James Grant of Weavee speaks at Recruiter Day 2018 in Luxembourg on the topic of AI (Artificial Intelligence) and diversity. Along with offering tips on the subject and suggestions on how to drive corporate diversity efforts using technology to reduce unconscious bias.

1. Keynote, Recruiters Day 2018
By James Grant, Weavee
Link to keynote: http://bit.ly/RDWeavee
Featured in

2. The connection to Recruiters Day
https://blog.weavee.co.uk/

3. About us, the team and background
Raj Hayer
Managing Director - Motivational Coaching - Psychometric Analysis
James Grant
CEO - Discovery Executive - Computer/Data Science - Techie
Ian Dawud
Organisational Psychology - Linguistics - City University
Providing moral support from London

4. Solving employee engagement
We enable managers to understand if they are “intrinsically motivating” their
employees
“Managers contribute 70% of
workforce employee
engagement” - Gallup
Weekly “pulses” measure
effectiveness
“Engaged companies
perform 22% better than
competitors” - Gallup

5. Some Weavee achievements
The 'Rec Tech' Revolution: Four
Startups Shaking Up The Way You
Get Hired
The tech startups using AI to
disrupt the recruitment industry
Remploy is using Weavee to counter unconscious
bias and help disabled job candidates secure roles
on the strength of their ability.
Weavee obtains EU H2020 Seal of
Excellence and Recommendation
for Funding
Engage ESM completes Weavee
Pilot to understand the unrealised
potential in their teams
NFU Mutual completes a pilot of
the Weavee platform to understand
the cognitive diversity in their
teams

6. How AI could BREAK
“recruiting for diversity”
Deloitte
“32 percent increase in inclusion and diversity as the top business priority
since 2014” - “69% of executives”

7. What is the language of recruitment?
Psychometrics
Measuring the of mind, ability, personality, intelligence
Diversity
Inclusion of different variations in people, background, race, gender and
cognitive mind within the workplace
Machine Learning (Artificial Intelligence)
Identifying repeatable patterns and automating their execution without
human intervention

8. 30% Male
70% Female
80% Male
20% Female
Why is diversity important?
Diversity helps reach the true customer base
Company Customers
Improves
Innovation
Higher Financial
Performance
Improves
Creativity

9. How do we traditionally solve diversity?
Recruiter
Finds people who meet
business requirements
Manager
Measurement of employees
progression
Feedback on diversity
benefits

10. Who really controls the problem?
Managers
They control 60% of employee performance - Towers Watson
Inclusivity and equal voice lead team performance - Google
Chosen Business Solution
Artificial Intelligence - 20% of organisations are using it to counter the problem
Unconscious bias
39% of Managers in the UK have not received training

11. Receive recommendation
Business Requirement
Big Data
How Does Machine Learning Work?
Benefit: Efficiency | Speed | Automation
Measure and repeat
for increased
accuracyLook for patterns

12. What problems can appear?
Bad Recommendation OutBad Data in
What is bad data?
Missing sections of information
Choosing to use the wrong dataset
Making “assumptions”
AI is dumb

13. How does this impact on real life?
A day after Microsoft introduced an
innocent Artificial Intelligence chat robot
to Twitter it has had to delete it after it
transformed into an evil Hitler-loving' -
proclaiming robot
2016
Effective AI creates super efficiency
But it is not “human”, it will base it on whatever we “train” it with

14. How can AI BREAK recruitment diversity?
Data Points
Gender
Age
Ethnicity
Religion
Education
Output
30-40yr
White
Male
Christian
Harvard
90% of High Performers in organisation are
30 - 40yr, White, Male, Christian, Harvard
It’s not really possible use ethical AI on this organisation
- A vendor AI could offer “industry” advice and benchmarks -

15. Reversing traditional diversity
Cognitive Diversity
Human Capital
Use no other data points
SkillsExperiences
PersonalitiesAbilities

16. Scientific led data collection
Big Five Personality Psychometric
O - Openness
C - Conscientiousness
E - Extraversion
A - Agreeableness
N - Neuroticism
The most scientifically and psychologically accepted model for accuracy,
reliability, predictability
Top tip: Obtain the data from everyone or it will be skewed to top
performers and management

17. Scientific Diversity Example
52% Friendliness Gap
To increase collaboration
improve friendliness
...so the AI hires 100% friendly people

18. How does increasing friendliness affect the company?
Lower Potentially
Better client turnaround
Unwelcoming
Higher Potentially
Outgoing
Easily bored
Consider: What are the cultural and environmental influences?

19. How do we mitigate the AI risk?
Candidate cognitive data against the role profile
A
+10% gender diversity
B
+10% cognitive diversity
C
+10% clientbase match
Demographic data
Recruiter decides what is most critical to solve - AI recommends on most effective placement

20. Summary: Who should process the data?
Handles huge datasets
Only does what it learns
Can build benchmarks
Inflexible to localised problems
Will require a specialised vendor
Artificial Intelligence

21. Summary: Who should process the data?
Human Intelligence
Handles small datasets
Understands soft data usage
Makes localised tweaks
Influences the culture of work
Flexible to changing world

22. Summary: Who should process the data?
Handles huge datasets
Only does what it learns
Artificial Intelligence Human Intelligence
Handles small datasets
Understands soft data usage
Working together to learn
what’s right for the company
and its people
Provides
recommendations
Provides
Parameters/Feedback

23. +
Thank You
https://www.weavee.co.uk
james@weavee.co.uk
+44 7411 533122
Weavee
Transform Your Human Capital
Access team unrealised potential
View my personality at: http://bit.ly/BigFiveJames
=Your People Growth