Open data as social platform

Everyone has the potential to change the world, but not everyone gets that chance. Coming from a low income family, I had to fight for my education and advancement. My career goals is to provide universal access to opportunities. The problem I want to solve is easier access to capital and reducing in information asymmetry, especially when choosing one's education. Every decade, the "dream job" changes. A few decades ago it was doctors and lawyers; after that investment bankers; and now software engineers. Problem is, the rate of change is accelerating especially when juxtaposed with 4 year degrees.

The solution I'm proposing is to share and predict the robust set of skillets required for the evolving job market, allowing flexibility to pivot into multiple careers. 

Implemented globally, it can potentially eliminate structural unemployment and significantly reduce frictional unemployment, with maximum utility for both the nation and the individual. 

Global unemployment rate is roughly 5% or 390 million people are looking for jobs, but unable to find any. Assuming average household of 2-3 people, this figure impacts 0.8bn to 1.2bn people worldwide. Even with a small market estimate for Korea, unemployment rate of 4% with a population of 50m (of which 40m eligible) and average salary of $35K USD, then the problem is a $56bn problem. Just on a population basis, US would have a $360bn problem. 

Assuming normal economic activities (i.e. US unemployment is sub 4% vs. 13% in Covid pandemic), unemployment rate is caused by structural, cyclical or frictional causes. Structural being a mismatch of demand and supply of certain skill set due to long-term market changes; cyclical being fluctuating demand based on industry cycles including downturns; and frictional employment from people in between jobs. 

Structural unemployment will become increasingly important as the "rate of change" accelerate. Amount of new jobs/ careers that evolve has been faster then ever, including content creators or even esports athletes. The future of work will continue to require different skill sets, and we will need to prepare for the future of work, especially starting in middle schools and high schools. 

Solution comes in two folds. 

First is open data platform to share datasets from the web, most often through scrapping data sources worldwide including the prominent, Linkedin. Idea is to aggregate different sorts of data related to employment and provide macro trends on future of work. Variables can include industry, skillset, job posting, and others to predict what skill sets will be most valuable in the market. 

Second component is a social component, which will allow users to not only see and analyze the data further, but contribute their own data and/ or research to corroborate or challenge the macro trends, especially when it applies to specific industries. Community based data-interpretation will allow both critical analysis of the data and application for prediction for industry-specific predictions. 

Technology itself is simple. As an MVP, it will start with basic web scrapes of key data that can be used to predict attractiveness of skillset, from corporate platforms like Linkedin to social platform like Youtube or Twitch. At the same time, open data initiative partnership with enterprise clients (Microsoft has this), will improve the quality and cleaning process of data. Consumer side will be a standard UI for social platforms

Target population is both consumer, governments, and enterprises in terms of timeline. 

Immediate service will be provided to students. When I was growing up in my farm town in rural parts of Manitoba, I had no idea what skill sets were valued. In fact, I only thought of things in terms of jobs rather than skill sets. By providing even macro trends and access to data to students, it can help them make informed decisions in pursuing the types of education whether it be choosing majors or not going to college at all. 

Governments who are fighting unemployment and making policy (especially around issues of brain drain) can make more informed decisions based on marketplace model of skill demand and supply today, and where it will be in the future. Once integrated, it can help inform much of policy from education to immigration. 

Finally, there will be some demand from enterprise clients to continue educating their own staff. Many staff today are laid off due to changing need of the company. Being able to leverage macro trends with their company specific data will allow HR functions to change hiring as well as employee development efforts over time. 

Coming from a low-income immigrant family in rural parts of Canada, I can tell you guidance on making the right call is extremely important. Without safety nets, individuals from marginalised communities have to risk their livelihood on every life decision they make. By providing the technical tools and a social community to inform on the future of work, we can invest in our future through informed decisions. 

For example, If we predicted coding as an important skill set 10 years ago, many individuals would have had the chance to learn affordably and benefit. Way out of poverty is information.