<?xml version="1.0" encoding="UTF-8"?><ns2:project xmlns:ns1="http://gtr.rcuk.ac.uk/gtr/api" xmlns:ns2="http://gtr.rcuk.ac.uk/gtr/api/project" xmlns:ns3="http://gtr.rcuk.ac.uk/gtr/api/fund" xmlns:ns4="http://gtr.rcuk.ac.uk/gtr/api/person" xmlns:ns5="http://gtr.rcuk.ac.uk/gtr/api/project/outcome" xmlns:ns6="http://gtr.rcuk.ac.uk/gtr/api/organisation" ns1:created="2026-06-22T07:57:45Z" ns1:href="http://gtr.ukri.org/gtr/api/projects/ED1C5C6E-5C9E-4FF1-9BE6-94E545F0699A" ns1:id="ED1C5C6E-5C9E-4FF1-9BE6-94E545F0699A"><ns1:links><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/persons/8467A9F6-E10B-439F-8C70-3BA3C0A96C5A" ns1:rel="PM_PER"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/B1B6B199-BE48-48BB-AB7C-739DF85D3CF7" ns1:rel="LEAD_ORG"/><ns1:link ns1:href="http://gtr.ukri.org/gtr/api/organisations/B1B6B199-BE48-48BB-AB7C-739DF85D3CF7" ns1:rel="PARTICIPANT_ORG"/><ns1:link ns1:end="2021-03-30T23:00:00Z" ns1:href="http://gtr.ukri.org/gtr/api/funds/B673D6BF-0EC9-486D-8268-26D1DF6BAFAD" ns1:rel="FUND" ns1:start="2021-01-01T00:00:00Z"/></ns1:links><ns2:identifiers><ns2:identifier ns2:type="RCUK">92689</ns2:identifier></ns2:identifiers><ns2:title>Recruitment Artificial Intelligence for Social Equality (RAISE)</ns2:title><ns2:status>Closed</ns2:status><ns2:grantCategory>Collaborative R&amp;D</ns2:grantCategory><ns2:leadFunder>Innovate UK</ns2:leadFunder><ns2:abstractText>Currently labour supply is on a demand-led basis. This is extremely slow and inefficient at dealing with economic and social change and also does not identify people who are currently &amp;quot;under employed&amp;quot; (those who are working but with less hours than they need/could work). The process of person specifications and screening is time consuming and often exacerbates equality and diversity inclusion issues by relying on metrics which can lead to unconscious bias. It inadvertently excludes good candidates by using inappropriate measures and makes it difficult for workers to transition between sectors, even if they have the transferrable skills to be successful.

The recent COVID-19 crisis has exposed how traditional recruitment approaches do not allow for sudden fluctuations in demand for labour which creates demand in some sectors (for example delivery drivers) whilst those in hospitality have no work. It also highlighted difficulties in mobilising a keen, growing volunteer workforce and matching them with tasks requiring completion.

RAISE will rectify this situation by developing a unique AI functionality to place the person at the heart of the system. It will take a 'can-do' approach and learn the best approaches to recruitment utilising candidate's competencies rather than credentials.</ns2:abstractText></ns2:project>