social Credit” systems which will track the “trustworthiness” of students’ psychological profiles in order to dictate not only their access to “career pathways” curriculums that determine job placement, but also their access to healthcare, transportation, housing, due process, and even food.
Take a look at a key pillar of the Reimagine Education project: a Gates-funded partnership with the New York-based non-profit corporation, InnovateEDU, which has developed a “Connector” app to help with COVID e-learning by linking Google’s BigQuery database to Google Suite for Education (GSFE) in order to streamline the data-mining of student and teacher psychometrics collected by Google Classroom for the purposes of developing “predictive learning analytics” that “personalize” virtual schooling. For a window into how BigQuery is primed to track students’ cognitive-behavioral and socioemotional learning analytics from Google Classroom into “Social Credit” or “Trust Score” databases, consider how BigQuery has recently teamed up with a burgeoning “distributed ledger technology (DLT)” corporation known as Hedera Hashgraph, which refers to itself as “a future built on trust.”
Hedera Hashgraph, which recently appointed Google to its Governing Council, has also recently partnered with ChainLink: a DLT “middleware” company that also contracts directly with Google’s BigQuery through Google Cloud Platform (GCP). ChainLink, which connects hashgraph and blockchain DLTs together while pulling “off-chain” data, such as BigQuery and other Google Cloud data, provides the “middleware” integration necessary to build ubiquitous DLT infrastructure capable of monetizing, or tokenizing all human behavioral data into digitalized “cryptocurrencies” that can be converted into Social Credit Scores, or Trust Scores, which dictate access to both the civil processes of the “public square” and the commercial exchanges of private business.
In brief, the Gates-financed Reimagine Education project is bankrolling public-private partnerships with edu-corporations such as InnovateEDU, which is setting up digital data-mining that funnels student-teacher data directly from Google Classroom into BigQuery, which is Chainlinked to Hedera Hashgraph: one of the “fastest growing” DLT platforms which can monetize, or tokenize, an exhaustive array of behavioral data, including workforce-training data, through “smart contracts” that calculate “Trust algorithms” for Social Credit.
A “Social Credit” Singularity?
In my book, School World Order: The Technocratic Globalization of Corporatized Education, I forecast how public departments of education, criminal justice, and health and human services will be merged together through corporate-government partnerships that utilize Big Data to track students for “lifelong learning” in a technocratic digital caste system managed by “Social Credit” algorithms. Now, emergency COVID policies, such as digital “contact tracing” and “distance learning” data-mining, are accelerating the techno-fascist merger of education, healthcare, and criminal justice into a panopticon system of Social Credit surveillance managed by DLTs.
But what is Social Credit? For a case study in Social Credit technocracy, behold China’s Sesame Credit System controlled by the Alibaba Corporation, which partners with the USA’s BlackRock Inc.: the “world’s largest asset management firm.”
China’s Social Credit System is a mass-surveillance system that uses biometric facial/voice-recognition cameras to track citizens’ public behaviors in real time while data-mining the citizens’ social media profiles, financial statuses, criminal histories, educational backgrounds, and other public records in order to digitally rank the people with Social Credit Scores which determine not only access to loans and luxury items, but also access to employment, healthcare, housing, education, transportation, online dating services, and even food. It should be noted that, in China, educational records include logs of students’ socioemotional-learning algorithms that are tracked by measuring the students’ brainwaves through “Focus1” EEG headbands engineered by Harvard neuroscientists who partner with the BrainCo Corporation: an ed-tech company financed by the China Electronics Corporation, which classifies itself as “one of the key state-owned conglomerates directly under the administration of central government, and the largest state-owned IT company in China.”
