Industry internship at Mettl to learn deployment of AI to improve effectiveness of mass hiring across Sectors

1. INTERNSHIP
AT METTL
BY: HARSHDA GHAI

2. TEXT
PURPOSE
▸Understand how AI/Technology based skills assessment is
helping companies to reduce Attrition and hire relevant
talent.
▸To understand the thought process that goes on while
programming such a platform
▸Look at the hurdles and develop a plan to overcome them

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TOPICS COVERED
▸Skills Assessment framework
▸What is NLP?
▸Practical uses of NLP
▸What is the project at hand
▸How does our project involve the use of NLP
▸Impact of using NLP

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SKILLS ASSESSMENT FRAMEWORK
▸Mettl is an online skills assessment platform which helps
companies with the hiring process
▸The various customisable aptitude tests help companies
recruit employees with a specific skill set
▸The IQ and EQ tests help form stronger and more efficient
teams
▸Such platforms help save time, money, and resources.

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NLP
Natural language processing (NLP) describes the
interaction between human language and computers. It’s
a technology that many people use daily and has been
around for years, but is often taken for granted.
In any case, the computer is able to identify the appropriate
word, phrase, or response by using context clues, the same
way that any human would.

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USES OF NLP
The 3 most common applications of NLP are -
1. Enterprise research. This involves allowing users to query data sets in the form of
a question that they might pose to another person. The machine interprets the
important elements of the human language sentence, such as those that might
correspond to specific features in a data set, and returns an answer.
2.NLP can be used to interpret free text and make it analysable. There is a
tremendous amount of information stored in free text files, like patients' medical
records, for example. Prior to deep learning-based NLP models, this information
was inaccessible to computer-assisted analysis and could not be analyzed in any
kind of systematic way. But NLP allows analysts to sift through massive troves of
free text to find relevant information in the files.
3.Sentiment analysis- Using sentiment analysis, data scientists can assess
comments on social media to see how their business's brand is performing, for
example, or review notes from customer service teams to identify areas where
people want the business to perform better.

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NLP EXAMPLES AROUND US
▸Amazon Alexa
▸Siri
▸Tesla
▸Google Assistant
▸Spell check
▸Autocomplete
▸Voice text messaging
▸Spam filters

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PROJECT
▸The AI department of Mettl has undertaken a new project to program an NLP-based
software to be used in the hiring and recruitment sector.
▸ Software would involve an automatic chatbot that helps in the efficient communication
between the hirers and the applicants.
▸Apart from this, several tests are being designed to test the applicants on their IQ and
EQ.
▸The information obtained would be used for the better formation of efficient teams

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ADVANTAGES
1. Saves time: It saves time by using AI tools in doing repetitive task. Recruiters
have to spend enough time to screen the resumes of the candidates. That too
screening is a repetitive job. AI helps in saving the time of the recruiters.
2. Talent mapping: AI helps in understanding the competency of the candidates . It
also conveys the applicants requirements to the recruiter . This helps the recruiters
to plan their career and place them on a right job.
3. Saves cost: As AI helps in the qualitative hiring, the role of the third party in
recruitment is reduced.This helps in saving the costs.
4. Reducing turnover: The employees get the updated information and they get the
answers for their queries. This satisfies the employees. It helps in reducing turnover
as an engaged employee continues to provide his services to the organisation.

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ADVANTAGES
5. Productive workForce: The AI results in qualitative hiring. It also helps in training and
development of employees. This leads to the improved efficiency and productive work
force.
6. No bias in recruitment: as the machine and not the humans are involved in the hiring,
there is any recruitment.
7. Quality candidates:AI provides not just the quantity but also the quality of candidates.
The AI helps in understanding the attributes and competency, skills and knowledge of
the candidates. The talented candidates are hired.
8. Standardised testing: AI replaces the biggest obstacle in recruitment. it provides a
standard scale for all the applicants to be judged upon .

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PROBLEMS FACED
1. Lot of data is required: Lots of data is needed to understand the psychology of people which is
very complicated and complex.
2. Lack of human touch: AI being a tool lacks empathy and HR without empathy. This tool without
empathy cannot fix the people in the organisation which a HR professional can with his human
touch.
3.Errors in testing: AI guarantees an 80% success and accuracy rate with the results. However
sometimes due to errors in the program, the aptness of the results may be compromised with .
4.Programming the chatbot: to respond to every applicant.This is because the chatbot can’t
remember the context of the conversation.
5.Hesitancy:several applicants were hesitant when told that they would be interacting with a
chatbot

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LEARNING AND CONCLUSION
▸Exposure to AI relevance and real world use cases
▸Impact of AI to improve the effectiveness in mass hiring field
▸Companies have observed a significant reduction in the
attrition rate of employees.
▸Formation of better-equipped teams to tackle specific tasks.
▸Identification of Industry use cases – Remote interviews,
Profile screening and shortlisting, Cycle time reduction for
mass hiring

13. THANK YOU!