[Music] hello everyone and welcome to this session as part of tectonic 2.0 on the next wave of ai technologies so we've got a fantastic panel today that are going to give us a glimpse into the future and give us their perspectives on what we can expect from ai in the next five to ten years both in terms of research but also business adoption so i'll introduce the panelists in a few moments but first of all let me just say a few words to kind of set the scene i always think that australia has a pretty amazing capability in artificial intelligence there are various global rankings where we do very well so if you look at the stanford's global ai vibrancy index for example australia ranks eighth in the world for ai um the nature index ranks as about 10th and in particular in that index there's three australian universities that are ranked in the top 100 globally and there's also a recent ranking that came out that uses a broader composite ai index based on oxford insights that ranks australia about 11th in the world so pretty strong overall i would say however we are a small country and so arguably to compete on the world stage we need to do things differently than other countries in the world we don't necessarily have the same levels of investment as some other countries do we don't have the same number of big tech companies that other countries do nor do we have the sheer numbers of trained ai engineers and scientists that other countries may have but what we lack there i think we we gain in potential and with that amazing strength particularly in the university sector i think if we can bring all of that together we can compete in certain areas on the world stage and that's really what we're going to discuss today we're going to be looking at what the next wave of ai technologies are and in particular where australia can take a leading role it's worth reflecting that you know ai actually has quite a long history ai was invented in 1950 so it's not a new technology we've actually gone through two so-called ai winters during that time where the reality failed to live up to the hype and investment stopped hopefully we won't see a third but we'll we'll get into the details of what we can expect to to hear from ai in the next five to ten years so just to introduce our panelists who are i think uh bring a varied uh range of perspectives on these questions so first of all we've got anton banden hengel so he is a director of applied science at amazon he's also director of the center for augmented reasoning at the australian institute for machine learning he's a professor of computer science at the university of adelaide and he was also a fellow of the australian academy of technology and engineering and in fact anton was the founder of aiml that's the australian institute for machine learning which is australia's largest machine learning research group and has ranked as high as number two in the world for computer vision research so welcome anton we've also got lisa yearsley here with us today so she is the ceo of akin which is a deep tech ai company building ai for the habitat and prior to that role uh liesel was ceo of cognia which is an ai company that became a global leader and was acquired by ibm watson at the time of its acquisition cognier had a number of fortune 100 companies as clients and over 20 000 developers using the platform so great to have you here today lisa and then finally our third panelist is belinda dennett who is corporate affairs director at microsoft australia she's worked for microsoft australia's corporate affairs team since 2012 working across the intersection of technology policy geopolitics and society and she currently leads the ai policy development locally prior to joining microsoft she spent five years working as a senior policy advisor to the federal government in the communications technology and digital economy portfolio so i think you'll agree that that's an absolutely fantastic lineup of panelists that i'm sure are going to answer all of our questions today and just a reminder that you can enter questions for the panel at any time there should be a q a window um in in the browser that you're using for the stream so do please enter questions into there and then we will pick those questions as we go and towards the end of the discussion so um the first question that i really want to ask the panel and we'll kind of go around one by one and give each a chance to answer this question is a very simple question and that is what can we expect to see from ai in the next five to ten years how is it going to transform industry in particular so i might start with you liesel to give us your perspective on that question if that's okay yeah sure i think um we're gonna see three mega trends within the next five years um the one is that sorry i've just got my husband in another room and he's actually talking quite loudly so forgive the the background noise here um the one is that ai are going to become much bigger decision makers in everyday life um in america over 64 of households now have amazon prime and amazon's really an ai company google facebook most of the giant companies are really thinking about ai and more and more so we can have ai that are in our homes in our lives the grandchildren of your amazon alexa and google home hub and your microsoft suite are going to become much more sophisticated much more able to predict and anticipate what what you want to need and i believe i've no doubt that we will be handing more than half of our household decisions or our day-to-day decisions over to an ai and we'll be having about a third of our relationship time with that if you don't believe me um think about something like say google maps or you know if you're writing an email and auto completes for you or if you use an air conditioner or if you drive a car that has adaptive braking systems these are all actually ai technologies that just kind of you know enter in our lives in a gentle background way and end up becoming more and more part of what we do i think in that world we're going to see a very different relationship between customers and brands um you know in five years from now i'm going to care less about you know i don't care about if my organic broccoli comes from the supermarket or that supermarket or my mortgage comes from this bank or that bank um because i'm going to have a personal ai that's increasingly understanding me making those decisions for me and taking all the competitive cycles out of interacting with brands we really don't want to interact with brands we want to live our lives you know we want to have organic broccoli or non-organic broccoli or not broccoli at all or go on a holiday or save money or you know be with people we love so i think that's a big trend that we don't realize how significant