Web 3.0 Design Framework: Scalable Custom User Experiences

Davinder Jawanda

Davinder Jawanda,
Managing Director, Startick Technologies Inc.

Buterin: Blockchain Use Cases

After pondering Vitalik Buterin’s recent tweetstorm about use cases and blockchain, I had a few thoughts about the ultimate use case. Buterin is of course the founder of Ethereum, the blockchain computational platform, and its associated computational contract based cryptocurrency, Ether.

He talked about improved scalability and User Experience in tweet #1, which will be the result of advancements in sharding and proof of stake innovations, which he mentioned in tweet #9.

“Blockchains are NOT about cutting computational costs (at least relative to centralized servers). Blockchains are about incurring a sacrifice in the form of INCREASED computational costs to achieve a *decrease* in *social costs*. Computers have become 1 trillion times cheaper, per unit computation, in the last 70 years. Human labor has gotten 2-10x more expensive. So incurring high technical costs to achieve reductions in social costs is at least sometimes a very good bargain.”

Indeed that bargain will, at scale, completely make up and move way beyond what’s lost in with increased computational costs. Additionally, ever smarter computational contracts of the public blockchain will further lower computational and transaction costs. The benefit of such efficient value exchange will be vast increases in the effectiveness of user solutions, to the point of truely precise solutions, customized for each individual cost effectively (at scale).

Much of this leap in productivity will be due to existing value trapped in inflexible business models due to an inflexible economic model built on scale through centralization. This trapped value will modularized, securitized and traded on liquid markets built atop distributed data networks. This model will be one of scale through integration.

“If layer 1 becomes cheap enough I literally foresee things like receipts of everyday purchases being published to blockchains. Because it'll just be the simplest tool out there for achieving the desired guarantees of verifiability, non-double-spending, etc.”

Sophia: Scalable Custom User Experiences

Perhaps the the best example currently of a custom user interface is Hanson Robotics’ Sophia robot. An what makes it potentiality particularly powerful is it’s tie-in with SingularityNet, a distributed data network based exchange platform in artificial intelligence program modules.

As an analogy, think of Sophia as a smartphone with an AI based OS allowing it to download and/or update third party apps in realtime from an online store, SingularityNet.io. This is akin to the iPhone and it’s App Store, or Android devices and the Google Play store. The key difference is that SingularityNet is built a top a distributed data network, the public blockchain. That means no centralization and thus, no potential overly dominating actors taking control of what could become the most powerful system humanity will ever know -- the ecosystem of artificial general intelligence.

A powerful combo such as Sophia and SingularityNet will be capable of producing ideal user experiences as the ecosystem of artificial intelligence producers grows and a critical mass is reached. Use cases for Sophia and the like among public institutional industries that soak of huge government budgets are particularly relevant. In the healthcare for instance, Sophia’s clients would be patients in a hospital or nursing homes. In education, it would be students in classrooms or in special ed programs. These are both public institutions in need of huge injections of value as both in their current states are failing society.

SingularityNet is the AI store where AI programs can be purchased and downloaded. With SingularityNet being a blockchain based application versus one that is run on central servers, it will not designed to monopolize the AI market and tie buyers to Sophia or a proprietary networking protocol, unlike Apple or Google who purposely utilize vendor lock-in strategies by tieing them to their proprietary protocols.

With SingularityNet being on the blockchain, transactions and user profiles are cryptographically (for security and transparency) stored on a public blockchain, preventing any centralized institution (including governments) from overly controlling, taking over, manipulating or locking-in the user base.

Instead, SingularityNet and Hanson are relying on an ecosystem and integrating that ecosystem’s contributions and encouraging further innovative contributions so that the Sophia-SN combo can produce custom solutions at scale.

What does a custom solution look like. Think of it as an experience tailored completely for you to solve your specific challenges as they happen and at a cost that doesn’t break the bank.

Data Driven Explorative-Declarative Continuum

You can visualize such an experience as one that provides both investigative possibilities (explorative) and straight answer service (declarative), and with a computational engine under the hood that consumes data and programs at a breathtaking processing pace.

This data driven explorative-declarative framework represents a basis for ideal elaborative rehearsal design. Elaborative rehearsal is a learning method involving the processing of meaning. Contrast with the alternative which is rote learning, which disregards meaning in exchange for memorization.

Elaborative rehearsal is the basis for abstraction, the basis for innovative ideation. The deep learning facilitated by elaborative rehearsal experiences build a knowledge foundation that allows learners to visualize the essential features without the complex details and before the physical manifestations are built. This ensures the resources are not wasted on building models or interfaces when the ideas for them are only half baked.

