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How To Power Your HR Apps With AI And
Make It Explainable
Harbinger Systems
in association with HR.com
December 5, 2019
©Harbinger Systems | www.harbinger-systems.com 2
Speaker Introduction
Shrikant Pattathil Maheshkumar Kharade
President
Harbinger Systems
AGM - Technology
Harbinger Systems
©Harbinger Systems | www.harbinger-systems.com
Agenda
Key AI Trends in HR Tech
HRTech use cases of AI enabled applications
Challenges faced in leveraging AI features and how to overcome those?
Summary
Poll #1
Are you using AI-enabled HR applications and solutions in your organization?
A. Yes
B. No
C. Don’t know
©Harbinger Systems | www.harbinger-systems.com
Key AI Trends in HR Tech
©Harbinger Systems | www.harbinger-systems.com
AI Trends in HRTech – Harbinger Analysis
2018 2019
• Talent Acquisition
• Training and Development
• Performance Management
• Time and Attendance
• Analytics and metrics
• Talent acquisition
• Training and Development
• Compensation and Payroll
Use of AI in HR Functions
Virtual Assistant
Recommendation Engine
Pattern Recognition
Analyze and Diagnose
Predict
Personalize
©Harbinger Systems | www.harbinger-systems.com
Top Expectation for AI enabled HR Applications
Ability to analyze (e. g. Run an automated analysis of a data set and then spot patterns)
Ability to predict (e. g. Predict which job candidate will result in the highest quality of hire)
Ability to personalize (e. g. Personalize training modules based on current knowledge
level)
Ability to automate (e. g. Use AI to create answers for HR related questions)
©Harbinger Systems | www.harbinger-systems.com
HR Tech Use cases of AI enabled applications
©Harbinger Systems | www.harbinger-systems.com
Example #1: Candidate Matching and Scoring
©Harbinger Systems | www.harbinger-systems.com
How to make sure that there is no bias in scoring and matching?
©Harbinger Systems | www.harbinger-systems.com
Example #2: AI-based Personalized Learning Experience
©Harbinger Systems | www.harbinger-systems.com
What details are captured to track user actions and search patterns? Is it collecting
any private information about users?
©Harbinger Systems | www.harbinger-systems.com
Example #3: AI-based HR Help Desk
©Harbinger Systems | www.harbinger-systems.com
Are the questions coming from a reliable source?
Poll #2
What challenges do you foresee while deploying such AI applications in
your organization?
A. Cost of implementation
B. AI technology is too new
C. Fear of bias in data
D. Lack of explanation how decision is made
©Harbinger Systems | www.harbinger-systems.com
Challenges faced in leveraging AI features and
how to overcome those?
©Harbinger Systems | www.harbinger-systems.com
• Data source
• Compliance
Quality of Data
• Organizing
• Cleansing
• Anonymizing
Data
Transformation • AI algorithms
• Explanation of
results
• Correctness
Insights into
working of AI
Challenges
©Harbinger Systems | www.harbinger-systems.com 18
Quality of data
Good
Data
Right
Model
Better AI
Getting “Good Data”
is the biggest
challenge and most
time consuming!
©Harbinger Systems | www.harbinger-systems.com 19
Data Transformation
Gathering
(Multiple
Sources)
Cleansing
Anonymizing
Organizing
Raw data transformation to
good AI data
Data
processing
is unique to
each
organization
©Harbinger Systems | www.harbinger-systems.com
Explainable AI
Ref: https://www.datanami.com/2018/05/30/opening-up-black-boxes-with-explainable-ai/
©Harbinger Systems | www.harbinger-systems.com
Example #4: Candidate Matching and Scoring
Using Explainable AI
Poll #3
Do you think all AI-enabled HR applications should be explainable?
A. Yes
B. No
C. Don’t know
©Harbinger Systems | www.harbinger-systems.com
Other Challenges
Innovation first occurring outside of the suites
Of limited value to smaller/lower volume organizations
Data science skills and experience within the HR department to ensure safe and effective
operations
©Harbinger Systems | www.harbinger-systems.com
Summary
©Harbinger Systems | www.harbinger-systems.com 25
Recap
AI in HRTech
• Talent acquisition
continue to lead the way
in using AI innovatively
• Use of AI for Prescriptive
and Predictive use cases
is catching up in modules
such as Training and
Development,
Compensation, Payroll
etc.
Challenges
• Bias in results due to
nature of data
• Evaluating the
correctness and
reliability of data
• Ensuring the ethical
capturing and use of data
• Understanding working
of AI models and
algorithms
Key to success
• Providing insights into
use of data by AI
• Explaining the AI results
• Provide explainable
interface
©Harbinger Systems | www.harbinger-systems.com
QnA
Please use Question Box
©Harbinger Systems | www.harbinger-systems.com
Thank you
27
Contact Us
Shrikant Pattathil – shrikant@harbingergroup.com
Maheshkumar Kharade – maheshkumar@harbingergroup.com

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How to Power Your HR Apps With AI And Make It Explainable

