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As the saying goes – “to write the same story, you need to be on the same page”. To convey a message, to have an argument, to have a discussion or to have a conversation, we need to be sure that the object and subject are the same in the minds of the actors; they should mean the same thing when they pronounce the terms of the topics.
One of the common issues when talking about identity – especially in the context of digital identity – is to be on the same page about: “What does ID mean?”. In a conversation ID may be thought of as identity, identifier, identifying, identification and many other things – all related but with different contextual implications which may lead to confusion.
In the context of this piece, we will consider ID as an ‘identifier’. In the organic world, where we utilise gifts from nature, the “past personal narrative” and identifiers are not needed explicitly to enable the cognitive process of identification. Human cognition, enabled through the sensory processes, allows the identification, and an explicit identifier is not generally part of the overall process, moreover, the usage of an identifier may hinder the process.
Having said that, the digital world is different: we don’t have the luxury of the “past personal narrative”, and the sensory processes cannot be used in the same way. In the digital world, computing machines are the proxies between humans, and identifiers are an essential construct for these computing machines to make the identification process functional. With Artificial General Intelligence maturing, we may be able to apply similar cognitive processes in the very near future, as we do in the organic world.
So, let’s look at some of the definitions of the term “identifier”:
Dictionary.com defines it as: “a person or thing that establishes the identity of someone or something”.
The Cambridge dictionary defines it as: “a set of numbers, letters, or symbols that is used to represent a piece of data or a process in a computer program”
The Oxford Learner’s Dictionary defines it as: “a series of characters used to refer to a program or set of data within a program”
All these definitions are using specific contexts to define the term ‘identifier’, most of them from computing perspectives.
Let’s try to have a baseline statement for what an identifier is so that our discussions have a better context. Here is what an identifier is:
“An identifier is a pointer to an identity”.
This statement is kept generic on purpose, so that we do not over-constrain the space around the concept of identity, diluting or even contaminating it. It is also useful to keep it generic so that it can be applied to all the entities within the digital world – including the machines and organisations/legal entities and not just limited to human entities.
It’s important to highlight that identifiers can be categorised into two different groups:
- Human-readable identifiers
- Machine-readable identifiers
The human-readable identifiers help to bridge between humans and computing machines in the digital world and the main driver here is convenience.
Let’s talk a bit about convenience. Convenience is an interesting psychological aspect; in fact, it is one of the most critical aspects of digital business for consumer psychology.
Convenience is a billion-plus dollar aspect, as witnessed through the now-expired patent of the one-click purchase from Amazon. Realising convenience as a game changer, Amazon applied for the patent of its one-click purchase in 1997 and the patent was granted in 1999, the patent expired in 2017, but between 1999 and 2017 – it has added billions of dollars of additional revenue to Amazon, and as the icing on an already rather appetising cake, Amazon has sold licenses to many other large organisations, including Apple, for the iTunes one-click purchase.
Convenience is a factor of time and effort; it optimises time and effort and reduces them. There is another factor – which is more psychological – and it is “perception” and that’s very important indeed.
There is an interesting story about the establishment of the first “convenience” store, which shows the power of convenience. In 1927, Jefferson Green (popularly known in the neighbourhood as “Uncle Johnny”) was running the Southland Ice Dock in Oak Cliff, Dallas, Texas, where people would come to stock up on foot-long ice blocks to refrigerate their food.
Unlike the local grocery stores, the Ice Dock ran the shop from 7 AM until 11 PM, seven days a week. So, Uncle Johnny thought, “Why not sell milk and bread and eggs, too?”.
The company embraced Uncle Johnny’s idea and rolled out this concept of extending the hours of operations and the content of the store to include grocery items across all the stores in various locations as they realised what they were selling is “convenience” giving customers a convenient time from early morning to late night for the consumers to buy groceries.
In 1946, these stores were branded as 7-Eleven and the first chain of convenience stores was born. Interestingly, the 24-hour convenience store concept came as an accident 36 years later, when after a football match at the University of Texas, customers flooded the 7-Eleven store in Austin, Texas and the store had to stay open all night.
Source: National Association of Convenience Stores
Convenience is a human thing; it’s not rocket science to understand why it is the critical driver for human-readable identifiers. We humans value convenience, consciously or subconsciously, above most things and this is proved by Amazon’s success by reducing friction for online shopping.
Here are some typical characteristics of a human-readable identifier:
- Short in length.
- Uses numbers and/or letters.
- Can be spoken.
- Easy to type in.
- Not a secret.
- Unique within practical contexts.
Examples of human-readable identifiers are phone numbers, email addresses, ID cards National Insurance numbers etc.
Here is a simple and very obvious schematic of human and machine-readable identifiers:
Machine-readable identifiers do not need to have psychological sophistication through convenience factors, and the drivers are generally efficiency, optimisation, privacy, and security. Examples of machine-readable identifiers are customer reference IDs, cryptographic keys etc.
It’s important to have both types of identifiers in the digital identity ecosystem, as they cater for different requirements and it’s not efficient to converge them. The human-readable identifiers primarily focus on convenience whereas the machine-readable identifiers primarily focus on machine usability and security. It may be argued that the machine-readable identifier can be reused as the human-readable identifier as well – although this makes it inconvenient for the human users and more importantly the identity ecosystem needs to be “Humanised”.
In the mobile network ecosystem – with the various components from the mobile device with the SIM card to the mobile network, there is a perfect balance of human-readable identifiers and machine-readable identifiers. The phone number is one of the most valuable and trusted human-readable identifiers and the machine-readable counterparts come in various forms – the most critical one is the cryptographic key in the SIM card.
This provides security and identification within the mobile network ecosystem. The trust in the phone number has an implicit assurance that generally the phone number is allocated after some form of KYC (unlike email IDs, where millions of email IDs can be generated using a script in hardly any time, and, with the advancements of Generative AI – most of the frameworks like Captcha can be compromised easily). This balance between the identifiers humanises digital identity. This is what makes Sekura’s SAFr Auth a humanised authentication mechanism – balancing between the usage of the phone number and the cryptographic key in the SIM.
Let’s humanise the digital identity ecosystem, let’s make the world a SAFr place.
With coverage across 5 continents, Sekura Mobile Intelligence is the leading global provider of mobile identity solutions, providing trusted, secure, and easy-to-consume solutions for ID verification, anti-fraud and secure online authentication use cases. Sekura works with established KYC, identity verification and risk data providers who have already integrated into leading global brands with demand for mobile identity solutions.
Through the integration of real-time mobile data into our partners’ existing services, we enable them to extend and enhance their customer offerings into new services, use cases and geographies through the adoption of SAFr, our single standards-based, mobile intelligence API.
To offer your customers the opportunity to benefit from our global mobile identity solutions, contact the Sekura team today.
