PART B
Date
: Tue, Oct 18, 2016
|
Sub.
: ROBOT INTERVIEW
|
VS,
Following
news story also appeared in yesterday's Times of India
Indian TalView has both types of offerings : Live , and : Asynchronous
Video Recording ( like HireVue )
I strongly
suggest that you prepare a " Compare and Contrast " type of tabulation of the
features / functionalities , being offered by TalView with our own proposed " OnlineJobsFair.com "
Then only
will you come to know whether our plan scores over theirs - and in what
respects ; a kind of benchmarking
I do believe
our plan has quite a few plus points
Do read
their FAQ for , both
the Employers and the Jobseekers
In the
meantime , today I spent 4 hours going through my old notes and have prepared 12
files , which I will
deliver to Kartavya ,
tomorrow morning
His senior
developer may also want to take a look at TalView web
site
hcp
------------------------------------------------------------------------------------------------------------------------------------------
ROBOT
INTERVIEW
Soon,
you may be interviewed by a robot for your next job
{
Source : TechWorm / 17 Oct 2016 }
------------------------------------------------------------------------------------------------------------------------------
Jake
Rosen, a recent graduate of UCLA, was taken aback when he was interviewed by a webcam, on a laptop instead of a human being while he
was applying for a job at NBC.
He recorded
his answers and returned
them to a hiring manager at NBC for evaluation at the company’s convenience.
So,
how does this robo-interview work?
You
are given a question on the screen for which you have a limited
amount of time to answer.
You talk
to your computer, record the responses, and send
them back to the
company.
At
times, prospective employees get a practice question to get used to talking
to a camera, while at times they may not. However, most often you get
a chance
to re-record your answer
at the end.
This
kind of interview may end up being a boon for those people who are introvert,
who need not go through formal greetings or be audible enough while answering
a question.
However,
it may be a little awkward for many wherein you are compelled
to stare at your big,
nervous face as you wax on about why you want to work at the company.
Essentially
speaking it is more like performing for an invisible audience rather than having a conversation.
Rosen felt nervous from the first question, as he was not used to being on
camera. As a result, he was nervous for
the rest of his interview, he said.
“I’m
not a YouTube star, obviously,” he said. “It’s such a weird experience talking
to a camera. It honestly
was pretty horrible.” Jamie Black, who suffered through the video interview
experience for a job at a school, said it felt “more
like a game show than an
interview.”
With
the human-free video job interview is on the rise, it seems that this
experience will soon become unavoidable for many of us.
HireVue,
one of the handful of companies making video interview software, works with 600
large organizations, including JPMorgan Chase, Deloitte, Under Armour, and
most of the major U.S. airlines.
The
company is expected to do 2.5 million interviews this year, which is an
increase from 13,000 five years ago.
Almost
90% of those are “on demand” interviews, with nobody
live at the other end.
The
attraction of the video interview for a hiring manager is primarily
efficiency.
“Companies
want to get to know way more people,” said Mark Newman, the founder of HireVue.
In a day, a recruiter can only get through so many 30-minute conversations.
Further, this doesn’t include the time lost to schedule or on bad
candidates.
Human
resources staff members with a video interview have to only
evaluate the answers, which they can do as per their own
schedule and without
travelling for on-campus
recruiting.
Hilton
got down its hiring process to 4.5 days, which is almost 20
days shorter than the
average interview process by using HireVue.
This
process helps companies save money. Cigna has cut travel expenses
for recruiters from $1 million a year, in some cases, to under $100,000.
On
the other hand, the advantage of robo-recruiting for a job candidate is convenience.
Normally, a company will give an interviewee a day or two to complete the
interview, which can happen anywhere. While this may sound like another
advantage, but for Rosen it only added to his stress.
“You
start to think about things you wouldn’t normally think about in interviews.
I started thinking about my surroundings,” Rosen said. “I had to find a blank
wall to sit in front of. … Should I put a bookshelf behind me? A plant?”
Recruiters say they don’t judge candidates on their
performance, appearance, or location.
“Judging
is an interesting word,” said Heidi Soltis-Berner, the managing director for
talent at Deloitte. “I would say the on-demand interview is truly for fact
sharing.”
Other
recruiters said they do assess people on their eye contact and communication
abilities.
The
entire setup can be a bit trying even if hiring managers are instructed not
to make decisions on how well a probable new employee can perform in front of
a camera.
