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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

  • and the fairness today is fascinating I think even more fascinating than ethics

  • there was a piece of work enough maybe you still could share the the link so

  • you can share with you regionally we did a piece on this and we found that

  • fairness is something that's constantly raised in all of these ethical principle

  • documents yeah and the very high level ones are all very laudable and they stay

  • on ethics so AI should be benevolent it should be good for Humanity it should be

  • transparent it should be fair and inequitable eccentrics yeah but are you

  • get to fairness there's in excess of 20 mathematical definitions of fairness so

  • if you then just take that at all who's it fair to yeah you can't be fair

  • universally to every single person in society

  • yeah therefore do you have to define who it's fair to yes so when you get into

  • those sort of conversations you can really make sure that the projects are

  • proceeding with that level of rigor of conversation certainty buy-in and a

  • conscious choice around what the project is is optimized to do yeah and there are

  • sort of things that the our own ethicists will

  • the ability to shape and starless conversations for our own projects and

  • clients that we work with the fairness thing is really interesting I think that

  • comes that's part of the ethical conversation because what you know like

  • the morality of an individual like what is fairness to you does that actually

  • warrior she told me about when we say fairness is a really interesting point

  • if if a a company came to you and went oh this is so great but we actually

  • trying to optimize for you know the the outcome the the monetary return and

  • actually maybe the fairness is not on a high or an agenda

  • well the sorts of conversations do you have there yes quite difficult I mean I

  • think I don't think I don't think we've had them like that yet but I think it's

  • an interesting question to raise alphabetically as as the market becomes

  • more sophisticated I think there's two things there I think that there there

  • may well get to the point where there's certain use cases and applications that

  • it's simply not appropriate to go near the certain industries that might be

  • more difficult than others to work with but I think we also have to respect the

  • fact that to attract the very best talent the best talent want to be

  • applying their skills to the you know the the appropriate use cases and with

  • that in mind giving people the the right to to not have to time partake in

  • certain projects is something I think that's getting slightly comfortable with

  • yes oh and we've seen this haven't we in that last a year with how breaks of

  • employee activism which i think is something which your organization's need

  • to take into account around so what we want to be aligned with doing yeah and

  • it's I mean for me it's look it's laudable that people who are taking

  • these sorts of actions in the face of things which go against their principles

  • they're you know internal I spoke to one of those people not so long ago actually

  • who Jack Paulson I don't know yeah of young he quit Google because of the the

  • arm stuff and one was the one of the first people to do so and then there was

  • all this action afterwards so it's an interesting thing that's happening where

  • people starting to take notice of how these technology

  • applied and when it's appropriate to do so do you have any kind of like hardline

  • ideas of what maybe isn't appropriate or having a specific yeah they think we've

  • got for where it's kind of like you know a list of no go no go I mean personally

  • this things that I you know don't feel comfortable with morally or that's or

  • Thomas weapons for example those conversation coming back to that's a

  • good point no coming back to your conversations

  • that you might have in government with the AP PGA I'm do you have these little

  • conversations about I mean obviously the general AI conversation has been hand

  • there but do you have the kind of robotics conversation about where when

  • isn't appropriate to use these sorts of technologies at the moment with the

  • government you know what I think the thing that actually gives me a lot of

  • optimism and and professional pride working in this part of the world around

  • this topic is that we've got a really quite sophisticated community that's

  • been active now for the best part of say two-and-a-half years or so so coming

  • from the all party group I've been on the advisory board fastened to start

  • that's then led through to the you know the the publication and the and the

  • evidence taking of the house of all a committee with with law Clement Jones

  • the the AI review with within wendyhall and drone Vicente and then now on to the

  • AR set deal which is now led to this proliferation of new activities and the

  • set of data ethics innovation the government office for yeah you know

  • we've seen a huge array of quite tangible progress in the last two and a

  • half years and for me that was counted number of times have been in Parliament

  • you know hearing or giving evidence in excess of thirty maybe in the last a

  • couple of years and yeah we've absolutely covered the broad spread of

  • topics from regulation and you know geographical

  • prominence and academia skills education ethics that the whole panoply of topics

  • I think it has been well well looked into

  • and some of these more contentious ones absolutely are are there yeah so you

  • know in defense of politicians it's easy to guess sweep it all up and say I think

  • I saw a tweet yesterday saying politicians don't get this actually

  • reject that I think I think a number of individual ones that I've had the

  • privilege of working with actually got a really good grasp of this so I think

  • it's a nice case of lumping everyone in the same bucket here yeah nice great I

  • was going to ask what the outcomes were I think you've nicely kind of well I

  • think I think we as a not only have we seen the the launch of the the AR 60 I

  • was part of industrial strategy and the launch of these new bodies you know the

