Will AI Take Your Job? Exploring the Realities of Automation

[Music] thank you hi everyone and welcome to the week ahead I'm Tony Nash today we're joined by Todd gensel Todd is an interest industry and Technology strategist spanning Healthcare mining oil and gas transportation and consumer goods thought it's your first time on the show thanks so much for joining us we've also got Chris balding Chris balding you guys all know well from Twitter he's the founder of a stealth mode AI firm and he's also the founder of new kite data and a recovering academic we've also got Sam Rines of corbu um who's on here regularly so guys I really appreciate uh joining us for the program today uh this means a lot you know I've wanted to look at the hype around AI for quite some time for non-experts it's really hard to tell what's hype and what's real we see stuff about chat gbt or you know whatever every day and we can't tell which real output what's simulated output or whatever so we tried to assemble you guys some experts to tell us what what's happening um and there's some real critical answers that we want to want to address why is a On The Rise right now there there are some reasons why AI is coming to the Forefront right now so what are those um will it take your job a lot of people or some people are joking about that some people are taking seriously some not but but really will it um how how will AI change corporate life what impact will AI have on markets and regulations and so on these are all things that we don't know all the answers to right now but we're kind of figuring this out as we go along so just over a year ago I published a fairly rudimentary illustration uh showing the pace of impact that I thought at the time AI would take uh in the workplace and on jobs so if you notice at the bottom most of the kind of infield jobs are retained a lot of stuff has to physically happen um and my view at least over the next say a few years is you know five to ten percent of jobs are automated and you know I think that'll largely grow toward the end of this decade so we have some key themes um first is the macro environment to blame for the rise of AI I think that's a real concern and we'll talk about that with Sam a second is how will AI change the Enterprise um we'll talk about that with Todd and he's a real expert there and I can't wait to have that discussion and finally will AI steal your job uh that that's kind of a silly question but I think it's one that everybody really wants the answer to and we'll talk about that with Chris so first Sam um I want to frame up the discussion with a little bit of understanding of the macro environment um we've had AI enthusiasm before you know you have these uh really robust AI uh eras and then you have kind of AI Winters um we had a really robust era in 2018 when s p bought a company called pen show which very few people talk about now this was just you know five six years ago uh they bought Ken show for 550 million dollars and really nothing happened with it they were folded into s p at the time I talked with people who had visibility to kensho they they didn't know what to do with it it really wasn't obvious value but s p kind of got the opportunity to take the box on AI so um in part s p wasn't adopted by S P's customers at least this is my running thesis um it wasn't adopted by smb's customers because wages had been pretty stagnant for 30 years so even in 2018 you could kind of throw people at analysis problems and the type of things that kenshaw is supposed to solve um but now we're seeing chat GPT mid-journey and and those types of large language models and image models being adopted pretty quickly Chachi BTS you guys know had millions of users in the first hours in the first couple days um so we can say that processing power and coding and that sort of thing is responsible for advancements in AI which is true um but adoption seems to be different than the actual capability so when we see chat GPT at Mid Journey adopted so quickly they're really taking out low and mid-level writing creative and analyst tasks that's what they're taking out right now is those tasks um these are things that earlier had in you know 10 15 years ago had been sent to say India another offshoring places but now it's being experimented with doing this stuff virtually in developed countries so I realize I'm talking a lot today I don't normally do this at the top of the show but I think we need to introduce some of these ideas for for people to watch so I'm sorry I'm talking so much today but one key Point here is that AI has always been discussed more as robotic so where it would take over the job of physical laborers like people in warehouses blue collar workers As Americans would call them but this generation of AI is different this generation is targeting professional jobs corporate jobs and office jobs which is new this is you know it's kind of unprecedented where this level of fear for White Collar jobs um is is discussed to be replaced by technology so Sam after that long intro um can you talk us through some of your thoughts on this is my hypothesis is there anything there can you talk us through some of the kind of capital versus labor and wage issues that we're seeing right now and is that having an impact on the adoption of AI yeah so don't throw too much at me at once um okay so let's take a big view of the history and kind of parse this out because I do think it's worth kind of going back to uh previous periods to look at what exactly spawns the adoption of various Technologies right because AI is a technology and uh it's incredibly useful for those people that want to become or can become much more productive over time so I think that's it's kind of a level set there but if you look back at the 70s and the level of inflation there it spawned a significant amount of capital investment in things like computers right it was expensive to hire an individual inflation was running out of control and you