Presentation of Sasha Lazarevic at HR Hackaton, April 2018

1. AI in HR
Sasha Lazarevic, IBM
https://www.linkedin.com/in/lzrvc/
LZRVC.com

2. 1936 1997 20162011
1950
Turing
Test
1981
1958
First
Chess
Program
AI as
research
1956 20061998 2014
IBM Jeopardy!
Google AlphaGo
Chatbot
Visual Recognition
Navigation
IBM DeepBlue
Geoff Hinton
Google Car
2012
Sophia Robot
2015
History of AI

3. Internet
Neuroscience
IOTBig Data
Artificial Intelligence
Machine Learning
Deep Learning
Natural Language
Processing
Robotics
Sensorial
systems
Multiagent
systems
Search Algorithms
Languages:
- R
- Python
- NodeJS
Platforms:
- Watson
- Amazon
Frameworks:
- TensorFlow
- Keras
Deep Learning and Big Data : Engine of the modern AI

4. Andrew Ng:
“AI is the new electricity”

5. Role of AI in the Enterprise
• Automation of simple and repetitive tasks
• Enhance workers’ capabilities
• Improve responsiveness to external events
• Learn from data

6. New Challenges for HR
• Improve Employee Experience (EX)
• Are new “AI” systems going to be added on top of the existent ?
• Building relevant data
• Hiring AI talents and AI training
• Cultural challenges
• Remove bias
• Robot as Manager ?

7. Role of AI in HR Processes
Process Impact Time Horizon
Planning Proactively identifying resource requirements 2-3 Y
Recruitment Multiple *) Now
Culture Development Alignment analysis 5 Y
Evaluation Use of multiple data and comm sources for
continuous evaluation (360 degrees)
2-3 Y
Remuneration Alignment and recommendations 2-3
Training Customized, AI-based training and coaching 5 Y
Absences Predict absences, contingency plans 2-3 Y
ERM and well-being Burnout prediction, Chatbots 2-3 Y
Retention Predictive analytics Now
Reporting and compliance Robotic process automation 2-3 Y
Exits Feedback analysis 2-3 Y

8. AI in Recruitement
• Identify internal talents
• Applicant tracking systems
• Bias-reduction tools
• Chatbots
• Personality Insights
• AI-based analysis of video interviews
• Comparisons
• Automatic responses and follow-up scheduling
• Useful feedback to the rejected candidates
Example: Hirevue AI assessment

9. AI in Retention
• Use external data (job market)
• Internal roles, promotions, other factors
• Recommendations on how to mitigate the risk
Example: Workday Retention Strategies

10. Other Examples
• Textio Augmented Writing for better job postings
(exceptional vs extraordinary, managing vs developing, “able to work under pressure”)
• Humanyze People analytics
(Organizational Network Analysis, Wearable devices to measure interactions at
workplace and promote balanced interactions)
• Pymetrics Recruitement games
(bias-free, machine learning to determine success factors from the existing employees,
testing 80 factors through games)

11. Cultural Challenges of the Use of AI in HR
• PWC study: “75 percent of hiring organisations provides no feedback to unsuccessful
candidates, while 18 percent of the candidates stops being a customer of the
company that rejected them. ”
• Match the expectations of the candidates with the expectations of the teams they
might be joining

12. Demo: IBM Watson