Advocates of Social Credit tout this system of surveillance capitalism as an innovative and efficient means of using technology to condition people to behave in officially “trustworthy” manners. However, according to the Globe and Mail, China’s “social-credit system is being used to silence dissent” as award-winning journalist, Liu Hu, who was listed on Reporters Without Borders’ 2014 list of “One Hundred News Heroes,” was “barred from buying property, taking out a loan or travelling on the country’s top-tier trains” as a consequence of accrued “fines” resulting from his reporting. Meanwhile, China has been issuing punitive Social Scores that “blacklist” people who belong to “illegal social organisations” which the Chinese government deems to be in violation of “correct political direction.” One example of a “blacklisted” social organization is a Turkic-Islamic ethnic “minority” group known as the Uyghurs. Located in China’s Western province of Xinjiang, the Uyghurs are targeted by social creditors who operate detention camps that re-educate these Turkic-Islamic people by brainwashing them into self-censoring their own ethnic-religious identities in order to conform to the “correct political direction” of the Chinese Communist Party.
Now that COVID-19 panic is prompting draconian lockdowns to ostensibly mitigate the spread of the virus, the Alibaba company that runs China’s Social Credit system is expanding their network to track digital “immunity passports” which the Chinese people must download through cellphone “contact tracing” apps that use green, yellow, and red color codes to determine whether people can travel or whether they must be quarantined.
If you think Social Credit Scores that track students’ brainwaves and immunization records can’t happen here in the USA, consider how American schools are already attempting to manage the post-COVID “New Normal” by integrating an arsenal of new “distance learning” and “contact tracing” technologies which collect troves of not only students’ learning analytics, but also their biological and mental health data, including their “socioemotional” biometrics and psychometrics. Essentially, the US school system is building the same Big Data surveillance grid as the Chinese Social Credit infrastructure, which is itself funded by globalist American finance corporations such as BlackRock. In fact, Joe Biden has nominated two BlackRock executives for his presidential cabinet: Brian Deese, the “Global Head of Sustainable Investing” at BlackRock, is appointed to be Biden’s Director of the US National Economic Council; and Biden’s US Deputy Secretary of the Treasury will be BlackRock Senior Advisor, Adewale Adeyemo, who was President Barack Obama’s chief negotiator for the Trans-Pacific Partnership. At the same time, China’s Focus1 BrainCo headbands have been gaining traction in the US at the 2020 Consumer Electronics Show in Las Vegas where investors from the United States have promoted the use of BrainCo’s EEG headbands in American schools.
In brief, the only thing missing from the USA’s Social Credit infrastructure is the legislative greenlight to digitally plug all educational, healthcare, and criminal justice data into Big Databases that aggregate all these psychometrics and biometrics into Social Scores, or Trust Scores, which technocratically micromanage every aspect of human behavior in real time for the purposes of centralized workforce planning and social engineering.
Reimagine “Social Credit” by Spending CARES Money to Pay for Deregulated AI Data-Mining
As the CARES Act dishes out hundreds of millions of stimulus dollars to pay schools to “upgrade” their technology infrastructures under the newly deregulated rules for federal “Distance Learning and Innovation” (85 FR 18638), massive pools of students’ cognitive-behavioral and socioemotional algorithms are being tracked and traced into Big Databases, such as BigQuery, Learnsphere, and Cortex. These Big Data enterprises “reimagine education” by deploying artificial intelligence to scan students’ psychometrics for the purposes of calculating “predictive learning analytics” that could be converged with healthcare and criminology datasets to build digital psychological profiles for Social Credit dossiers.
To be sure, there is a network of data collaboration between Cortex, Learnsphere, and Google’s BigQuery through the Gates Foundation’s public-private “reimagine” partnership with New York Governor Andrew Cuomo and Eric Schmidt, who is an “advisor” at Alphabet Inc., which is Google’s parent company. In particular, the Gates Foundation is financing the New York-based InnovateEDU, which just developed a “Connector” application that links student data from Google Classroom to Google’s BigQuery repository where large datasets are aggregated together for the purposes of conducting broadscale predictive analytics that can be fed into “Social Credit DLTs.” Meanwhile, InnovateEDU owns and operates Cortex ed-tech, which integrates a “student information system (SIS),” a “learning management system (LMS),” and a “formative assessment engine” into a distributed learning-analytics platform. At the same time, InnovateEDU’s Cortex is partnering with Learnsphere: another massive “learning science” datahub that aggregates student and teacher data for the purposes of engineering “personalized” AI ed-tech.