“You
just see yourself and a stopwatch ticking
down,” said Black, who said his answers often got cut off by the timer.
Black
said that if and when he has to do it again, he would practice in front of a mirror with a
stopwatch before the interview.
When
the interview is taking place, it may help to have someone sit behind the computer,
Rosen said, as it would be like conversing with a person
instead of a screen. Just stare at the camera so that you are not
distracted.
However,
the best advice might be to just relax.
Scott
Mitchell, a recruiter for American Wedding Group, which uses video interviews
to pre-screen the 1,900 independent contractors it works, said, “It’s OK to
come across as uncomfortable in front of the camera, because everyone is. We
all assume you’re going to be uncomfortable. We’re putting you in an
uncomfortable position.”
Human
interaction hasn’t be entirely replaced by the robo-interview.
It is often used as a replacement for first-round
screening interviews by many companies, which is later followed by more
traditional one-on-ones.
However,
this kind of interview might not be happening for interviewees who would
prefer the traditional way of interview.
With the video interviews, organizations can look at more
people and a more varied set of people, and also additionally save money.
“Candidates
will generally say, ‘I would have preferred
an in-person interview to
this,’ but that’s not the right comparison,” HireVue’s Newman said. “The
alternative is no interview at all.”
---------------------------------------------------------------------------------------------------
Also
take a look at :
|
Date
: Tue, Oct 18, 2016
|
Sub.
: RE:
OnLineJobsFair.com
|
VS,
It is important to remember that in "OnlineJobsFair " , there will
be 2 types of Resumes and 2 types of Job advts
Resumes >
Submitted online by registered jobseekers > Uploaded from back end (
current 47 lakhs )
Job Advts > Posted
online by regd Employers > Received in our database thru
daily RSS feeds
As far as job advts which are received thru RSS feeds
are concerned , a jobseeker will be able to search/locate online and "
Apply Online " . He may even receive a Job Alert for some of these ( and
apply ) , through mobile app " My
Jobs "
But , for such job advts , obviously , there cannot be any online interviews thru
OnlineJobsFair feature
Similarly :
For resumes uploaded by us thru
backend , there can be no online interviewing thru OnlineJobsFair
But , employers can still search for these / shortlist
and download ( FREE )
For such resumes , there will be no
facility for the Employers to send out any Interview Calls ( emails ) ,
directly from our site
Of course , after downloading , employer can contact
that jobseeker thru email / phone etc
hcp
|
Date
: Mon, Oct 17, 2016
|
Sub.
: OnLineJobsFair.com
|
Kartavya,
This has reference
to our telecons today re development of OnlineJobsFair.com portal for CIBR ( Hyderabad ) . As mentioned , Mr V Srinivasof CIBR has been in touch with me in this regard for past 3
months . During his last visit to my office last week , he , more or less ,
finalized the broad outline of this portal , which , I have forwarded to you
As suggested
by you , I will visit your office next week Thursday at 11:30 am , for detailed discussions on the
features / functionalities of the proposed portal
In the
meantime , by today evening , I will deliver to you , copies of
my handwritten notes covering :
#
Job Alert Recommendation System / Match Index System ( file # 258
)
#
Recruitguru.com ( Screen shots / Logic notes / Tariff plan
/ Parsing Logic / GuruSearch etc )
( file nos 257 and 288 )
# Resumine / ResuSearch ( file no 243 )
#
" My Jobs " mobile app ( file no 289 )
Tomorrow , I
will try to go through several other files and , out of those , may send you
some more
Since your
Senior Executives are busy this week , I hope they will get time to go
through these files , early next week , before my visit
Basic
configuration of the portal will be :
CORE :
This will be
, more or less , my existing portal , www.CustomizeResume.com ( minus some frills )
We will be
in a position to make available to you , full source-code / documentation /
databases etc for this . That would also include the source-codes for the
mobile apps , " My Jobs " and " Resume Blaster "
AUXILIARIES :
Here , the main
feature will be " OnlineJobsFair ", for which complete design /
logic / UI and Page Write-ups , are ready ( handwritten ) , which , I will
send to you tomorrow . Of course , these are also available on my blogging
site and you can read these by clicking on the link
Another
feature is ResumesExchange .
