Okay, I think we'll get started thanks folks for joining there's some people join it coming in please for free to see where we like Thanks for joining this session today about balancing productivity that Large language models and inference API is an AI give us with the responsibility of Accountability particularly when it intersects in cloud native and I'm going to talk to you from my own experience Building and submitting a project the CNCF and some of the challenges that's encountered. So just very quickly Yep, just very quickly. I am a principal engineer at AWS I work in region services, so it's building out regions and everything that entails but you know, that's not really why I'm here today I think What I'm really here to talk about is the sort of more existential fit side of things that interest me which is sort of the rise of Artificial intelligence, you know, you get images generated by Dali you have non-stop conversations about all through kube-con But I think really interestingly if you ever read Isaac Asimov for anybody as a fan You can sort of see where the world is going and it's it's interesting because we've started in the virtual and AI Eventually will be making its way to the physical What what's kind of funny is that the reality of that right now is it has very little spatial awareness It's typically used to regurgitate coding problems and produce bad images But once you have agents running on top of models and models going on top of models that are high They're tuned to perform to optimize the models beneath them We'll get to a state where it becomes highly performant and applicable in every walk of life We've already seen that for the past decade or so where financial models insurance models have been Guided by by ML and now we're starting to see that this is coming into the physical world Where that's kind of sweet of AI ML is being applicable for things like transportation security and health care What's interesting about this as well is that all throughout this kube-con so far we've heard about this intersection of Cloud native and AI and I would sort of challenge. How much do we actually really know about it? I think it's it's an interesting set of domains to kind of entwine But if you think about the crowd of machine learning engineers and data scientists versus folks who are typically involved in cloud native They're a very different type of community and they're very different needs and so this Because epimetheus is his name is the husband of Pandora here using the key that Zeus provided to Unlock Pandora's box and I think we're kind of getting that getting towards that point fairly soon So today I'm going to talk to you about a few things We're going to discuss Kind of the accretion of knowledge to how do we get here today? We'll also be discussing The kates GPT project. I want to show you sort of what is it about? Why did I think it was an interesting idea and what are some of the challenges? from an ethical point of view but also from a Community and technical point of view with starting to build some of the first Practical cloud native applications with AI and then we'll end up just discussing briefly kind of where we're going and what does the future look like? So to get started let's talk about the accretion of knowledge Well, a lot of these projects that you see today have been the beneficiaries of hard work for the past 50 years I'm not going to go through all this in super detail But when you look at things like deep minds convolutional neural network and the capabilities for image processing that that enabled Are you look at the announcement of Bert? These two key technologies then and enable things such as chat GPT and other services And so you can see that over the past decade or so there's been a for trajectory in terms of how we can get to where We are today and to the you know services We know such as chat GPT I think that that's been really the first exposure the public has had However, many papers have been published and I think there's been incremental process progress Especially moving over to GPUs as it's for to train and to serve so I think what I wanted to sort of Reflect upon here is that we can see that there's some really interesting opportunities of genitive AI You know, it's great at being able to produce images and text and sound It's even better yet at looking at patterns and recognizing trends within those patterns and we can perform some prediction I mean people from the ML world. This isn't new, you know You have a dimension with features you perform a linear regression on it or you'll run out some other format of regression And you can start to build out fairly accurate models But I think what's interesting is when you apply technology such as transformers You're suddenly Decreasing the amount of time taken to train you can reuse models rather than to start from scratch And you're also starting to enable people to play around with hyper tuning and waiting I won't go too much into that side of the house today Other than to say that all of this sort of came out about the time I was working heavily in Kubernetes and I was experiencing exactly these kind of problems Looking at patterns that you find in Kubernetes debugging in failure modes looking at how to translate those complex error logs event logs and Figuring out ways to then predict if there'd be a future failure so it felt like there was a natural synergy between some of the capabilities and Superpowers of generative AI and some of the things I was looking for So I want to talk a little bit about the esotericism of Kubernetes. It's a bit of a mouthful that Effectively Kate's is a really interesting system because it's more than just a substrate these days And this is my little haiku that chat GPT wrote for me earlier on and I thought that was kind of an act an at Observation, you know fixing is certainly very rare for me anecdotally, I remember working in American Express and We had h.a. proxy failures and we were dropping packets and we Narrowed it down to several nodes and it turned out to be that there's a soft IRQ reset That was being caused by various contract issues and what was funny about that It was really nothing to do with Kubernetes But when you're starting at that viewpoint and that's your optic It's very difficult to see what's actually wrong And just in this little illustration here, you know the signal-to-noise ratio I think we often see is very skewed because you're looking at the the the yaml You're looking at the logs You then got your observability on top and then you might even have something coming out at the the Linux kernel Dmessage level so there's a lot of different places. We're expected to look and there's a couple of Second-order problems there the people who know how to do this stuff crystallize that knowledge in their head and get really good at it And they accrete that knowledge and over time they get more valuable But the delta between their knowledge and a junior becomes even larger and this chasm Is almost insurmountable because you have 20 years of sysadmin knowledge On top of the case knowledge that you're applying to the problem So that was one of the areas that was that was really difficult to surmount Also a lot of case issues. I would probably wage a 90 odd percent of case issues are effectively Linux issues issues I used to work economical, you know, who built the Ubuntu operating system and Many times I'd find I'm looking at Ubuntu rather than actually looking at kates. For example, you know U limits any kind of system ctl configuration Even ip table rules could often be a problem as well as system b itself I just love this gift. So I thought I'd put it in there But but effectively what I'm trying to take Emphasize here is that kates debugging is getting harder and harder, especially with virtualization, right? When you have a hypervisor layer on top, we're talking about things like gpu acceleration And there's a lot of intrinsic knowledge there. For example, if you're using kuda mig vgpu Even if you're doing network accelerator Acceleration as well on a smartnik as an enormous amount of context you need to have to debug that particular problem So here's here's sort of where we are in terms of what I think are the really big challenges that kates debugging That top one the amorphous end dimensional layers effectively means the complexity of kubernetes is not linear Because every time something wax something on top it comes with its own state of the world So for example, whether you're using backstage argo, whether you're using an operator They're all at odds with the modus operandi for kates You're now adding a new set of things that could break a new set of things that can break in new interesting ways with their own dependencies You've also got tacit knowledge formed, right? So you've got this idea that Only people who have actually worked through this before can solve it Because this requires Critical thinking that's not linear. You need to make a jump to be able to say, ah, okay I understand that problem because I've seen it before so that that's an inherent challenge When you're trying to troubleshoot kates and then in the last one just to touch upon that again That's signal to noise ratio as we start to move to all this world of managing 2030 clusters with several hundred namespaces with several thousand pods the signal to noise ratio is incredible If even if you have an observability vendor, you're drinking from the fire hose looking at events You're purely relying on alarms to to help you to debug before you then have to jump in to look at the The analysis of metrics and whatnot So it's challenging So this is where I kind of was inspired, you know I was really keen to take back the power in terms of it's getting out of hand This isn't this is my really poor attempt at building gifts here And what I thought was interesting was look we have an opportunity