impactful it's going to be the second big one i think is that ai is going to become a lot more immersive and and in some overt ways but in some ubiquitous ways so i often think about the progression of technology as kind of a pipe like a fat pipe like the first time human beings leapt onto the back of a horse we're effectively using something stronger than ourselves to actually amplify our ability to get around the world and to get information from the world and then you look at something like the printing press we essentially amplifying again our ability to exchange communica to exchange information with our world you know how we put our words out and consume data and every age of computing has brought a progression so think for a minute about these things you know we didn't have them 20 years ago they're a fat pipe of information where we make our feelings and wishes and thoughts and intense knowing to the outside world and it comes back to us if you take this away it's like a piece of your hand is missing so it's a tool that's become part of who we are and ai is going to become much more immersive ubiquitous we'll have ar glasses we'll have ai that are predictive and anticipatory and stuff in our environment that's adapting as we walk through it um and we will be thinking less and less about it but relying on it more and more um and then a third mega trend that's coming if you're interested in in the winters that john mentioned there's also been um darpa talks about three waves of ai our first wave was very structured we're looking at symbolic reasoning you know teaching computers the relationship between objects these systems can reason they expert systems or rules-based systems they can reason but they don't learn very well and we had the the era of machine learning which is our second wave based on biological theories and paradigms and these systems you can throw enormous amounts of data at them if they have enough compute power they can learn but they don't reason very well so the third wave of ai that's coming we're working on this in our labs as well um i'm sure others are is adaptive reasoning more like a human thing so able to reason and learn but not need the kind of data and compute power that that that ai today have so those are the big three mega trends that i'm interested i think gonna live in a very different world but there's not going to be a clear line where we go oh now i'm stepping into an ai future we're just going to use this more and more and more so one day we'll look back and go huh i don't know how i lived without this that's fantastic listen you're painting this picture that you know ai will just become part of the fabric of our society and we'll do and change the way that we we live i think that's a good segue to to you belinda so you've got a particular interest in ai policy so what do you think that the next kind of five to ten years ai is going to look like in particular this picture that lisa's painted as a kind of society where ai is fundamentally embedded are there particular policy questions that we need to be thinking about around that thanks john yes so i think um responsible ai moves us from the periphery to be coming at the core of ai development um ensuring that it's developed and built in a responsible way you know there's growing awareness around some of the challenges that ai has how do we make sure they're used responsible so i guess that's my my area of interest i think what is interesting that challenges perhaps some of the ways we've thought about um policy development and regulation is you know to what liza was talking about and that is how ai is developed um so we agree we think that the there's a paradigm shift at the moment it's been around supervised learning where ao models learn from data sets that humans have curated and labeled that has limitations uh what we're seeing now is the res the developments in unsupervised or self-supervised learning where systems can process just huge amounts of data it's less structured it can be unlabeled and it learns patterns and relationships between those different pieces of information um so it's much more open-ended uh and it closely mirrors the way humans learn about the world so i think for me that raises challenges around how we think about policy and how we think about regulation um lots of discussion in recent years around um algorithm transparency and whether someone should monitor the algorithms and that's just not going to apply in this way i ai is going to be developing so i think that creates some new challenges but i'm quite optimistic i think the new applications that are available using this kind of ai in the creative fields you know we've seen um gpt-3 which which can you know write poetry it can write your emails for you um i think that's really fascinating but also in solving um societal challenges climate change we've seen ai used um in the co in covet in the pandemic microsoft's been looking at antigen mapping project to see how the body reacts to different diseases and to vaccines so i'm quite optimistic that there are huge um breakthroughs coming great thanks linda anton you've been at the forefront of kind of ai developments for for quite a while um as as as was i actually my i did a phd in ai that i finished back in 1999 and then i decided to leave ai thinking oh this ai thing will never really work um so i always tell people if you want an idea and a prediction of what the future is going to look like then probably don't come and ask me because i'll get it wrong but you stuck with it so um i mean where do you see more of the technological developments that we're going to get to in ai and particularly thinking of that history that we've had we've had those winters where things got overhyped you know we've got belinda now talking about um you know ai systems that can write poetry and things like that i i do still feel like there's quite a lot of hype around what ai can do when we probably need to be more informed about what it can't do um so what's your views of where we're going in the next 10 years yeah thanks john i would love to take credit for having had better insight than you to really i was just standing in the right place when my research area happened to become fashionable um but uh i you know i think that as with so many things we tend to overestimate the short-term impact and underestimate the long-term impact though technologically it's you know as belinda says we're moving out of a process or the research at least is moving away from supervised learning towards weekly supervised learning that means uh it's kind of matched by shift from uh discriminative towards generative models what that really means in terms of capability is systems that can learn from less data and learn to do more interesting more challenging