Skillzminer
Lead Participant:
SKILLZ MINER LIMITED
Abstract
"Our vision is to improve social inclusive growth and boost productivity via our digital concept called Skillzminer.
Our project will demonstrate how artificial intelligence, can better predict the skills, values and behaviours required to boost productivity today and in the future.
We want to apply machine based learning to our technology so that when we assess skills, values and behaviours at an individual level and demonstrate the impact on social inclusive growth.
We will:
* Measure and predict the impact of Governmental regional investment and behavioural interventions
* Offer a scaleable solution that gives jobseekers and employees the ability to understand what their core competencies and how they might be developed and applied today and in the future
We will achieve this by:
* Engaging with a frequently overlooked and marginalised talent tool via a conversational assistant
* Identifying skills that can be transferred and evolved
* Developing 'next best' algorithms that predict what interventions job seekers require. This will allow us to stimulate behavioural change within job-seekers to reduce risk interventions
* Driving insight from our dataset which contains regional economic data, skills, values and behaviours
* Visualising opportunities for jobseekers, matching employer opportunities with jobseeker profiles and tracking job-seekers through their evolving career path
In doing so, we will help minimise welfare expenditure, reduce risk interventions and increase productivity within local economies.
The outcome of this industrial research will be a market ready scaleable solution to a growing market which includes Government, a National Employability and Training provider and a consortium of major employers.
The resulting data will provide tangible evidence of the effectiveness of the underpinning core technology, the sentiment analysis requirement and machine based leaning algorithms.
The proposed project is expected to run for nine months and cost £481,797\."
Our project will demonstrate how artificial intelligence, can better predict the skills, values and behaviours required to boost productivity today and in the future.
We want to apply machine based learning to our technology so that when we assess skills, values and behaviours at an individual level and demonstrate the impact on social inclusive growth.
We will:
* Measure and predict the impact of Governmental regional investment and behavioural interventions
* Offer a scaleable solution that gives jobseekers and employees the ability to understand what their core competencies and how they might be developed and applied today and in the future
We will achieve this by:
* Engaging with a frequently overlooked and marginalised talent tool via a conversational assistant
* Identifying skills that can be transferred and evolved
* Developing 'next best' algorithms that predict what interventions job seekers require. This will allow us to stimulate behavioural change within job-seekers to reduce risk interventions
* Driving insight from our dataset which contains regional economic data, skills, values and behaviours
* Visualising opportunities for jobseekers, matching employer opportunities with jobseeker profiles and tracking job-seekers through their evolving career path
In doing so, we will help minimise welfare expenditure, reduce risk interventions and increase productivity within local economies.
The outcome of this industrial research will be a market ready scaleable solution to a growing market which includes Government, a National Employability and Training provider and a consortium of major employers.
The resulting data will provide tangible evidence of the effectiveness of the underpinning core technology, the sentiment analysis requirement and machine based leaning algorithms.
The proposed project is expected to run for nine months and cost £481,797\."
Lead Participant | Project Cost | Grant Offer |
---|---|---|
SKILLZ MINER LIMITED | £478,797 | £ 335,158 |
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Participant |
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INNOVATE UK |
People |
ORCID iD |
Kirsty Mitchell (Project Manager) |