Leonard Cheshire is an international charity and works in communities to support people with disabilities into employment. It wants to explore the potential of artificial intelligence to reach more people with its lifechanging programmes.
|Technology||AI Workshop, Data & Artificial Intelligence|
- Inspired the client in what way Artificial Intelligence can help their business.
- Collectively with the client came up with a number of ideas on how technology can improve the lives of people with disabilities.
- Selected the top idea and supported the client in applying for the Microsoft AI for Good grant within deadlines.
What could be better than using AI to extend the reach of Leonard Cheshire’s ambition and enable more people with disabilities to earn a living?
The UN estimates that 80% of working-age people with a disability in developing countries do not have their own income. Candidates lack the confidence to pursue their careers, there is often no roadmap for success, and employers often don’t give them a chance.
The organisation has grown into one of the world’s largest disability networks and works with the World Bank, ILO and UNESCO. For over a decade, the Leonard Cheshire charity has run programmes in Africa and Asia, getting people with disabilities into employment.
As a result, 38,000 people have got jobs or started self-employment and a further 83,000 have had vocational training.
But how can Leonard Cheshire scale this up significantly with only a limited number of offices, partnerships and support on the ground?
To consider this challenge we held an Objectivity ‘Art of the possible in Artificial Intelligence’ workshop to examine the client’s pain points and see how AI might provide the solution.
We started with a discussion about the current pain points in Leonard Cheshire’s work.
We wanted to focus the following parts of the workshop on solutions that could bring the greatest social value. We learnt that one of the key challenges is to scale Leonard Cheshire’s operations and one of the most effort consuming processes is the recruitment for people with disabilities. Also, many other pain points were listed, where AI could potentially help.
Four aspects of AI were identified:
- Natural Language Processing such as voice recognition and generation, chatbots and translation
- Recommendation Systems that could help match candidates with vacancies
- Computer Vision that recognises faces, barcodes and analyses pictures
- Advanced Data Analytics providing anomaly detection and forecasting.
We gave practical examples for each of these technologies and explained how Objectivity has used them to solve particular client problems.
We also inspired the group by talking about future trends.
To solve Leonard Cheshire’s key challenges the team split into groups and brainstormed on the ways to apply AI. The groups generated dozens of valid applications of technology to everyday problems.
In just 20 minutes three groups came up with the ideas and potential solutions on how to apply AI technologies into the Leonard Cheshire environment and processes. The ideas were grouped and analysed together. We have discussed the business or social value each idea may bring, the difficulty to implement it and how this could be supported by the existing data.
From this creative session we eventually decided to choose an AI candidate profiling tool that suggests to an individual the best career path. This tool would help Leonard Cheshire to reach many more people with disabilities, without involving a lot of internal and partner resources. In order to develop this idea into a concept, we used the Product Canvas technique to analyse the chosen idea. This technique enabled us to define the solution at a high level, establishing its major goals, target groups and the roles of the users who will interact with it.
The self-assessment tool captures the person’s skills, abilities, experience, education, motivation and aspirations. Based on these findings, the
recommendation engine will propose a career path. We helped Leonard Cheshire to create a business case (including the cost estimate) and to write a successful grant application.
Discovering potential ‘quick wins’ and proposing immediate and long-term architecture improvements in the client’s Data Warehouse solution through employing the Objectivity Consulting Auditing Framework.
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