here There are a bunch of apis that are becoming available. How can we leverage those to solve some of these problems? So if you don't know kates gpt and I assume most people probably don't I'm just going to run you through it very quickly, right? So effectively what it enables you to do is to intelligently aggregate different types of signal and to return responses on those signals It has a bunch of different analysis capabilities that are built into it And it runs as both a cli and an operator So you could run it in your cicd pipeline as a as a cli or you could run it continuously as an operator It produces either crds or jason or whatever you like really to spit out the reports You can also see there it can categorize cvs based on their priority So in the beginning when I thought about this, this was probably last april prior to the kubecon then I was trying to figure out what should it integrate with I I was familiar with hugging face And I played with some of the generators, but I I'm not an ai ml experts. You might have Might have gleaned So I looked to open ai because they had a public api and I felt right but let's start there So we built an inference api the two of us at this point in time I'd roped a friend into to helping me And we had some really cool results. So we had a pod analyzer We could scan the state of pods We could compress down the events and create a context window with some relevant prompt data Soon after we atore a colleague and friend from spectro cloud Built out local ai which was a c++ wrapper for inference And this was really interesting because he was able to go off and build Interesting projects of ktpt and local ai and that created a natural community One that I wasn't really aware of at the time, but I kind of looked at it and moved on After this came an azure integration that was committed by the community That's not such a big deal because the azure integration was effectively the open ai api but hosted by azure After that we got a cohere integration and that was really cool because I think this is about june time We were working with several key contributors We were having a great time building up functionality And this was an inflection point where we started to see people outside of our immediate community want to contribute a back end After that came bedrock And today comes sage maker So all of these things now integrate in a first party way with ktpt And this is pretty cool because the project only got built about five months ago So how does it actually work? I've explained it. I've kind of bigged it up and I make it sound very grandiose And I saw this picture on twitter the day and I thought it's kind of funny This is just a remark towards what open ai has now said they're going to do to companies that are building on top of their platform So it's not a gpt wrapper, right? It doesn't run in a window in electron and and just call open ai The way it actually works is there are a set of analyzers I think there are 13 or 15 in total now. It's all based in golang It's all publicly available. These analyzers are just codified sre knowledge. There's nothing magical behind it I actually wrote part of this code when I was still a practicing sre trying to train up my team This is unit testable as well because you can mock out the kubernetes api You can see here that we're simply looking to see an ingress class as it exists This is packaged in a fairly neat way. This isn't particularly full of context But what I'm trying to emphasize here is that there's no magic behind it The magic happens when you actually pass the correct type of context and explain to the Inference api that what you actually want back isn't isn't kind of a guess But just to repackage the english or the language that you choose So that the user can understand it in a more meaningful way And I think that's an important differentiation from what a lot of people are doing with generative ai I think they're asking it to guess on things that it doesn't necessarily hold subject matter expertise on But what it is very good at is linguistics. You know, it's built on nlp So if we've got a complex error message, let's leverage that to make it a bit simpler Again, you can see that this is part of the cohere client There's no magic here other than we're sending these things off and returning back a simplified version of the message So probably that takes away a little bit of the magic there, but let's see what It actually looks like under the hood Effectively you have an analyzer. I picked the pod analyzer right here That pod analyzer interacts with the api server either directly through proxy And it has a few other modes as well Effectively what it does is it picks up different events of various types It looks at pod statuses pod health and then it will bundle those into a set of pre-analysis results The pre-analysis results will then go through the api provider parser So that it can then effectively build out what we call A sort of a result analysis and that enriches those results and comes back again What's interesting as well is that we've built this capability so that you can now start to Cache those results based on a key so that different api providers might give you back different results And you can see all of those different types of results Whether it's bedrock, whether it's cohere open ai You can start to build a broader opinion on what the best way to triage a problem is And so this very quick ability to switch between ai providers is a superpower in itself I also mentioned that we have a kate stupity deployment Again, you just deploy this into your local cluster or remote cluster and it provides you Custom resources so you can see here the operator will be running continuously And it produces these custom resource definitions So custom resources rather and you can then link those into your pipeline They show up in our go cd, which is quite cool as well So you can see the relationship between kate stupity and the custom resources And they can hold anything from errors to cvs to any other findings that it picks up in the cluster What we're seeing now is that people are starting to use kate stupity in an even more unknown way Bit of a bit of reverberation. I apologize We're starting to see it used in an even more unknown way and that is starting to use it in active training Where you combine two clusters together typically using cube flow Where lang chain will be feeding in hyper parameter tuning and then serving back into the kate stupity deployment This was originally done using local ai But having now brought this to cube flow was seeing that those workflows are starting to now Give us the capability to do fine tuning on top of the existing model being used in the cluster I'll talk a bit more about this later on because it's quite interesting to actually think about what type of models are supported locally And I think what's also interesting about that is you're starting to answer some of these ethical questions that will come up about in a moment So if you're interested in the project, I just wanted to call out some sort of key metrics here We have three different production use cases actively on at the moment We have a community of over 30 key contributors And we've I think were something like as I say 13 to 15 analyzers with over five different back end providers So check it out. See what you think and as I say we're moving towards a model of trying to toe the line And delicately walk between security privacy, but usefulness and application So let's go to a demo and actually see what it's all about Okay, so here's my screen. I'm just going to show you very quickly What my Kubernetes cluster is running? I've got 36 or so pods. I have a bunch of different Arbitrary programs that I've written. I've got some stuff that might look familiar as well Your first experience of kHGPT is probably going to be looking at the orth list Which gives you a kind of view on what are the local providers that you can use Secondarily to that you might want to see what kind of filters Are available oops So here you can see all the different types of resource that we scan at the moment and can make insights on This is kind of interesting as well because we have an integration with Tools like trivy that can bring their own custom resource definitions into the into the cluster, but also into the scan analysis So let's go ahead and just have a look and analyze without any kind of AI enrichment This was really key for me was that you should be able to get value out of this Even if you aren't connecting it to the AI back ends So what this is effectively doing is aggregating and simplifying pretty well known problems in this cluster When you apply the dash e command It will actually package these up. It was pretty quick there because I've cached some of this these responses So you can see we're immediately giving Some some ideas towards how do you simplify this? How do you then? Go about debugging and triaging it now I'll come on to some of the fall the fallacies and some of the shortcomings later on But immediately one of the things that this is Exciting for is because if you're not a systems Admin or you're not an expert and you've only been doing this a few years This immediately gives you a window or at least a path to try and follow to debug And so we're finding that a lot of the users of this tool people who are learning kubernetes for the first time And they kind of have this side by side, right? They literally they install kind They're doing a ksgbt analyzed. They're they're building their vs code Deployment putting it out there and they're running it kind of in that in that flywheel. So that's quite cool to see So so what we can then do is we can start to think about taking You know processing it in different ways we can put it into jason, but I think what would be quite cool For this group to look at is if we actually look at