Revolutionizing the Workforce: Work X and the Internet of Skills

Abstract:

Scarcity of talent poses a significant challenge in today's landscape, where a company's worth is intricately linked to the caliber of its workforce. The emergence of platform economies has reshaped the dynamics between employers and employees, as well as freelancers and clients. Driven by technological advancements and the repercussions of the pandemic, companies are increasingly favoring adaptable workers over fixed staff. However, the existing form of platform economies faces sustainability hurdles, serving as commercial intermediaries and imposing substantial commissions.
Enter Work X, a zero marginal cost platform recognized as 'The Internet of Jobs.' This platform revolutionizes the work landscape, providing a sustainable solution with minimized commissions and optimized salaries for any work type under any contract.
In a scenario where technology and job requirements are advancing exponentially, individuals tend to progress linearly, resulting in skill gaps and job losses due to misalignments. WorkPi addresses this challenge by seamlessly integrating with learning experience platforms (LXP), learning management systems (LMS), assessments, and human resource (HR) platforms. WorkPi assesses skills, characteristics, and preferences, storing this data in self-sovereign identity (SSI) wallets. This process establishes the world's most extensive skill database, laying the groundwork for the 'Internet of Skills,' offering personalized job and education recommendations.
Recognizing the significance and sensitivity of personal data, WorkPi emphasizes data ownership, allowing individuals control over data sharing and the ability to revoke access at their discretion. To refine machine learning algorithms without compromising privacy, WorkPi employs sophisticated techniques, ensuring continuous enhancement while safeguarding individual privacy.

Introduction:
In the corporate realm, the scarcity of talent poses a substantial hurdle, given that a company's value is intricately linked to the quality of its workforce. The architects of innovation and growth, those building products, are the linchpins of success. However, identifying and evaluating available talent remains a formidable task. Connecting this talent with high-performing teams in suitable companies proves to be an even more intricate challenge. The existing process of aligning the supply and demand for work relies heavily on human intervention, deploying expensive recruiters, job boards with steep fees, and assessment and education providers. Unfortunately, this process lacks robust resources for assessing and aligning the skills of individuals and teams.

Platform Economies:
The advent of platform economies has blurred the conventional boundaries between employers and employees, as well as freelancers and clients. The trend toward hiring flexible workers over fixed staff, accelerated by technological advancements and the global pandemic, is reshaping the employment landscape. Geographical barriers are diminishing, if not altogether disappearing.
Commercial freelance and gig platforms such as Upwork and Fiverr are capitalizing on this trend, representing a transformative shift in how work is approached. However, these platforms suffer from economically inefficient business models. For instance, Fiverr imposes a 20% commission on its workers, regardless of whether they are working on a $10 or $100 gig. Similarly, Upwork utilizes fixed commissions up to $500. Other platform economies, including Booking.com, Airbnb, Uber, DoorDash, Deliveroo, etc., charge a minimum of 15% commission on transactions. This high commission structure prevails even for straightforward services like payrolling and matching. The move towards decentralized business models has the potential to significantly reduce these commissions, and with today's technologies, Work X aims to facilitate a matchmaking environment with a maximum network commission of 5%.

Measuring Skills to Match the Jobs of Tomorrow:
Historically, university grades and diplomas have been the primary metrics in candidate application processes. While education credentials offer insights into candidates, they fall short in measuring actual knowledge and skills. Personalized assessments are emerging as valuable tools for quantifying various skills, characteristics, and preferences of individuals. These measurement points, referred to as 'indicators,' focus on assessing both teams seeking new talent and talent seeking new teams. The goal is to predict optimal matches, eliminating mismatches in the labor market and ensuring the efficient deployment of talent globally.


Data Ownership Reclaimed:
The sovereignty over data, career paths, and personal growth has slipped from the hands of individuals. During the early internet era, the true value of data went unrecognized, allowing tech giants like Google, Facebook, and LinkedIn to pioneer a novel business model offering free services in exchange for user data. Today, a growing awareness prompts individuals to reclaim authority over their personal data, education, and development, acknowledging the potential risks of its misuse. Work X offers a remedy for this predicament while also delving into broader solutions for data-related challenges.
In historical contexts, enterprises have been reluctant to share data with other companies, driven by privacy concerns and the fear of losing their competitive advantage. This reluctance not only stifles their capacity to train accurate artificial intelligence (A.I.) models but also inhibits the accumulation of valuable insights. Our staunch belief is rooted in the empowerment of individuals through the restoration of personal data. We see this as a mutually enriching arrangement, fostering equitable economic practices and contributing to personal success for both individuals and enterprises.

Work X is introducing 'The Internet of Jobs,' a zero marginal cost platform economy, to address the changing landscape of employment towards gig-based models. The rise of independent contractors and flexible arrangements is reshaping the employer-employee relationship. Traditional gig and freelance platforms face sustainability challenges with high commissions.
The problem lies in inefficient matching mechanisms and the lack of true value in current platform economies. Work X aims to bridge this gap by creating an economically optimal platform with minimized commissions and optimized salaries. The goal is to leverage technological advancements and create a sustainable business model.
The ecosystem around Work X includes the Work X Platform, accessed through the Work X token ($WORK), functioning as a highly efficient highway for work. Various services, such as WorkPi, contribute to this ecosystem, focusing on enriching data profiles through assessments and development courses. WorkPi addresses the challenge of skill gaps, offering an enterprise solution for employers to identify indicators of success.
In this ecosystem, service providers, employers, and assessment providers contribute to a decentralized platform for work. Work X aspires to be a place where any employer can list vacancies, recruit candidates, and benefit from a more efficient and sustainable platform economy.


Work Intelligence Lab, part of the Work X ecosystem, prioritizes data ownership and privacy. It leverages advanced machine learning techniques to improve algorithms without compromising privacy, encouraging user contributions for algorithm enhancement. Introducing Work Performance Indicators (WPI), it categorizes them into Skills, Characteristics, and Preferences. The matchmaking mechanism, WorkPi, utilizes an AI-driven strategy to match candidates with job openings based on WPIs. The process involves listing jobs, identifying WPIs, matching candidates, and following up on the hiring process. Continuous data gathering enhances the AI-recruiter's accuracy and identifies new WPIs for improved predictions, contributing to an intelligent, data-driven recruitment system with a focus on individual data ownership.