Recent issues with Facebook, Equifax, GDPR compliance, … have brought us to a tipping point in data. The basic structure of how data is: permissioned, shared, used, accumulated, analyzed, sold, regulated, … must change. Google and FB operate in a Big Data 1.0 architecture powered by the “virtuous cycle”. Edward Snowden showed us how the NSA also acts in this centralized model as a data vacuum (not so virtuously). Literature and entertainment have created broad awareness of the dangers of centralization and loss of privacy: 1984, the Borg, The Circle, Black Mirror, … etc.
How will things change? Federated data, and control of use (see this blog). As I outlined in Building Networks; when network intelligence develops, it will initially aggregate, then subsequently disseminate.
“The network forms around a function and other entities are attracted to this network (affinity) because of the function of both the central orchestrator and the other participants”.
Given that each node and cluster is resource constrained, each maintains connections to a finite number of “efficient” orchestrators/networks. Thus, early networks build very substantial momentum.
In the last 20 years, early internet companies formed proprietary structures to enable trust and value exchange (eBay, Paypal, Amazon) as well as discovery (Yahoo, Google). Today Trust, Reputation, and Discovery are portable within in these environments (not across them). Your interaction within them enables them to serve you better, and your community reputation keeps you from leaving (information intensity). The separation of identity (ex. authentication), reputation (ex FICO Score) and discovery (below) separate from the network is transformational.
It is important to note that the Internet provided connectivity standards, not the STRUCTURE for resources to discover or transact. Structure can be viewed as the legal operating agreement, the standards, the pricing mechanism. Thus the services needed to enable commerce are moving from closed platforms to services where trust can be managed across nodes (ex Alibaba across 1000s of small businesses). What is “Trust” and why does it matter?
- Trust in Identity
- Trust in Contract/Rules/Transaction
- Trust in Operations/Fulfillment
- Trust in Quality
- Trust in Transparency/Auditability
- Trust in…
The Trust dichotomy between online and offline networks (and commerce) is readily apparent. For the next phase of growth we must enable trust and structure (see Internet 3.0). Improving how we manage data and enable trust/permissions will impact MUCH MORE than consumer experience or data governance.. it will be central to maintaining freedom and value of human capital (see below).
Apple is a great example of the future. As a consumer champion they keep data locked away under the permissions of the handset holder. Similarly, the founder of the internet (Tim Berners-Lee) is seeking to build a NEW SEARCH reclaim it from Google and Facebook (see this excellent article in Digital Trends). Tim’s new project, underway at his MIT lab, is called Solid (“social linked data”), a way for you to own your own data while making it available to the applications that you want to be able to use it. This is also my team’s focus at Commerce Signals, Inc.
Trust and Communications
In the Solid example trust is transparently managed by the network of counterparties you choose to enable your search. Thus you control how you collaborate with other node (example fellow wine enthusiasts) collecting intelligence and choosing who to share it with and understanding how it will be used.
Fine grained control of use is central to verbal communications, social structures and commerce today. Individually, we interact and converse based upon our level of trust and the objective of conversation. The need to communicate differently to different audiences shaped our language. The ability to throttle (and add color to) information allows the owner of information to control its flow and restrict its context (ie how it can be used). Richness of language permitted information to flow with different levels of trust with each interaction. We call these rich interactions “signals”.
The ability to control and disseminate information has been key to our role within society and our environment (ie food water/sources). Verbal communication allowed for very complex interactions:
The party releasing information understood:
- Purpose of communication (use)
- Value for releasing information
- Identity/reputation of receiver (ie Trust)
- Language used to communicate based upon trust and value
The receiving party endeavored to:
- Create trust
- Communicate use/value
- Communicate context of the discussion
- Ensure a common understanding of the environment (ie common reference point)
- Understand language (verbal and non verbal) of communicator
Merchants trading between communities (ie Marco Polo) created linkages between localized communities and resources. High degrees on uncertainty were mitigated through experience (number of interactions) and expanding groups of specialists (trust). Economic value was created from specialized knowledge and the communities which created it (think of 1500s and Spanish Gold). The path to discovery (and economic value creation) required relationships, trust and communication.
Example. Today most quality data can’t play in advertising, because its use and dissemination can’t be controlled. For example, a banks view on what a consumer just bought is a more powerful signal of intent than any search.