one of the error messages in particular you can see that We've got things such as container back off and Immediately because we're passing a very well-defined Window of context This is a pod that actually exists in the cluster and we can go have a look at what's going on So again, if I go to look at my foo, we can see that again It gave me the correct name in that pod and we can go off and see what's going on Equally if we want to do some security scanning, we can go integration list. We can turn on something like the trivia integration Now you've got a couple options here. This can either go fetch trivy and install it into the cluster Or you can use an existing integration We're also planning to build out a pre-prometheus integration and the interfaces are pretty simple as well What's interesting about this is that what you'll see also happens is in my filter list I now get this new vulnerability report integration That's an analyzer that gets pulled in by the integration and it knows how to categorize cvEs based on What that what their priority is in terms of their severity This is just an example of where you can start to bring additional functionality into the tooling We start to think about other things as well like having web service specific integrations So if you're running on azure or if you're running on eks, you could see some some specific stuff to that platform I'll just end this by showing you when we actually go back to the cluster And we can see that some scans have been run. Let's go and see if we get any difference in our analysis. So I just do another Analyze command It's always good when it's live because you never know how long it's going to take um at this point in time you can see that we've got Some configuration issues being found and we can see the severity as medium and so Even though this is fairly raw We're starting to be able to reduce that signal to noise for the user And hopefully as we evolve this as a as a project It we're going to improve the relevancy and make it so that there's a bit of a gilded path to fix things for people as they go along So I want to just recap there on how is this actually useful and what's what's what's the the the thing that I think is like the usp here So firstly it's faster debugging times right you as a as an sre as a sysadmin Whatever you might be you can debug quickly and you can solve those issues by looking at stuff that's come up before and seeing it codified Codifying that knowledge is a really integral part of it because you can add your own analyzers as well People can contribute those from the community saying hey you missed an analyzer for persistent volume claims where they're unattached And we see it all the time. It's a waste of time so people can contribute that and they have Also a consistency of diagnostics So actually having a repetitive process that can be tried several times in a row makes it Far easier to get to the root cause if you're analyzing it in the same way each time And finally lowering the bar for operators making it a little bit easier to be effective as I said sysadmins And other operators with a lot of experience that might be great, but for people who are just learning this stuff It's a really helpful thing to have So you might be asking yourself, you know, why about why don't you what about scanning logs? What about metrics? What about all of these other pieces of the puzzle that we haven't described yet in kubernetes? Well, that's where you get to this sort of ethical dilemma of What should I do to increase value and usefulness versus what's going to open up a lot of existential problems? these are some of the These are some of the key issues we see on github that come up time and time again, you know Due diligence around provenance of model data Accountability who owns my information is another good one as well as how can we make sure that things isn't aren't poisoned? If you if you were to try and summarize that I think a lot of it comes around So it's you know tiptoes around security privacy and perhaps ownership So I want to go back and look at one of the one of the integrations because this was sort of our immediate answer to it And you know kudos to the project. This is another open source project on github and What's really great is that it supports a bunch of different models, right? Whether it's gtp4, whether it's uh, you know lama What's nice about local ai is that this was our immediate solution to say ha well if you don't want to run your code through Through through open ai try this and so that's what we recommended This was the initial kind of architecture for that We had people who would run a local ai deployment in the cluster They would then serve Through this endpoint here and the khtpt deployment would pick it up and we had some pretty good success early on of course As you might know serving that endpoint is kind of heavy Especially in a small you know edge cluster or something that doesn't have a lot of oomph behind it equally and the storage layer Having these models locally isn't for everyone. So I wanted to make sure there was another solution that was Adequate that kind of overcame some of these hurdles Just about the same time titan came out and titan Is basically a catalog of high quality Foundation on models What's really interesting about titan is that it's starting to put filters in front of the models So that you can it has this thing called just ar responsibility so that There are certain things that won't return to you in a certain data It will scrub and this is appealing to some companies and individuals because they can control the kind of things That the model is likely to respond with and finally it has fine tuning built in And that was something that I think we'd been missing early on in these in this interaction with open ai I'd always felt somewhat frustrated the only variable I could change was the temperature or the top k So With that sort of in mind we we came back to the community and said look we've got open air We've got open ai we've got local ai and there's still a lot of people who are really curious about well How can we actually start to anonymize our data? How can we start to? Tokenize that data so that it's not so obvious what bank I work out or what what's a particular application I have In response we added anonymity into the api And so you'll see just from this little code snippet There's a a masking process that allows you to tokenize your Your prompts and the responses that come back and then it Unabufuscates them and prints them so that you can then Act on them with the knowledge that there's not been too much data leakage there It's not a perfect system mind you, but it certainly moves closer towards that ask I just wanted to post this Last slide with a few different statements there because These things might look a bit unfamiliar if you've not worked in ai ml, but You know, this is the one I think many of us have seen right and this effectively temperature Is a control on how creative the responses from the model are and so again one of our advice Pieces the community was to modify The the sample size and the temperature of your model But again, we were learning what the community were looking for and many people who started using ksgbt in the early days Was saying that open ai had a lot of hallucinations on particular types of analyzers If you think about it the corpus of data inside of open ai is about three years out of date So gateway api for example wouldn't be in there if you wrote an analyzer And this is where you'd have to start thinking about customer training or to have a model that was slightly more up to date So i'm trying to illustrate again that it wasn't that we had all the answers Is that we were we were attempting to rally around some pretty existential issues that were starting to crop up quite quickly in the project When we look at the project as a whole and where we're taking it There are things that we haven't solved and i'll be very clear about that right I'm not entirely sure Who is accountable for auto remediation If there's a failure or if there's a some sort of data breach of vulnerability Obviously, it sounds like the person who installed it on the cluster But then is it somebody who is responsible for the model catalog? Is it the operator that enabled it? We also look at things like should we be going more down the route of tasks specific ai rather than llms lms are appealing to us because we can get them off the shelf from You know places like hugging face But really we're going to have to rely on the quality of training and data And I think that's something that's going to hinder us quite honestly So I took this it took this to heart and this is also one of the reasons behind why we have so many other back-end providers Titan is one example But there are other companies like and fropic with claude who are trying to also solve this by building high quality a api So ai one of the criticisms you often see on the news is that a lot of these lms were trained on public information That not doesn't necessarily have the right to to draw upon And so I think many companies are now reevaluating that mind you it does cost a lot of money and take a long time So there's some big questions that are still open This kind of is where I wanted to get to in the last few minutes is that we're entering this period of time where We don't really have the answers for everything. I think that this was summarized quite well I was looking at the unesco website around ai ethics just before this talk and I thought that gabriella really succinctly kind of Put the world's rights in this in this passage here But this bit I thought was pretty scary is that the world is set to change pace not seen since the deployment of printing press I think that from everything I've taken away here at kubecom We're focusing very much on the initial feedback loop of ai models of