  • sense of data ethics of now you know publish their interim findings on a

  • couple of key areas I would advise I think in criminal justice and I think

  • the other thing is is how this now translates to the international picture

  • and some of the best practice I think that we've started to put in place here

  • I think he's being looked at with interest by a number of countries I get

  • to go and visit as well and seeing how they can learn from other UK's doing

  • this so yeah I think in terms outcomes in terms of international influence it I

  • think it's been pretty well received yeah Matic Euler area so it's kind of a

  • leadership role there that people are taking out of will it be something that

  • if we put in together regulation in that way that people also

  • take note of that well possibly and then taking it out of the AI out of the

  • equation our legislative system and the legal profession is looked at by many

  • parts of the world as as exemplar and many disputes are settled here for

  • example so if we can map that across to AI then yes it's a good chance that must

  • become one of the international benchmarks that people will try to ape

  • the underworld awesome you did a TED talk a few years ago no

  • two years ago no that's probably approaching two years here are phobia

  • yeah and in that talk you you talked about your children and then that's very

  • high on the agenda of the talk it's and that's how you tell the story of

  • what a I should be doing in a positive way and you kind of glossed over this

  • question but what is it that we should be teaching our children you know going

  • forward in this for the future yeah I'm conscience fire I didn't know

  • dispensed this specific times that I see the ends of fire I guess we only have

  • like 70 or 18 minutes to shoehorn it all in and the time flew on that talk

  • actually but um I think about it's a huge amount and I think the the thing

  • I'm settling honest what you might kids now grow up and that the nine and eight

  • and and three now it is there's so many of these reports we see dropping on an

  • often weekly monthly basis you know there's gonna be explosion in the growth

  • of both flows of growth in the need for phaser scientists or engineers get more

  • people coding and programming you know gonna see exponential growth in this for

  • a while yet so although forget all that we need to now focus on the liberal arts

  • and soft skills and getting people focused on cognitive flexibility and

  • emotional intelligence because the machines can't ape that and yeah you

  • know that there's this there's plenty of arguments on both sides of the equation

  • I think what I'm increasingly getting to the point of is just ensuring that they

  • have an absolute joy of learning full stop whatever it is to a certain extent

  • it doesn't matter I think maybe there are some core skills that are always

  • useful and whether it's literacy and numeracy of course that debate mark or

  • but but that the whole point of this is that the the formats and the assembly of

  • careers in the future is going to radically change we we have done some

  • research around that which you can talk about but whether it's some get a extra

  • sense of jobs that change or you know it's a white person I think we can be

  • certain it's people's career paths are going to look very different and one of

  • the key requirements is not just education but this whole concept of

  • learning how to learn and you're only going to want to constant continue to

  • learn how to learn if you love learning yeah and been able to very comfortably

  • pivot and adapt and change course at the drop of a hat

  • I think it's just going to be par for the course for the workforce in the

  • future so just an extent I'm not being prescriptive by trying to force

  • them down a path that I'm just trying to invigorate and and celebrate you know

  • anything that they seem to thrive off a particular month and not trying to sort

  • of force them down a certain path because I think anyone that gives a very

  • firm forecast about what's going to be in high demand in 10 20 15 years time

  • well yeah I think they're smarter people than me

  • right okay come on just we'll do a bet on it and just well I mean the first

  • throwaway line up I uses is simply that we know that AI and and some of these

  • techniques they do struggle with British sarcasm aha so nice people that can help

  • and anyone leave they know there's another study I think but another

  • organization I think looked at this that sort of AI explainer role I had to embed

  • an in view technology with common sense and a real-world interpretation yeah so

  • it gets it anything that falls down when you're faced with the kind of like hard

  • English flat comedy yeah exactly right yeah great

  • so we're okay for now I think so yeah I've got way to go yeah so you talked

  • briefly about the workforce and and that's sort of thing in this

  • conversation we're having about maybe how that's going to change in the future

  • given you know the educational piece is there is there like a stark headline but

  • you see though is it just kind of like you know over the last couple of ten

  • tens of years there's jobs that never been known before like Kim I used to be

  • a web designer that wasn't a thing you know 30 years ago and data science

  • wasn't a thing more than ten years ago so we get these new jobs or new labels

  • maybe found jobs and is is there some new jobs that are going to come in and

  • everything's gonna be fine or is this gonna be this kind of precipice maybe

  • that and that's normally the news angle they

  • gamings head of the attention yeah I mean I'll follow the slap headlines and

  • then walk back a bit against the nuance which the headlines never cater for okay