Data in Centralized Architectures
Since the printing press, (~600 years) we have lived in a world of “information centralization” (ie libraries, professional societies and Big Data). Centralization enabled scarce information (ex books) to be discoverable without relationships. Broad discovery accelerated the creation of new ideas/information and new centers of specialists. These “hubs” of information became key societal institutions (schools, monasteries, government, companies) which subsequently expanded the number of specialties and creation of new content/ideas. Similar to the merchant function above, communication between specialists created networks across hubs, further advancing the both the art and broadening the availability of specialists geographically.
Star networks make the most intuitive sense to people, we have strong models in Airlines, Banks, Facebook communities. Technically it is much easier to score or index data held in a single location (the hub).. then intelligence held in unstructured (or scale free) networks. However centralization of data CAN NOT be the future. The “virtuous cycle” creates natural monopolies and loss of privacy/freedom.
As I outlined in Small Wins, my hope is that we are evolving to a more thoughtful treatment of consumer information. While initial treatment of private data with the same tools and techniques developed for public data is a logical first step, we must seek to change the process. Centralization of information provides enormous advantages to scale (governments, vendors, …etc). Federated data and federated discovery provides advantages to consumers, privacy and small businesses.
Economically, the centralization of behavior and the destruction of anonymity impact both supply and demand thus disrupting both pricing mechanisms and commercial networks (ex perfect real time information flow on EVERYTHING). Economists have demonstrated how imperfect information flow shapes markets and margins. For example, markets have played the central role in economic discovery (goods and price). If I can predict demand and influence your behavior before you are “in a market” I have destroyed “the market” and created a new orchestrator of demand (see Transformation of Commercial Networks).
The logical corollary here is that perfect information flow destroys the value of human work and society. Wow.. big picture thought for the day.. and certainly a compelling case for change. How will this change come about? I see three options:
- Government will set the terms (GDPR)
- Consumers will associate with those they Trust (Apple)
- New infrastructure will develop to enable Trust, collaboration and destroy advantages of centralized architectures
When observers (ie Google, Facebook, …etc) can combine their views and uncontrolled fashion (ie aggregation), uncontrolled insight can be gained. Not just insight into past behaviors, but predictive insight on future behaviors (see article). Zola’s Project Insight Algorithm in Captain America capture a nefarious future use https://www.youtube.com/watch?v=qGpz8Q4Jq6A
Most businesses are willing participants in the opaque exchange of data. Unfortunately it is generally accepted that the only way to make data decisions is to have all of your data lumped together in one place where it can be actioned. Certainly, having all of the data co-located allows for lots of great free-form analysis… after all you don’t know what you might uncover.. but that IS THE PROBLEM: once data leaves your facilities you have lost control.
My ONE PROBLEM
If you were to have a role in solving just one problem what would it be? Mine would be engaging the world’s population in a new economy. I look at the under engagement of rural poor and the enormous pools of capital seeking risk and wonder “WHY can’t this capital find investment”? I started my personal quest focused on connecting consumers to finance (blog). However the ability to take risk, and create value, is highly dependent on the economic structure through which resources engage with each other (Trust blog).
Functional economic structures encompass: the market, government, supply chains, and corporations …etc. Each model has a very strong influence in how discovery, risk, and asset allocation work (see Milton Friedman – Freedom to Choose). For example, plugging into something that already exists reduces complexity, uncertainty and risk. As beta drops, investment pools increases. How do we expand economic structures to cover smaller resources? There is certainly a desire by underutilized resources to discover use, and there is certainly capital available seeking risk.
For the last 500 years, the economies of scale were driven by asset intensity. Supply chain leaders created networks which were optimized to cost/quality. These supply chains were “small worlds” where leaders defined choices, created predictable “demand”, influence competition, and defined “closed standards”.
As an example, how did we get white flour? Bread makers wanted consistent flour that yielded consistent white bread. Companies like Archer Daniels Midland orchestrated: seed, harvest, storage, distribution, mills, …etc. Farmers had a known buyer, bakers had a known cost/quality, and consumers had a consistent product. But I hate white bread.. and it seems silly to ship all the grain off to Chicago and then have finished product shipped back. The push for quality and cost thus limited selection. The central problem to diversity of bread (and flour), was discovery of demand by small farmers. How could a farmer trust in the demand for a local flour? This type of problem plaques all economies.
We must have a different model of interaction to enable trusted interaction between parties. It must include privacy and for both businesses and individuals. All people understand that Data and Trust are core to freedom (of thought, association and action). I also believe that TRUST is the key to unlocking the next phase of global economic growth, and maintaining your brand.
Action plan? See my previous post on Equifax