inference as I said at the start of this talk There are already projects Such as lang chain such as a gpt agent that are looking at modifying the output of prompts You're going to get several layers of recursion that are occurring and at that point the abstraction layer becomes so complex It's very difficult for humans to intervene And so I'm trying to be very Thoughtful about what we do and don't decide to do with case gpt One of the early suggestions and options was that we could actually enable auto remediation in the cluster It's not that difficult to do because several of the major inference apis take functions As a prompt and can return to you the the output of those functions So there is a way to programmatically get there, but should we do a thing that's up for debate So I think what we really need to do as a collective is to come together to bridge the gap between the ai ml data scientist world and folks in the ai and data lf foundation and the cloud native computing foundation And all the projects that are within we have a great amount of opportunity Specifically with kubernetes to proliferate these projects very very quickly But back to that pandora's box photograph at the beginning sorry illustration at the beginning of the talk I think that once we do that it's going to be almost Impossible to pull it back in you know You think about something there are helm charts that you can install an operator with an lm packaged into it I was just in a conversation yesterday About actually making lm's into oci artefacts that gets you to the point where you can't Control the distribution anymore because they'll be in the wild So trying to counter this kind of gap of I guess I guess thought leadership and trying to bring people together I proposed This tag a while ago, and I'm really happy to say that there's been some amazing people who have stepped up and Helped us to build this into a into a working group. And this is a call for action here That we're spinning up a working group for artificial intelligence, and that's our slack sorry my My search light they didn't go very well And I would really invite you to come and share your thoughts You might be far more knowledgeable than myself on the subject. You might just be starting out but in every walk of life within the Underlying substrate of technology you'll find that your influence store at least can have some thoughts on the subject I also wanted to just share that we ran the first a i hub meeting yesterday in Conference, and there were some great sessions. You can see probably maybe not at the back But people were asking questions about how do you autoscale lm's on kates? How do you build ai for products? How do you train across different geographic locations? There are more questions than there are answers at this point in time And so I think what would be really powerful is that we can come together as a community to answer some of those In terms of the future, what do I see it holding for the kates tpt project? Well, I'm going to try and answer some of those ethical questions But I think one of the speakers in the keynotes this morning quoted Solomon hikes with regards to You know no is temporary and yes is forever It's very much the case the case with kates tpt is that I want to take it slowly and make sure we're thoughtful and provide value If all the ai back ends were turned off tomorrow the project still needs to have value So what I want to do is to Try and get this accepted into the cnc of sandbox because I'm not a company I can't maintain it on my own right and so What's great about this process as you may or may not know Is that you get access to a lot of contributors maintainers and community But it also sets the bar. I have to prove that it's an active project And so we've been trying to work towards this over the past few Months and I'm happy to say we're getting really close to that. I feel and the ai working group will be Certainly part of that process But aside from that I couldn't not scratch the itch Of trying to do full auto remediation by closing the loop And so I started a project recently which has started to yield some pretty exciting results This project is effectively only for aws Because I needed a model that didn't hallucinate at least to the level where I couldn't Or I could rely on What this project is starting to show is that if you connect the model To something like adb sdk and you can rely on the data source inside the model and you start to apply those changes You can create a full feedback loop And so what we're seeing is that This is potentially going to be the future direction Of a lot of DevOps tooling where we're starting to trust the outputs if we can trust the inputs to the model Isotope is very much in its alpha phase. I would invite you to Come and take a look at it I was a little bit obsessed with starship troopers when I was making this I apologize But it please there's a qr code. The the code is all in rust. It's it's pretty pretty quick It's pretty straightforward But what we're seeing already is as I said, this is yielding some interesting outcomes For example, when you have a public s3 bucket you run this it makes it private when you have An s and s q that's failed you run this it fixes the q it's scary where it's going to right? And so I think that's also where this idea of thoughtfulness And making sure that we're thinking Long and hard about the capabilities we're introducing is important So that said I wanted to thank you for your time and your patience And I would invite you to think about artificial turnips inside the cncf and bringing communities together If you have any questions, please let me know and get involved in the projects. Thank you


Hello everyone, I just I want to say good morning because it's morning here I see there's people from literally all over the world, so it's not morning everywhere, but good morning from me Good day to you whatever time of day it is. I'm Brian here.  We're live on YouTube. We're live on Minerva's Facebook So there are plenty of ways for you to watch us By us, I mean me and this mannequin and of course Matt back over here Who's gonna be watching in the chat to make sure that everybody is behaving? Wow? That's what's up. I like that. Oh That's cute though. Now. It's like I can hug you Social distance in the bubble. Yes. What's up guys? Welcome if you guys have questions posted in the chat type q put in your question If you have a question for Brian, I'll see it in the chat I'll put it up there and he will answer it for you guys have fun join in the chat if you're new type New if you're og if you've been watching this for a long time. Thank you for for being there for us Make sure in the chat if somebody asks where you get the tools or what our website is or what our app is as an Og it is your responsibility on these lives to just add a link tell them where to go Keep everybody informed because we can't always answer everybody in that way But if you have questions about the technique type q put in your question and we're gonna have some fun Yeah, yeah, so much fun. I really want to answer as much as possible and I gotta tell you I Get like so much satisfaction seeing where everybody's from. It's so much fun Like please I want to come on. Tell me where you're at. It's cute. It's cool. I like seeing oh so far away You're oh, it's so early. Thank you Okay, so today we actually have a lot that we're gonna do in today's class So I'm going to try to talk and work at the same time. This will be a first. So let's see The look that I went with it's so funny So I send map my little descriptions of what the class is gonna be and then just like the the hopes in my my heart of Hearts of what I would call it if that's how things work. So today I named our class What was it Rudy Tutti blonde and Rudy? Yeah, it's a it harkens back to my first job as a waiter at I hop for three and a half years. I used to make the big truckers say that they couldn't just say I want the Rudy thing it'd be like no say the full thing and they would wait Where did you work at this one at I hop? I didn't get fired from I did once but like it wasn't a real firing It was like Brian you're in trouble. I'm like, yeah, yeah, just give me the right up slip It's fine. I was 16 and they wanted me to work on Christmas. I'm like come on I'm too young to be missing holidays with my family. Okay, so I like kind of got fired from that So the look today is when somebody wants a nice like it's it's a good look It's great for this time of year. We're leading into spring. We're coming off of people Typically having slightly darker hair. They chose darker tones. So it's a fun way to sort of update it Not really like completely mess up what you've been doing with your guests But give them something kind of fresh and new and cute and cool and just really fun-looking so it is dictated by it's a dimensional look that is going to have more depth at the roots and Lighter through the ends while still having real nice pops of dimension and we're going to do that with foil work and Through what we do with the toning. So today there's going to be two noodles One lasagna. So this is our lasagna for the day. Notice how pretty she is There's a little bit I'm sure the camera is picking up this dimension that we have through here as you'll see while I'm actually putting the the foils in There is the strong money piece up front because that's my jam and then there's going to be some decent depth throughout the The roots all over the head not just on top and then later on the ends Which is going to be nice and easy to achieve because most people have lighter ends anyway All right, so I'm going to jump right in I'm going to take this beautiful lasagna away for a little bit From Virginia. Hello, Virginia Hello, Virginia Virginia's Virginia's for lovers. So you got to say it like that. Oh, okay all sultry and Ohio is for lovers No, I don't