How will AI, Machine Learning, Deep Learning, Blockchain and VR change the way we attract talent.

2. Artificial Intelligence disruption:
How technologies are predicted to change the
way we manage talent
Przemek Berendt
VP Global Marketing
Luxoft
@pberendt Linkedin.com/pberendt

3. Are we doomed?

4. DEFINITION
AI is a collective term for computer
systems that can sense their
environment, think, learn, and take
action in response to what they’re
sensing and their objectives
What is AI
Source:

5. AI Taxonomy
Deep Learning Machine Learning Artificial Intelligence
The subset of machine learning
composed of algorithms that permit
software to train itself to perform
tasks, like speech and image
recognition, by exposing
multilayered neural networks to vast
amounts of data.
A subset of AI that includes
abstruse statistical techniques that
enable machines to improve at
tasks with experience. The category
includes deep learning.
Any technique that enables
computers to mimic human
intelligence, using logic, if-then
rules, decision trees, and machine
learning (including deep learning)

6. AI works in 4 ways
Hardwired
/specific
systems
Adaptive
systems
Assisted Intelligence
AI systems that assist
humans in making decisions
or taking actions. Hard-
wired systems that do not
learn from their interactions.
Human in the loop
Assisted Intelligence
AI systems that augment
human decision making and
continuously learn from their
interactions with humans
and the environment.
+
Automation
Automation of manual and
cognitive tasks that are
either routine or non-routine.
This does not involve new
ways of doing things –
automates existing tasks.
No human in the loop
Autonomous Intelligence
AI systems that can adapt to
different situations and can
act autonomously without
assistance.

7. AI revolution is already happening

8. Productivity growth
1850 - 1910 1995-2005 1993 - 2007 2015-2065
0.3%Steam Engine
0.6%IT
0.4%Early Robotics
0.8 – 1.4%Automation
Source: McKinsey Global Institute
The activities most susceptible to automation are physical ones in highly structured and
predictable environments, as well as data collection and processing.

9. Where will the value gains come from with AI?
15.7
trillion
Global GDP growth
by 2030

10. AI in Talent Acquisition

11. Candidate Journey
Awareness
Application Recruitment
process Background
check
Offer
On
boarding
Day 1
Look alike
modeling
Engagement
Exit planning
Research &
Exploration
Job
Discovery
Apply
Interview
Paperwork Negotiations
Profile
augmentation
Candidate
outreach
Chatbot
CV Screening
Company
Candidate
Language
competency test
Advanced
competency test
Appointment
setting
Video interview

12. Programmatic advertising – look alike modeling
Identify
applications of
ideal candidates
Career website
Track growth and
conversion of
incoming web
traffic
Pipeline growth
Capture their
cookie data from
website
Cookies
Find ‘cookies’ that
look alike your data
set
DMP
Advertise to ‘look
alike set’
Advertising

13. Profile Augmentation
Data we control
Search engine data
On-site search data
Intent Graph
+
Behavior data
Browsing history
Pages visited
Valued outcomes
DISC Profile
Social Graph
Shared content
Brand affinity
Data we don’t control

14. Candidate Outreach – 100K versions of EVP
Intelligent targeting Marketing AutomationData Science
Analyze millions of
data points to
understand personas
and their behaviors
Build multiple ways
your EVP is
conveyed
Deliver right
messages at the
right time

15. Candidate Outreach – personalize the message

16. Chatbot
• Works 24/7
• Can proactively talk to career
website visitors
• Can nurture candidates across
funnel
• Handle basic questions on company
culture benefits
• Guide through application process
• Provide immediate feedback on
application

17. ChatBot & ML Assisting Application
Linkedin Social
Login
CV Upload Machine Learning
identifies gaps
Chatbot
Capture Basic Data Convert text into
data points in your
Talent Management
Solution
Compare candidate
with records of your
employees
Fill out gaps by
asking questions

18. CV Screening
Your HR data Automated CV Screening Find patterns
CVs of your
employees
Scan not only key words
but meaning
Talk to most
promising candidates