Mr Srinivas
has some doubt if this can work as a downloadable tool , which carries out
the parsing of the TEXT resumes offline and then upload on our server
As a result
, we felt that we just revive our old / tried and tested , RecruitGuru.com , online ( as part of the proposed
portal , where registered Employers can upload their TEXT resumes and get
these parsed to create a Structured / Searchable Resume Database ( just like
old times )
We will
store such resume databases , " Employer wise " , should they want to search
only within their own database
But,
Simultaneously
, we will also MERGE these
( donated ) resumes into our COMMON / PUBLIC database as well , which can be
searched by ALL registered Employers
" My Jobs " :
For a couple
of years , this is defunct ( although , we will be giving you the source-code
) , because , it was partly " serviced " by HP , from their USA
based server , which they discontinued and we never got around to revive it
from our own server
We would
very much like to revive this and get some Ad Network ( such as InMobi ) to display advts on it ( as they
were doing , when it was working )
" Resume Blaster :
This mobile
app was developed by Shuklendu and we can give you the code
But , at
least , for the moment , we have no intention of reviving it
" Resume Rater "
:
This offline
tool is supposed to work in conjunction with www.IndiaRecruiter.net
Unfortunately
, since we had de-hosted IndiaRecruiter for several years now , this tool has
stopped working
But ,
we need its
functionality to be built into the proposed portal ( which , I presume should
happen when we revive ( really , redevelop from scratch ) , RecruitGuru
parsing engine ( giving RAW score / percentile score to each resume )
Finally , it
would help , if your concerned developers take a quick look at www.CustomizeResume.com , and let me know , what " Documentation " they would like Shuklendu to
give along with the source-code ( due in 8/10 days )
Of course ,
I am sure , even a little later ( before Shuklendu's team forget everything
), he would be happy to answer any questions that you might have
regards,
hcp
---------------------------------------------------------------------------------------------------------------
VS :
If you
finalize the functional specifications by first week of November and place a confirmed
order on ATIDAN , byend Nov , then , there is a possibility
that you may be able to launch by 1st May
I have ,
thought of one more method of charging the Employers indirectly ( value added
service ), about which , I will write to you tomorrow
|
Date
: Sun, Oct 16, 2016
|
Sub.
: RE: Phase I
|
Dear Sir,
In reference to our telephonic discussion, please find
the takeaways listed below:-
1.
Resume download/upload
will be completely free. This applies to enterprises - giants, very big, big,
medium, small and micro.
2.
Our revenue model will
be primarily based on Online Job Fair and value added services. We have to
create auxiliary services like sending emails, recording employee response
etc.( we can finalize the list when we brainstorm) which will be charged. For
employees it will based on ad based revenue through InMobi.
3.
No charge to job
seekers or applicants. The whole idea is to democratize the job process.
4. You will discuss
this with Kartavya and ask him to come up with a functional specification.
Regards,
VS
|
Date
: Sun, Oct 16, 2016
|
Sub.
: RE: A BLUE OCEAN STRATEGY
|
Dear Sir,
There are 2 questions that I have in mind.
Q1: When we debut with “Jobsite and OnlineJobsFair” we
will challenge the market. How much time do you think will Big Daddies Naukri
and Monster will have to strike back?
Q2: What should we do that they are not able to strike
back by replicating our model. We will have to factor the deep pockets they
have and create similar “OnlineJobFair” model like ours.
Vidyanext recommendation service is also apt for
Healthcare. I find this suggestion extremely tailor made for Healthcare too!
Will discuss with Dr. Kiran today itself of implementing this in our phase 2.
Regards,
VS
|
Date
: Sun, Oct 16, 2016
|
Sub.
: RE: Phase I
|
Dear Sir,
Good Morning!
I agree with all your points except point 4 which I have
pasted below. Resume barter and “cost of per resume” has to be part of
strategy from day 1. There are few reasons for this:-
a) Resume barter will
help build our database which is critical for growing the database mass. I am
sure employers will love this model because, they will be able to put their
burgeoning resume database to good use. For employees they can earn credit
points to avail some complimentary services from the jobsite.
b) You have a revenue model
from day 1, which is crucial to the growth of business in long term.
c) Employers can pay
for this through credits instead of actual money and this will be a USP
4. We are aiming to
disrupt the current model wherein subscription fee is the barrier. This
to be replaced with pay as you go service for employers wherein the cost of
resume shall come down by 90% - 95%. This model can be further developed
wherein, if an employer uploads one resume which is not currently available
in the database then he/she can download one resume for free. This makes
bartering more effective. ( We will think about this in Phase
2 )
Rest all are other points are fine, if need be let’s
have a quick call to discuss this and then you can meet Kartavya to take this
ahead.
