Google has already started using algorithms to hire and fire employees. New startups are developing hiring algorithms that aim to eliminate bias by screening candidates based on skills rather than attributes like relationships or demographics. While algorithms may match candidates to jobs faster and cheaper than humans, they still struggle to evaluate human qualities like passion and personality that are important in hiring. Relying solely on algorithms for hiring has drawbacks, and human judgment remains valuable to complement their assessments.

1. Hired by Algorithms
Already started
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2. Speculations
There are speculations that in the near
future we would get hired by the
algorithms, but Google has already
started doing that.
You will be hired (or fired) by an
algorithm in a learning machine
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3. Smart machine is hiring You
The latest algorithm is proclaimed having hiring
capability better than a human judgement, and the
abstract qualities that only a human can look out for
seem preposterous.
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4. THE MACHINE IS LEARNING
ABOUT YOU AND WHETHER YOU ARE THE RIGHT ONE
Machine Learning teaches a program to learn from the
experience and improve their experience. This learning is
based on learning the complex patterns and using them to
take intelligent decisions. This is achieved by developing
intricate algorithms based on computational and statistical
concepts. Other concepts used are logic, probability, stats,
control theory, pattern recognition, data mining, robotics and
more.
Machine learning will help to build smart and data-driven apps
that will have the ability to analyze the real-time activities,
learning from past and predicting the future.
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5. Be ready to get hired On-Line
New Start-up companies
around the globe, especially in
the US are working on various
ways to automate hiring. The
idea behind building the
software is that it could
eliminate possible biasness like
an applicant who is a
school/college junior or knows
the best friend of the
interviewer.
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6. Social on the net – You’re hired
Utilization of data science,
consumer-friendly
technologies, and predictive
analytics. The “hiring”
algorithm uses employers’ own
data from places social
network pages of various types
to find people whose skills
match the requirement of the
companies.
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7. Another way to crack the interview to get the job.
Developers have also designed an algorithm that uses machine
learning and language analysis to search job postings various
companies.
The algorithm focuses on data to screen the candidates from a
variety of places and match their skills to the job.
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8. There are both supporters and detractors of the
new hiring approach of certain algorithms
Method of uncover phrases that indicate a bias of
some sort (language, gender, interests etc.).
Language like “top-tier” and “aggressive” and sports
or military analogies like “mission critical” decrease
the proportion of women who apply for a job.
Language like “partnerships” and “passion for
learning” attract more women.
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9. Auto Recruiter
Some headhunters are already
using such kind of algorithms into
their work. There could be a trend
if we see this works perfectly
as hiring process could become
faster and less expensive.
Data could lead recruiters to more
highly skilled people who are better
matches for their client companies.
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10. Auto Recruiter vs. Manual or?
Some do not just want skill and
technical knowledge.
They look for humane personality
traits as passion and appetite for
success.
Learning machines do not handle
these elements very well yet.
No data algorithm handles variables
like passion and hustle as most of
the times they are based on
intuition, gut feeling, and/or
chemistry.
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11. Conclusion?
Data analysis is one of many ways
to hire the persons you need.
Ned to compliment with evaluation
of personality and the human
thought process.
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12. Saving Money Now or in the Future?
Or is it about long term investment and see a potential develop worth
the investment. Saving a dollar today might prove loosing value added
investment today.
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13. www.Valioso.rocks
sak@ec-ba.com
Stig-Arne Kristoffersen
Questions? Comments?
We are happy to help you!
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