The Future of Skills- A Protocol
The Case for Protocols
Protocols resonate in us all as members of communities, political organizations, and nation-states. From natural resource distribution and religious order to economic policies and the political practices of today, protocols have always had a strong influence on the experience of living in society. Decentralized protocols are no different. Their purpose is to generate a mode of behavior for key processes. This standard allows every actor’s actions to evolve through a modus operandi of rules and incentives-maximizing the benefit for an entire community. However, it’s fair to say that some decentralized protocols don’t always pan out. Bad actors, poor planning, and inherent inefficiencies in the scalability of current blockchain technology is a challenge Web3 is still working on.
But, if we reach into the database of human history we’ll see cases of inefficient and unscalable protocols present in society long before the Digital Age. From revolutions to enlightenment in human history, we find all sorts of instances in which protocols were promoted by archaic machines and thinking — some of these are still instilled in us today. The current canvas of decentralized protocols built on the likes of EVM and Polkadot allows us an experimental space to freely investigate new iterations of how individuals interact, transact, and commune as a species. That’s a frontier worth exploring. New iterations of new machines could have the power to influence and emphasize social evolution.
Honing in on a Protocol for Skills
Man vs. Machine generates a familiar human narrative -Animosity and conflict with an “other”. In this case, a cold and heartless mechanical intelligence that lacks the humanity to lead us towards the next step in human evolution. We have a distrust of automation and want to believe that human perception is enough. Currently, this narrative fits into what we know of as today’s skills economy. From higher education and upskilling to recruitment and talent allocation as well as alignment, we rely on very human perceptions of how talent should grow and be distributed.
We look at a CV/resume to get a snapshot of a professional. We hope to be impressed by educational backgrounds at prestigious universities and projects completed with familiar brands or fortune 500 companies. All while hoping a 15–30m interview will allow us to make the best talent decisions for their company growth. Maybe we hire experts in recruitment to consult us, or we ask for references from an exclusive pool of vetted talent.
But even when we make hiring decisions, we realize we still need to invest in growth. 87% of companies today, for instance, recognize they are or will be experiencing skills gaps within the next 5 years.
And the gap between the skills talent has learned and the skills they need to apply in IRL work contexts are also felt by incoming talent- 53% of college graduates have not applied to an entry-level job in their field because they felt unqualified, and nearly half (42%) felt unqualified because they did not have all the skills listed in the job description.
But, we carry on with the analog protocols of talent vetting and growth- maybe with a little help from a machine learning algo to sift through the sea of resumes to pretend that processing texts that highlight a degree from Stanford or work history at Meta is equivalent to success and the grit or determination it takes to work on a vision or collaborate effectively on projects.
The reality is that the skills economy of today, from education to talent ops, is left tattered and beaten by an acceleration of technology that leads to an expeditious evolution of skills. A human, a group of them, or even an institution of them — can no longer keep up with this. We are reaching critical mass- and phenomena like the Great Resignation are the weak signals that force us to revise the protocols we’ve established to solve the problem of skills. The verticals of education and work have to come together to create a new vertical- the skills vertical. And that new vertical should be characterized by the virtues of personalized identity and talent sovereignty along with a robust digital skills identity interface for end-users. The vertical could be a protocol that allows fluidity of interaction between companies and talent, projects and teams. This is Grey’s Future of Skills vision.
The Proof of Skills Protocol
Institutions of work and academies of learning today are slow, bulky, and bureaucratic- creating an experience that all of us as talented professionals navigate in order to make the right moves in a rat race towards success. The protocols in these institutions resonate with our human history, but the nudges in these protocols are outdated.
Modern skills institutions serve as skill gatekeepers, monopolizing exclusivity in the form of elitism and standardizing curriculums for efficient manufactured production of professionals. This is also true of standardized e-learning platforms that create digital assets and deliver them linearly to millions of users to maximize the monetization of the certification of skill without any practical impact on real-world projects.
Current talent protocols for vetting and acquisition are no more efficient, with companies spending $4,000 and 24 days to hire per position during a Great Resignation that shows no signs of slowing down with only 65% of people planning on staying with their current employer.
Learn and work, grow and do.
On one hand, you manage inputs- growth experiences and learning experiences that enrich you. Without them, you are unprepared and overwhelmed by challenges in projects and work. On the other hand, you manage outputs- professional experiences in large companies, boutique startups, and freelance projects. These activate your learning inputs through individual task completion and collaborative project success.
Grey’s Proof of Skill Protocol is a system immutable digital identity in the form of Dynamic Skills NFTs with on-chain claims. These claims populate metadata learning experience completion onto a Skills NFT and are associated with the application of skills through the completion of specific work projects and real-life challenges (outputs). This defines the parameter of the Skills Protocol Grey implements.
The combination of the Skills NFTs one owns will generate an entire skills identity easily managed by end-users to then be staked into Project NFTs (work experiences) and new Learning NFTs (learning experiences).
These experiences are recorded onto your Skills NFTs, increasing your Skills Profile in reputational value for any opportunities you come across in your life.
The Proof of Skills Protocol is also the beginning of a network- where dApss and DAOs can build upon this paradigm.
Conclusion
The Proof of Skills Protocol is only a start for the future of skills and how we maintain our skills identity. Grey comes at the advent of Web3 and the future of decentralized protocols as concepts of work and learning drastically evolve towards a more viable future. In this future, professional empowerment is the staple between working and learning. A vision where professionals are valued for their immutable skills regardless of origins, location, race, orientation, or creed. A future where professionals are polyprofessional, working on multiple projects with multiple teams, building guilds with the DAOs and professionals they value while maintaining a work/life balance that sustains them.
A future, where a protocol has made current academic institutions a historical curiosity- an abstraction lost in future iterations due to a new standard that correlates learning with doing.
It may be true that our human history is littered with academic or business leaders and experts who have approached these problems and contributed to the evolution of skills through multiple solutions. They are only solving the symptoms and not the disease. The reality is it’s time to allow a benevolent automated protocol to solve problems in a new vertical. From that open-source protocol, new advances in skills analytics will help us to understand the correlations between learning and doing. Advancing this link creates new approaches to skills in the forms of dApps and DAOs. A Grey native network will sustain the future of work and the future of education platforms that help advance a modern workforce.
In the times of thought leaders, politicized knowledge, and conflicting expertise- humans are showing the flaws through error. Leaders in their efforts to serve the people, eventually err. Protocols are more reliable.
