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What Is Data? Part 1 : D is for ‘Dangerous’

– ANOTHER WAY OF LOOKING AT DATA

This is the first of a four-part series about ‘data’ that concludes with my take on the topic and why it is important. Nontechnical, hopefully fun, definitely not definitive and absolutely a work in progress.

Don’t underestimate the DANGER we face if we get this wrong.

Phrases like ‘Data Protection’, ‘Big Data’, ‘Anonymized Data’, ‘Data Ownership’, ‘Data Protection’, ‘Metadata’, ‘Data Security’ …. have crept into our daily lives seemingly overnight. I’m old enough to remember when ‘data centers’ were those big windowless things in the middle of industrial parks that ‘other people’ dealt with. Today, it’s everywhere and it is crucial for everyone to at least know something about what it is, what it means and why it is important.

The point of the series is to help understand how we can get a better handle on data;

  • ours and others
  • private and public
  • personal and social
  • first, second and third parties
  • and and and …

With that understanding, maybe we can then work towards turning the tables and start to use data as a tool for ‘empowerment’, not subjugation. That we think about data. Protect it even. Rather than blithely and unconsciously allowing corporations and business to take it, without so much as a ‘by-your-leave’ – much less permission!

There’s an old joke that asks the test question “Describe the universe and give three examples.”

The problem, of course, is that there is only one universe.

And yet, in a way, there are two universes, and they overlap. One is physical, the other virtual. One is generated by the laws of physics and chemistry and the other by binary mathematics. These coexist and overlap. The latter arises from the former but is not entirely reducible to it. After that it all gets complicated.

In any case, there can be no metaphor for either of them, because they are not like anything else.

But we can’t help trying to make sense of the connected digital world, and the moving bits that comprise it, and we can only make sense of things metaphorically.

Thinking is metaphorical. Mathematics is metaphorical.

Doc Searls

Doc wrote this after a long back and forth a couple of years ago among a large group of people who think about and work in ‘identity’ on our behalf. (I know right – who knew!).

At the time the group was discussing ‘analogies for data’. Bottom line, I am kinda with Doc, we can’t reduce the meaning of data to a place where the analogy makes sense. But we can, should and will continue to explore this, because, at the end of the day, even though analogies don’t define – they do help us understand.

Data is one of the Pillars of People First and this series emerged as I attempted to get to grips with understanding what it was, to the point that I can not just explain it, but also shed light on why it needs to be understood. By everyone. And I don’t mean the dictionary definition. Nor the mathematical meaning. I mean its essence and why it actually is important. I mean the way everybody is going on about it – it must be important. Right?

This only works if we are absolutely laser-like as to what we mean by data. Can we agree on what it is? Whose it is? Where it is? Who has rights to it and over it? Can it be private? Is it all fair game? If you can have private data can you share it? To who, for how long and for what reason? If I give you my data, can I get it back? How?

And we need to do that at every level of engagement. Ourselves, our family, our friends, our government, our community, our workplace, in business, in churches, in society, in clubs, online and offline … and it is imperative that we individually and in the groups, we belong to … agree. Ethicists, Philosophers, and Human Rights advocates are all weighing in on the topic, attempting to ensure we don’t end up in a catastrophic mess. Shouldn’t we too understand what is going on?

The Danger

Failure of society and ‘we the people’ to do this will mean that the last few hundred years of societal development was for naught and we will return to the feudal states from whence we came.

And, to pre-empt your question, no I am not exaggerating ….

Many scholars have taken to describing these new conditions as neo-feudalism, marked by the consolidation of elite wealth and power far beyond the control of ordinary people and the mechanisms of democratic consent. Piketty calls it a return to “patrimonial capitalism,” a reversion to a premodern society in which one’s life chances depend upon inherited wealth rather than meritocratic achievement.

Shoshana Zuboff, The Age of Surveillance Capitalism.

She’s talking about data and to give you a clue about how so very careful we must be about data … let’s explore one single piece of data together that we think we already know.

Specifically … Dates.

No, not those kinds of dates … these kind ⤵︎

Consider this fact: ‘Samuel Morse died: 04/02/72’

If I were brought up in America, I would ‘know’ instantly that Samuel Morse died on the 2nd of April. If you are from the UK, based on that data point, you would correct me and let me know that he actually died on the 4th of February.

The absolute truth of when he died, using only that single piece of data is at question because we do not even have an agreed understanding of how dates get abbreviated. Not only that – was that 1972? 1872? 1772? … If you know who Samuel Morse is, you could surmise that the year was 1872, but you still don’t absolutely know that he wasn’t an old school friend of my father who died February 4th, 1972 in the UK.[1]

And we wonder how it is that basic world facts can get so convoluted!

To be absolutely accurate we also need to know where he died – and the time. After all, dying at 2 am on a Thursday in Germany means that you died sometime between late morning and early evening on Wednesday in the U.S.A.[2] Morse actually died in New York City – a full five – if not six (it changes) – hours ahead of Hawaii Time.

It gets worse and I don’t intend to bore you with the many ways that this ‘gets complicated’ – as Facebook would have it, but as ‘Steve’ used to say;

One More Thing

Global society has mostly agreed that the last two digits in the xx/yy/zz format are always ‘the year.’  Yet, we still can’t agree over day first or month first. Well, specifically most of us can – it is – once again, the Americans that are at odds with the world.

02/04/72 is the 4th of February, 1972 in the USA and the 2nd of April, 1972 in most of the world. The USA is the only country in the world that interprets the basic data this way.

To Conclude

Personally, left to my own devices China is the only country that has the date formatted that makes sense to me … year – month – date …. but that is another story and happy to discuss in the comments if someone raises the question.

Back to that date

A birthdate is a data point, but only with the context of at least understanding whether the date format is d/m/y or m/d/y do you get to the information behind the date. Ideally even dd/mm/yyyy

So even simple data – to have meaning – must have context – and oh so much more

SEE YOU OVER IN PART TWO | CLICK HERE

But maybe before then, and if you have a spare ten minutes, this is a fun video that really gets down to some specifics. Ten minutes – purely on Timezones. Funny and informative.

[1] Ok – I made that up … but you see how it gets complicated very quickly.

[2] We can’t be more specific because the U.S.A, has six time zones – and without looking it up, had ‘the clocks.changed’?

John Philpin
John Philpinhttps://peoplefirst.business/
JOHN'S career spans 30 years, 2 continents, and organizations as diverse as Oracle, Citibank and GE. A Mathematics graduate, John moved to California in 1990. He helps technology companies create, develop and deliver their story for fund raising, market development and influencer programs. He also works with businesses to ensure they understand, and are ready, for the ever accelerating changes that technology is bringing to their industry. John is a co-founder of Expert Alumni and gleXnet and long before futurists and industry watchers were writing about the impending challenges that industries were going to be facing, they predicted a perfect storm of issues like skills gap, declining work forces, the gig economy, people trained to do work no longer needed, demographic shifts, economic and social change, market upheaval and rapidly changing ways of doing work. From the beginning they have promoted the idea that massive change was coming to how organizations should think about their workforce, with a singular focus on simplifying the interface between people and their work. Understanding the challenges ahead of the curve, the solution was built to arrive at a better understanding of the greatest restraint to business operations - competence, not capital. gleXnet provides unparalleled insights into an organizations people and operations by flipping the problem from the perspective of people, not the business.

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