know what Ohio's for but it's not for lovers. What's Ohio for oh Panama City, Florida used to live there I Did get fired from a job in Panama City Beach Very nice restaurant I had a very nasty manager. I sort of voluntarily got fired to prove that he was a jerk All right, so for our highlights today, I am going with my fave right now Sinker lift Paul Mitchell lots of lift without prashing the hair Which is always a bonus because you know we want everyone's hair to look good, but also feel good I'm not measuring Because It just don't do that. I'm sorry. I'm a consistency measure With lightener with light yeah, oh, what's funny? Yeah, it is just lightener because with color You should see some of the formulas that I have in there. They're so unnecessarily precise I guarantee that point one ounce does not make a big enough difference for me to be that anal about it But I am but when it comes to lightener I go consistency I like it firm enough to sit in there nice I don't like my lightener too running Because I typically move foils around a lot and I feel like if they're too running Then you just run the risk of things going places. You didn't want them to Okay, so for my sectioning I went with the sectioning that I've been using Where I start with wherever their part is this one was slightly off-center and I take a panel through the top that has the part inside of it somewhere It doesn't have to be directly in the middle But it just needs to be in this top panel and then I drew a line in the side panels from behind the ear To the back of said panel forming a nice little triangle that gives me something easy and clean to work with and Then I just split what was left over in all of the back in half. I was explaining to Matt I actually really like this section because so often there's so many color techniques that leave out way too much of the back and This sort of forces you to address it because it does travel so high up that at least it's some Juncture you need to come back here to have a complete look.  I'm not going to do a complete look today I'm only going to do half of the head. So do as I say not as I do All right, so we're gonna be working with a variation of weaves and slices because we're going to be again This is up to your discretion. Whatever your guest is going to want the best but Because we're going to be going over with a darker demi for the root I am going to actually be doing slices throughout like down the part places that you'll see it So Yeah, I'm good to start. I'm gonna start right on this hairline my favorite little My favorite bit. I like to start in the money Because that's where I want the hair the brightest if you are worried about this taking you too long and That you're worried about that over processing then you can either lower your developer or Start elsewhere. I'm just telling you for this This is where I would like to start on that front hairline I like to do a Small little my little version of a little baby light Because I feel like when you do baby lights on the hairline you can do back-to-back baby light weaves and Achieve a really nice We need to come out a little more Lock it in lock it in whoa hi from Greece. Hello, Maria Mama Mia hi Maria I'm not proud of that You do know it's just as easy to get here from Greece as it is from like Philadelphia on the internet. Yeah, but it's still cool Because it's what she didn't have to travel any further than Brian Langston from Alabama Gulf Coast That's where I went to high school. Is it really? Yeah with him. I don't know about with him I think I was the only Brian in my height. No, there was one other Brian and it wasn't Brian Langston, but Alabama Gulf Coast I went to Daphne High School Got fired from the I hop in Spanish And then lived in Mobile where I was fired from many jobs That's so funny until this show I never really realized how often I was fired in the past My mom still gets credit for being the first person that ever fired me She's really proud of that one All right, little baby waves Tell that story another day Again just back to back get in there with my 10 volume. I'm using 10 volume again because it's a mannequin I leave that up to your discretion, but I know people always want to ask I Don't need to make this Crazy crazy bright because she's just my little mannequin. So that's why I'm going with the 10 cool, I like to lock it in again because I Am somebody I typically move My foils a bunch so I like to keep them locked just so that they don't slip too much a Loja from Hawaii. I love that. I've wanted to say Aloha so bad But because my yoga guy that I take his classes He starts every class with Aloha and it makes me just want to say Aloha back But having no ties to Hawaii. I feel like that is certainly cultural appropriation So when you say Aloha to me, I can say it back. So thank you so Kel's got a question about I think she was the one talking about these the vet I don't know how you say those combs, but Do you think they will cut down your time or maybe Too good to be true tools. Oh the highlighting. Yeah, I know I got one of mine I have another one being sent so I can try them out. They do look a little different Yeah, I I do think that there may be something to it It's different. I mean the only thing that it does throw off a little bit is that there's no it takes away Your ability to change the size of the weave so much You know what does that make sense? Yeah, like yeah, there's different combs, but it's a I mean, it's a tool It's a uniform tool. So Well, we'll we'll get back to you. Let me play some more Alright, so I did my few foils up front to give me my back-to-back baby lights money piece right there So we're good to go. So I'm gonna take a little skip Leave that darker because I know the ends are light So it's not going to be a huge chunk of dark, but it's gonna add a little bit of depth behind my highlight So that it'll make those you need that dark behind it to make the brightness pop. So Cool cool cool. All right, so Gina is asking about the foils. I think they're from our right now What they say? Yep from our from our from our I Really wish that foils did not cost as much as they do Like I just went to go pick some up because they were pretty the other day and then I'm like what no too expensive Yeah, but even the not pretty ones are expensive I know can someone own like an aluminum farm, please and just sell cheap foils to hairdressers and The lightener he's using is synchro lift by Paul Mitchell. Yep. Synchro lift plus, right? Plus yeah, it's a plus now. Yeah jumping on that bandwagon. What's up? That means it's plus ear plus ear I Like it because it's clean. I get hella lift and it leaves the hair in great shape So again down the part just doing a nice little slice here again Not worried about it being too stripey on the part because I am going to be going in with a dark Demi to create my rooted look and then by the time that fades This will have grown out enough that it's not going to look like a stripe on the part If you are choosing to go with a rooted look, but you want a lighter Demi at the base. I'm going with a six so it's going to be decently deep But if you are choosing to go with something later like a seven eight or nine Then you might want to take into account. What's going to show? You might want to switch this to doing some weaves or doing some teased highlights That's where I want you to take think about Begin with the end in mind think about the end result what you want it to look like and what you're doing is going to look like Yeah, I'm just thinking watching this like how you could you could do that teasing at the root and just do more and more as You work your way back. Yeah, absolutely Because that's how we did in that first video and is that what that Rihanna We did tease highlights along the part Gotcha Candace new gal from Georgia. Hi Got me all distracted almost did back-to-back Lonnie from Georgia to Another Georgia, Georgia's in the house And then Darina from Brussels, don't forget All right Somebody in the chat on YouTube if you want to catch up Ashley up. She's late, but we can help her out What's up? You want to explain to her not you Brian? Oh, but Anybody in the chat just a couple things that we did if you want to type that in on the front We'll catch you up Ashley. Don't you worry, but not me Not Brian. I mean you kind of already talked about it Somebody will write it in there. There wasn't too many steps.   