data on when your student starts and stops a lesson, the responses your student makes to questions asked, the timing of your student’s responses, your student’s choice of lessons to play as ‘Performance Data.’ We will use Performance Data to (1) measure your student’s performance in each lesson within Cortex and to provide data for the school to adapt the programs to his or her learning needs and (2) improve Cortex and learning objects contained within the programs in Cortex. In addition, we may aggregate your student’s Performance Data with the Performance Data of other students participating in the Programs for marketing and other business related [sic] purposes.
In addition, Cortex, which utilizes a Google OAUTH “authenticator” app, “may aggregate the information that we collect from users of our website to create demographic and performance profiles regarding student’s [sic] progress in Cortex. InnovateEDU may share aggregated information with marketing professionals or potential investors.”
As the Gates-financed InnovateEDU traffics student data through its Cortex and Google’s BigQuery, the latter plugs into “distributed ledger technologies” designed for Trust Scores and Social Credit while the former is linked up with Learnsphere’s “distributed infrastructure,” which consists of several interconnected datahubs, including an
Educational Data Mining Workbench [which] support[s] learning scientists to perform a number of analytic tasks including 1) define and modify behavior categories of interest (e.g., gaming, unresponsiveness, off-task conversation, help avoidance), 2) label previously collected educational log data with the categories of interest, 3) validate inter-rater reliability between multiple labelers of the same educational log data corpus, and 4) provide support for running the labeled data through a machine-learning tool, such as WEKA or RapidMine.
To simplify, Learnsphere’s “Data Mining Workbench” aggregates student data so that “learning scientists” can evolve “personalized” AI ed-tech through a “machine-learning tool” that scans “learning analytics” from students’ “behavior categories,” such as cognitive-behavioral stimulus-response algorithms and socioemotional-feedback algorithms which track “unresponsiveness, off-task conversation, help avoidance,” etc.
According to Learnsphere’s LearnLab DataShops, the “learning scientists” who are eligible to access Learnsphere’s digital edu-conditioning databanks include “Educational data miner[s],” such as “Computer scientist[s], Psychometrician[s], [and] Learning analytics researcher[s]”; “Course developer[s] [and] Educational technology researcher[s],” such as “ITS/AIED researcher[s] [and] User modeling researcher[s]”; and “Psychologist[s],” such as “Cognitive scientist[s] [and] Educational psychologist[s].” In brief, Learnsphere’s distributed databases are collated so that “learning engineers” can synthesize massive pools of students’ psychological data for the purposes of evolving adaptive-learning and SEL-feedback algorithms to build artificial intelligence for ed-tech which will supply building blocks for a panopticon of Social Credit surveillance wherein students are permanently “graded” on every aspect of their behavior for “lifelong learning” both inside and outside of the classroom.
In sum, as COVID lockdown forces schools to convert classroom learning to virtual online learning subsidized by federal CARES funds that pay for deregulated AI ed-tech which data-mines student psychometrics, the Gates Foundation is bankrolling public-private partnerships with educational non-profit corporations like InnovateEDU, which networks with Big Data infrastructures, such as BigQuery and Cortex, the latter of which links up with Learnsphere. In turn, this proliferating network of “distributed” Big Databases is being set up to streamline the flood of student and teacher data pouring through the new CARES-funded ed-tech infrastructure so that the total spectrum of psychometric “learning analytics” will be ripe for tracking in a Chinese-style Social Credit technocracy.
