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hi and welcome to the Machine ethics podcast this month I'm talking with rod
McCargow director of AI and PWC I met up with rod at PWC office in London and we
chatted about modeling unintended consequences, AI ethics audits, working
with dubious companies and intentions, what we should be teaching our children
and future careers a recipe for AI future mitigating job displacement and
other AI for good topics. If you like this podcast then check out the other
episodes at machine-ethics.net or you can contact us at hello@machine-ethics.net
you'll find us at Twitter, Instagram and YouTube, to support the
podcast go to patreon.com/machineethics extended interviews reviews and
more my thoughts on the episodes and AI topics and news of the month, thanks
again to Rob and hope you enjoy
Hi Rob thanks for joining me on the podcast
thank you having week could you introduce yourself and what you do
absolutely so I'm the director of artificial intelligence at PwC in the UK
so our team is basically and tasked with applying the technology across the
breadth of our organization on both internal projects but also working with
that clients across all industry sectors on solving some of their hardest
business problems as well using different forms of AI and a lot of the
other things I'm involved with also involve working with governments around
the world on the impacts on national strategy and policy and as part of our
assets on the advisory board of the All Party Parliamentary Group on on AI
amongst other appointments yes so it's been said that you're the nicest man in
AI how'd you feel about that depends who said it well it's just first I've heard
so on that point Robin to you kind of what is AI when you're talking about AI
what are you talking about more specifically well I think it depends on
the the audience that we're dealing with at the time and if we're working with
clients across different corporate functions across HR for example and
compliance maybe we don't necessarily get into a deep deepest of technological
descriptions but for me I think it's a high level to differentiate from
technology of old technology that falls into the AI domain of technologies that
can sense think act and through an iterative feedback loop learn and they
clearly sit as interesting bedfellows along more mature technologies such as
robotic process automation for example but we tried to focus across the breadth
of the main AI technologies but if I'm being candid the very first thing I do
in any of these things is state that I keep the job title to get me into the
room but the first thing I do is say they are doesn't really exist we have
this assembly of really interesting technologies on the pinnate from machine
learning and deep learning to natural language processing and generation and
other techniques that make up this AI family yeah so so the AI of
kind of science fiction doesn't exist necessarily but you've got this kind of
suite of things which go under that banner at the moment indeed yeah
great and we were talking briefly before but kind of how does PwC fit in with
this how they're talking about a I and and what they're doing in anyway I guess
as well well I think where right now is we've seen amazing breakthroughs of the
technology in in consumer use cases in use cases of fascinating utility but not
necessarily a huge amount of consequence on people's lives
so there's fantastic things being served up through iron maps or movie
recommendation engines and all sorts of ecommerce types of applications I think
where we're starting to see businesses in for example heavily regulated
industries healthcare financial services banking insurance et cetera criminal
justice starting to wrestle with this technology realizing that this has a
profound impact on their business they have to get moving on starting to
embrace and adopt but by doing so this opens up this whole cupboard of new
risks which I'm sure we'll get into over the course of the conversation today so
for us I think because we're already working with just about every
organization across the across the land it's some capacity are the auditing or
advising them in some capacity we're often on-site there is the trusted
advisor to help debunk some of the myths ology provide the right level of comfort
and confidence around the tech and allow them to get started and start moving a
pace with the innovation offered by AI so I see you a lot at
these sorts of conversations that you mentioned the kind of what happens when
you have these sort of technologies in those places in healthcare in the
justice system oh there's something like top-level I mean obviously this machine
at these forecasts and we took up a lot about this sort of things is there some
of the things which you're keen on like things that you are interested in
talking about in terms of those sorts of ethical issues yeah I mean I think be
more led by the you know the explosion in these events that I get the privilege
to go and speak at and and I think judging by the Q&A after them the two
areas that seem to elicit by some comms severable distance the most interest and
the most inquiry first of all I think is around the impact on the workforce
through automation through human machine interaction and through education skills
and future proofing of careers yeah I think that's one big category that
always creates huge amount of interest and then anything else that falls into
that AI ethics bucket is again of significant interest and and that's for
me is is a fascinating area and as we start seeing this started to scale in in
these use cases of significant consequence this brings a whole level of
interest across the breadth of different corporate functions to make sure that
people are fully conversant with the implications on their business yes II
think it's really important that those business leaders are appreciate the
technology and they might not have a low level understanding but if they're going
