Implications for Life in a Time of Big Data

Executive Summary

Today much of the data (also referred to as information and knowledge) in Big Data comes from the living individual or the once living individual enmeshed in a living world environment. Today much of the scientific community and the human population at large see the earth and even the stars and space in general as an interconnected web of the living and the once living. In fact in life science and biology an emergent third state of individual living, not just human, is beginning to be articulated as dormant individual in addition to an alive or dead individual. The full implications of the dormant state of individual living is beyond the scope of the present Big Data work but will at every turn have an effect on the development and governance of Big Data.

It is fair to say that few developments in contemporary culture, technology and science reveal more about the intractable inter-connectivity of living individuals than Big Data. Big Data often shows how and how much individual life needs other life and that the inter-connectivity has an essential social aspect. This social inter-connectivity is the kernel of the ethical challenges and opportunities Big Data presents and that must be resolved.

Big Data for all its rapidity and volume today requires thoughtfulness, self-examination discipline in action and the development of new kinds of choices. A living individual’s very mutability is a primary source of its value but must not be the sourced for exploitation and inequity. It is for this reason that the benefits of the ownership, value and governance of a living subject’s data must be drawn out and studied in a time frame adequate to go beyond limited self-interest. Today this has created a situation where individual living data is treated as a natural resource where the first one that “captures” has a profound and apparent irreversible advantage. There is a kind of a stampede and gold rush underway to “mine” it, to possess and own it. All of this is happening before the data has given anything back to the living or shown the capacity to add value to living and in a way that is commensurate.

 

Many—but not all—of the conundrums of Big Data such as ownership, value and privacy are created a third party stampede and tussling over the possession of the individual subject’s data. Possession is not an appropriate measure of ownership once it has be taken from the original owner—the data subject be the third party a commercial enterprise, a government, a scientific endeavor, a clan.

Today in many sectors of our human community such as healthcare, financial services, education and government it is customary to assert—and not without reason—that more data about an individual subject will lead to better decisions about how to manage the business and innovation of that sector in profitable ways. In part this has led to competition to acquire more and more data about living subjects. In healthcare, for example, this often means that the most useful data is embodied in individual human behavior. Because most living is more or less individuated and the subject of the data, the problem of data privacy and governance is built into Big Data analytics and its usefulness. Certain key questions and concerns then are central to the aspirations and application of Big Data. The purpose of this White Paper is to flesh out these questions, concerns, solutions and aspiration as they impact on living individuals and communities of living individuals particularly in the un-and-underserved and a few primary archetypal uses cases.

 

At present among the key questions to be highlighted are—

What are the implications for life from an extractive and capturing approach to Big Data?

Is the Big Data Subject alive?

Can these questions and answering be built into the Big Data Analytics and Reference Architecture?

 

 

THE CHALLENGE

How to govern and value the data that is captured and/or collected in databases and other ICT systems so as to realize the wealth inherent in large stores of data. This white paper will demonstrate solutions on two emblematic use cases clusters, first the un-and-underserved and 3 primary archetypal use cases. (To be attached).

 

THE SOLUTION

The NIST Big Data Public Working Group practice guide <title> demonstrates how data scientists and citizens can instantiate NIST Big Data Reference Architecture (NBD-RA) to address the un-and-underserved, and 3 primary archetypal use case in the financial services, healthcare and nonprofit sectors.

This White Paper further demonstrates how the central questions and concerns including security, privacy, data governance, ownership and value can be addressed and supported throughout the governance of Big Data analytics lifecycle. This includes specifically how to interact with NBD-RA components – Big Data Definitions and Taxonomies, Big Data Governance including Provenance, Curation, Preservation and Processing, the Data Provider, Big Data Analytic Provider, Big Data Framework Provider, and Big Data Consumer and Big Data Subject’s Experience.

 

The guide:

 

  1. Identifies key areas for innovation needed to sufficiently analyze the given dataset.
  2. Identifies the use case characteristics needed to sufficiently govern and analyze the given dataset with (analytics algorithm.)