19. Language competency
Natural Language
Processing
• Fluency
• Pronunciation
• Vocabulary usage
• Grammatical complexity
• Topical coherence
• Progression of ideas

20. Advanced competency test
Neuroscience games
Cognitive traits
• Processing speed
• Pattern recognition
• Continuous attention
• Ability to avoid
distraction
• Impulsivity
• Working memory
• Planning
• Sequencing
• learning
Emotional traits
• Trust
• Risk profile
• Reward sensitivity
• Perseverance
• Tolerance for ambiguity
• Emotional sensitivity
• Creativity
• Learning from feedback
• Ability to delay
gratification
Understand the candidate
on a deep level through fun

21. Video Interview
Natural Language
Processing
+
Facial Recognition
• Body language
• Word choice
• Tone
• Interview transcript
https://www.hirevue.com/blog/how-to-take-a-hirevue-interview/

22. Appointment setting
https://x.ai/how-it-works/

23. Blockchain Resume
Blockchain
A blockchain is a decentralized and distributed
digital ledger that is used to record transactions
across many computers so that the record cannot
be altered retroactively without the alteration of all
subsequent blocks and the collusion of the
network. This allows the participants to verify and
audit transactions inexpensively. They are
authenticated by mass collaboration powered by
collective self-interests. The result is a robust
workflow where participants' uncertainty regarding
data security is marginal.
https://en.wikipedia.org/wiki/Blockchain
A person (subject of verification), educational
institutions and employers would have a
unique ID and participate in such blockchain
Every event
• Completed course
• Degree
• Job
• Role
• Assignment
Is reflected in the blockchain as a transaction
in the ledger
No need for background checks!

24. VR
Source; Facebook Spaces
Use cases:
• Video interview
• Meet the team
• See your future working environment
Benefits
• Enhanced candidate experience
• Might remove unconscious bias

25. Are recruiter jobs at risk?
“Just as spreadsheets drove costs down and demand up for
calculations, machine learning—the application of AI to large
data sets—will do the same for predictions, argue Ajay
Agrawal, Joshua Gans and Avi Goldfarb”
“The combination of the AI system and specialist
staff has brought about increased productivity,
meaning Otto customers are now getting their
orders sooner and are therefore more likely to
remain loyal to the company.”
https://www.weforum.org/agenda/2017/06/why-ai-technology-
isn-t-always-a-threat-to-your-job/

26. How your role may change
Teach AI systems how
they should perform
AI Trainers
Using AI to architect
educational and
career track based on
data
Career engineer
Bridge the gap
between technologists
and business leaders.
provide clarity, as AI
systems’ opaqueness
increases.
Explainers
Will help ensure that
AI systems are
operating as designed
and that unintended
consequences are
addressed with the
appropriate urgency.
Sustainers
Using data, and AI
analysis to find best
next move
Career Coach
http://sloanreview.mit.edu/article/will-ai-create-as-many-jobs-as-it-eliminates/

27. How much time we have
Katja Grace's team at the University of Oxford’s
Future of Humanity Institute contacted 1634
leading AI academics and industry experts from
around the world to ask them when they thought
intelligent machines would outperform humans
at a variety of tasks and occupations, and when
they would be superior at all tasks.
A total of 352 experts responded, and the
researchers calculated median dates based on
their predictions.
https://www.weforum.org/agenda/2017/07/how-long-before-a-robot-takes-your-job-here-s-when-ai-experts-think-it-will-happen/

28. Companies to watch
https://x.ai/how-it-works/
https://www.hirevue.com/https://www.thiswayglobal.com/https://beamery.com/https://www.pymetrics.com/
https://hiremya.com/
http://jobbot.ai/
http://nordic.businessinsider.com/unilever-artificial-intelligence-hiring-process-2017-6/
https://ideal.com/ai-recruiting/

29. How to prepare
Stay up to date with
emerging technologies.
Identify missing skills
Learn
Keep trying existing
solutions
Experiment
Bring AI tools to your
daily work, see if it
can help you
Adopt

30. Thank you
@pberendt Linkedin.com/pberendt