Complaints about the use of personal information for everything from predictive product recommendations to credit ratings and consumer credit card interest rates have provoked lawsuits, increasing consumer outrage, and a growing chorus of demands for tighter governmental controls.
The greater accuracy of the Tribes algorithm plus its ability to perform in a totally anonymous data environment offers a way to increase sales and ease consumer concerns about of data while addressing many of the concerns of big data critics.
Integrating Tribes with existing system can improve their accuracy while easing regulatory and legal pressures.
Making Predictive Systems More Accurate
In addition to helping ease consumer and regulatory concerns about the use of data, making accurate product recommendations increases the accuracy of any predictive system by eliminating product purchases which a consumer would not repeat because of dissatisfaction.
In other words, predictive systems based on purchase information and outmoded paradigms like “people who bought this also bought this” are filled with dirty data. Current sysetems provide no reliable way to determine whether or not the purchase was satisfactory and would be repeated with the same or similar products.
Existing feedback loops are filled with consumer friction which the dissuade many from making follow-up. In addition current feedback systems –– Such as those used by Amazon –– do not capture or use their data effectively.
Algorithm Critics Find A Prominent Voice
A highly claimed book published early this month––The Black Box Society: The Secret Algorithms That Control Money and Information–has given voice to this new movement and increased concern through its many examples of what it considers corporate abuse of big data.
According to the book’s publisher, Harvard University Press,
“Hidden algorithms can make (or ruin) reputations, decide the destiny of entrepreneurs, or even devastate an entire economy.
“Shrouded in secrecy and complexity, decisions at major Silicon Valley and Wall Street firms were long assumed to be neutral and technical.
“But leaks, whistleblowers, and legal disputes have shed new light on automated judgment.
“Self-serving and reckless behavior is surprisingly common, and easy to hide in code protected by legal and real secrecy. Even after billions of dollars of fines have been levied, underfunded regulators may have only scratched the surface of this troubling behavior.”
Increased Scrutiny Along With Legal And Regulation Problems Loom For Big Data
Government and consumer activist scrutiny of uncontrolled data-gathering has been mounting, will continue to grow and will certainly result in increased regulation and the necessity to change the way data is gathered and used.
This will make merchants easy targets for legal and regulatory bodies, especially in Europe.
This will be particularly thorny for existing recommendation engines, such as those employed by Google, Amazon, Netflix and others which rely on gathering more and more personal data in an attempt to make more accurate recommendations by their collaborative and content filtering systems.
Tribes = Small Data Improvement For Big Data Systems
Tribes addresses the immense legal and regulatory privacy issues inherent in other recommendation systems.
Because Tribes is an anonymous social network that clusters numeric metadata rather than user identifications or personal data, it can be implemented in a completely private manner.
Tribes gathers no personal information and needs none to make accurate recommendations. In many ways, the Tribes algorithm is an anti-algorithm
The only information needed from a user is a pseudonym. Tribes can provide accurate recommendations with no other information.
If users desire to opt-in for coupons, special deals on products or other communications from merchants, they may use a pseudonymous email address which does not reveal their identity to the Tribes system.
As regulators, legislators and plaintiff’s attorneys increasingly target privacy violations, a prudently implemented Tribes system — alone or in combination with other systems — will provide a safe haven for merchants and the most accurate recommendations for consumers.