to apply it then they better well know what they're applying yeah this this is
now an absolute necessity rather than a nice-to-have this is a fundamental
prerequisite for a four up for a executive C suite member of a board for
example because this these specific use cases will more often not rear their
head in their departments and I think the one that I found very interesting to
look at and make sure that we're clear focused on are some of the the HR
applications you and I monitor this the press and the media quite a bit around
keeping up to date and what's happening and the ones that seem to constantly
rear their heads like social media where we first met I think are are those sort
of ones around recruitment for human performance type of monitoring systems
and as a consequence you know people like HR directors absolutely have to get
to grips with this technology and quickly yeah
or and there's some stories there of how that's been negative or like done not
necessarily really badly but like in a you know kind of good and evil sort of
way but like dubiously something that maybe we don't want to promote
thing and there's the Amazon example comes to mind about having you know
promoting men in their CV machine learning tactics and things of that and
because of past bias data than this little thing so it's really about
getting around that sort of Missy misunderstanding
maybe not the malicious use but like a stupidity in these high stakes arenas
but yeah I'm a big believer that the substantial majority of people were
configuring and deploying these systems are coming in with the best of
intentions yes with with good values more often not but and we we I think we
see where they don't always work out well they don't always leads to the best
outcomes they often can lead to amplification of bias and discrimination
for example and typically affecting vulnerable groups of they called us or
all customers it is often because that there's not been the right mixture of
people in the room to provide the right level of challenge and I think on the
one hand we very well aware that there's a substantial issue around the
homogeneity of the workforce you know it is very well noted that it's extremely
white a male which there's a lot of great corporate ishutin cluding some of
ours to try to address that imbalance but I think I'm also looking at the
Disciplinary homogeneity as well and it's absolutely critical to out there
are people in the room to give that level of challenge and and that go/no-go
power of veto and for example when wherever configuring a specific use case
in our team will always make sure we have the right subject matter experts in
the room and and even beyond that in fact I've been talking about ethics and
AI in business for quite a number of years now and I thought about it
actually take some action on this and that we've just hired our first AI
ethicist to the team months ago cool who we we know with the level of rigor we
face as a organization and scrutiny we know that we're confident that we meet
the high standards around data security and privacy around regulatory compliance
around around you know the whole issues of risk and quality
but specifically with regards to ethics that need to now think through not just
secondary but tertiary unintended consequences it's now critical that
giving people that power and freedom to explore investigates and model and
challenge I think it is something really valuable now and and that's you know
giving us that interesting new type of job they'll be talking about the jobs of
the future what we've just created you know anyone for our organization so
prove it's gonna happen yeah that's great they what's that kind
of remit is it kind of like future rising or is it more like philosophy or
people yeah this twenty word Lander in in the real life world of what's
expected yeah which is actually that's what I mean yeah London in the kind of
reality of what's happening on the ground I mean really we have the
opportunity to meet some of these for a meet the world-class academics and
philosophers and ethicists working on this and you know it's fascinating I've
learned a lot in recent years but if you sitting there in business making random
decisions to drive profit or to reduce cost or future prove the organization
there's maybe not the same man you ship of deliberation that happens and if you
think about ethics specifically with of course in this explosion of publication
of new ethical principles in the last two years in particular I think at the
last count we'd we'd come across the in excess of 70 if you add together the big
tech companies the World Economic Forum the I Triple E the baking principles it
having all these together yeah you've got a lot of material out there and we
have reality of businesses going to be able to read all of those and discern
which one is most appropriate for their particular geography and setting yeah
and and acts accordingly and so what we what we have is we actually have read
all these whole team on it and went in with a fine-tooth comb and built
effectively a traceability matrix so what we can now be able to say to
clients through what we call our responsible AI approved
is okay we feel that with for the right governance in place around the project
its had the right approach in terms of identification and the biasing of
datacenters prior to training we're confident that it's appropriately
scrutinized from a security and privacy perspective and for this particular use
case it's got the appropriate level of interpret ability and explain ability
now moving beyond that we can say it's got this relatively clean bill of health
with the caveat to give you the confidence to move forward now there's a
conscious decision to make as a leadership team running these projects
to say what do we optimize this solution for is it to maximize profit performance
is there a trade-off to be made that allows you to drive even
further transparency into the system and you want to then optimize for fairness