In Information Technology and tech startups, we talk about “systems of record”. It’s a system that is the source for particular data. That “system or record” is the ultimate source of truth. It’s the canonical record of data.

We often talk about these systems as the place a single company puts data they can refer to later as the single source of truth. A modern company will have a bunch of systems of record including products from companies like: SAP, Microsoft, Oracle, Intuit, Workday, Salesforce, Atlassian, etc.

As we move into the federated and distributed world of IoT and AI, new companies will need to be formed to store and process common data at the next layer of abstraction above these names. This is the universal system of record.

As we move into the federated and distributed world of IoT and AI, new companies will need to be formed to store and process common data at the next layer of abstraction above these names.

This is the universal system of record.

The key to this model is that the value of the company or system comes from creating and managing a common pool of data shared among independent institutions.

The value comes in two parts:

  1. They are a place to store and share common data
  2. They are a place where common wisdom can be derived from the stream of shared data

This model won’t make sense for some companies, use cases, and data. But, as the value of large amounts of data becomes greater, the inventive to share data to create new use cases will become too great.

And, creating your own features based on your own data (and not being a customer of the USR company) won’t be worth it. The networked data from your industry will be more valuable than your own siloed data.

The networked data from your industry will be more valuable than your own siloed data.

What does a universal system of record (USR) look like?

The characteristics of a USR are:

  1. Multiple institutions/ company have useful data they are willing to share
  2. There is value to the data across an industry or wider group
  3. One (or small group) of companies form to store common data
  4. Depending on the industry and use case it may also enable a learning loop by processing the data it has access to

Examples of current universal systems of record

Business communication data: MessagePath
The application I’m building with several other people will create a universal system of record for business communication patterns that will benefit all customers. On its face, the mission of MessagePath is to facilitate global business communication. But what’s different about us is that we’re going to be the canonical store of optimized business writing. Individual companies won’t need to keep up with the nuances of the language of business for marketing, sales, support, industry, and legal nuances. They will just use (or plug-in via API to) MessagePath.

We have 4 API customers in the pipeline who know that the only way to get the language patterns that MessagePath supplies is to use our API. There’s no reason to build your own language data-set. There’s only room for us and a couple more canonical companies in our space. This is because the value is in what’s being learned (language practices and patterns) across all our customer activity. Trying this a within a single company won’t give you enough value to compete.

AI, bot, and workflow data: BotChain
The last company I co-founded was a blockchain company. Blockchain can be a good technology for building universal systems of record. BotChain allows companies with bots and workflows to share a common platform to store bot identities, bot actions, and bot decisions. No need for each company to figure out how to operate with each other one by one. Plugging into BotChain will be the universal system of record for bot transactions and identities. (Note: There is a company that will hold BotChain related activities, but the product BotChain is an open-source distributed system.)

Medical data: BlocHealth
The team at BlocHealth in Boston (I’m advising) is putting a universal record of all core medical licensure/credentialing documents on the blockchain.

Examples of future universal systems of record

USR for self-driving vehicles
I’ve had some private conversations with engineers working on the next generation of mobility. In the future (starting to happen now), when one car learns new HD mapping data, the company that made that car will also learn. But is that good enough? With lives on the line, I think that some of that data should be shared for the benefit of all mobility/ logistics. This is where the universal system of record for mapping and self-driving data comes in.

USR for government
I’ve thought that we need to re-think government for a couple decades now. There is a ton of government-related data at many layers of abstraction within government. Some of it’s public and some of it’s private. I’m skeptical that it’s organized and shared optimally to improve government and lower the cost of government. A simple example — no matter what front-end you put on it, a USR should house all the data in cities pertaining to crime, mapping, potholes, etc.

Defense against the looming AI threats

Another benefit of pioneering universal systems of record is that it’s the solution to several looming problems:

The problem of data privacy + AI
Other companies with fewer privacy rights (like China) may move ahead of the US due to their access to their population’s data. This is training data for their AI.

Solution: I propose public (or public/private) universal systems of record that ensure privacy and also allow innovation with the data sets. I’m not sure what this looks like. There’s a lot more thinking to do around rules and encryption. I’m interested in homomorphic encryption for this potential use. If we can get this working we would allow free societies to ensure privacy and also innovate in the area of AI.

The problem of “out of control” AI
People talk a lot about the dangers of sentient AI. I think that will be an issue, but not anytime soon. The real problem will be non-sentient AI that optimizes in ways we didn’t expect. Think of nature. It’s not sentient, but it’s a complex system. And complex systems that impact the real world (like AI will do more and more) are dangerous.

Solution: Systems of universal record can allow us to record, predict, and halt non-optimal decisions (and bad results from those decisions) before they happen.

Next Steps
The best way to know the next steps is to start building. I’m looking forward to see what companies are we need to build to manage common NLP, AI, and IoT data over the next 10 years. Some of them are already here.

Source: On Canonical Companies – Will Murphy – Medium