  • 1. How To Power Your HR Apps With AI And Make It Explainable Harbinger Systems in association with HR.com December 5, 2019
  • 2. ©Harbinger Systems | www.harbinger-systems.com 2 Speaker Introduction Shrikant Pattathil Maheshkumar Kharade President Harbinger Systems AGM - Technology Harbinger Systems
  • 3. ©Harbinger Systems | www.harbinger-systems.com Agenda Key AI Trends in HR Tech HRTech use cases of AI enabled applications Challenges faced in leveraging AI features and how to overcome those? Summary
  • 4. Poll #1 Are you using AI-enabled HR applications and solutions in your organization? A. Yes B. No C. Don’t know
  • 5. ©Harbinger Systems | www.harbinger-systems.com Key AI Trends in HR Tech
  • 6. ©Harbinger Systems | www.harbinger-systems.com AI Trends in HRTech – Harbinger Analysis 2018 2019 • Talent Acquisition • Training and Development • Performance Management • Time and Attendance • Analytics and metrics • Talent acquisition • Training and Development • Compensation and Payroll Use of AI in HR Functions Virtual Assistant Recommendation Engine Pattern Recognition Analyze and Diagnose Predict Personalize
  • 7. ©Harbinger Systems | www.harbinger-systems.com Top Expectation for AI enabled HR Applications Ability to analyze (e. g. Run an automated analysis of a data set and then spot patterns) Ability to predict (e. g. Predict which job candidate will result in the highest quality of hire) Ability to personalize (e. g. Personalize training modules based on current knowledge level) Ability to automate (e. g. Use AI to create answers for HR related questions)
  • 8. ©Harbinger Systems | www.harbinger-systems.com HR Tech Use cases of AI enabled applications
  • 9. ©Harbinger Systems | www.harbinger-systems.com Example #1: Candidate Matching and Scoring
  • 10. ©Harbinger Systems | www.harbinger-systems.com How to make sure that there is no bias in scoring and matching?
  • 11. ©Harbinger Systems | www.harbinger-systems.com Example #2: AI-based Personalized Learning Experience
  • 12. ©Harbinger Systems | www.harbinger-systems.com What details are captured to track user actions and search patterns? Is it collecting any private information about users?
  • 13. ©Harbinger Systems | www.harbinger-systems.com Example #3: AI-based HR Help Desk
  • 14. ©Harbinger Systems | www.harbinger-systems.com Are the questions coming from a reliable source?
  • 15. Poll #2 What challenges do you foresee while deploying such AI applications in your organization? A. Cost of implementation B. AI technology is too new C. Fear of bias in data D. Lack of explanation how decision is made
  • 16. ©Harbinger Systems | www.harbinger-systems.com Challenges faced in leveraging AI features and how to overcome those?
  • 17. ©Harbinger Systems | www.harbinger-systems.com • Data source • Compliance Quality of Data • Organizing • Cleansing • Anonymizing Data Transformation • AI algorithms • Explanation of results • Correctness Insights into working of AI Challenges
  • 18. ©Harbinger Systems | www.harbinger-systems.com 18 Quality of data Good Data Right Model Better AI Getting “Good Data” is the biggest challenge and most time consuming!
  • 19. ©Harbinger Systems | www.harbinger-systems.com 19 Data Transformation Gathering (Multiple Sources) Cleansing Anonymizing Organizing Raw data transformation to good AI data Data processing is unique to each organization
  • 20. ©Harbinger Systems | www.harbinger-systems.com Explainable AI Ref: https://www.datanami.com/2018/05/30/opening-up-black-boxes-with-explainable-ai/
  • 21. ©Harbinger Systems | www.harbinger-systems.com Example #4: Candidate Matching and Scoring Using Explainable AI
  • 22. Poll #3 Do you think all AI-enabled HR applications should be explainable? A. Yes B. No C. Don’t know
  • 23. ©Harbinger Systems | www.harbinger-systems.com Other Challenges Innovation first occurring outside of the suites Of limited value to smaller/lower volume organizations Data science skills and experience within the HR department to ensure safe and effective operations
  • 24. ©Harbinger Systems | www.harbinger-systems.com Summary
  • 25. ©Harbinger Systems | www.harbinger-systems.com 25 Recap AI in HRTech • Talent acquisition continue to lead the way in using AI innovatively • Use of AI for Prescriptive and Predictive use cases is catching up in modules such as Training and Development, Compensation, Payroll etc. Challenges • Bias in results due to nature of data • Evaluating the correctness and reliability of data • Ensuring the ethical capturing and use of data • Understanding working of AI models and algorithms Key to success • Providing insights into use of data by AI • Explaining the AI results • Provide explainable interface
  • 26. ©Harbinger Systems | www.harbinger-systems.com QnA Please use Question Box
  • 27. ©Harbinger Systems | www.harbinger-systems.com Thank you 27 Contact Us Shrikant Pattathil – shrikant@harbingergroup.com Maheshkumar Kharade – maheshkumar@harbingergroup.com

Editor's Notes

  1. Agenda - What u will get
  2. Are you worried about bias?
  3. Effectiveness of AI currently implemented