  • so so the headlines I think if you look at the the the the most stark headlines

  • around this probably the most influential report around this was the

  • the guy at the frailes born guys at Oxford University who posited that 47%

  • of jobs could be disrupted and removed by the work from the workforce in their

  • 2035 time horizon the OECD zone figures suggest it could be a lot lower it's a

  • 14% now that the PWC analysis we launched last year suggests we split the

  • difference a bit and think it's about 30% of the existing jobs yeah now

  • there's so many caveats to this of course first of all significant variance

  • across gender sector educational attainment geography to start with then

  • you're looking at the the other side of the equation which is around what AI we

  • believe does in terms of driving the economy so another study we launched

  • which was incorporated into the the government's industrial strategy was

  • looking at the economic impact of AI so we did a global study and break that

  • down by the UK which suggests that AI through first of all driving

  • productivity growth but also through driving down the costs of goods and

  • services and hyper personalising those services cease this consumption boost as

  • well so the headline figure there was so we felt that my 20 30 a I could add an

  • additional fifteen point seven trillion u.s. dollars to the world economy in

  • that time frame in the UK we think adds about 10 percent of GDP by 2030 so if

  • you have this fairly substantial economic boost as well

  • that means through we think that as it drives down the cost of goods and

  • services it also drives up labor demand so whilst you see certain roles

  • disassembling and reallocating together with a new collection of different tasks

  • and then through bias economic growth this new category of job potentially

  • starts coming through so we think that if that happened

  • and you see profound adaptations to the education system and you see employers

  • for example and different institutions hardwiring this lifelong learning

  • approach into inter people throughout their career not just at the start of

  • their educational cycle we think we could mitigate and in fact neutralize

  • job displacement with job creation there's many people that poopoo that

  • they think that it's going to be much more pakka lipstick than that or it's

  • not going to happen it'll be the same as previous revolutions but there's so many

  • caveats in that and there's not much time on our side to start making those

  • generational changes so so if rule this code like this possibility of moderate

  • optimism about this at the same time as potentially the improving work removing

  • gradually removing risk and danger from jobs the reassembly of highly cognitive

  • tasks and and just making work good for larger numbers of people hey this can be

  • debated all day long I think where we get to also is this other interesting

  • debate around the shape of jobs in the future about where they're housed in the

  • economy and something that we we had some fun doing last year was creating

  • what we felt work four distinct worlds of work and thought what a quiz I'm

  • going to share with you guys as well you know could you see corporates growing in

  • strength so they have effectively bigger GDP than many smaller mid-sized

  • countries do you see you know this massive disaggregation of corporates

  • into a platform economy where the entire employee basis is on a contingent

  • workforce basis zero hour contracts effectively do you see companies pushing

  • much more into societal good and focused on purpose and environmental

  • contribution so so you know did you see these different directions of travel and

  • the way that people therefore engaged changes from simply that the

  • nine-to-five permanent job contract forever a day

  • and it resourced the entire workforce economy on the back of that so huge

  • topics up for debate around this and and the people that attempt to be too

  • precise but a fine a point on it I think sometimes don't always listen to the the

  • prevailing disagreements on the other side of the fence and I simply say I

  • think increasingly every time I've decided to become far less specific with

  • my future gazing and simply boil it down to substantial substantial change is

  • going to come it might not happen next year but a change will come because big

  • change has always come at the back of industrial evolutions and we have a

  • conscious decision about how we protect people in that process and and that is

  • both the responsibility of governments of employers and to an extent

  • individuals as well to be prepared they're not skilled and aware of this

  • seismic shift that's likely to happen in the next 5 10 15 years or so yeah so it

  • could be quite a nice seamless transition or it could be this kind of

  • big coming together of being a big problem

  • and it seems like you kind of have a good idea of how we can to get some of

  • those things that you've looked at as being possible problems with a new

  • saying the upskilling and life learning and the work there companies having more

  • very kind of societal view and the government's doing some more in the

  • education side of things so it's it's almost like you've got that you feel

  • like you have the answer there well I mean I I've got I've got I've got an

  • opinion that means that they get boxed into a corner too much and someone's

  • gonna come take me to task in 15 years time but you know I'm on you know I know

  • many people on different sides of the of this fence I'm carefully struggling and

  • then if you've had for example Callum chase on the on the podcast you know

  • he's yeah his view on this of course is a little different in terms of the

  • possibility of significant technological and employability this very interesting

  • developments happening with the u.s. presidential race at the moment with

  • andrew yang the Democratic candidate is running on a basis of the universal

  • basic income freedom dividend I think he calls it in his son and in his campaign