Regards,
VS
|
Date
: Sat, Oct 15, 2016
|
Sub.
: Phase I
|
Dear Sir,
Good Morning!
It was a pleasure meeting you on Thursday at your
office. I always feel refreshed whenever I meet you!
As per our discussions the following are the features in
Phase I –
1. Job Site + Online
Job Fair
2. Resume Rater to
sort best resumes as per job description. This will also be used for rating
applicants for interview purposes in Online Job Interviews.
3. Resume Sync or
Resume Barter to be enabled to encourage cooperative type of movement where
resumes are exchanged freely.
4. We are aiming to
disrupt the current model wherein subscription fee is the barrier. This
to be replaced with pay as you go service for employers wherein the cost of
resume shall come down by 90% - 95%. This model can be further developed
wherein, if an employer uploads one resume which is not currently available
in the database then he/she can download one resume for free. This makes
bartering more effective.
5. Online Job
interviews to be charged at highly subsidized cost for employers.
6. There will be no
cost involved during any time in the process for employees or applicants. We
will introduce InMobi for ad based revenue for employees. This will work
based on a Youtube or a Social Media model.
7. Payment Gateways
to be inbuilt.
8. Other
features will be introduced in further phases.
Please let me know if I have covered everything as per
our discussion. My apology I couldn’t send the email yesterday itself.
Regards,
VS
|
Date
: Sat, Oct 15, 2016
|
Sub.
: TIME TO CHANGE GEARS
|
VS,
Here is one
more proof that on internet , it is not the BIG who overtake the SMALL , it is the FAST who overtake the SLOW !
hcp
------------------------------------------------------------------------------------------------------------------------------------
Source :
Economic Times / 15 Oct 2016
NEW DELHI:
Mumbai-based mykindofjob.com, an online portal
that says it’s signed up 100,000 registered
users in less than a year, recently closed a
round of funding worth $1million from brothers Mayank Shah and Shreyans Shah, making it the
second flexi-jobs site to have raised money in the past 12 months.
The Shahs are said to have turned to angel investing after reaping handsome returns from the sale of their pharmaceutical business, Biochem Pharma, to Zydus Cadila in 2011.
The flexible employment market is attracting investors as more people opt to set their own
timings and work from outside
the office.
Mykindofjob.com, which says it has 800 companies on board, offers interactive web platform where registered users cancommunicate with each other and prospective employers. Users range from students looking at internships to retired professionals seeking short-duration projects.
“Funds will be used
to increase our team size and invest in
technology as well as ramp up our geographical
presence,” said Ankit Bansal, founder of mykindofjob.com. The Shahs couldn’t be reached for
comment.
Bansal, who previously managed wealth of HNI clients at Standard
Chartered Bank, started the portal last year. “Investor interest in the
online flexi-work space has increased due to the scalability of the model and
the fact that more companies are willing to parcel out work as opposed to
executing all of it with full-time staff,” said Padmaja Ruparel, president of
Indian Angel Network.
|
Date
: Fri, Oct 14, 2016
|
Sub.
: FW: A Brave New World
|
VS,
I forward
below , my mail concerning " Pa-Rank "
that I mentioned during our discussions yesterday
You may also
want to look up :
After I get
your email re Phase 1 , I will meet Kartavya personally and explain all the
features envisaged , in detail , to enable him to give you , a rough estimate
of time and cost for development.
regards,
hcp
|
Date
: Fri, Oct 14, 2016
|
Sub.
: PHASE 2 FEATURE
|
VS,
This could interest you , in light of our own plans to " predict
job market in India
" , based on those 2 million job advts posted on job portals
over the past 7 years by some 50,000 + companies ( which , I believe , removes
any biases in the dataset , considering its vast spread )
hcp
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Source : DNA / 13 Oct 2016
A recent Harvard Business Review (HBR) interview on misuse of
algorithms got me thinking about whether the algorithms we use can reinforce
our biases. However, before I explain why I feel that way, I would explain
how machine learning algorithms work to classify data points into multiple
classes. In order to do so, I will step back to explaining what
classification means.
Classification is the task of classifying a bunch of objects
into separate groups. Say, an organization wants to build a prediction engine
that would be able to separate out the excellent performers from the average
and the unacceptable.