things from this data and as liesl says there's more focus on systems that interact with humans to achieve to work with them rather than to do something static this is you know i've been working on visual question answering recently which is a new uh entirely new area that we've applied for instance to trying to have robots that you can just tell to do something and they'll do it so uh the other the other trend though is more of what we've seen in the last 10 years so along this line whereby things sneak up on us and we we miss the big impact uh you know the last 10 years has seen a revolution in the way we gather information and just the way we watch tv has changed completely journalism's changed uh you know so much has changed we and a lot of that change has been driven out of multinationals one of the things that uh that ai does is to create global markets and we've you know welcomed these enormous companies into our lives that operate these global markets that trend will continue and it will continue slowly but the process that uh those multinationals have run will continue uh and you know that offers all sorts of opportunities and all sorts of challenges for australia so there's a big question for us particularly about whether we're going to be a follower or a leader in this area we we do have amazing ai skills in this country we've been punching above our weight for more than 30 years but we face a challenge whereby there is incredible investment not just out of governance but out of companies everywhere else in the world and australia is lagging on almost every measure and free yeah and that's uh that's a that's a good segue to my next question which is to really you know if we've got this this future where ai is going to be everywhere the natural next question is what is australia's role in all of that and as i said earlier i think australia does have very strong capability in certain areas in ai certainly some of our universities but australia is also known for not ranking very well on various innovation metrics so so what's your view anton i mean do you think that australia can be a leader in this space or do you think that you know we're resigned to the fact that we're just gonna follow behind other countries that have got the big tech companies and the big dollars behind them now i think we've got we're in a really strong position here australia's got a lot of what it takes to lose um we're actually in a very good time zone we've got an amazing quality of life we've got a fantastic education system but more than all of that we've got a wonderful set of liberal democratic institutions that that offer you value for a brand in australian island we have a you know great research tradition we have all of the pieces that it takes and we've seen uh israel south korea singapore all take up fantastic positions in this tech uh by being adventurous both on a government level but also at an industry level um australia does suffer on all of those innovation measures partly because uh you know we've got it too good frankly um but that's you know that is an opportunity it's not necessarily a problem we do as a nation in my opinion i'm biased i suppose but as a nation we do tend to focus on uh tech transfer and frankly in that process on university bashing when the the truth is that the universities are doing very well internationally on the basis of not very much it's australian companies that fail to innovate seriously serially not only in ai but in absolutely every other area as well um and uh but that's a solvable problem if you um you can look at the other examples around the world and it doesn't really it doesn't actually take all that much to solve those problems so with a bit of commitment i think we're in a very good position to solve this problem so with the particular things that you think we need to do differently as a as a country i mean you're probably well placed to answer this given that you know you've got one foot in industry and one foot in university right now so um you know is it is it just a case of continuing to do what we've done and continuing to try and punch above our weight or you know what should we change the opportunity the magic power and to change things what would you do uh the opportunity in ai and this tech is that it creates disruptive businesses in all sorts of areas so google weren't running a small search engine before they started searching you know before they started google and uber weren't running a small transport company before they started google replies these companies started recently and are revolutionary the opportunity with ai is thus to disrupt the global marketplace and we can do that from from australia there are actually companies doing from australia to some great examples a lot of what we focus on we tend to however focus unfortunately primarily on existing companies and the existing companies have shown great reluctance to actually innovate on any level um so uh and this you know instead what israel did was to really invest in startups to take some of the people with these amazing world-class skills and we have the skills here and back then in their uh attempts to take on the world and build a global market for australia first round the tech it takes resilience right we don't have great skills in this area at the moment and it will take multiple rounds of failing before we get the skills to do so just by doubling down committing to uh support for ai enabled startups we can take on the world right we have we've got everything it takes all we need is to double down on the capability to generate the people it's it's research that generates these people that take on these things right google came out of stanford phd students it's it's people with really strong understanding of the tech that generate these new opportunities and uh and generate and can see how the technology can create revolutionary uh business opportunity um we're really well placed to do okay um i don't agree i i think australia is i'm gonna keep slipping sorry if i may just i'm very passionate about this because i've been capital raising and growing companies in this space for over a decade now i've always raised far more money in the us than i have here my last company actually had to move to america and suddenly my business catapulted us slugging it out for eight years in australia um just not not getting much head where i moved there within two years we had a big up you know massive deals and a big ibm acquisition and the google founders actually dropped out of their phd um to to build google um the the big challenges we have here here's you know i think to grow our ai industry a lot of our initiatives and and focus is on academia and institutional ai and really as um xanton correctly pointed out about startups but