  • messaging so that's interesting to see how that might come through and I think

  • that he's a lot more work and research around how do we ensure that the the

  • fruits of this technological revolution are are shared equitably across the

  • broadest cross-section of society yeah I mean there's there's a response I have

  • which is a personal response to that which is the the disassembling of

  • capitalism right there's is that there is you you alluded to it earlier that

  • there are companies that will have more you know turnover than a small country

  • and so in the face of that and let's let's say that I think that's a problem

  • and not everyone will grieve me there but is there a sense that maybe we

  • should do something about the infrastructure of how we run our society

  • is the the the commerce set that bit I think I think changes is absolutely

  • necessary how that comes about and to what is that it's the exam question here

  • so there's there's a great guy here if you've not spoken to you know on the

  • podcast well I John havens who is the executive director of the I Tripoli's AI

  • ethics initiative spoken to John John is great and so and I'm on the industry

  • committee of that has been a great sir coming together of people across the

  • world to put those principles in place and he's very much focused on this whole

  • beyond GDP initiative for that's been the the stock measure of human progress

  • or for many a generation now and appears to be ill suited to where this now goes

  • how do we ensure that we have the right measures in place going forward that

  • measure what he describes beautifully is human flourishing and well-being and all

  • those best indicators rather than purely the block of economic growth by my

  • country yes and there are a number of measures I think that

  • investigation but it doesn't require entire rewiring and the focus upon

  • corporate purpose and I see some interesting early signs there there's

  • been some some really meaningful progress towards the interpretation and

  • grasp of corporate responsibility embedding of purpose societal impact of

  • corporate behavior very admirable efforts by for example at Paul Polman

  • the outgoing CEO of Unilever around this topic and many much of this I think

  • actually is driven by employees demands i think the generation coming into the

  • workforce now want to feel that the lofty values espoused by companies

  • genuinely are embedded and there's tangible action being taken towards that

  • and you know for example we're very very much focused upon their carbon

  • neutrality and and you know circular economy behavior of our organizations

  • around the world but that's not certainly expect that to take place now

  • so the signs but this is such a rapid technological shift isn't it it could

  • come at is quite fast so yeah there is a need to focus minds on this and I think

  • this for me this is why I mean a great hopefully your podcast reaches are quite

  • broad cross-section of an audience and for me the opportunity to get this

  • conversation out of the technology community all these kind of niche

  • narrowly focused fora in to a mainstream conversation that is not just about

  • frightening people with pictures of terminator you know front pages

  • newspapers constantly it's like a drinking game you know every time you

  • see a terminator or something like that in the news is absolutely right yeah

  • yeah would you like to talk about anything

  • else specifically yeah yeah this one area I think I'm quite excited about so

  • for the that for the past three years we've been the the founding a corporate

  • partner of what's been called the AI for good global summit just been based at

  • the UN in Geneva and really the unity to start looking at how aie can be

  • harnessed to help us accelerate progress towards achieving these sustainability

  • goals is absolutely now a hot area we'll see some great applications there in

  • terms of climate change with the number of reports on that happy to share some

  • of our work on that so marrying up this technology is stove

  • Grand Challenges I think's massive exciting empowers the staff it really

  • wins hearts and minds over and we think can meet some tangible progress to move

  • this with a dial on this as well so yeah the ARP good gender is really exciting

  • for me I mean I think overall I'm much more excited about the the use cases

  • that they put a requirement of explaining they're not ones that jump

  • out on the headline but the ones that when you sit down and work through step

  • by step and demonstrate the value they add aa third monthly valuable you know

  • we're doing a lot of work around workforce well-being making sure the

  • right people are doing the right jobs at the right time that suits their

  • interests it means that their travels reduced and a carbon footprint needs

  • increased but they're not stories that jump off the front page of the other top

  • tech publications explained a lot a lot of explaining for quite some time so

  • yeah the ones that I think are solving proper hard business problems and

  • leading to tangible benefits and another SCYTL good yeah the ones that get me out

  • bed in the morning nice and and those are sorts of things that you can

  • communicate you know in your in your work as well to hopefully if we keep

  • communicating the good side of things that that more good will come back and I

  • think it inspires the next generation of people to want to come into this

  • profession it's red hot is you know we're hiring people hand over fist we've

  • just taken on in the UK 110 school leavers who were fully funding through

  • university to build our AI workforce in the future so hopefully four years time

  • I'll come out with no debt work experience and some terrific skills to

  • get straight stuck into some of these interesting projects and and you know

  • how we how we sort of demonstrate what they could put their skills towards I

  • think you a really important selling point for

  • business yeah great where were you 10 and a bit years ago it was I 14 years

  • ago 50 yeah 15 year where are you 15 15 days Oh God

  • yeah very long circuitous career path to end up here actually oh yeah I mean now