This then, is a classification task since the algorithm is
required to go through the list of employees and put them in one of three
buckets, viz., excellent, average and unacceptable. Now, data scientists
would use a machine learning approach. Simply put, machine learning
algorithms look for patterns within datasets and learn these patterns
corresponding to each of the buckets into which they need to classify items.
Hence, using our example, the algorithm would learn the patterns
for excellent, average and unacceptable performers.
These algorithms then require a lot of historical data.
Essentially, we need to 'show' these algorithmic examples of excellent,
average and unacceptable performers. This process is known as 'training' the
algorithm.
This in effect is similar to how we teach kids the alphabet
where we show them the letters again and again and correct them when they get
it wrong so that ultimately they are able to recognize the characters. This
is exactly what happens when we train our algorithm.
This allows the algorithm to then identify 'signatures' for each
of these buckets. When it is then presented with a different data point, it
compares the new data against the learnt patterns and if there is a lot of
similarity between the two, it assigns the new data point to the
corresponding bucket.
So what can go wrong, you ask ?
To train the algorithm, we need to provide it with a lot of
examples to learn from.
Let us assume that we are looking at ABC Inc, a traditional and
a conservative business based out of Bangalore. Most of the people employed
in ABC have come from the southern part of the country.
Moreover, given the conservative attitudes of their managers,
women are under-represented in this organization in general and at higher
levels in particular.
ABC now wants to build a model on the best people to hire for their organization and for this, they have made available their historical employee database.
This is where the problem is. All their biases are part of their historical
dataset. Hence, any models that will be trained on this dataset will
also inherit these biases.
As an extreme case, if we now have a woman
applicant from Delhi, she might well get filtered
out by the algorithm since
she doesn't fit the typical profile that the model has been trained on.
While this is a gross simplification of the issue, it does
illustrate the pitfalls associated with building models based on historic
data without taking into account biases inherent in the data.
Given that most organizations will have some biases, be they
about gender, age or educational institutions, how
can they build predictive models if these biases are implicitly
included in models built on this dataset?
There are no easy answers here. One way is to utilize publicly
available datasets or
pool with other organizations in the space to obtain
datasets that normalize the biases. However, whatever be the approach,
any data scientist worth her salt ought to be aware and look for these
built-in biases before undertaking any model building.
( Author : Arun Krishnan / Founder &
CEO - nFactorial Analytical Sciences )
------------------------------------------------------------------------------------------------------------------------
hemen parekh
Marol , Mumbai , India
( M ) +91 - 98,67,55,08,08
|
Date
: Sun, Oct 16, 2016
|
Sub.
: RE: A BLUE OCEAN STRATEGY
|
Dear Sir,
There are 2 questions that I have in mind.
Q1: When we debut with “Jobsite and OnlineJobsFair” we
will challenge the market. How much time do you think will Big Daddies Naukri
and Monster will have to strike back?
Q2: What should we do that they are not able to strike
back by replicating our model. We will have to factor the deep pockets they
have and create similar “OnlineJobFair” model like ours.
Vidyanext recommendation service is also apt for
Healthcare. I find this suggestion extremely tailor made for Healthcare too!
Will discuss with Dr. Kiran today itself of implementing this in our phase 2.
Regards,
VS
|
Date
: Sun, Oct 16, 2016
|
Sub.
: RE: Phase I
|
Dear Sir,
Good Morning!
I agree with all your points except point 4 which I have
pasted below. Resume barter and “cost of per resume” has to be part of
strategy from day 1. There are few reasons for this:-
a) Resume barter will
help build our database which is critical for growing the database mass. I am
sure employers will love this model because, they will be able to put their
burgeoning resume database to good use. For employees they can earn credit
points to avail some complimentary services from the jobsite.
b) You have a revenue model
from day 1, which is crucial to the growth of business in long term.
c) Employers can pay
for this through credits instead of actual money and this will be a USP
4. We are aiming to
disrupt the current model wherein subscription fee is the barrier. This
to be replaced with pay as you go service for employers wherein the cost of
resume shall come down by 90% - 95%. This model can be further developed
wherein, if an employer uploads one resume which is not currently available
in the database then he/she can download one resume for free. This makes
bartering more effective. ( We will think about this in Phase
2 )
Rest all are other points are fine, if need be let’s
have a quick call to discuss this and then you can meet Kartavya to take this
ahead.