wanted to maintain your margins if you were a corporation so what did you do you made people more productive by employing technology specifically the computer at the time right it sounds kind of ridiculous to say that the computer was a productivity enhancer because you know we all know that now it you know productivity is not necessarily enhanced by a computer in front of you but then it was incredibly enhancive for productivity so when you have significant inflation pressures against a business it spawns the want and the need to go ahead and invest in incremental Technologies so kind of fast forward to covid and if you were a Leisure and hospitality company or a company that you know faced individuals you had an incredible incentive to invest in an underlying technology to allow your business to either exist in a couple of years or to survive right I mean that was and maybe even Thrive if you were very good at it right you had to go out and you had to make sure that your website could offer uh delivery or pickup options for food you had to really invest in technologies that previously didn't necessarily have to do were they emerging were they in interesting yes but all of a sudden they became existential to your business and the ability to survive going forward so you saw an incredible amount of investment in uh platforms that allowed for delivery and pickup of food Etc um kind of coming out of covet now what you have is an incredible shortage of workers and a significant amount of wage pressures and you have inflation pressures so if you're a business looking to maintain margins grow going forward AI is an incredibly interesting potential tool for you to be able to make some of your best workers and best you know call them thought leaders and intellectual leaders much more productive and allow you to grow going forward without having to worry about whether or not you're going to be able to find that incremental employee and I think that really is an understated Catalyst for why chat GPT 4 is so incredible right I I love it it makes me a lot more productive at my job I mean I'm still playing with it and I don't actually publish anything can I just give you an example just give you a tangible example of what you're talking about I know I know that you understand the sound but for our viewers so so my staff last week uh put together a Persona in a large language model and called it Nash and it re it looked at all of our previous shows of the week ahead and that it came up with a persona for Nash so last week's newsletter complete intelligence newsletter and going forward they're largely written by this Persona in chat gbt so we didn't have to spend the time anymore to actually write our newsletter of course we'd clean it up a little bit but it has my voice it has my word choice sentence structure and so on and so largely our newsletter is automated and of course there are little tweaks here and there but for the most part those are the types of things where maybe I had to hire a newsletter person before even if they were offshore but now it's done in three minutes CA Futures is our subscription platform for Global markets and economics who forecast hundreds of assets across currencies commodities Equity indices and economics we have new forecasts for currencies Commodities and Equity indices every Monday morning we do new economics forecasts for 50 countries once a month within TI Futures we show you our error rates so every forecast every month we give you the one and three month error rate for our previous forecasts we also show you the top correlations and allow you to download charts and data you can find out more or get a demo on complete intel.com thank you no and again I mean that's productivity enhancing for your team right and it allows you to say okay now this now that we've really kind of come up with a way to automate this newsletter what else can we do right so it allows you to be not only productivity enhancing but potentially Revenue enhancing potentially bottom line enhancing producing new products new Services et cetera et cetera so in my mind that is the one of the Tailwinds uh two AI adoption at this point is that you really have not only and call it a curiosity with it but also a need to replace the incremental employee because you can't find them right if the incremental employee doesn't exist you're not destroying jobs you're creating slash enhancing ones that exist so I I this the idea you know I'm kind of running ahead of us I know sorry but to me that's really the Catalyst behind the current adoption right and if you look at one of the most labor-intensive uh businesses out there and we kind of touched on this while we were chatting before uh reporting if you look at agriculture I mean John Deere has been working on AI tools for Farmers for a decade and has brought up a significant amount of Ip around that to not only allow Farmers to become much more productive but potentially make it so the farmer doesn't have to be in the tractor during planting during you know when they're spraying the plants early on and during harvesting the farmer can go do other stuff so I think as we begin to really understand that there aren't enough Farm Workers out there that there aren't enough people to hire into various businesses I mean just look at the participation rate the participation rate is not exactly coming back the way anybody thought it would after covid and it's unlikely that it's going to recover anytime soon with the number of retirees you know retirees have a significant demand for services if you're going to provide those Services you're going to need to not only adopt new technologies and new tools you're going to have to come up with new ways of doing things generally so I think AI always was going to be something interesting but it's the something interesting at the right time with the right Catalyst moving forward and this is not something that's going to be I mean you know there's a little