Trustworthy AI: From Dating to Hiring
Key Points
- The speaker outlines four trust pillars for personal advice—unbiased recommendations, privacy of shared data, adaptability to evolving preferences, and transparent reasoning behind selections.
- These same pillars define “trustworthy AI,” which is essential when businesses rely on AI advisors for critical decisions like hiring.
- New regulations (e.g., New York’s upcoming law) will require firms to demonstrate their AI models’ trustworthiness after a year of production, prompting a need for formal governance and accountability.
- Implementing trustworthy AI involves a structured process: defining business goals and target outcomes, assembling cross‑functional teams (HR, compliance, privacy), establishing governance structures, and rigorously developing and validating the model.
Full Transcript
# Trustworthy AI: From Dating to Hiring **Source:** [https://www.youtube.com/watch?v=V7kWAZ-dV0w](https://www.youtube.com/watch?v=V7kWAZ-dV0w) **Duration:** 00:05:28 ## Summary - The speaker outlines four trust pillars for personal advice—unbiased recommendations, privacy of shared data, adaptability to evolving preferences, and transparent reasoning behind selections. - These same pillars define “trustworthy AI,” which is essential when businesses rely on AI advisors for critical decisions like hiring. - New regulations (e.g., New York’s upcoming law) will require firms to demonstrate their AI models’ trustworthiness after a year of production, prompting a need for formal governance and accountability. - Implementing trustworthy AI involves a structured process: defining business goals and target outcomes, assembling cross‑functional teams (HR, compliance, privacy), establishing governance structures, and rigorously developing and validating the model. ## Sections - [00:00:00](https://www.youtube.com/watch?v=V7kWAZ-dV0w&t=0s) **Seeking Trustworthy Dating Advice** - The speaker outlines criteria—unbiased, transparent, private, adaptable, and explainable—to ensure any advisor, including AI, provides trustworthy guidance in finding a boyfriend. ## Full Transcript
i'm looking for a boyfriend
and
i've been asking around i've been
soliciting some advice but how do i make
sure that that advice is trustworthy
especially when it comes to something
this monumental
so i've been thinking and there are a
few things that i would like out of this
advice in order to trust any advisor in
making this decision
so first i want to make sure that
they're unbiased right i want to make
sure that they're open to everything
i certainly am not ruling anything out i
want this to be a fair process
i also know that in order to get the
optimized outcome i'm probably going to
have to share a good amount so it's
going to be a give and take a
transparent process
but if i do share that data i want to
make sure that it's not being used for
additional purposes that they're not
telling other people that they shouldn't
i want to make sure that my
preferences are private
next i want to make sure that they're
robust so
my dating history maybe not that
indicative of my current preferences
i want this advice and this advisor to
be able to adapt with me to take in
these new parameters uh as we learn and
grow together
the last piece says when we finally do
get to a point where some lucky fellow
is selected i want to understand what
was their thought process behind it why
do they think that we'll be a good fit
these are the different pillars of trust
that would be important for me for
making this decision but they are also
crucial to any business
having any ai advisors help them make
decisions and this is how we define
trustworthy ai
but now that we have these models
or these different traits we don't stop
there right we actually have to create
the model we actually have to create the
selection process
so we're going to switch to something
that's a little bit more contextualized
in business terms and this is hiring
practices right now so many fortune 5
fortune 10 companies at this point do
use hr
ai models to help them with their hiring
practice for selecting top talent but
this has proved to be tricky to say at
the least
and there's legislation that's coming
out at a federal level in new york it's
rolling out of the first of the year
that says that you have to prove that
your model is
trustworthy
by january 1 and it has to have been in
production for over a year and prove
this how do we do that we start with
the model proposal
so at this point we need to make sure
that we are selecting the right business
outcomes we want to know who we're
selecting for why we're selecting for
what different data sources we also want
to make sure that this is a team sport
hr department's involved compliance
maybe privacy if you're worried about
that but this is the part where you set
up the governance structure inside your
model organization so that there is
accountability throughout
this is a crucial step
the next is we want to make sure
that we're doing
the model development correctly so this
is when we're pulling in our
developers our engineers they're
creating the model as we have defined it
previously
after that we're going to do a
pre-implementation review
and during this piece we're going to
make sure that our model here doesn't
include anything around bias right we
want to make sure that we are selective
of all groups getting back to this
fairness piece we also want to make sure
that it's a transparent process we're
not sharing any data it's private and
it's going to be adaptable and
explainable so once we feel like we get
this piece done
that's when we're going to come in here
and we're going to involve
the model approval
and the model approval piece is going to
bring in an overall governing structure
again so remember right we're setting it
here but then we're actually having
people come in we've created our model
we've proven that you know it's got all
of these different components of
trustworthiness and then we're saying
we're good to go we're going to put this
in production
typically we're seeing that
organizations at this point are
involving you know a board an ethics
board this is something that's being
outsourced into more and more divisions
within your organization at higher
levels because this is not a technical
discussion this is the technical piece
but in terms of implementing the model
and creating trustworthiness that's a
line of business opportunity here so
once this gets the approval then we go
and we put it into production but
at certain intervals we're doing the
compliance and validation testing so
we're not done there at certain
intervals that we've set here right
we're going back and we're saying okay
is this fair is this is there any bias
has there been any drift is this still
achieving what we need it to so in this
way you can see that this is going to be
an iterative process where we're going
back and forth to ensure that your model
will always be trustworthy
thank you
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