New School Methods for Old School Tricks for Disappearing People

11942334_10153577638946575_8114869526653973585_oNew Orleans    In the age of “big data” we are led to believe that eyes are everywhere on all of us. All is known by the all-knowing. NSA is up our nose. It goes on and on.

Yet, somehow we are losing people.

We lost more than 400,000 people on certifications under the Affordable Care Act that was four times the number we lost last year. Ostensibly these are re-verifications of citizenship status, but of course the fine print indicates that people only had 10-days to reply and, trust me on this, many found the forms and requests mystifying, and so it is more likely that people simply dropped through the crack. One immigration health expert essentially said, “Really? who in their right mind would have risked being deported by filing for health insurance? Duh.”

You know who else is disappearing? The elderly it turns out. A group called HelpAge International says old people are slipping through the cracks by the millions. In fact they put out an annual Global AgeWatch Index, and report that almost half the countries in the world – 93 of them — have zero data to offer on their elderly. Worst, unsurprisingly, many of these are the poorest countries in the world where many of us would most like to have some information, including the United Nations which has made raising living standards a huge priority over the next fifteen years. In a Times’ article they mention that “Of 54 countries in Africa…there was enough data available to include only 11 in the index.” Even for the data available of course there’s bad news in that the “gap in life expectancy at age 60 between the countries at the top and bottom has increased to 7.3 years, compared to 5.7 years in 1990.” Talk about “aging out” once you get long in the tooth you just flat out disappear it turns out.  Who knew that was so easily accomplished in the age of big data.

Speaking about being invisible and besides the elderly we’re back to migrants and refugees. Running errands from the ACORN Farm someone on public radio was going on and on about whether the waves of people coming into European countries from Syria and the Middle East these days are refugees from the civil war or economic migrants. The reporter was arguing that this was a political issue, which it is, but fortunately by the end of the piece they admitted it didn’t change the fact that we had to do the right thing no matter what label was placed on it. Another commentator reminded the American listener that we needed to be careful tut-tuting since during the heart of the depression in 1930 we had forcibly removed an estimated one-million Mexicans, 60% of whom were American citizens, in a so-called “repatriation” to Mexico. These same pictures of people on trains would have been of US trains from Los Angeles and other cities to the Mexican border. This atrocity is news to many, if not most, of us.

The real solution to this invisibility problem for the elderly, poor, immigrants and others is not big data in all likelihood, but being willing to look around us in the first place.



Too Much Data in Too Many Hands for Both Good and Evil

Word Cloud "Big Data"New Orleans      An observation decades ago always stuck with me. It was a comparison of Americans and people who live elsewhere. The point made by the author, whose name fittingly has long ago left me, is that we have too much information at hand and too little ability to process it. Ironically, that was then, and the observer would have been dumbstruck by the exponential increase of information now available to us and just about everyone else on the other end of hands pounding the keyboards, but some people have the ability to process it. What’s out there and who has the capacity to understand it though, still might leave us at the same point as a generation ago without the ability to use the tools effectively. Too many of us are at the Stone Age, while a few others are flying to the moon.

A case in point can be found with the new data on doctors and their paymasters, including and especially drug companies and others who would interfere with good judgment. Part of the Obamacare reforms are already tracking what various hospitals now charge for specific procedures, and starting in September, we will all have this information if we have access to a website. Excellent news! How many will be able to effectively access that data to make the choices that it promises and within the ACA, how many of the doctors a patient might want to avoid will be in or out of the network allowing the power of such information to give rise to voice and the threat of exit? Well, that’s a whole different question entirely, but today it’s safe to say, the information is more powerful as a selective threat from the government than a promise useful to many people.

More disturbingly is the availability of what some called “hyper-specific” community data. As the Times posed the question, if you…”Want to find a ‘family-friendly’ community within 20 miles of Boston with a high Asian population, a low poverty rate and a median home value of $400,000…” then there’s a bunch of websites for you! With some simple key strokes and a semi-passive real estate database and an agent steering you into its use, then you can effectively violate the Fair Housing Act and racially discriminate all day long. It’s not so much “redlining” anymore but it is a kind of data-mining discrimination that eviscerates Fair Housing, the CRA, and a host of other public policies.

We have police looking at broken windows in our cities as a deterrent, but no one should be able to look at personal computer screens due to privacy restrictions. Well not exactly, since a federal appeals judge just allowed federal prosecutors access to email and data records for a customer whose info was held at a Microsoft data farm in Ireland. We already knew there were no boundaries for the NSA, and it appears there are no foreign borders either.

It seems clear that the level of data now on everyone and everything and the ability of some, but not all, to access and process that data has outstripped our ability to regulate, legislate, protect privacy, establish and maintain rights and entitlements, and of course hold us safe and sound. We may not all be planning a trip to the moon, but we’re living on a planet and in an age that none of us truly understands anymore.

Just saying.


People Analytics are a Scaring Part of the Hiring Future, but…

WorkforceAnalytics-PersonIcon3DGenericOcean Springs, Mississippi    Another article in the holiday reading pile was a piece in The Atlantic called  They’re Watching You at Work.  The reporter, Don Peck, reviewed the current utilization of “big data” to create something that big company human relations departments were calling “people analytics.”   In a nutshell these outfits are crunching the information they have received in the recruitment process from tens of thousands of applicants, comparing it with other information they have on workers they judge to have been successful by their standards, and then trying to devise tools to fit these two pieces together to create the perfect decision in hiring a new employee.

At some levels, who is surprised?  And, alarmingly, using the examples from Michael Lewis’ book Moneyball about the ways that general manager Billy Beane reconstructed the Oakland Athletics into a winning team with less money in a smaller market using a wider array of statistics than just the veteran scouts’ eyeball looks and long experience is seductive, because at its heart that book was about how biases in baseball influence the recruitment of talent regardless of production and performance.

In fact,  Peck ends up making the case that people analytics might be better for workers given how much bias continues to be ingrained in the employment process.  The cited studies that revealed that there was bias based on whether names sounded white or black; others that revealed bias when employers knew the applicants were men versus women; and, very interestingly, bias in the way those hiring tended to hire people who they felt had a personality, background, or interest, “similar to mine.”   The most hardcore Luddite among us would be hard pressed to defend any of these hiring “methods” as anything but biased, but in some cases we would have to concede that almost inevitably any of us could have unwittingly been guilty of some of biases, especially the one of tending to hire people who we think might have elements of our own experience.   It may not be the “old school tie,” but it’s bias none the less and springing from the same roots.  It’s certainly no secret that other studies have found that the most effective way to find a job for seekers is through personal networks that connect people to job openings.

Nonetheless it was scary to read about big companies that would like to hire people solely on their scores based on taking various digital games that might reveal this data, since you can almost throw away folks from the job pool who have been trapped on the other side of the digital divide immediately.  The number of HR recruiters who expressed the desire to completely discontinue any person-to-person interviews and just hire from the tests was startling as well, even give the fact that the direct interviews would likely trigger the systemic biases.

This was one of those articles where you got to the end more depressed than informed.  The brave new world of employment based on people analytics, even if less biased perhaps on some levels, seems to erect some permanent, unscalable barriers virtually at birth for millions posing some ethical and societal challenges that remain unanswered.