bit of fattiness to it in different ways but I don't think it's going to be one of those passing fads that everybody's like oh well remember when AI was a thing I think it's much more of something that we're going to interact with on a daily basis across a whole lot of services and a whole lot of businesses that we did not anticipate prior so two things there um technology generally is deflationary right I mean aside from like a 1400 iPhone or whatever generally technology is deflationary for kind of status quo activities is that fair to say sure that's good um and then you said something like um we're going to x with AI but people are already experimenting with that stuff so you know we do have people who are already doing that and it's really a question of it going at of things going broad market like I don't want to be the AI hypster here I'm I'm really just kind of asking you know these types of questions uh just to understand your your view on this stuff sure I mean I think it's pretty it's pretty straightforward right it's you have to have some way of replacing a non-existent labor market right and AI does that in a fairly efficient manner so it's demographics wages demographics wages I mean you know none of the demographics you know change slowly then you know than all at once right it's not as though you can simply incentivize the demographics to change right yep that's exactly that ship sailed a long time ago so so generally to your point demographics are a powerful force where when you have a significant amount of people that are older and out of the labor force demanding a significant amount of services you have to figure out a way to deliver those Services into them with fewer people in the labor force which is a massive long-term Catalyst to tools like AI like chat PT that type of thing and it's not going to stop there yep okay good points okay so let's move from the kind of context and thanks for that Sam let's move into how will AI change the Enterprise Todd you've consulted and Lead strategy for really some of the world's largest companies uh in Enterprise circles we hear about AI projects from Big consulting firms or a firm like palantir which really is a consulting firm um these are largely pet projects to take a box but at least in my mind the kind of AI portion of these projects is extremely Limited at this point so given the economics context that Sam discussed and the corporate dynamics that you're aware of is AI in the Enterprise a real thing right now yeah I I think that you probably have to break it into a couple of groups I I think you know the earlier statement about agriculture and John Deere is true in oil and gas is true in healthcare I mean there are lots of companies that have been at this for a while um and they've got relatively mature environments and and in those environments they're really playing a different game it's not a check the box I mean it really is kind of fundamental to business models I think there's sort of a sort of much larger group of organizations that are just beginning to be aware of the opportunity um you know in the kind of intermediate and long-term I'm super positive I think this is unquestionably the direction this has been headed for a long time I think in the short term we're going to see what we always see during these periods of technical transition uh it's gonna be messy I think you know it's it's important to always remember that there are real power dynamics around any adoption of new technologies and in a lot of cases the people who are in leadership and the people who are making these decisions are the authors of the current state um and so they struggle to sort of conceptualize what the world would look like under completely different set of norms and I think unlike some of the previous generations of technical advancement I mean I I would argue we're coming out of the age of digital enablement we've talked about transformation I think there's been very little transformation I think it's mostly just enabling some core things we were already doing and gaining some minor improvements in productivity AI is one of you know a dozen exponential technologies that plays a very very different role in accelerating Innovation and accelerating business model development and changing operating models that's where things get really dicey and I think they're going to be winners and there's losers and I know Tony you and I've talked over the years about you know when you do scenario planning you sort of right off the bat assume that there's really no good or bad future it's good for some and it's bad for others and I think that's going to be true here I think what we're going to see is there are organizations who have spent the last decade really creating the kind of agility uh the kind of resilience that's necessary to make a transition like this and really capitalize on it and there's going to be some organizations that really struggle and that's why I actually think that this may not be the age of the incumbents I think that the the people who are really intending to disrupt have a window of opportunity here you know while while people are kind of working through the internal dynamics of what it means to adopt these new technologies and brand new ways of working people who are unencumbered by those cultures and those kind of leadership Norms are gonna be able to move much more quickly and and likely be able to sell into that world and I think that's going to give rise to a whole new group of Consultants I think there's always the system integrator model and you know we're going to sell the big thing and we're going to work it out over five years and the rest of that I think that the people who will play most prominently in this next phase really are hyper Specialists and they're going to come in and they're going to solve significant real problems so when you say that the current I think you said the current operational architecture is a reflection of the current