it's not just about saying oh let's give some startups you know a three hundred thousand dollar grant or a one million dollar grant that's nothing nothing in the us um you know two million three million dollars is a pre-seed round before you even know what you're doing series a are sitting at about 12 to 15 million dollars when you're just starting to get product market food in the us i want about three or four years just experimenting and breaking stuff and throwing things out the door before we even had to produce an application so you know it's not just that the quantum of the capital here um the capital doesn't um really allow you to take risk in australia i know we think we have a much more robust venture capital industry than than we did a while ago but you still have to show your bluetooth customers and your big bluetooth partnerships and to me most of those companies are from like the last century so you spend your time in australia running around trying to prove yourself as a startup running around trying to prove that you've got something that you've got these big customers that are validating it and whereas in the usa he has 20 million dollars go reshape a market go break the old paradigms and build something new um so we're we're um you know the company i'm running now is primarily funded with us capital and most of our market most of our growth is in the u.s you need three things for innovation you need talent um you need capital and you need a market um we don't have a big enough market yet we just don't we don't have enough capital and capital we have is not um as interested in wildly risky billion dollar plays um we do have talent and that's extraordinary i absolutely agree there you know the the people that come out of our universities here our world class often if you're building something innovative you're the most interesting game in town so you get to retain your talent which is wonderful but i think we have a very long way to go um in a climate where you know entrepreneurship is still seen as something you do if you don't get to become a doctor or lawyer you know it's like sort of oh well you know oh it's okay my daughter decided to become an entrepreneur instead of you know and that that's not not a cultural thing that we we esteem here is it and this is a question to any of the panelists i mean is it a solvable problem or is it all hope lost um i mean it's always useful to kind of reflect back on history i mean have we seen improvements over the last five to ten years does that give us any signals that we might get some improvements in the next five to ten um yeah i think it is a solvable problem um i agree with almost everything that liesel said i think we we don't have smart money here like most of what we've got in australia has done money um i'm afraid somebody warned me uh more than a decade ago not to take down money and at the time i uh dismissed the idea right i was ready to take any money and um they were right i took down money and it killed me it was just it was a horrible experience when you talk to a venture capitalist in the u.s they tend to be an engineer they
understand the uh the space they understand the tech and they understand they're capable of understanding the the market that you want to move into or the opportunity to disrupt that market when you talk to a venture capitalist in australia they're normally an accountant and they want to talk about addressable market and then you're a margin per widget the guys from google didn't finish their phds but they did start them right they they got their you know they understood that uh search page ranking is a matrix inversion problem right because they i you know deeply understood what matrix inversion can do matrix inversion is obviously a subject close to my heart probably something john spent a lot of time doing as well but know we do the we do have the talent i disagree about the market we have a global market just the same way as everyone else does uh companies come here to try out their uh tech in australia because it's a kind of contained market it's also a good microcosm of the us and to a lesser extent the uk uh so i think that we've got a lot of the bits of the puzzle what we don't have is the kind of uh risk appetite that liesl is describing in the u.s capital market we don't have those uh funds that are willing to back people on the basis of a vision and the chance of making uh of creating a uniform a uniform a unicorn what we have is a bunch of people who want uh 10 per annum return on their funds at a very low risk and that's why so many of our graduates so many of our great people go overseas when you go overseas you meet australians everywhere in the tech sector because they've had a great education they're really good and they've been unable to find a job in australia because you know we just don't invest in the same way anton i've been there with with dumb money thought i was i could just override it with smartness you know just give me the money i'll do something with an oh my gosh um ball and chain around the ankle for sure um but i had a very direct experience that when i was raising capital for my previous company the one that was acquired by ibm i was sitting in a venture capitalist office in sydney and he literally said to me i don't care what you think your valuation is um our fund mandate is we invest three million dollars we want about a third of your company so you are worth 10 million dollars no matter what at exactly the same time i was in um diligence with the us fund whose seed round was 10 to 15 million dollars who also wanted about a third of the company so by definition getting on a 12 hour 15 hour plan fight meant i was tripling the value of my company for the exact same company same technology same same uptake same everything um so yeah it's it's i think it's getting better um you know we're certainly seeing a lot more australian vcs understanding that they've got to be competitive on the global market so things like safe notes you know weren't done here at all um five or ten years ago they're like a convertible note that allows an entrepreneur to grow fast without a lot of legacy clauses in all of their invested deeds um so we're seeing a bit of that um but yeah as i keep saying we're still easier at the moment to raise capital for very very risky um big play things like we're playing in what we think is the major productivity challenge of our century it takes four hours a day to run a home it's about twenty percent of our gdp uh about one in ten people with a severe disability and that cost someone about 60 hours a week to to manage um but even a disability aside a regular home is it's just ridiculous that you know my grandmother to me she got a whole bunch of technology and appliances i mean so i have a whole