 

  1. Maps un-and-underserved and primary archetype characteristics to Big Data Analytic Provider

<others…>

BENEFITS

<The white paper is based on an ethical approach and assumption that the benefits, including monetary from Big Data analysis need to be:

A: inclusive of all the living interests of the data subjects and stakeholders from which the benefits are drawn.

B: equitable to all the data subjects and stakeholders from which the benefits are draws.

C: should demonstrate through a metrics to be discussed in due course how the capacity for life and individual living is enhanced by and through the collection, development, analysis and governance of the data.

1         Introduction

<Background info>

1.1        Goals, Methods, Models, Dilemmas and Opportunities for Life

 

  1. <Goals statement Big Data Goals for Life — Survival?

Today the world store of human life has grown greatly. It is not clear that any other form of life has increased as rapidly, except perhaps the microbes and other life that cohabitates on/in human life. This increase has brought with it many concurrent and emergent problems and opportunities for life, not only human but all life. These problems and opportunities have simultaneously brought to bear the limits of our creative capabilities in understanding human survival and the survival of life. Someones of us have yelled fire, and millions of people and their technology are looking for answers and understanding. Generally speaking this development is a good thing; on some level every life wants to survive and even flourish and thrive. The question and the context then becomes; Is our collective effort of gathering knowledge—data and information for the survival of life?

For now it is important not to be distracted nor to make too much of the differences in terminology here of data, information and knowledge, as if in our case, data is something fundamentally different from information and knowledge. It is not. It may be reasonable to point out that data and information are kinds of knowledge and/or contexts of knowledge without inferring that these contextual differences are greater than the common ground of knowledge. We could claim our subject to be Big Knowledge or Big Information. For now Big Data may suffice.

 

Implicit

             For Whom

For What

For When

Principles

Projected

For Whom

For What

For When

Principles >

 

1.2        Approach

< Living Methods and Models

             The Role of Thinking

The Role of Reflection

The Role of Metaphor and Mapping

The Role of Security

The Role of Privacy …Approach description >

 

1.2.1       Technologies Used

<Technologies description>

 

1.3        Benefits

<Benefits statement>

 

How to communicate justice and generosity

My thoughts are along the line of:
To IDESG Legal Counsel:
The Identity Ecosystem Framework the IDESG is working to create is in important respects a new kind of community and organization based on a set of principles agreed to across a broad and diverse set of stakeholders. We would like our agreements/contracts to reflect its unique character. In the IDESG and the IDEF it is well known that documents like Terms of Use are frequently too long and complex and are frequently clicked through without understanding or some would argue informed consent. The IDESG would like to innovate in creating TOU that more effectively communicate our character. To that end we would like to be able to have the essential liability protection, perhaps in the form of a disclaimer, but not one that is a buyer beware notice. Rather because we need and hope for broad adoption of IDESG NSTIC* guided services and products we want to indicate that as a community all of us including the IDESG are in this together not trying to simply gain some special advantage over our service/product participants and users.
We would like your guidance in how to balance these needs in our first product/service “the SALS” TOU in order to set the desired tone, and to provide a model of how IDESG policies will unfold in the future.

NSTIC Guiding Principles

How to Measure Human Trust Online and in Cyberspace

Human  Trust  Experience Metrics

in a nutshell

Online, In Trust Frameworks, In Cyberspace and in the Identity Ecosystem

1.

Approach/Goal

1. Assisting the human user in understanding the user’s evolving vulnerabilities in cyberspace and how an evolving NSTIC compliant certification “Trustmark” facilitates the user in understanding and making informed choices when establishing relationships, within an IDEF Identity Ecosystem. Such choices should be informed as to security, privacy, usability, and interoperability capabilities and protections provided by the NSTIC compliant “Trustmark” presented by a given class or set service providers, community of interest or other IDEF certified entity.

2. Content

Measurement should begin by creating a metrics of

  • human understanding of his or her evolving vulnerabilities in cyberspace
  • the ability and satisfaction the human user has in making informed choices online.

Once a  human-user understanding-baseline has been agreed upon and established then further metrics can be developed and folded in to the measurement criteria regarding the human user’s experience with other aspects of interacting and transacting with the NSTIC compliant IDEF Identity Ecosystem.