leadership or something like that um and it sounds like they won't change willingly so just to be a little bit brutal here or is there going to have to be a wave of retirement or something like that for AI to really hit larger firms or or what would push larger firms to attract or to adopt really interesting levels of State Technology and productivity [Music] [Music] yeah I mean it could I mean I think that we're at a kind of a unique place where a lot of the things that made us successful in the past are the things that actually inhibit our progress um and you know if you've got folks who are relatively intransigent I mean really the only option is to to move on I mean we we used to have a firm I worked for this sounds really crass we had a phrase you either change the people or you change the people and I think we're at that kind of a moment where you know if you find yourself in an environment where the leadership and the operating Norms really are not particularly conducive to making these key pivots you know everything Sam said is is right on the money I mean these are economic realities you're going to have to make these changes to remain competitive and you're going to have to find a way to a new way of operating that will allow you to do that again and again and again because this isn't a Embrace AI it's Embrace tool after tool after tool that's solving these problems it's a very different discipline but it's also spinning up a bunch of interesting um challenges I you know I was just talking to somebody this week that was working on some some things around Material Science and leveraging AI in that space and we are so rapidly spinning up new materials that it's difficult to find people who are capable by way of their training of conceptualizing the utilization of those materials uh and so the these opportunities in some cases take a little while not just to ingest but to train up people to leverage these to their their full extent which is why I think this the short term is going to be really a story of fits and starts there's going to be some big wins and there's going to be some you know significant resistance one of the places where I'm kind of most interested right now is is what was mentioned earlier about sort of the top of the food chain right you're talking about very elite top level professional jobs you know we're already seeing some really incredible things in the healthcare space around second reads uh scans what does that mean second reason yeah so the radiologist takes a look at your you know x-ray or MRI and says this is what I see and then it automatically goes out to an AI engine that goes in and makes sure that everything was caught and what we're finding is that we're routinely catching things with the the AI well that's beginning to tell a story not just about supporting the work of a radiologist but potentially over time the machine actually becoming a superior mechanism to leverage as a first read and a second read and you can actually create alternate models and you know these are things that are not science fiction these things are already happening these are institutionalized systems are doing it really to mitigate risk I I now can say I've looked at it multiple ways and we feel fairly confident at what we're seeing that's happening in Industries right now where we're actually seeing real live serious use cases that are mitigating risk lowering costs improving outcomes that needs to be scaled and that's really what I'm getting at I think that you see these really interesting spot treatments right where we're looking at something saying I can solve that yeah the question is how do enough of those actually begin to be leveraged it becomes a way of working rather than just a tool in the box that we go to in very specific and very very narrow circumstances yep so what about those people who say oh I'll never let AI be my doctor I'll never have a robot for a doctor or I'll never let AI be my CPA or something like that I mean will they have a choice yeah I don't I don't know that they will I I will tell you that there's some pretty sophisticated tools that are already on the market that are um very very close to being able to achieve the same level of efficacy in diagnosis as the very best physicians that we have uh when you think about that as a language model I mean if you think about like a physician Desk Reference and you're asking questions and you're getting the you know medical history and you're making decisions and you're there's things that the machine is capable of doing that's just far more capable than the human mind in evaluating the different levels of risk and the likelihood that this is what's what I'm seeing versus this other thing because we've seen such a remarkable advancement just on that front in the last four or five years and you've seen its adoption you look at you know the NHS or you look at Medicare and you say like there's absolutely no way at least at that first level of diagnosis that we're not moving very aggressively in that direction for a lot of reasons number one it's much cheaper but number two it's super available it's easy access and we're actually catching these things long before they become genuinely problematic and cost the public a whole lot more by way of healthcare dollars so I get it I understand it I think there's sort of an Impulse initially to say I'm very uncomfortable with that but increasingly there is a whole lot of diagnostic stuff that's happening behind the scenes that people aren't seeing that's already in place yeah that's a pretty significant part of their care right okay so this is where I'm going to give a little Shameless plug for complete intelligence just to give people a little tangible idea of what can be done so um we do uh budget forecasting for for companies and we have one company a client 12 billion dollars in Revenue they have 400 people who take three months to do their annual budget process um we did that in 48 hours