I want to see tag me when you do one of these please tag me I want to see your interpretation of this because I know what my interpretation looks like I look at it every day But I want to see yours So now we're going to work in the side panel. This is where I typically like to work Lock in I like to work Off of the the hairline so my foils will get a little bit a little small I can turn them if they need to to get more coverage if that's what you're looking for But for this is going to be just fine I am going to do that nice fine baby light By the way Matt as your cameraman over the years if I start to go bald I need you to tell me when you zoom in because I don't see that part of my head Yeah, I think you're doing okay. Okay good But I trust you me on the other hand not so much well It's the camera that tells us so I know you got to let me know and I think you're doing fine I'm doing fine, but not like but fine is like super duper fine Yeah All right, so again, just like the money piece although I don't do as many when I do the sides Like I typically only do like one or two because I'm not looking for Money pieces in the temples I just want to make sure that it's bright enough on the hairline so that when the hair goes back Which most the time it's going to these days It's still gonna show so now I'll give that little bit up front and then I'll take a little skip I Might actually change my angle a little bit just because this is Longer hair so I want to hit a highlight that's going to fall forward into Like I know because I did this haircut It's like kind of a face frame through these front sections So I'm gonna make sure that my panel of highlight mirrors that so when this falls forward and kicks out or does whatever fanciness I'm gonna make it do it's really standing out as much as it can cool Right oh Glasgow Scotland I had a friend from Glasgow when I lived in Alabama actually I gotta be honest your ability to read the chat and foil at The same time is impressive Like I do this all the time or something It's better than my ability to guess how much lightener. I'm gonna need Tell you that Almost there someone was like your saturation was great. Well, not so much anymore cuz I've totally run out Yeah, so just pretend like that is beautiful saturation in there I'm gonna mix up a little more and we're gonna chat. Yep. Let's do some questions. Yeah, it's time for questions Dorka from Pennsylvania Cool same Let me see if I can find any cues here you guys have questions type cue put in your question Oh, there we go. I've never placed foil sideways. Yeah get in there You got to be able to do it at any angle like an astronaut. Is that what they do? Yeah Astronauts are doing highlights in space. Yeah at any angle at all angles. No question. I ought to talk about those combs though Yeah, we'll see I might love them. I Might just think that it's a bad. What clips are you using my clips are Are They shark. I think they're called shark. They're way as far as park. Yeah. Yeah, why as park shark clips? I like them But they're not all the time clips they're great for holding a bunch of hair really firm They're not great when it comes to holding foils because they will bite through a foil like just mm-hmm, but You know, you just learned how to Learn how to navigate that and adapt And you'll be just fine somebody else from Georgia Dana beautiful hair If that's you If that is in fact you Dana if that's really your name Okay back in action. Why are you not using a scale? We did kind of talk about this, but I'm not using a scale because when it comes to lightener. I really just go on consistency Also because it is my mannequin head The precision of it is a little bit sacrificed But I I use a scale to the point one ounce when it comes to my color But when it comes to my lightener I go more on feeling consistency just because I like I've worked with a lot of different lighteners and that seems to be a pretty common thing throughout a Lot of brands like they have the recommended Measurement for lightener, but it's just recommended It's not because they do understand that a lot of people like consistency now There are certain lighteners that you mix too much developer and they swell or you know Yeah, you have issues, but we don't have issues right if you whatever your salon uses Get used to however you're supposed to do it some salons want you to measure that out to the tee like I Know people that are like yeah in my salon They actually are really strict about measuring lightener. Okay, then do it. Don't get in trouble because of me I get myself in trouble enough. I don't need other people getting it, but Yeah, it's a lot of words for a very simple answer All right, uh Low maintenance highlights is there such a thing Yeah, I mean there's 100% there's Low maintenance Balayage, that's like I don't feel like it can get any more low maintenance than Balayage But then when it comes to foil work Yeah, this is gonna be pretty low maintenance because like I said this is going to Soften your the harsh line that foils can leave you When we do the the next step the Deming So it's going to make it like I said by the time the Demi wears off the hair will have grown a little bit So it's not going to have too harsh of a line at the root Which is going to make it less obnoxious for your guests and therefore more low maintenance for both of you So good question why 10 volume on dark brunette? I'm only using 10 volume just because it's a mannequin I If it was a person and I was looking for max lift I typically foil my people with 20 volume Just because it's nice. It's predictable. It works for a long time without overworking But again, it's just 10 volume for the mannequin because I would like to use her again in the future the other thing is It's really important guys not to over lift So like 10 volume a lot of times can take you where you need to go and we're aiming for like What the Demi would you use like six and ten?   Let's just do a little pop springs right around the corner. It was really warm here yesterday. Yeah, so I pretend like it's spring and I just did ten volume on her because I knew it was going to lift enough and it was going to sit that long Like I was doing a root touch-up. So you got to take into account how long that's going to be sitting So I'm looking at at least a half hour So ten volume was just fine because it got her nice and bright without Blowing her hair apart cool All right, so we're just gonna move into the back section because while I was talking I did the other side and you missed it Sorry. All right. So now I will have my guest Because I again I like to work with the client's hairline So that when their hair is pulled up it always looks nice because That is the reality people's hair goes up a lot Get a little weave. Okay. Well, baby Get in there There's a question about how long to keep it on after you complete Color, so I mean it's ready. Yeah, I mean I I'm one of those people. I firmly believe I don't think that there's a Set Thing when it comes to blonding like there is no you need this many foils You need it to process this long and you're always going to tone with this. I really do think that Every single person and every single case is to be treated differently. I babysit all my blondes some people a balayage will process in 15 minutes Some people foils are gonna take 45 like you I know that it's not the easiest for Poor Janet answer in our phones to know how I want to book my color But she is completely understanding and that It is really different for different people New clients and booked the max amount of time so I can figure out what that is and then I make notes as needed Like hey, don't worry about it. You can do a full head of balayage and process in an hour and a half for this person That's awesome. All right, so we just keep traveling up doing full slices still because Of the smudged root that we're gonna do Get in there Lock it in. All right, I'll do one more just because I'm and I'm gonna have it touch that side panel Because then it marries everything together see what it did there see what it did. It sounds like a little brickly Okay, that part's good and then while I'm folding this foil. I will miraculously do the other side too boom Done Done if I weren't shadow rooting with the slices still blend from Emma Not entirely. I mean they are slices So they're made to stand out. That's the the point of them like when you want a bolder Panel of color to run through the hair. That's when you're gonna do a slice so No But because of how I'm putting them. Yes, it'll work into the hair. It'll look good It just might not absolutely like blend because I'm again doing a strong highlight on A darker base like this That good makes sense Cool makes sense to me. That's my whole thing if it makes sense to matt we're good Like he gets it. I'll ask him the the cutting questions And if I can make sense if he can understand me anyone can Adele Guess what what we're gonna show you the toner. Oh my goodness. Wait, but it's so many questions there Yeah, look at the bottom tv on Oh, what toner do you use? All right, so it's so funny that you ask that so I do want to say something that means so much to me I had a teacher in Beauty school and it has stuck with me ever since I love Jess if she's ever if you ever watch this Jess This is because of you and she always said that she never respected the hairdressers that she worked with That knew what toner they were gonna use before they ever even checked a foil She said that's not that's not a good Blonde hairdresser like you shouldn't know what you're gonna tell them with until you know what you're working with You can have an idea of where you'd like to go But you shouldn't know what you're gonna slap on just everybody when they sit down.  I'm just saying In this class, I know what we're gonna use but in reality Know what you want to go with But then look at what you're working with to know what you need to use to get there cool Okay, so these noodles are done And she's nice and highlighted and we loved her. She was beautiful and did a fabulous job All right, ashley This is a big one. Yeah, let's talk because I have more stuff to mix. Okay. Does does mapping highlights?  