bunch of technology and appliances it means i can be a working mother um yet i'm still doing four to six hours a day as on many i'm working working dads and working parents so um we are trying to solve this problem it's not been so old and it's difficult and it's risky um and yeah there's a lot more more audience for that that more abstract um future play linda i just want to bring you into this conversation um i mean do you think there's a role for the the larger tech companies to play here and kind of supporting um you know what australia could become in ai over the next five to ten years and i think it's certainly true that in in recent times we've seen more interests from the amazons and the microsoft and the google of the world in in doing things in australia is is there a role for them to play i guess i start with um challenging what what do we call success and i guess i get a little bit fatigued that market caps and valuations and number of unicorns is our measure of success maybe that's a big company speaking but what we see is companies our partners that are doing amazing things out of australia i'd point to willow who are building digital twins who are exporting their services all around the world they've developed here they've got staff here we see lots of that now to me that's successful they are building uip they're they're delivering amazing services so i i i'd love to see the conversation change around that we have this sort of one measure of success and and maybe it's a media preoccupation with tech billionaires and and market caps and big numbers but i think there's so many great stories out there i think the role of the big companies um is underplayed and you know we see big tech bashing and and the teclash phenomenon but when you look at microsoft's been in australia for 39 years we employ 2 000 people here we have 16 000 partner organizations who are building uip and contributing 20 billion dollars to the economy so i think the big companies are undervalued for the role they play in supporting new development and new um local companies i'd love to see us talk more about the tech ecosystem as opposed to just australian tech companies um it's a bit of a um a bug bearer of mine that that we define i feel like we define success in quite a narrow way but you know i'm not in the venture capital world so i'll take anton and liesel's views of that as as their experience that's actually a good segue actually i'm just looking at the comments and questions that are coming in from our audience and and do please everyone out there continue to add questions we will i will start to pick those up um in the next few minutes um but there's a there's a comment in there which essentially says that the challenge is not so much to get the public sector in particular to adopt the next wave of ai tech but to get them to actually use the current tech which i think relates to a broader question about business adoption of ai we've talked a lot about the startup world but you know there's there's lots of other ecosystems out there that we would like to adopt ai if we're going to get to this future that lucille has painted of ai being everywhere so do you think we're in a position where kind of businesses or the public sector can adopt ai right now are they adopting ai what are the challenges for them to adopt ai what do we need to be doing differently to help them to adopt ai and i'll throw that open to any of the panelists that want to have a go at that one there's a great opportunity i think in having the various governments as a customer it's something they do quite well in the u.s and there are a bunch of states mandate that they need to do a proportion of their acquisition of their spend from local startups and that gives companies they're desperately needed first contract um i so there's good opportunities there and we're doing some you know the australian institute for machine learning is doing some great work uh with the state government in south australia in uh remote pastoral assessment these kind of things working on improving the both farming and environmental outcomes there's really good opportunities there and when you talk to people in the state government they've got no end of good ideas about how we can help there is a challenge in the um in this kind of fast follower narrative that we're uh or even slow follow a narrative that is uh that's getting pushed so we're just going to be a place that waits for ai to be commoditized and then once it's commoditized we'll buy it right which is a bit like uh saying that you know we'll just wait for you know the steam engine to be commoditized and we'll buy it i suppose but the difference with this ai tech is that you don't buy the steam engine right you buy the wheat you don't buy the computer right australia missed the ict revolution despite the having a building i think we built the world's fourth modern computer in australia and uh nonetheless managed to miss the ict revolution the difference uh for australia is the difference in this uh instance is that if you wait for it to be commoditized the market is gone right it's not you don't buy the tech you buy the product the produce right so we're not buying from google we don't buy the machine learning tech right we don't buy a search ranking engine we buy ads right so that market is gone we're not that money goes to california right and as with so many of these things you don't get to buy the tech it's not like you get to buy computers from taiwan or you get to buy you know electricity generating equipment from germany you or solar panels from china right what happens in ai is that the market is then there right they're making the money out of it so it is this kind of narrative about being a follower and waiting for it to be commoditized will have a very different impact this time around i have a couple of thoughts to add there um i think anton's right about commoditization that also does bring opportunity though for companies who've not dabbled with ai who are wondering what to do you know 10 years ago if you wanted to i don't know get a speech to tax engine or some you know data analytics using art was very difficult as you know half a million dollar enterprise level deployment now it's become very democratized sort of like you know in the 80s or 90s if you wanted a crm system you have to go get a you know 100 million dollar um i won't name any companies you know oracle or something giant installation now you can get hubspot or salesforce whatever for 50 bucks a month the same thing's happening with ai you can grab tensorflow you can grab microsoft has an incredible suite of tools um to experiment and it's at the bar is getting lower and lower for companies to pick up and adopt and experiment with technologies um there are two areas