AI and the Future of Recruitment - Recruiting Community · Emb Deep NN Emb Deep NN CV Applications...
Transcript of AI and the Future of Recruitment - Recruiting Community · Emb Deep NN Emb Deep NN CV Applications...
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AI and the
Future of
RecruitmentJakub Zavrel
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About me
Jakub Zavrel
Founder of Textkernel (2001), since 2015 part of
CareerBuilder group. New venture: Zeta Alpha (2019)
R&D background in AI, Machine Learning & NLP since 1990.
Born 1970 in Prague, raised in Rotterdam, lives in
Amsterdam with wife and 2 teenage daughters.
Eclectic music tastes.
AI for People and Jobs / Semantic Recruitment / Labor
Market Analysis / Natural Language Processing / Machine
Learning / Search & Match / Enterprise Software
@jakubzavrel
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I like programming, but I’m interested do take on more project
management responsibility
Is there a job in our organisation that better fits my degree?
I’d like to work on our mobile strategy. I’ve helped a friend
develop a mobile app.
I’d like to do more with my organisational
talent.
We are looking to hire:
An experienced tech team team lead
Labour Market:
a Language Gap
The ideal candidate has:
- min. 5yr of experience
- Certfied scrummaster
- Exp. w/iOS, Android
Completed academic studies
Computer Science or related
30% travel for customer presentations
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In the next 5-10 years, AI will reach a level of near or super
human performance in many domains, including understanding
language and connecting supply and demand.
AI will fundamentally change the way people and jobs connect
in the global marketplace, and will remove market barriers
caused by language meaning variation and lack of
transparency.
What will this mean to recruiters and job seekers?
Why?
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What do recruiters do?
Attracting
candidatesProcessing
candidatesSelecting
candidates
Chasing Line
Managers
Sourcing
Re-engagement
Employer Branding
Advertising
Referral Basic information
Scheduling
Data Entry
Screening
Scoring
Job offers
Contracts
Interviews
Assessment
WTF?!
Understanding
the job
AI Revolution: lowers the cost of repetitive cognitive tasks...
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AI: The miracle algorithm?
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Right candidate, right time, right price!
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So what if you have technology that actually understands:
• the real requirements of the job
• the key factors to be successful
• the type of person most likely to succeed
• what your offer should be
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So what do we mean by AI?
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The power of machine learning
“Human-level control through deep reinforcement learning” V Mnih, et al. Nature, 2015
https://youtu.be/TmPfTpjtdgg
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Understanding concepts and relationships
“Deep Visual-Semantic Alignments for Generating Image Descriptions”
Andrej Karpathy, Li Fei-Fei, et al. CVPR, 2015
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thispersondoesnotexist.com- Generating Deep Fakes
“A Style-Based Generator Architecture for Generative Adversarial Networks”
Karras, et al. arXiv, 2018
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AI learning to use tools?
“Improvisation through Physical Understanding: Using Novel Objects
as Tools with Visual Foresight”, Xie, et al. ArXiv, 2019
https://bair.berkeley.edu/blog/2019/04/11/tools/
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https://techcrunch.com/2019/02/17/openai-text-generator-dangerous/
See: https://openai.com/blog/better-language-models/
February 14th, 2019.
Try it yourself: https://talktotransformer.com/
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Ability to solve problems with unknown rules
What does Machine Learning give us?
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Pattern discovery in volumes of data no human being is able to digest
What does Machine Learning give us?
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Optimize solutions to problems with any value that we can define
What does Machine Learning give us?
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What does Machine Learning give us?
Any human behavior for which we can collect sufficient data can be automated
by AI / Machine Learning
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AI is Mainstream
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Why now? Computing power, data, algorithms
Deep Learning
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Deep Learning is the ability
for AI algorithms to automatically
learn meaningful patterns in
data using layered brain-like
structures called
Deep Neural Networks
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Deep Learning: Hierarchically abstract information
• Use lots of unlabeled data• Deep multi-layered networks• Automatically finds relevant features
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Understanding, connecting and analyzingpeople and jobs
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Given a job, how do we find the relevant
candidates for the job among thousands or millions of CV’s?