I go with the flow typically Whatever question you just asked me the answer is go with the flow but um Yeah, I go I I try to focus on a general idea for the mapping Yeah, but like I I'll map out To say okay, this is what I want to achieve and then look at what I'm working on and change it accordingly so This so for this particular one I'm like, okay. I want to do this and that and there's the things but if I look and they've got Some root going already that's like pretty substantial Then I'm going to address that and maybe how I do my foils or what kinds of foils or where they go If I don't need tons and tons of dimension Because their highlights are only like six to eight weeks grown out Then I might do weaves instead of slices because I don't need extreme bands of color at the root Make sense Basically, I trust you to take a take a map and then cater at how you need All right, I'm just needed to make an entrance That's right Not like the front door is in line It's not Oh, well, that's why I told her to come through here. We locked her out Sorry, I'll get you back tomorrow. All right, so I'm doing Maroutte I didn't even walk I'm just pouring the lines So Here's my little There you go Make it look pretty I'll work Gorge So here's my darker route For the lasagna that you're seeing I got my hands on some of this great new Demi line from Paul Mitchell. It's their nb's Again, I'll we'll show you the the after when we get there, but uh, they're really really pretty because they sort of I'll show you but they showcase like a natural warmth without looking Too brassier. I notice most people translate when their hair is warm as my hair is red So it's not too red. It just gives that nice natural warmth to it Even at the level 10, which I was really happy to see Okay, so Now I've mapped out What we're going to do I took out my money piece because for that I'm not I'm just going unless you're going darker than their natural base is I'll just leave whatever their base is in between If you are choosing To really bring it down darker, then you might want to tap a little bit of the dark color at the root But if not, again, I leave that up to you So I've got my my depth And I'm just going to come in here and do this like a regular root retouch I want to turn it just a little Yes, I do There it is I have a feeling that this might also want to be just a half a head thing Unless you want to watch me do a full root retouch Yeah, I think it's fine I like working with the demi from Paul Mitchell, especially with my blondes Like mostly with my blondes because You get great tonality while still maintaining the dimension. It's perfect for a look like this because The work that you put in with your foil work Is still really going to show through It's like a really nice fast easy way To get a super dimensional look without You know months and months of visits Just for speed I always start at the bottom So I can hold everything in my left hand I like to go through and do pretend like you're doing like a gray coverage just for Consistency's sake Because you don't want to miss anything. This is a this is a look you're creating here So you got to be good. You got to get your coverage Got to go everywhere So I'll get my roots How are we doing on questions? I'm explaining everything so thoroughly that no one wonders anything Sandy sand, thank you for the ongoing education. You can always learn more. Thank you for what you do Oh, yeah, your soup's welcome. We love doing it. I'm glad there's people that are interested I always say There's people all over the world that love What we do as much as we do And so it means the world to be able to just Throw a little bit of inspiration your way so that you can just keep making people happy Maybe in a new way today try something new Try doing foils like an astronaut on the side Here's a question. Would you um, this isn't from anybody in the chat But would you put this on dry hair or wet hair? I You can do this on wet hair if it is a time crunch I would try to give it an extra few minutes maybe just because it's going to be working against the water in the hair um For the maximum pop and for like the most guaranteed Like you know what you're gonna get Dry hair is gonna be what's best. Yeah, be totally honest um But like I said if you're in a crunch and you have to work on wet hair Just try to give it an extra at least five minutes All right, so once I go through and get all my roots on I'd like to think of it is it's cool because that's going to sit A little bit longer, but at the roots is where you want it the deepest so that's totally okay Now i'm going to go through and try to cleanly work But i'm going to drag my color down into the mid shafts Trying to make sure you don't go too too far because I do want to create some blend With my higher level In through the ends Uh, let me just check in and carry says what level demi are you using? Uh, so I'm pretending that this is the level six That I'm doing uh for the the final look the final look is it was level six At the root and ten on the ends And this is something that people should take um Into consideration too like when you're toning hair Level six level seven level eight are all blonde tones. So we're always putting level tens on Hair but like we never even lifted it to a level ten So think about where you're actually trying to get the hair to and sometimes a level seven toner Can create a very beautiful blonde like he's doing a six level six root right now, but Um, and he's going to soften it with the ten on the ends But depending on how you lift people and how much tone you want to get You got to um take that into consideration as well. Yeah, again, this is The way that I do my classes are this is just a template. This is not the way to do it This is hopefully to inspire you and educate you To do what you think would make this look best You know, you may have somebody That's so light that you're doing an eight root or somebody that's darker and you want to do a four root into Seven ends, you know, like it's totally open to interpretation. That's what I'm saying I want you to translate this into something that works for you and then tag me in it just so I can see because I guarantee you guys are going to come up with some stuff that I didn't think of And I love that it's all about sharing caring all right So I'm not going to get rid of my bowl of six because I might need some to uh smush So now I'm just going to measure Very precisely Kim's asking when you were foiling, why did you start in the front? I always thought front developed quicker It does and I want that to be nice and bright Which is why I started up there because I was using a lower volume and The uh, I knew that it wasn't going to over process because Of how many I was doing like I said if you're not comfortable starting up at the front Then don't I just have done it enough that I knew it was going to be all right I thought I did such a good job prepping the brush I mean I can use this one We need him to blend Blending a better way. All right, so then when I do my blends Because you really got to saturate So I'll start right below where I stopped with the six And just load it on there because then I like to work it with my hands And that's how you get your blend And then as you get to the ends, it's just the 10 Boom Can't you see it perfectly? Oh wait. No, it's not processed yet. So again A nice heavy bit just below where I stopped with the darker color Because that's what's going to be used In blending Smoosh moosh. It's a very technical term And then move on lots of color pull it through And now there's color on your white floor Well, Daniel already tested it out with blue color and that was fine. Cool. Cool. Cool. You got on the tape though That's not coming off. Uh, I'm sorry I didn't put in a white floor Thinking it was gonna stay. Yeah, I could have told you that my apartment I thought my white floor was beautiful and reflected so much sunlight. It does It also shows every single footprint So that's fun. All right load up the mid shaft Bring it down through get it on the floor How we doing? We're good Trying to see if there's any portions Do you put this under heat on the the foil part not the the foils? Yeah, I mean if you want to you can again That depends on your lightener what you use If that would benefit it then yeah, sure go for it Uh, so then after I get my ends Then I will tone the front last because I high I foiled it first so it would get the brightest now. I'm toning it last so it'll stay the brightest Like it So that's just straight up 10 just 10 And then when I set my timer it'll be off of this because This is the money piece. This is the really exciting bit that is going to be right up in their face And it's not going to harm anything by letting it sit a little bit longer In the back because that's where your shadow root is cool Uh, somebody asked a different volume on the scalp. No because this it's a demi So it's just the processing liquid that I'm doing on the scalp. So it's a darker color not a different volume Yeah, it's best to use a demi Obviously over over top of your highlights because It shows all the dimension that we just yeah work to put in there foil wise But you can see as it's coming through that we've got lighter tones that'll be Throughout the ends. We're gonna have some depth Now we take the noodles and boom lasagna So I want to pull through. Yeah, I'll show you off This is the side I was just working on as you can see But she's got that depth throughout Yes, you can use all the plex with this bleach She's got the depth throughout But there's also dimension throughout as well. I brought some foils in close I used a lot of slices So that when I put that six on through the root and then smooshed it And pulled through the tens through the end I've still got that really pretty flow of color And this is what I'm talking about with these ends. So I just Lightened the daylights out of this mannequin with these ends and so it had that very hollow colorless just bleached look to the ends and I didn't have a ton of expectations with a 10 demi because I mean it's they can be very light sometimes But it added a really really beautiful Just depth to this so it didn't look Like you can see it. It doesn't look just like Bleached and overdone It's just a really light beautiful blonde that works really nicely with the depth and the warmth Of the six at the ends and then it just came together really nicely through the mid chefs And Yeah, I was actually really happy with this. This is something It's a good technique to have in your pocket because there's a lot of ways to translate this to use this for your guests I've actually been using it a bunch on mine, especially this week um I feel like this is a very good time of gear for this technique because like I said, we're transitioning a lot of people from Darker into lighter. So, you know, it's it's tis the season Tis Take the show on the road.  