Regards,
VS
|
Date
: Sat, Oct 15, 2016
|
Sub.
: Phase I
|
Dear Sir,
Good Morning!
It was a pleasure meeting you on Thursday at your
office. I always feel refreshed whenever I meet you!
As per our discussions the following are the features in
Phase I –
1. Job Site + Online
Job Fair
2. Resume Rater to
sort best resumes as per job description. This will also be used for rating
applicants for interview purposes in Online Job Interviews.
3. Resume Sync or
Resume Barter to be enabled to encourage cooperative type of movement where
resumes are exchanged freely.
4. We are aiming to
disrupt the current model wherein subscription fee is the barrier. This
to be replaced with pay as you go service for employers wherein the cost of
resume shall come down by 90% - 95%. This model can be further developed
wherein, if an employer uploads one resume which is not currently available
in the database then he/she can download one resume for free. This makes
bartering more effective.
5. Online Job
interviews to be charged at highly subsidized cost for employers.
6. There will be no
cost involved during any time in the process for employees or applicants. We
will introduce InMobi for ad based revenue for employees. This will work
based on a Youtube or a Social Media model.
7. Payment Gateways
to be inbuilt.
8. Other
features will be introduced in further phases.
Please let me know if I have covered everything as per
our discussion. My apology I couldn’t send the email yesterday itself.
Regards,
VS
|
Date
: Sat, Oct 15, 2016
|
Sub.
: TIME TO CHANGE GEARS
|
VS,
Here is one
more proof that on internet , it is not the BIG who overtake the SMALL , it is the FAST who overtake the SLOW !
hcp
------------------------------------------------------------------------------------------------------------------------------------
Source :
Economic Times / 15 Oct 2016
NEW DELHI:
Mumbai-based mykindofjob.com, an online portal
that says it’s signed up 100,000 registered
users in less than a year, recently closed a
round of funding worth $1million from brothers Mayank Shah and Shreyans Shah, making it the
second flexi-jobs site to have raised money in the past 12 months.
The Shahs are said to have turned to angel investing after reaping handsome returns from the sale of their pharmaceutical business, Biochem Pharma, to Zydus Cadila in 2011.
The flexible employment market is attracting investors as more people opt to set their own
timings and work from outside
the office.
Mykindofjob.com, which says it has 800 companies on board, offers interactive web platform where registered users cancommunicate with each other and prospective employers. Users range from students looking at internships to retired professionals seeking short-duration projects.
“Funds will be used
to increase our team size and invest in
technology as well as ramp up our geographical
presence,” said Ankit Bansal, founder of mykindofjob.com. The Shahs couldn’t be reached for
comment.
Bansal, who previously managed wealth of HNI clients at Standard
Chartered Bank, started the portal last year. “Investor interest in the
online flexi-work space has increased due to the scalability of the model and
the fact that more companies are willing to parcel out work as opposed to
executing all of it with full-time staff,” said Padmaja Ruparel, president of
Indian Angel Network.
|
Date
: Fri, Oct 14, 2016
|
Sub.
: FW: A Brave New World
|
VS,
I forward
below , my mail concerning " Pa-Rank "
that I mentioned during our discussions yesterday
You may also
want to look up :
After I get
your email re Phase 1 , I will meet Kartavya personally and explain all the
features envisaged , in detail , to enable him to give you , a rough estimate
of time and cost for development.
regards,
hcp
|
Date
: Fri, Oct 14, 2016
|
Sub.
: PHASE 2 FEATURE
|
VS,
This could interest you , in light of our own plans to " predict
job market in India
" , based on those 2 million job advts posted on job portals
over the past 7 years by some 50,000 + companies ( which , I believe , removes
any biases in the dataset , considering its vast spread )
hcp
------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Source : DNA / 13 Oct 2016
A recent Harvard Business Review (HBR) interview on misuse of
algorithms got me thinking about whether the algorithms we use can reinforce
our biases. However, before I explain why I feel that way, I would explain
how machine learning algorithms work to classify data points into multiple
classes. In order to do so, I will step back to explaining what
classification means.
Classification is the task of classifying a bunch of objects
into separate groups. Say, an organization wants to build a prediction engine
that would be able to separate out the excellent performers from the average
and the unacceptable.
This then, is a classification task since the algorithm is
required to go through the list of employees and put them in one of three
buckets, viz., excellent, average and unacceptable. Now, data scientists
would use a machine learning approach. Simply put, machine learning
algorithms look for patterns within datasets and learn these patterns
corresponding to each of the buckets into which they need to classify items.