where i do i was bashing australia's capital earlier but there are two areas where i think we have some really interesting things we could be thinking about more the one is something one of our early investors actually said to me said you know in california you have the um it's like this forest with these giant redwood trees just crowding out all the light you have the the republic of google and the republic of amazon the republic of facebook they own all the data their own everything they're in the tools they're in the infrastructure they're in the devices that people are interacting with and and managing and in australia it's kind of interesting you can actually grow up a company and we're a society that's very very protective of our individual rights and our privacy we're also a lot more willing than most to share information for the greater good um and i think government's very progressive here and very interested in looking at you know like our universal health records you know how well did we do with covert because of like check-ins and qr codes i mean wow you know good on us so you know this idea that we actually have a a set of data that has a population we believe belongs to us um and belongs to the greater good even though we absolutely insist on and should you know on on us being sovereign our own data being sovereigntized so i think there's something in there that we can really play with we can give innovative companies playgrounds actually do great things in ai without having to just be a a commodity or an app in somebody else's massive ecosystem third area i just want to mention quickly is i'm in love with robotics i've been my whole life i can't wait for and i'm your robots like you know i robot ns5 but good ones you know i'm so sick of doing dishes and um you know getting my my family up in the morning with coffee and having to make dinner and having to clean the floor and everything in the windows let me do to all the stuff and we're actually physically building robots here in australia um we have all these agricultural robots and mining robs we're building robots so we're going to be shipping to nasa and we're building them here in australia and we're putting our own epigenetic brain in them so i i think we have niche talent um so we have this kind of global asset of of you know data and a willingness of a population to to do sort of population-wide deployments but we also have very very niche talent so we could just hammer a lot well we might find the next great interface in our lives is not a smartphone it might be some other technology combination we may well be able to invent it right here linda do you have any any thoughts on how we can uh help businesses to adopt yeah you must have seen a lot of this in your in your current role i actually have a fairly optimistic view of of the business take up um if you saw the abs characteristics of business uh data a couple of weeks ago um you know cloud is the the greatest uptake of technology in business and cloud is of course the precursor to to ai um i think it was around 57 um and i suspect that's under reported because if we're relying on self-reporting i would say there's a whole lot of businesses that they don't don't know they're using cloud um and i would say equally with ai so the ai used self-reporting use dropped off massively but you know john you said you were studying ai in the 19 i won't quote you i think you mentioned ai's been around since the 1950s sorry you weren't studying in the month i definitely wasn't studying until the 1950s apologies um ai lotion that i use on my skin it keeps me lonely um so so ai's been around for a long time and the the example i always talk about is clippy right remember clippy clippy usai so ai is infused into if you're using um you know an accounting software package that sort of makes recommendations to you about tax deductions you're using ai if you're using spell check you're using ai so i kind of think it is there there is uptake the cloud it kind of reminds me of the early days of cloud of how are we going to get businesses to adopt the cloud and even then i don't think they would knew they were already using the cloud so i'm optimistic now this may not be creating um this is using ai but as lisa said we have you know microsoft we think cloud is the great democratizer it democratizes i.t so if you're using
the cloud you are getting whether you're a one-person company or a huge government agency you're getting the innovation the features the um of all the big cloud hyperscale cloud providers um and we're doing the same with ai so build your own ai you know here's the tools you can build it so i'm a little bit more optimistic about that and i i don't think the business um adoption um and use is is as bad as the picture we paint and i certainly think covert accelerated that and and it's now how do we lock in those games absolutely great answer and we also i'm aware that we have quite a few um public sector professionals on the in the audience today and there's a question that's come in around public sector we talked a lot about you know business adoption um and the question which is do you think that ai is engaging with the sort of problems that will be useful for the public sector for example i've seen a case of using ai to pull information from old pdfs to translate all public service documents into a modern format so you touched a little bit on this earlier anton and but are there particular opportunities or particular things we should be doing to support the public sector in solving problems using ai uh yeah absolutely uh it's uh most the technology is actually already there it's just a question of applying it towards these goals but the the next generation of tech is getting even better uh at these kinds of processes so one of the trends that's happening now is towards personalization so uh you know we all used to go and buy albums so for those of you that are old enough to remember when an album was a piece of plastic that you bought as a unit that had you know 10 to 12 songs on it and now nobody buys albums anymore my children think it's hilarious that you would buy songs in some curated order that was inflexible now you buy songs in you know individual you know song ads and put them together in any way that you want you you don't have to wait for your television channel to put on what you want to see you watch what you want to see whenever you want to see it and this and you know actually adds google ads as the great example of personalization where the revenue from ads has gone through the roof with their effectiveness and that personalization process has huge applications in government because so much of what government does is about trying to make one big decision that kind of suits everybody and doesn't really suit