taking one of their people less than a week of their time to transfer knowledge to us so so we we had better results in 48 hours than what 400 people did over three months and this is a very tangible way of identifying the opportunity that's available with AI tools and other technology tools it's not just replacement it's not RPA robotic process automation it's not that it's better right and that's where people should be a little bit uh aware where we're talking about doctors we're talking about people with mbas we're talking about Highly Educated professionals where we can have a machine do that work better and faster so and that brings us to Chris balding to to give us great news Chris thanks Todd I really appreciate that and you guys jump in on this anytime Chris um you know the real question here is Will AI take my job right my job I'm hoping it does but for most people will AI take their job I think um you're about to launch an AI NLP natural language processing firm um first question I guess is how has starting that firm change your mind about the application of AI today versus even just a few years ago um I think there's this discussion about will it take people's jobs and if you look back on really any technological breakthrough um you know from from the cotton gin to uh to fracking what you really had is is the per unit price would drop of of a t-shirt or you know how much it costs to get that oil and gas out of the ground but what happened was is it consumed people that had the Technical Training higher levels of Technical Training you know if if you think about AI people will say well you know hey we don't need as many coders well you know what what's going to happen is is that opens up a whole new field of cyber security risks and all those and all those coder jobs are going to migrate into cyber security because all you're doing is opening up cyber security risks um as a simple example um if you talk to any I.T guy um you know uh inside big companies or whatever there's typically a a list of about 40 Projects you know management wants them to work on and you know there's 20 that are constantly at the top of that field and they never get to those more advanced you know maybe investment longer term types of product um well if you're if you're able to blow through those 20 faster as a simple example you can move on to those more creative you know um risky type of projects um so when I hear people talk about well it's going to take my job I think it's absolutely going to change um how people work I think it's going to change um uh the types of jobs that we do um you know for instance you you know one type of coding might move more into cyber security is it going to eliminate these jobs um so that the total level of employment you know disappears absolutely not it's just going to change how we work and the specific jobs we do so is it at least at this phase is it more augmentation than it is automation so it really it really kind of depends on what you're specifically saying one of the things and I I think uh open AI has has even said uh things to this effect um you know we talked about macro and other stuff but really what has what is undergirding this is that really for the past uh let's say five to ten years you've basically seen this you know exponential increase in AI type stuff and that is really driven by you know to just to be blunt the the hardware of what you can do um with gpus um and part of the reason that you know we talk about this is um you know going forward the the amount of GPU capacity that you're going to need is is I mean you're going to start sucking down I mean the the amount of energy that they were sucking down uh from gpus to do Bitcoin is Will pale in comparison um if if it if it really takes off the way people uh say it well um I I've used it for a lot of like loading and similar types of things and what you really see is especially on more complex types of projects um you you kind of use it to kind of seed what you're what you're doing you know maybe take specific steps um it absolutely I don't think is is is near the point where it can basically manage entire significant projects um and so it's absolutely a time saving tool you know we talk about this with coders it's absolutely a time saving tool is it taking over their job no ABS absolutely not it's going to help them do things faster move on to uh more complex types of uh processes that they're trying to automate okay but if it helps people do things faster then that means it it they're spending less time doing the job they have now so somebody's somebody's losing right like somebody's losing a job right because it's if it's helping people do stuff faster than companies have to spend less time on headcount right I mean I just I'm trying to No I'm trying to get out of the hey this is replacing jobs but uh I it's we kind of end up there with with this type of Technology yeah but so so think about it two ways let's assume let's assume you have a an I.T Department all of a sudden um that I.T department is doing is is doing less work making sure that you know um there's not a paper jam at the printer and that the computer can talk to the printer okay there's there's less time spent doing that but I guarantee you there's hackers in Russia that are that are now using chat GPT to say how do we break into this sure part of the issue is is that guy who started out in it is probably going to move over to cyber security okay or they might say Hey you know um we can let go of a couple of people but now we want these other guys to focus on these bigger investment type projects that maybe we had had kept on the back burner because they just didn't fit within our budgetary priorities okay so those are relatively fungible skills but if you're like the radiologist that Todd's talking about can those Todd can those skills be repurposed to something else well I I honestly I think it's it's Case by case but I mean Radiology is a great example and