How Google’s BigQuery Is Being Linked to Hedera Hashgraph’s “Trust Algorithms”
If you think that Chinese-style Social Credit surveillance could never happen here in America, note that this “distributed” infrastructure of educational Big Data is already being integrated with blockchain, hashgraph, and other “distributed ledger technologies (DLTs)” which can monetize, or tokenize, any data (including psychometric learning analytics) transferred through “smart contracts.” By connecting Google’s BigQuery to Hedera Hashgraph, student and teacher data extracted from InnovateEDU’s Google Classroom Connector could be channeled through BigQuery into Hedera’s DLT platform, which is being tethered to other blockchain and “off chain” networks through Chainlink oracles in order to distribute cryptocurrencies across a broad range of DLTs that can monetize, or tokenize, a wide array of data through “smart contracts” that can be converted into Social Credit or Trust Scores.
BigQuery, which compiles Google Classroom data transmitted through InnovateEDU’s “Connector” app, has recently been plugged into the burgeoning DLT network of Hedera Hashgraph: the next generation of decentralized ledgers that can process cryptocurrency transactions at a rate over 800 times faster than Ethereum and more than 3,000 times faster than Bitcoin’s pioneer blockchain. Through Hedera-ETL (“extract, transfer, load”) applications, Google’s BigQuery database tabulates “smart contracts” that have been transacted through the “mainnet” of Hedera Hashgraph, which describes itself as “the trust layer of the internet.” By advertising its DLT as “a future built on trust,” Hedera’s BigQuery-backed system of data-authentication echoes the ominous “Social Credit” rhetoric of Apple’s iPhone “Trust Scores,” which track user data to purportedly prevent “fraud.”
As Bill Gates and Google executive Eric Schmidt reimagine education via public-private partnerships that expand Google’s BigQuery into a massive repository for data-mining students’ learning analytics through Google Classroom, BigQuery will be caching students’ psychometrics into a Big Database linked directly to the Hedera Hashgraph DLT, which monetizes, or tokenizes, “smart contract” data into cryptocurrencies and authenticated “trust” algorithms. At the same time, Hedera Hashgraph uses Google Cloud Platform (GCP) to transmit “smart contracts” and other data transactions into BigQuery through Hedera’s ETL apps and other open-source “mirror nodes.” According to a blog post authored by the Hedera Hashgraph Team on July 7, 2020, “Hedera-ETL populates a BigQuery dataset with transactions and records generated by the Hedera mainnet or testnet, pulled from public AWS [Amazon Web Services] and GCP buckets” in order to “integrate both real-time and historical network data directly into . . . business applications—whether it’s for audit support, transaction analytics, visibility services, security threat modeling, data monetization services, or something entirely different.” It should be noted here that the Google corporation was appointed to Hedera’s Governing Council on February 11, 2020.
Chainlinking BigQuery and Hashgraph to “Off-Chain” and Blockchain Data, Including China’s BSN
This Google Cloud-based Hedera-BigQuery network is also being built to integrate a vast array of data from other DLTs, such as Ethereum blockchain, through Chainlink “oracles” that can also transmit a plethora of “off chain” data, such as web API and “internet-of-things” data, which can be monetized or tokenized into cryptocurrencies and “trust” algorithms. Another blog article authored by the Hedera Hashgraph Team states that “Chainlink and Hedera are setting the standard for trust and enabling the next generation of smart contracts to become the primary method for establishing digital agreements,” which “will allow developers writing Hedera-based smart contracts to access real-world data, events, and payment information.”
Libertarian Clothing for Men and Women
At the same time, Google Cloud’s BigQuery database is also Chainlinked directly to Etheruem blockchains through “hybrid cloud-blockchain applications” designed to conduct Big Data analytics for “prediction marketplaces, futures contracts, and transaction privacy,” according to the Google Cloud News Blog. Authored by Google Cloud Developer Allen Day, the blog article reports how the “smart contract platform (Ethereum) can interoperate with our enterprise cloud data warehouse (BigQuery) via oracle middleware (Chainlink).” By enabling “Ethereum Dapps [decentralized applications] (i.e. smart contract applications) [to] request data from Chainlink, which in turn retrieves data from a web service built with Google App Engine and BigQuery,” the Chainlink between Ethereum and BigQuery builds a pipeline that connects “on chain” Ethereum data with “off chain” BigQuery data stored in Google Cloud.