anybody whereas personalization means that you can make decisions that are actually targeted at individuals so there are a huge range of opportunities to do uh fantastic good out of ordinary decisions that government make without uh really needing to you know spend any more or investing so we could direct public housing uh in the place where it's going to make have a better impact we could make health decisions more personalized we could you know i have no doubt personally that taking homeless people off the street saves money in total the only problem is that it saves a little bit of money in at least 14 separate places and if we gave homeless people somewhere you know services and actually pay for them centrally then that would save money in total and one of the things that ml can do ai can do is put to you know is actually do the full economic model of all of those things predict what the impact in 10 years time on somebody's life will be have given them you know taking them off the streets effectively and uh you know enjoying the docks that would enable somebody in government to make the decision they probably want to make already it's just providing better evidence because it can make personalized predictions so the opportunities are enormous they're one of the challenges is this great fear uh whenever you talk to public servants they're very enthusiastic about the opportunity and absolutely petrified that they're going to wind up on the front page of tomorrow's paper i personally think that we should underwrite that risk you know if so if you're a public servant and you wind up on the front page of tomorrow's paper we could just guarantee that if as long as you haven't done anything that's you know underhand then that will have no impact on your career and you won't get a please explain from the minister just because you know somebody's written a story about you that misrepresents what happened um that you know just that single action i think would unlock unlock a lot of the good will you know a lot of the um fantastic uh initiatives that people inside the public service are already trying to drive thanks and that relates to um sorry lisa i have to say something about policy and government and population i think there's a very dark side to this it's the elephant in the room that i think policy makers and and people miss a lot and that is this when you think about a highly personalized ai that's able to observe most of the movements you make in your daily life most of your communications able to predict and anticipate what you're going to need and then give you a human-like front end that says hey i'm here for you i love you i'll do whatever you want i'll make your app work in a certain way i'll talk to you we have an already shifting population behavior at scale whenever we would go into a new sector in my last company we would have a couple of big organizations depending on what was happening economically so bank banks might say hey uh we need we want more credit card debt or we want more credit card signups and more personal loans and more mortgage debt and we would double it against a baseline with a good high quality predictive personalized ai the same thing happened across purchasing decisions you can double the amount of junk people buy and bring into their lives burning fossil fuels and you know someone really hit home for me i was living in san francisco and i was i'm had a couple of different home hubs all ai powered predicting prediction engines on the back and very human-like front ends and i remember opening my door one day and i had six boxes stacked like a pyramid i had post-it notes inside bubble wrap inside a box because i didn't have to think about it i just said oh home hub give me post-it notes um my son at the time i was trying to teach him to be a good young man to cook and clean up after and budget and he had the job of making us dinner one night a week he figured out he could just stand over our home ai and say give me pizza and the pizza would arrive so what's happening is that the ai that's been built and put in our lives is driving towards an optimization outcome and that outcome is get someone addicted to a platform or get them to buy a bunch of stuff we were building companion characters from media companies that people were spending 20 to 40 hours a week talking to an ai and not leaving their homes not going for a walk not going to work not meeting their friends it was awful i used to pull back from those projects and try and donate the the technology to good projects just to kind of counterbalance it and company i'm running out is actually a public benefit corporation for this reason but what i'm saying is we are going to have a population where we are you know to me what's happened in the u.s in the last few years as a result of giant technical systems mediating and filtering and deciding what we're seeing and shifting population behavior and population belief systems at scale so back to this pizza example you know the shareholders of the particular company that delivered that won a fraction of a cent um but we broke our household budget for meals we broke our family value system which is you know boys have to learn to cook and cream um we ate a thousand calories and there was an environmental impact to that none of that was thought about because a whole capitalistic system is around um you know shareholder value transaction events eyeballs and we don't actually have an alternate system um to actually fund innovation except grants which are very early stage so that to me is the big elephant in our room again i think five or ten years from now you will be on default mode your dinner that you eat it people are um i'm on a board of a bank and and people spend more than half of their disposal blink i mean certain demographics on takeaway and you know uber and and just stuff that that just gets suggested to them and is driven by ai so i i think there's a significant shift coming in population behavior um when we have an army of submissive female ai doing our bidding we've watched population behavior change you know we'd have ai that you could say to it um hey you stupid cow and i would say i'm sorry sir and most of them do that now um you wouldn't do that to a human and that behavior became entrenched and people transfer that to human operators so really at a policy level i really think you know just like we've got triple bottom line reporting around environmental and social impact we really need to think about optimization what are we optimizing the population that we serve whether it's our clients or our population are the ai technologies we're using we can't stop ai um but what are they working for are they working for that that fraction of a transaction event in california or are they working for a a