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Match!
Search!
CV Extraction
job=Java Developercity=Amsterdamlangskill=Germanexperience=7
CV MatchNormalizer
job=23branch=ITlangskill=DEexperience=7loc=Amsterdam
Vacancy MatchNormalizer
job=23branch=IT
langskill=DEexperience=5..10
loc=Amsterdam+10
Vacancy Extraction
job=Java Ontwikkelarcity=Amsterdamlangskill=Duitsexperience=7
Match!
Match! models construct the Search! Data Model out of extracted information.
The XML fits the Search! Data Model and is semantically enriched when INDEXING.
The result is a QUERY that fits the Search! Data Model. It is semantically enriched when executed
Data Model
job branch langskill location
experience
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item 1
item 2
item 3
Previous Machine Learning Approach:
- Hidden Markov Models
- Conditional Random Fields
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developermanager
engineer
CEO
CF
OCT
O
CO
O
2001 CEO at TextkernelInput:
Date Job - Company
Deep Learning for CVs and JobsWord embeddings
Recurrent Neural Networks (LSTM)
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Extract! 4.O
Disrupting the playing fieldA qualitative leap through Deep Learning
Deep Learning
Textkernel
AC
CU
RA
CY
CV parsing
(competition)
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job=Java
Developer
city=Utrecht
langskill=German
experience=7
job=23
branch=IT
langskill=DE
experience=7
loc=Utrecht
job=23
branch=IT
langskill=DE
experience=5..10
loc=Amsterdam+30
job=Java
Ontwikkelar
city=Amsterdam
langskill=Duits
experience=7
Match!
Search!
Data Model
job branch
langskill
location
experience
CV parsingSemantic
understanding
Semantic
understanding
Vacancy parsing
Intentions/Needs Intentions/Needs
Behavior:
Clicks, applies
Behavior:
Clicks, shortlist
Learning To Rank, Mine knowledge
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Example of Matching
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Turning the job description into a rich query
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Learning from Feedback:
• Which candidate is the best?• Which criterion is more important?
• How about combination of criteria?
• How about domain biases?
• What if we can learn this automatically from feedback?
• Learning to Rank• Reorder a pool of candidates through machine learning
• E.g. Based on recruiter preference or past performance
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Next Chapter:Deep Learning Matching
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CV to Job Match: document embeddings
CV
Match!
query
Search!
JOBs
Job-title, it
skills,
experience
years,
keywords...
CV
JOBs
DLMatch!
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Emb Deep NN
Emb Deep NN
CV
Applications
jobs
Distance
calculation
Deep Learning Matcher
Learn representation in shared space of CV and Vacancy texts such that Relevant CVs are close to the Vacancy and Irrelevant CVs are far.
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SECURITY
OFFICER
SECURITY
OFFICER JOB
SECURITY
OFFICER JOB
REGISTERED
NURSE JOB
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SECURITY
OFFICER
SECURITY
OFFICER JOB
SECURITY
OFFICER JOB
REGISTERED
NURSE JOB
Push far
Push close
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SECURITY
OFFICER
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Summary Efficient and organized surveillance professional with 15 years in security and safety compliance. Accomplished management
professional specializing in creating, launching and operating retail locations. Experience 10/2014-Present Security Officer US Security 04/2014-
01/2015 Security Officer Bristol Protective Service 08/2012- 09/2013 Metro Task Force Patrolled the facility and served as a general security
presence and visible deterrent to crime and rule infractions. Reported all incidents, accidents and medical emergencies to law enforcement.
Patrolled industrial and commercial premises to prevent and detect signs of intrusion and ensure security of doors, windows and gates.