just Healthcare generally I think we've all probably heard that we have a nursing shortage and that you know you can't find an endocrinologist and like we're constantly dealing with this really serious labor issue a lot of that is because across the board in healthcare you have people really failing to operate at the top of their license because they're spending an incredible amount of time doing the paperwork meeting the CMS requirements and so you have doctors who are doing 30 doctoring because the rest of their time is basically meeting all of the obligations to all the different stakeholders right right what we're likely to see is these people who are sitting in that sort of again that sort of top tier of kind of professional expertise really spend more of their time doing value creating work I think if you if you think about what's really going on you know we have effectively an opportunity cost that's baked into everything that we're just not doing because we're doing all of these things that really don't require somebody operating at that level right what we're trying to do I think and I think this is really the the way we should be framing the the future of AI is that if you really get focused on value creation and you start talking about that opportunity cost Gap I need every one of these employees operating at the very top of their capabilities regardless of whether they're a physician or a coder and I need most of their time being produ being pushed against Real value creating activities rather than all the stuff that really should be relatively easy to put off to this other to this other way of operating and I think you know you can be threatened by it or you can recognize that the greatest inhibitor to Innovation over the course of the last decade has not been our ability to produce technology it's our ability to free up capable people to really focus on the Innovative things that need to get done in order to make things go to the next level this is at lynchpin moment and like every leader ought to be asking the question like how do I maximize the value you have every single human asset that I have and really get them operating on top of their license and if that's not the focus then this probably is going to be a challenging period and it will become about cost and it'll become about reducing by way of eliminating positions that's not I think the the way to go I think that's actually probably the wrong way to think about it I don't doubt that there will be people who will be in that trap because they just are going to have a hard time to make the move but the Smart Companies are going to be able to understand that very quickly and move aggressively to make that happen yeah and I think that's a critical point that should not be overlooked is you can be scared of it or you can embrace it and use it as a tool to enhance your one your life because you don't I mean none of us like doing the lower end of the spectrum stuff that we always have to do if you use it to eliminate that and get to do the stuff that is much more highly value-add that is incredibly accretive not just in business but also to your lifestyle in general right I think embracing it and actually having a positive attitude about it and saying how can I use this to make myself more productive and generally more happy right because hopefully we're doing things that we love to do how do I how do I how do I use this to do that I think it's all about the mentality of approaching it rather than saying oh my word is this going to take my job I think that's it's a fundamental thing that if you think it's going to take your job it probably is simply because you're not going to embrace it and learn and try to adapt to the new technology you're going to fear it and shut it and I think that's the that's going to be the fundamental difference between those that succeed with the new technologies that are coming and those that fail and fail in a meaningful way yeah but I think fear is a natural response to something like this right I mean we're all kind of we're not all of us but a lot of us are afraid of new stuff you know we've had our same job for 10 20 years we have a routine we go in we do our work we leave it you know five and and call it a day that's most people vast majority of people and I don't necessarily think like maybe I'm a skeptic here maybe I'm a bad person for thinking this but as Todd you know you talk about people want to look at the greatest value ad they can have within their job and that will help them from being kind of automated I don't know that most people think that way maybe they do but I think most people are just kind of going in for hours to do a routine job and those are the things that are the most dangerous I think uh the positions that are the most dangerous so I I I don't before we kind of wrap this up I don't want people to think that I just kind of loaded this with people who I knew would have the same view as me so guys let's take the other side of the table for a little bit so and I'm not accusing you of having the same view as me but I you know let's let's take the other side of the table a little bit let's assume that large language models and Chachi BT and all these things are over hyped right now okay what could stop the implementation of these Technologies so that they aren't adopted across companies and across the economy what could stop this stuff Chris you're muted uh I think one of the things is Todd has alluded to this is you're going to need so basically the basic technology to chat GPT used is really probably just 10 years old They just added a lot more data and a lot more gpus I mean the fundamental technology is not new in the least um what you're really going to need what is going to stop this is is now you have to get domain experts coupled with those those Tech Geeks to say what can we do together um so whether it's an endocrinologist whether it's you know a financial analyst whatever it is um and one