Graduates often believe their degrees are just what they need to get the desired job. In recent times, employers value hard, technical, and soft skills much more than the pre-requisite degrees. This project will highlight the importance of learning these skills and also distinctively segregate what skills are required for different jobs.
This project aligns with a previously conducted project by the Lagos Nigeria chapter (AI for Unemployment in Nigeria). The same methodology will be employed to derive robust solutions to understanding the relationship between skills and jobs in Africa. The first step would be to understand the supply and demand of jobs in different fields, search and scrap for available top jobs in various fields in Africa, search for the skills employers look for in applicants’ resumes to land the job, gather a substantial amount of graduate resumes, and employ Natural Language Processing to distinguish the connection between these available jobs and resumes with and without these skills.
We want to better understand the disconnect between skills and jobs in Africa, particularly digital skills.
According to the AfDB, Africa’s youth population is expected to double to over 830 million by 2050. Still, currently, out of Africa’s population of nearly 420 million aged 15 to 35 years, one-third are unemployed, another third are not secure in their jobs and only one in six is in wage employment. More youth than ever are graduating from schools and universities, but are not finding jobs.
Why? The social problem we want to help avoid is youth becoming discouraged and turning to militancy, insurgency, and risky illegal immigration. The potential impact is better alignment between the skills youth are attaining and the skills that employers need, which will lead to more and better jobs, fewer people facing poverty through unemployment, and greater human well-being across the continent.
We envision an AI solution that can aggregate various public big data to help better assess the demand and supply of jobs and job seekers. Ultimately the outcomes can influence curriculum, learning approaches, public-private partnerships for job training, higher education policy, and industrial policy.
The AI solution can compare supply data from unemployment data, graduation data, jobs data, etc., and demand data from online job postings, numbers and types of private sector companies in specific sectors, etc. to identify gaps or skills mismatches. It can also be used to compare skills training offered online, apprentice programs, and on-the-job training opportunities.
Finally, the AI solution can use sentiment analysis and natural language processing to have a better understanding of how companies, schools, and individuals feel about the education they receive, the jobs available, the skill levels of job seekers, and policies that incentivize greater skills/jobs alignment.