Data driven elaborative rehearsal facilitates artificial immersive interfaces, ie, a path to capitalizing on Web 3.0 convergence (AI, blockchain and IoT). Sophia is a quality example of high user immersion.

Regardless of if its a robot, online maps or financial services, these principles of design are universally relevant. Web 3.0 distributed platform applications will incorporate all mediums including, robots, AI chatbots, Natural Language Processing (NLP), 360 degree video, augmented reality experiences, virtual reality simulators, etc.

But the endless integration possibilities that realtime automated transactions of modularized value is the economic model that will bring about true wrap-around (enveloping and immersive) user experience services for the masses because these services will be scalable and affordable.

Design Framework

By utilizing a proper framework for growth, new features are added in a way that enhance the existing user workflow. Without proper foresight, new features seem bolted on. Getting the perspective correct from the beginning avoids costly radical changes later on -- costly especially in slower user adoption or negative user migration.

The X-axis represents more so the content -- conceptual on the left side and data driven on the right side. The Y-axis represents the user's intentions, with exploration at the bottom moving upward to understanding. The result is a four quadrant matrix which represents idea illustration, idea generation, routine data visualization, and visual exploration.

The X-axis represents more so the content -- conceptual on the left side and data driven on the right side. The Y-axis represents the user's intentions, with exploration at the bottom moving upward to understanding. The result is a four quadrant matrix which represents idea illustration, idea generation, routine data visualization, and visual exploration.

To determine the ideal client interface in a RA 4.0 world, it’s best to group the user’s intentions into these four quadrants. The process of grouping can be done by asking two questions of each user workflow component:

1. Is the information quantitative (data or updates) or qualitative (conceptual or mental images)?

2. Is the desired outcome an immediate decision (declarative), or research for a possible future decision (exploratory)?

Once the workflow components are organized in such a way, the interface can be designed for an optimal user experience, amplifying productivity:

• effectiveness through richness,

• efficiency through convenience, and

• intuitiveness through natural flow.

Elaborative Rehearsal

Depth of Processing Levels (DOP; deep vs superficial learning) is a continuum with the superficial called Maintenance Rehearsal and the deep side known as Elaborative Rehearsal (deeper, more meaningful analysis).

Understanding how to integrate a variety of supporting media and content is Elaborative Rehearsal, which powers exploration (which in turn supports the declaration). The same is true when it comes to integrating a variety of supporting content or subservices into an enveloping ultimate solution.

Depth of Processing

A deep level of processing is at the core of elaborative rehearsal which facilitates superior user experiences. Depth is Improved by:

1. Multiple Presentation Media: subject matter presented from multiple mediums (eg video combined with captions)

2. Immersion: users purposefully engaged through elaborative rehearsal (eg interactive Q&A, and first person role playing)

This diagram helps quickly visualize an improvement in experience based on depth of processing principles.

Progressive Disclosure

UI design is a constant balancing act: simplicity vs completeness. To maintain an ideal balance, here are some useful principles of progressive information or feature disclosure:

1. Initially show only the most important options

2. prioritize according to user needs & business goals

3. offer a larger set of specialized options on request; disclose additional features or info only if or when the user asks for them (or needs them)

Good design requires designers to present only what’s required for the very next step in the user’s workflow. Users don’t need to be confronted with secondary data until they either need it or ask for it. This progressive disclosure helps users manage complexity without confusion, frustration or disorientation.

Information Architecture

Information architecture (IA) is the structural design of information environments or interfaces. The four essential components of IA include:

1. Organizational Structure

2. Labeling Systems

3. Navigation Systems

4. Search Systems

Once Web 3.0 critical mass is reached, the information architecture possibilities of distributed platform applications will expand greatly generating a huge leap in user experiences for the average global citizen, well beyond today’s software or mobile applications. Think Sophia.

The Tipping Point and Leap Forward

The future of tomorrow requires all businesses and contributors to compete on design at a strategic level. All businesses in some form or fashion are digital entities. and thus will be impacted by Web 3.0 economics.

That’s a world of modularized value from multiple parties that combines in an ecosystem of automated processes to deliver custom solutions at scale. The modular value require interfaces and so do the ultimate user solutions. Interfaces are mediums and a mediums are about design. So in that way, all businesses are in the media and design business.

That critical mass will be made possible by distributed data networks and smart contracts powered by AI and fueled by IoT. Unprecedented latent value will be released from the shackles of existing walled gardens platforms and proprietary products. The rise in productivity from this tipping point will be analogous to the economic rise of nations when they move from latent value holding, protectionist economies to open value releasing, international trading economies.

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