  • you see with that sort of you know offer you know taking taking you know when I

  • went for university oh around odd a bit the hand off if you could you know put

  • me through university yeah you know fully funded with no doubt the end of

  • its and work experience job offer great in the hottest area in the job market

  • mister it's a no-brainer you did you did microbiology right yeah yes this testing

  • the brain sounds interesting though he goes more looking at the the most

  • horrific of profitable medical diseases madly so that was quite interesting but

  • tipping you've could I mean that's fair lights but scientific so you must have

  • led to you know possibly I mean standing that maybe yeah but I think having had a

  • create much more focused on like that the people agenda and that's swayed me

  • more towards that than the technology very candid yeah and so we're getting

  • towards the end there's a question I always ask at the end the podcast which

  • is probably somewhat already answered through our conversation but it's what

  • excites you about AI and future and what is it something that scares you about

  • that well this mr. Lester this shoot down

  • this said that the fear one first of all shall we I don't think AI scares me what

  • I think is really important that we get our act together with at the moment is

  • the appreciation that yes there's some remarkably complicated long-range issues

  • that some of the greatest minds are wrestling with with regards to

  • existential risk the implications of artificial general intelligence and the

  • singularity and AI safety in maintaining you know the issue and runaway

  • intelligence fascinating stuff I love reading about

  • with regards to how that matters to life today in business in society right now

  • I think its wealth services hot that funding it can continue on but for me

  • it's much more important to appreciate and demonstrate and illustrate people at

  • you know in the society at large this is here it's already having profound

  • impacts on people's lives whether it's a democracy or in their choices as

  • consumers and citizens or in criminal justice or health care it's here it's

  • happening it's making a profound impact today and therefore everyone has to now

  • have start being brought up to speed about this participating in shaping how

  • this is being evolved how its governed the standards around it and most

  • importantly is providing access to the most diverse array of people possible to

  • create AI that's fit for purpose to everybody in a positive way so there's a

  • little bit of kind of like NIM enough to separate out the strands here of the

  • longer range fascinating stuff with today and next year and getting me

  • interact together around that now so so so it a part of that is is dispelling

  • the fear and giving people positive confidence that this tech is wonderful

  • if it's scrutinized and governed and trained and inspected and harnessed the

  • right way it can solve amazingly positive things and just to finish on

  • that positive note one of the things that personally keeps me engaged in this

  • is the source of problems is now able to start solving so several years ago I I

  • lost my very inspirational mother to one of the worst diseases possible which is

  • motor neurone disease the terminal debilitating illness which is absolutely

  • horrendous and the chink of light in this is that already this british-based

  • AI accompany for Neverland a I'm I've heard of them again remember Mariners

  • shields you might recall Cena speaking that they've already started making

  • progress with their machine learning to start you know ingesting clinical

  • studies at scale using that to identify potential new

  • novel treatment regimens and compounds so in club discovery is really

  • interesting around this field they can accelerate drug research you know

  • significantly Swift a factor than the standard human research can do so all

  • menteng the experts in that field to start solving really important problems

  • that improve our lot in life and and rare diseases is one particular

  • intractable problem that the system doesn't yet economically sustain and

  • support the research into so yes for me it's less about how do we use this to

  • sell more advertising and how do we harness it and hook it up and start

  • applying it to the most important problems facing us is society at large

  • yeah and we should be pointing ourselves in that direction nothing so yeah well

  • Rob thank you it's fascinating at all control of your time today it's been a

  • pleasure thanks left me off hi and welcome to the end of the podcast things

  • get too rough for finding time for me in a schedule

  • I think he's often out of the country so he had to slap me in two months in

  • advance I think it was I think there's lots of stuff the executive kresk grew

  • up further on I think maybe one of the things they asked about working with

  • dubious companies companies that maybe are optimizing for things which are bad

  • intentions or things which are more capitalist maybe in their way of looking

  • at optimizing money over maybe social good that sort of thing I think we could

  • have spent more time in there and I think that we could also spend more time

  • on universal basic income Zoar what what future jobs might look like indeed but

  • these things are all kind of hard to grapple with and we only had so much

  • time unfortunately so so hopefully I find Rob in the future and tackle some

  • of these things if you'd like to hear more of my thoughts on this podcast and

  • some of the other news from the month in AI then go to the patreon patreon com4

  • slash machine ethics and thanks again for listening and please rate us

  • on iTunes and wherever else you get your podcasts and hopefully see you again

  • you

hi and welcome to the Machine ethics podcast this month I'm talking with rod

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