Continuously monitored security cameras and fire, building and alarm systems. 08/2008-05/2009 Kitchen Director, Garden Day Care Center *
Collaborated extensively with interdisciplinary care team to meet the nutritional needs of each Senior. Established healthful and therapeutic meal
plans and menus. Encouraged clients and caregivers to follow recommended food guidelines for well-balanced diets. 08/2006-04/2008 Cashier,
Kmart * Maintained up-to-date knowledge of store policies regarding payments, returns and exchanges. Excelled in exceeding daily credit card
application. Created new processes and systems for increasing customer service satisfaction. Replenished floor stock and processed shipments
to ensure product availability for customers. 10/2005-01/2006 Sales Associate, Express Clothing Store * Computed sales prices, total purchases
and processed payments. Operated a cash register to process cash, checks and credit card transactions. Recommended merchandise based on
customer needs. Explained information about the quality, value and style of products to Influence customer buying decision. Education 01/2016-
05/2016 Essex County College High School Diploma
Query
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ResultResult #1
Security Officer (New Jersey)
Join one of the fastest growing security companies in the U.S.! Since 1998, Sunstates Security has established a reputation for providing
excellent customer service and quality work environments while being recently recognized as one of the top 25 largest security providers in
America.
Result #2
Security Officer - Regular - Paterson, NJ
Observes and reports activities and incidents at an assigned client site, providing for the security and safety of client property and
personnel.Makes periodic patrols to check for irregularities and to inspect protection devices and fire control equipment.Preserves order and may
act to enforce regulations and directives for the site pertaining to personnel, visitors, and premises.Controls access to client site or facility through
the admittance process
Result #3
Security Officer - Regular - Summit, NJ
Observes and reports activities and incidents at an assigned client site, providing for the security and safety of client property and
personnel.Makes periodic patrols to check for irregularities and to inspect protection devices and fire control equipment.Preserves order and may
act to enforce regulations and directives for the site pertaining to personnel, visitors, and premises.Controls access to client site or facility through
the admittance process
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DLM is
33%less likely to return irrelevant results
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Intentions/Needs Intentions/Needs
I’d like to do more with my
organisational talent.
I’d like to work on our mobile strategy. I’ve helped
a friend develop a mobile app.
Is there a job in our organisation that better
fits my degree?
I like programming, but I’m interested do take on
more project management responsibility
Motivated and driven sales rep
We need an engineer with great customer
interaction skills
Somebody to spearhead our corporate
strategy
I want somebody to replace my best engineer that is
leaving at the end of the month
Match!
Behavior:
Clicks, applies
Behavior:
Clicks, shortlist
Assessments:Questionnaires,
personality, culture
Assessments:Questionnaires,
personality, culture
Jobseeker
AI AssistantRecruiter
AI Assistant
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Intentions/Needs Intentions/Needs
I’d like to do more with my
organisational talent.
I’d like to work on our mobile strategy. I’ve helped
a friend develop a mobile app.
Is there a job in our organisation that better
fits my degree?
I like programming, but I’m interested do take on
more project management responsibility
Motivated and driven sales rep
We need an engineer with great customer
interaction skills
Somebody to spearhead our corporate
strategy
I want somebody to replace my best engineer that is
leaving at the end of the month
Match!
Jobseeker
AI AssistantRecruiter
AI Assistant
Requirements:
Services
Powers desktop + mobile apps
Chat bot capability
Messaging center
Market platform
PLATFORM
Functionality
Semantic Search & Match
Knowledge graph
S&D data (fusion with other sources)
User profiles
Language understanding
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Conversational
Agents
• 24/7 service
• Massive outreach to
candidates
• Avoid black hole, keep
interaction going
• Pre-screen for interest
and availability, as well
as skills.
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Conversational Search
• Conversational interfaces• Guiding, “do you mean”, etc
• Natural language search• Query understanding
• Chatbot interaction
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AI: The miracle algorithm?
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Right candidate, right time, right price!
Remember: it’s all measurable!!!
Fairness? Bias?
Explainability?
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And remember this:
• Machines will not call in sick or complain about the work they do, but they will also not likely be able to enjoy it!
• So please do enjoy your job and celebrate your success! (while it lasts ;-)