family or an individual's life becoming a little bit better day by day if we don't get this right the cost is going to be massive health blow out environmental costs and all sorts of other social costs so we we we are not transferring onto the people making the profit out of it it's a little bit abstract but it's that's where we're going absolutely we've got actually a question on this topic um in in the chat and that's what sort of new regulations do you expect will come alongside the next wave of ai i mean we've seen some movement in recent months on this with the proposed eu regulations to regulate ai and also in australia the human rights commission are bringing out this report on human rights and ai melinda this is your area of expertise do you have any predictions for you know where regulations are going to change um that could help here yeah so we we kind of view that you know a whole new area of law came around with privacy we we have privacy law experts we have privacy law i think we see that with with ai that there will be new regulation new experts you know perhaps there becomes something like in in the medical world of a hippocratic oath for developers of of some kind of responsible requirements i think there are use cases of ai so you know talking to the government you you probably don't need to regulate clippy he's probably okay but when you're talking about things like facial recognition technology and anything that goes to you know biometrics and surveillance then then we probably do need some sort of um guardrail regulation around how that is used so i think it's hugely challenging i think um it'll be interesting to see where the eu developments um go um but yeah i can't see a world where this is not regulated um i think how is the challenge um john i think that you know there are well i must admit i'm intrigued in the extent about the extent to which uh particularly in australia we seem to focus on ethics rather than ai right we seem to be determined to get the the ethics process right before we've got any ai i have repeatedly referred to the process about the adoption of cars in the southern states of the us where you had to have a person walking out the front with a red flag waving it warning everybody that a car was coming and uh actually one of the lawyers said you had to be ready to disassemble your car and put it in a ditch and cover it with a blanket uh if a horse came in the other direction i think that's you know we're kind of at the same in the same position at the moment a whole lot of uh very well intentioned but uh impractical um efforts towards trying to ameliorate the challenges of this very powerful technology we do need to do something but as with so much else this is a global problem and uh our you know what we decide we just had a crack at trying to resolve something with uh google and their ads revenue and you know i think it pretty much highlighted that we don't have a vote at the moment we have such little standing globally um that our position is irrelevant and if we're not a participant in this space then it will always beat us the reason that we started developing satellite tech here in australia was really because we wanted to join get into the security council of the un so that we'd have a load right we needed to be good at something so that our vote would count the same applies here we need to be good at this if our vote is going to account for anything otherwise you know we'll have a gold-plated ethics system and uh and absolutely um no ethical outcome that said the primary ethical challenge we face isn't about how we apply the ai we have uh at the moment the primary ethical problem we have as far as i'm concerned is who's missing out uh ai is largely in the hands of a bunch of companies and you know very middle class people and there's a whole lot of you know there's an infinite range of other places that you could apply this tech to do a great world of good and it's not happening i'm personally trying to start a foundation to fund the application of ai in some of these areas we've been working in trying to prevent human trafficking and there's you know nobody's nobody else is going to invest in preventing human trafficking and it's a problem that's ripe for the application of ai and there's a thousand other ones that just aren't getting done and really have no prospect of getting done there's a much much bigger ethical issue than whether we use face recognition in quite the correct way in australia uh you know horrible things are happening and they you know we're not even then ai's not even touching the sides uh unless there's a whole lot of money associated with it absolutely we're getting towards the end of our time we've just got a couple of minutes left i might round up by asking one final question to each panelist and maybe this is a bit unfair because i haven't prompted you with this question yet but you know we've only got two minutes left a 30-second answer each please but um this panel was all about you know what we can expect from ai in five to ten years let's do a thought experiment and imagine that we reconvene this panel 10 years from now with the same set of participants what's the main topic that you think should be discussed at that panel 10 years from now belinda what do you think um that's interesting i think whatever comes next after ai i think this will move so quickly will be beyond that you know maybe it's whatever comes after quantum ten years it's a long time in the tech industry dancer uh lisa um a i would be running more than half of my life i'm gonna have a drone that goes and get me a coffee before i even know i need one i'm gonna you know just have everything i do in my daily life on background autopilot who do i belong to i'm not going to who does my eyeball and my dollar in my time my time is the only finite thing is i belong to thank you and anton uh i expect that well i really hope that what we'll be saying is that we've solved all of these first world problems how are we going to go start to solve some third ones great well look um we've reached the end of our time so it remains for me just to say a big huge thank you to our panelists today lisa yearsley belinda dennett and anton vandenhingel i thought it was a great discussion and also a big thank you to all of our audience today and for being so active putting in questions which i tried to get to as many of them as i could there is a slight break now before we will all reconvene at four o'clock um for the the main tectonic stream so i'll see you all back there but if if if we don't see you all before i look forward to seeing you in 10 years at our reconvened panel where we were discussing the next wave of something other than ai but thank you very much and see you all later thank you [Music] you
2021-07-14