Hence, using our example, the algorithm would learn the patterns
for excellent, average and unacceptable performers.
These algorithms then require a lot of historical data.
Essentially, we need to 'show' these algorithmic examples of excellent,
average and unacceptable performers. This process is known as 'training' the
algorithm.
This in effect is similar to how we teach kids the alphabet
where we show them the letters again and again and correct them when they get
it wrong so that ultimately they are able to recognize the characters. This
is exactly what happens when we train our algorithm.
This allows the algorithm to then identify 'signatures' for each
of these buckets. When it is then presented with a different data point, it
compares the new data against the learnt patterns and if there is a lot of
similarity between the two, it assigns the new data point to the
corresponding bucket.
So what can go wrong, you ask ?
To train the algorithm, we need to provide it with a lot of
examples to learn from.
Let us assume that we are looking at ABC Inc, a traditional and
a conservative business based out of Bangalore. Most of the people employed
in ABC have come from the southern part of the country.
Moreover, given the conservative attitudes of their managers,
women are under-represented in this organization in general and at higher
levels in particular.
ABC now wants to build a model on the best people to hire for their organization and for this, they have made available
their historical employee database.
This is where the problem is. All their biases are part of their historical
dataset. Hence, any models that will be trained on this dataset will
also inherit these biases.
As an extreme case, if we now have a woman
applicant from Delhi, she might well get filtered
out by the algorithm since
she doesn't fit the typical profile that the model has been trained on.
While this is a gross simplification of the issue, it does
illustrate the pitfalls associated with building models based on historic
data without taking into account biases inherent in the data.
Given that most organizations will have some biases, be they
about gender, age or educational institutions, how
can they build predictive models if these biases are implicitly
included in models built on this dataset?
There are no easy answers here. One way is to utilize publicly
available datasets or
pool with other organizations in the space to obtain
datasets that normalize the biases. However, whatever be the approach,
any data scientist worth her salt ought to be aware and look for these
built-in biases before undertaking any model building.
( Author : Arun Krishnan / Founder &
CEO - nFactorial Analytical Sciences )
------------------------------------------------------------------------------------------------------------------------
hemen parekh
Marol , Mumbai , India
( M ) +91 - 98,67,55,08,08
|
Date
: Thu, Sep 29, 2016
|
Sub.
: RE: IN A FAST MOVING
WORLD
|
VS,
B2CmessageBlaster / TV Job Channel / End to end , Recruitment Process Management System etc , are
among a host of " Add-ons "
that are , not only possible but also have the potential to re-write the
rules of the Online Recruitment Industry
At this stage , what is important ( and URGENT ) for you is to freeze the " Functional Specifications " for
what the Internet Marketing pundits call a , MVP ( Minimum Viable Product )
It is only with such written clarity that companies
like ATIDAN ( Kartavya Chitalia ) can give you an estimate of
the time and cost for development . Call it PHASE 1
One should think about Phase 2 , only after Phase 1 is
running smoothly and your Marketing Team manages to get a few thousand
Employers and a few lakh Jobseekers to register
Without spelling out TIME and COST , you just cannot get any funding
!
I have spoken to Kartavya today and he would be happy to
join us for giving his own technical inputs to enable you to draw up a plan
I await your intimation re your proposed visit to Mumbai
regards
hcp
|
Date
: Thu, Sep 29, 2016
|
Sub.
: RE: IN A FAST MOVING
WORLD
|
Morning HCP Sir,
The TV channel looks like a novel idea. It can be also
be a standalone TV channel like a Naaptol or any of the merchandise selling
items. This can also be one of
mediums for ResumeSYNC, wherein
job seekers can register for a job through TV (of course we need to
build the concept around it).
Yes Sir, the putting resumes on cloud will be a better
and smarter idea, meantime ResumeSYNC will
keep transferring resumes from users systems to the cloud. Do you also think
there could be other privacy issues around users installing ResumesSYNC on their systems.
Regards,
VS
|
Date
: Thu, Sep 29, 2016
|
Sub.
