Big Data and Venture Capital

  1. Big Data and Venture Capital

Data

“Data” is another word for information. It includes facts and statistics about a person. Data can be as simple as address, height, age, or ethnicity, health history, family income, or work history. Data for students includes facts about performance in subject areas, test scores, and behavioral records like detentions and school suspensions. In an age on “online everything” data is captured all…the…time. Amazon knows what books you like to read, Facebook knows your social interests (and who your friends are), Google knows when you’re taking a vacation (and where) based on your search history, and online education companies (if you use their products) know if you learn math better before lunch based on the bits of data they collect on how well you respond to each individual question in an online assessment.

 

Big Data

The term “big data” tends to refer to the use of predictive analyticsuser behavior analytics, or certain other advanced data analytics methods that extract value from data, and seldom to a particular size of data set. Predictive analytics encompasses a variety of statistical techniques from data miningpredictive modelling, and machine learning, that analyze current and historical facts to make predictions about future or otherwise unknown events. Behavioral analytics uses data to study behaviors of large groups of people.  It looks at patterns of human behavior, and then apply algorithms and statistical analysis to detect meaningful anomalies from those patterns—anomalies that indicate potential threats

 

Algorithm

Is a process or set of rules to be followed in calculations or other problem-solving operations, especially by a computer.According to Slate.com:When you ask a digital assistant, like Siri or Cortana, a question, algorithmic operations inform both its sense of what you’ve asked and the information it provides in response. Machine learning likewise helps Google Maps determine the best route from one location to another. And there’s a virtually unlimited array of other functions that algorithms can serve: Some of the earliest commercial applications of algorithms involved automating tasks such as payroll management, but with the rise of contemporary machine learning, they’re used for much more sophisticated tasks. Algorithms determine who should receive government benefits, contribute to predictive policing, help anticipate health crises, reschedule airline flights, and much more.” http://www.slate.com/articles/technology/future_tense/2016/02/what_is_an_algorithm_an_explainer.html

 

 

Privatization

Is an economic term that refers to taking public goods and services like public roads, libraries, and schools and handing them over to be owned and managed by private companies and individuals who can profit from the gains and losses in those goods and services. Instead of being concerned with the general public, privatized industries are now concerned with their investors and how much money they can make. The argument “privatizers” (people for privatizing things) make is that public programs are failing or are inefficient, and that, if privately managed, they would do better. There is no evidence to support that this theory is true or that it works. Think of private prisons- which motivate police to arrest more, and courts to convict more people (even innocent people!) because more people in prison means more profits.

https://www.poemhunter.com/poem/federal-prison-privatization/

 

Innovative

Technology-centered products and practices, which are untried, unproven and disruptive to classroom practices (“status quo”). Disruption is a sought-after property, to create conditions favoring a take-over. Venture capital is thrown at unproven educational apps. Synonyms 21stcentury education, “Future Ready.”

What tech innovators say: “If we can disrupt and break the public system, you’ll allow us to experiment on your children to see if we can get the results we need to meet our “pay for success” impact investment projections.”

 

1:1 Devices

Each child having a tablet or laptop of their own to connect directly with cloud-based vendors, and with teacher activities run through their management programs. In schools today where everyone is expected to do more with less and justify oneself with data, administrators will be able to reduce the number of human teachers and build enormous data sets on everyone. It may bankrupt your district, since you’ll be paying off the tech bondswell beyond the lifespan of the devices and infrastructure you’ve purchased; but it will help the bottom line of the tech and finance industries so we’re hoping everyone will just play along.

 

Data Dashboards

Where the data is kept and summarized for quick viewing and analysis. Software products that consolidate and arrange standardized scores, metrics and sometimes performance scorecards on a single screen for each student (like SAT test scores, or student performance information from certain online reading programs). Online learning management systems and gamified behavior management programs enable us to rapidly build robust profiles of each student with much less effort. In 1:1 device schools we always know exactly where students are, plus with dashboards we can “grade” schools and teachers in real time and using predictive analytics.

 

Gig Economy

A gig economy is an environment in which temporary positions are common and organizations contract with independent workers for short-term engagements. Uber drivers are a good example of workers in a gig economy. In a gig economy everyone contracts (agrees to) short-term jobs rather than long term employment by one company. Think of how musicians play “gigs” at clubs. In a gig economy, because the work are short-term contracts, workers will less likely have benefits like health care and retirement savings through their employers (since everyone will be working for themselves).

 

Pay for Success

Venture capitalists put money into social programs (like education, foster care, prison recidivism) and get paid with added profit when performance targets are met.  Runs on big data, to demonstrate “impact” and “efficacy” and show that profitable “solutions” (largely online) are “evidence-based.

What venture capitalists say: “Honestly, we oligarchs have accumulated so much money we’re having a tough time finding new investment opportunities. The number we did on the housing market was a doozy, and it took us a few years to come up with a new trick. But we’ve been thinking long and hard about it with the Rockefeller Foundation, and our new plan is to ‘do well by doing good.’ Since governments are short on money, because we’re so good at ducking our tax bills, we’ve decided to pitch public-private partnerships as the solution to funding for public programs. Going forward, your education, health care and mental health services will be increasingly mediated through digital devices (like FitBits). We need that datato justify our investments, and you can be sure we’ll pressure everyone using those services to provide it. Direct access to human service providers will be limited, since they’re less reliable in providing the data. But hey, that’s a small sacrifice for fiscal prudence. It goes without saying we’ll also define terms of “success” in ways that work best for our interests since we have all the best lawyers setting up the partnership agreements. You’re ok with that aren’t you?”

 

Social Impact Bonds (SIBs)

Is like “Pay for Success.” Bonds (that aren’t actually bonds but rather contractual agreements) where private capital (see privatizers) is invested in a public/social program that is supposed to save the government money. If a private data clearinghouse determines money was saved (using algorithms), the “savings” are paid out to investors as profit, instead of going to other programs. For example, saving on special education costs by providing pre-k or reducing recidivism (chances you’ll commit a crime again) costs by offering prisoners workforce training.

SIB’s supporters say: “We hear governments are interested in education and workforce training SIB opportunities. If the programs we invest in meet the agreed upon measures of “success,” we’ll net a profit. The one wrinkle is that programs that involve success metrics like workforce outcomes require tracking participants for years to determine if our investment was “successful.” But what’s a bit of surveillance in the name of fiscal accountability and transparency, right? We’re not sure there is actually profit to be made in the SIB deals themselves. The big money will be in derivatives, bets on the SIBs once we bundle them into asset-backed securities. Then, we’ll be able to trade them in global financial markets; it’s legalized gambling. It worked so well with mortgages we’re definitely bullish on the prospects for a futures market in education data. We just need to get all the devices into schools, the data dashboards online, and Pay for Success legislation approved nationally and we’ll be good to go.”