of the things is outside of the outside of the mainstream that you've seen a lot is how can you how can you develop these language models that are providing uh very precise answers for very specific Fields I'm a tax accountant I am an endocrinologist I am whatever um so if you don't bring those domain experts together with uh with those Tech Geeks um and you're just you know stuck with chat GPT which is basically you know trained on the internet you're going to get a lot of bad answers rather than being able to uh augment what those what those humans can do well I would go further on that and say that those domain experts are critical especially at this moment in time right like you start thinking about Healthcare Aviation um mining oil and gas places where there's really some very significant risk uh and you say look those domain experts working side by side they see that risk coming they bake that into the conversation they talk about what to actually put in that learning model to actually create an environment where you accomplish those kind of incremental improvements but without exposing the organizations to exponential risk the I would tell you right now the the issue is it's it's early and so there's not a lot of domain expertise that's actually fluent enough in this to have a dialogue that's meaningful to kind of push this forward uh and the risk that's inherent to that is sort of ugly pre-adolescence as we sort of learn our way into using the Technologies appropriately getting out over our skis and getting some things really profoundly wrong that that really creates sort of a downdraft right like oh this failed or this didn't work or it opened up this massive amount of risk that that's a human error question that's really just a function of moving I'll tell you just just to kind of add to that give me one second Sam I'm sorry about that um is one of the issues that especially in an issue like the medical field and I've heard this talked about in multiple other fields is um humans are there for a reasoning especially if there's a license if there's legal liability etc etc um no no human no matter how good the the technology is even if the technology is demonstrably far superior to human no no he human is going to turn that legal liability over to a computer without saying I'm gonna I'm gonna sign off on this I'm going to check it and as you said Todd you know that uh that machine learning was basically double checking what the radiologist was doing you know just verifying yeah and and to Todd's Point and to Chris's point and this is this is and I think this is really important if we don't get the domain experts in there to actually help and make better decisions better outcomes better reporting by the by chat GPT four five six seven eight we are going that you know AI in general is going to end up being regulated in a meaningful way it only takes a couple of really big instances you know car crashes et cetera before you end up with the FAA before you end up with the transportation agency etc etc right so I think in Department of energy you know however you want to look at it the amount of Regulation that will come down on top of this in a landslide like way if you don't get it right from the beginning and have some sort of self-regulating mechanism whatever it might be it is another I think understated supplicating Factor right there's nothing that suffocates Innovation like regulation and if you don't get it right and you don't get it right pretty quickly yeah the amount of Regulation that's going to come down on this particularly when it's consumer facing when it's labor facing I mean those are some very powerful lobbies that are going to absolutely Hammer this if it if it's deemed to be unsafe or dangerous I mean it's that simple interesting so basically what I get from you guys is we're likely to have at least a few years where it's more augmentation where those experts are feeding back into the models to help them understand what they do before these things can really go off on their own is that is that fair to say so you know we can't just open the box today replace a bunch of jobs and and you know everyone's on government payments or whatever for the rest of their lives it's going to take a few years for this stuff to really get some some practical momentum in the workplace I think that's right but I think to that previous comment like the industry has to be very careful to sort of self-moderate here I mean there there are going to be folks who really very diligently go about the process of ensuring that we do it right and then there will be people who inevitably will play it fast and loose it's the folks on that side of the fence that actually create the downward pressure from the legislative and Regulatory environment and so this is kind of an interesting moment in time because it's sort of the learning period that really puts it on a solid footing but it's also a period where there's a great deal of volatility and potential for there to be some kind of significant things that happen that actually harm the long-term ability to get it implemented in a way that makes sense for the public very interesting yeah I think that regulation point is so super important okay guys anything else to add before we wrap this up this has been hugely informative for me um anything else that's on your mind about this I'll just say don't fear it use it I mean if you're not if you're not using it if you're not trying to learn about it then I mean you know make it make you better or get out of the way exactly watch a few videos learn how to do some mundane tasks use it to your advantage and do things like we do with our newsletter just just get some really routine tasks automated and then just start learning from there so guys thanks so much this has been really really valuable thank you very much have a great weekend thanks Tony thank you Tony foreign

2023-04-14 09:20

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