: IN A FAST MOVING WORLD
|
---------------------------------------------------------------------------------------------------------------------------------
VS,
You may want
to check these out
Today's news
paper also talks about Facebook re-negotiating
with Indian Government re FreeBasic
With arrival
of Reliance JIO and
the Central Government laying Optical Fibre Cables to connect up 225,000 Gram Panchayats , the digital
access scenario in India will witness a sea-change in next 12 months
I have also
prepared a CONCEPT NOTE / LOGIC , for delivering " Job Alerts " to candidates on their home TVs and then " Apply Online "
, when they come across a suitable alert on TV !. This was 5/7 years back
One TV
Channel had shown interest initially but later backed out !
I had even
booked URLs ( www.JobsChannelTV.com / www.JobsTVchannel.com )
It may be
easier NOW to implement this due to improved technologies ( internet
connected Smart TV ) and
greater competition amongst TV channels
Incidentally
, in ResumesExchange ( ResumeBarter or, still better , ResumeSYNC ), there may not be any need for the
Central Server to " deliver "
millions of Resumes onto the hard-disks of thousands of Users ( who have
installed ResumeSYNC on
their servers ), every morning when they login
I suppose
ALL resumes can remain in the CLOUD and
each User can simply " access / search / shortlist / send out
Interview-Calls " , by login !
No need for
us to build-in " GuruSearch "
( Resume Search Engine ) into the ResumeSYNC tool
!
This opens
up the possibility for extending this Online Service into a total ,
end-to-end , Recruitment Process
Regards,
hemen parekh
Marol , Mumbai , India
( M ) +91 - 98,67,55,08,08
|
Date
: Tue, Sep 27, 2016
|
Sub.
: RE: STATUS
|
VS,
What you
have described , should be our general guideline
Specifically
,
#
Jobseekers
Nearly all
job portals offer their services to jobseekers , FREE
For them ,
the main services are Resume Posting ( Registration ) / Job
Search and Apply Online
Some job
portals charge a lump sum for :
* Resume
Blasting
* Re-writing
Resumes ( lot of manual
work ! Resume writing service )
As far as
you are concerned , suggest keep away from " Resume Re-writing
"
But , you
may consider charging jobseekers for sending their " Personal
Graphical Analytics "
( function graph / tenure graph / salary graph etc which CustomizeResume
generates automatically )
Again , do
not get into any charge for " Resume Blasting " ( no online Resume Blasting )
But , make
money from InMobi delivering Ads on
" My Jobs cum Resume Blaster " combined mobile app
We should NOT have " Apply
against Job Alerts "
page online ( as in CustomizeResume )
Jobseekers
can " pull " job alerts " only thru My Jobs ( first 5 free ) / Rest
on touching an Ad
Of course ,
we must also NOT charge jobseekers for participating in Online Interviewing
thru OnLineJobsFair feature
You want to
attract not only millions of jobseekers ( 3.5 million fresh graduates
coming out of colleges each year ) but also millions of MSME ! Then only you
can have thousands of interviews daily and be in a position to capture those
Interview Conversations to be able to develop QuestionBot !
#
Employers
Most job
portals make their money by charging a monthly / quarterly / annual "
Subscription " from Employers ( Rs 3-6 lakhs per year ) Naukri gets 99 % of its revenue from such subscriptions !
Same with
TimesJobs / MonsterIndia
This enables
Employers to Post Jobs / Search
and Download Resumes
In our case
, we should allow FREE job posting but NO resume search !
If Employers
want Resumes then they have to ( after registering ) , download and install
on their server , tool " ResumeBarter " !
Of course ,
as and when , you introduce " QuestionBot " , you can charge them for its
use , during conducting online interviews thru OnLineJobsFair ( which they can use FREE for basic function )
Where you
should plan to make money should be in launching ...www.B2CmessageBlaster.com ( for which , I have prepared a
concept note ) You will need to reimburse me
separately for that
Essentially
the jobseeker data ( parsed and structured resumes ) of MILLIONS of
jobseekers that you manage to CAPTURE in your FIRST property , will be used
for enabling thousands of Consumer Goods and Consumer Durable Goods Companies
( including Foreign Companies ) , to blast their " Product / Services "
advts to sharply targeted " Demographic Profiles " of Indian
Consumers !
I have
called this " Ad-Sharp " , which would be a hundred
times more POWERFUL / RESULT GIVING , as compared to Google's Adwords
/ Adsense or Inmobi's ad network !
There is no time to waste , making lots of Business Plan projections
!
You must be able
to SELL your DREAM to any VC , while riding an elevator to 10th floor !
hcp
|
No comments:
Post a Comment