Power of AI: The key to equal employment

February 17, 2019

Reading Time: 3 minutes

As many nonprofit programme managers know, finding jobs for young people with disabilities can be a challenge. One major reason is that skill development programmes may not be linked to what employers need.

One way to address the challenge of equipping youth with disabilities with employable skills is through apprenticeship programmes.

The ROI of our apprenticeship programme
We pair adolescents who have dropped out of school with a master craftsperson as part of a six-month programme. A master craftsperson is an experienced worker or shop-owner within a particular trade. Two apprentices per shop learn a hands-on trade, which is chosen based on market demands.The programme is called skills training for advancing resources, or STAR, and was presented as 1 of 9 global solutions for young people by UNICEF’s Generation Unlimited initiative.

The results speak for themselves: 95% of STAR graduates find a job within one month of graduating.

A successful programme requires mentors
To help young people with disabilities be job-ready, they need to be matched with great mentors. Therefore, one of STAR’s goals has been to create a community of master craftspersons that can successfully train, as well as mentor, to ensure their protégés complete the programme.

Mujila with hearing impairment showing how many months it took for her to graduate from the STAR programme. (Dhaka, 2018) Ⓒ Noor Ahmed Gelal

To find the right mentors, STAR used machine learning, a specific application of artificial intelligence, to analyse seven years of data collected from master craftspersons who have successfully trained youth with disabilities. The data included their demographic profile, financial condition, professional experience, and educational background. This resulted in a trained model that could predict whether a master craftsperson was a likely candidate for successfully training a young person with disability.

These are the four most relevant factors of a master craftsperson’s profile we have determined to predict whether she or he will be an effective mentor:

  • Earned a minimum of a junior school level certificate
  • Owns the business they are running
  • Previously trained people for at least 4,000 hours
  • Has at least eight years of business experience in the particular trade

By taking advantage of the data analysis capabilities of AI, STAR has created a pool of reliable business owners across Bangladesh. Additionally, a trend among the apprentices with disabilities was observed. The success rate for graduation and graduates’ income are significantly higher when they specialise in the following top three trades:

  • Tailoring and dressmaking for women
  • Tailoring and dressmaking for men
  • Beauty salon work for women

Our application of machine learning is now at a point where it automatically adapts to changes in the collected data of business owners. Before we started using AI, our STAR programme had 865 mentors suitable for youth with disabilities. Now we have 407% more mentors. Alongside this trend, we have seen a 2% increase in youth with disabilities completing the programme – within only six months time – a number we expect to quickly rise, given the large increase in available mentors.

Abdus was 10 years old when he lost his leg. Relatives helped to cover the medical expenses, but he could not continue his education. Abdus joined STAR as an apprentice in 2016. Today he earns BDT 16,000, roughly USD 190 per month. This is twice as much as the current minimum wage in Bangladesh’s garment industry.

Programme management with AI is not rocket science
You’re wondering how to enhance your nonprofit programme with artificial intelligence? You can start moving your data to a cloud. That’s the first step to process your data and finding actionable insights.

At BRAC, we have used Taroworks and Salesforce.org Nonprofit Cloud to create and administer mobile data collection surveys, digitise key elements of daily field management, and identify trends or roadblocks by visualising the data on dashboards. Field staff – who were not accomplished technology users – embraced the mobile app and cloud platform, to the point of even offering ideas for new data collection forms and building custom reports themselves. This was really exciting for us. As a result, BRAC scaled the system from the original 15 pilot branches to 141 branches overnight. Currently, we have a database of around 84,581 people, who have benefited from our programme interventions, with the plan to expand to a half million over the next few years.

This article originally appeared on Salesforce.org.

 

Shifur Rahman Shakil is a deputy manager working with the technology for development team at BRAC Skills Development Programme. Samira Syed is a senior manager at BRAC.

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