In sum, Google Cloud’s BigQuery repository, which aggregates Google Classroom data through InnovateEDU’s “Connector” app, is Chainlinked to both Ethereum’s and Hedera Hashgraph’s expansive DLT infrastructures, which can monetize, or tokenize, wide spans of data through smart contracts that can be programmed with “Social Credit” or “Trust” algorithms. By Chainlinking Google’s BigQuery directly to Ethereum and Hedera, this distributed infrastructure of “off chain” and “on chain” dataflows can provide a direct pipeline to streamline student-learning analytics from Google Classroom through BigQuery into Ethereum and Hedera Hashgraph for the purposes of monetizing, or tokenizing, students’ psychometrics through smart contracts that calculate students’ “trust” or “risk” algorithms for “prediction marketplaces” which track Social Credit metrics.
It should be noted here that Hedera’s Governing Council includes not only Google, but also International Business Machines. In addition, IBM, which has developed its own blockchain platform, partners with Chainlink, Microsoft, and Hedera Hashgraph as members of the InterWork Alliance, which describes itself as a non-profit council of corporations “dedicated to creating the standards frameworks [sic] needed to increase innovation across token-enabled ecosystems.” It is also worth noting that IBM, which provides automated adaptive-learning analytics through its Watson AI, was also represented on the “Accreditation and Innovation negotiating committee” that oversaw the deregulation of federal “Distance Learning and Innovation” (85 FR 18638), which has opened the floodgates for a deluge of CARES funds to pour into AI ed-tech being set up to route students’ psychometrics through Chainlink into Hedera Hashgraph under the “standard frameworks” of the InterWork Alliance.
While the InterWork Alliance between IBM, Microsoft, Hedera, and Chainlink is orchestrating the standardization of data flow from BigQuery onto Ethereum, Hedera Hashgraph, and other DLTs in the United States, Chainlink oracles are also being contracted to support China’s Blockchain Services Network (BSN), which is primed to leverage the data surveillance powers of China’s Social Credit dystopia.
A Concerted Effort?
It is foreboding enough that CARES-funded and Gates-financed ed-tech is being disseminated to track students’ learning analytics onto “distributed” Big Data centers, such as Google’s BigQuery, which links up with Hedera Hashgraph and other DLTs through Chainlinks that can monetize, or tokenize, data into Social Credit or Trust Scores. Yet it is even more ominous to consider the timing of all these public-private Big Tech partnerships, which appear to have been orchestrated in concert. Here’s the timeline:
On February 11, at the onset of the COVID-19 panic, Google was appointed to Hedera Hashgraph’s Governing Council.
On April 2, a few weeks after schools shut down across the America, Secretary of Education Betsy DeVos authorized the new deregulated rules for “Distance Learning and Innovation” (85 FR 18638) with the help of IBM.
On May 5, New York Governor Cuomo announced his Reimagine Education partnership with Gates Foundation and Eric Schmidt of Google’s Alphabet Inc.
On April 30 and May 12, five days before and seven days after the Cuomo’s announcement of the Gates-Google Reimagine Education partnership, the Gates Foundation issued two separate grants to the New York-based InnovateEDU.
On May 18, InnovateEDU announced the development of its Google Classroom Connector app that links student data to Google’s BigQuery.
On June 2, the InterWork Alliance “formally launched operations” to standardize DLT smart contracts in partnership with Microsoft and Chainlink, which partners with Google’s BigQuery and Hedera Hashgraph
On July 7, Hedera Hashgraph released its “brand-new Hedera-ETL software tool that works with Google BigQuery.”
You don’t need any predictive analytics to quantify the trajectory of this timeline.
By John Klyczek