And take I've always wanted to win. Yeah, but susan just wants her hair done It's not like she's saying like take this show on the road. Sell lots of tickets. It'll be worth it I mean she's saying come do my hair. Maybe We're doing it in a winabago and need models The only way this is going to happen is if susan lives in georgia because apparently We would do great. We're huge in georgia We just went to georgia. I want to go back to that barbecue restaurant. We did. I'm nervous in georgia Yeah, I say just that was two years ago. That was a while ago. Yeah. Come on. I was just there um Okay, are there any questions if we do susan? We will we'll do your hair for sure. Don't don't worry. We won't keep it a secret Uh watching for my spin bike. That's awesome. Oh nice peloton Keep going. We could be the next peloton. I I mean ride your bike while watching our bodies clearly You want it? This too could be you. You need some inspiration Just keep battling trust me come to gettysburg. That's actually possible Where's that is that virginia? No, that's p.a I don't know. Isn't it? I don't know. I mean, it's like history books. Well Apparently I missed that one Where's kettysburg kell? What state are you in? She's in p.a. kettysburg is in p.a You're very short. I am very short. There's not too many things, but i'm I mean if i'm wrong, i'm gonna feel really bad, but i'm pretty sure i'm right I well, I don't know so i'm okay with that. I'll buy a ticket hair physician says there you go. That's right Thank you for that while we're getting in the bottom of this. All right I'm gonna hear the term. I'm going to gettysburg p.a. All right. That was right donna. It happens I'm gonna got it. I want some yeah the battlegrounds right. Yeah, I know that there was a battle of gettysburg I just didn't know where I wasn't there So Well, all right, I'll give you that here. I'll show you the back. All right. We got one minute one minute Let's give it a rotation. You did good. Yeah, let's give her some spins I'll show you the back because that's what also is like amazing Yeah, you can see that I wish this was a wig I would wear the hell out of us Oh dibs on scotland. I'm happy. She's a happy girl. All right 30 guys. Thank you so much Be sure to check us out free salon education across all platforms hairstyle Oh, wait, let me put that up also across all plat. Let me put that up. It's literally tattooed on my flesh I know, but that's hard to read. It's old. It's fancier rude You can't read any of my tattoos either Hayden you can read that Okay, you can kind of read that Whatever you can't read mine. Hayden was like, what does that say? I'm like, it's just old Oh the one that says map back. No. Well, that one's real bad. I'm getting that. He just laughed at that one I'm getting that for my 40th birthday. All right All right, so yeah, be sure to check us out. I need questions. I need Inspiration tag me in things. I want to see what you did. I want to I want to I want to chat I'm gonna make this. Uh, this is a two-way relationship. So thank you guys so much. I'll be back next week Or I may just crash Danielle's class tomorrow. I'm just gonna say hello Okay, all right anything else matt? Uh, I think that's it. Thank you guys so much for tuning in make sure tomorrow We got Danielle. She's doing some hair styling some curly hair styling tips. So yeah, super excited for it So 10 a.m tomorrow morning Eastern standard time. We'll see you guys tomorrow. Thanks so much


Good afternoon, everyone. It's a real pleasure to be here at the Singapore WUSH Conference 2018. So today I'm going to give you some insights into how we approach work health and safety in Australia and how we're tackling the changing face of work health and safety that's being caused by new and emerging workforce trends. So I'm very proud of the system that we've got in Australia. It's the product of much hard work, consultation, collaboration and innovation. And over the past 10 years, there's been a steady decline in workplace fatalities and injuries, which simply inspires us to work harder to make that decline even steeper. So in about 2011, Safe Work Australia developed a single set of model work, work health and safety laws for implementation by each of the governments of Australia. Most governments in Australia have done this and it's through this that we have broadly achieved national harmonisation of work health and safety in Australia. This is no mean feat in a country that's as large and as diverse as Australia and with its multiplicity of independent systems of government. There isn't one central federal government in Australia that controls everything. There are a number of jurisdictions and each of those had to implement the model work health and safety laws through its own parliament. There are two very important principles that underpin the Work Health and Safety Act. The first is the hierarchy of risk control and the second is good work design. So I'm sure in terms of the hierarchy of risk control, you're all very familiar with that. So in Australia, the onus is placed on what's called the person conducting the business or undertaking. The PCBU used to be the employer, but it's shifted slightly to select and implement measures as close to the top of the hierarchy as far as reasonably practicable, such as elimination of the hazard or substituting the hazard with a safer alternative. And then the second principle is good work design. And this really does underpin the Australian approach to work health and safety. Good work design sits at the very top of the hierarchy of risk control and it means designing work systems, processes and plant so that they are inherently safe so that hazards and risks to workers' safety don't even enter the workplace. Failure to consider how workers' design can be a breach of Australian work health and safety laws. So in Australia, we're very proud of the laws that govern the minimum standards for achieving work health and safety compliance, but we want more than just compliance. We pursue the ideal of best practice to reach far beyond compliance and to ask ourselves, okay, what's the next challenge? What are the new things that we can learn? How can we further innovate? And what more can we do to protect workers? Because work is changing, so must we. So we started a process in 2012 by developing the Australian work health and safety strategy, the 2012 to 2022 strategy. It's a forward-thinking long-term national strategy, it's halfway through at the moment, which promotes the vision of healthy, safe and productive working lives and provides measurable targets to be achieved by 2022. It places focus on a set of priority industries, and that's those that experience the highest number of fatalities in industries. Injuries, I beg your pardon, and places the emphasis on designing workplaces and work so that they are inherently safe. The national strategy drives work nationally, so that all of the work health safety regulators across Australia have a common objective and a common aim to work towards. So I said earlier work is changing, and so must we. What I'd like to do now is talk about the ageing workforce, automation, the rise of artificial intelligence, remote surveillance, early health, global communication, gig economy. These have all shown us that industries, markets and workforces can change with astonishing speed. So our work's now digitized or relies heavily on digitized capability. How work is done will involve more humans interacting with more machines and technology, and this without doubt is going to bring new and unexpected challenges, but also opportunities for improving work health and safety. In particular, we're on the cusp of discovering exactly what impacts the changing face of work will have on the mental health of our workers. This is really important, and I'll come to this a little bit later in a bit more detail. It's clear we stand at a new frontier for workplace safety. So in Australia, we did some work with a body that's called the Commonwealth Scientific and Industrial Research Organization, CYRO for short, and we had a look at the challenges and opportunities for work health and safety presented by this new frontier. We looked into the future, and over the coming 20 years, and identified six mega-trends that will disrupt and change the work done in Australia. So the big questions for everyone in this room is, if work is changing, do our work health and safety and workers' compensation systems as well, do they also need to change? Or are the existing systems robust enough to cope with the powerful forces of change and disruption? So the resulting Workplace Safety Futures report provides an intriguing insight into the future of Australian working life, but that was just the start of the conversation. So as policymakers, the report gives us a context that we need to discuss what we want work health and safety and workers' compensation to look like in the future, and also how to get there. So I'd like to spend just a very little amount of time at the moment looking into those six workforce mega-trends that were identified in the report and the impacts that are predicted as a result on workplace safety before I'm going to just give a bit more detail on one of the mega-trends. So mega-trend one. Advanced automotive technologies offer a plethora of challenges and opportunities to workplace safety. Robots are getting smarter, cheaper, more common. They're going to become more prevalent in our working places. The cost is going to fall. We're going to see them a lot more. But automation can make workplaces safer. A great recent example for out of Australia is that one of the state work health safety regulators offered farmers the opportunity to access a virtual reality training package to improve their safety on quad bikes. Quad bike fatality and injury in Australia is a significant issue both in the agricultural industry and in the recreational industry. New works are going to evolve. So while artificial intelligence and robots might be able to take on the load of repetitive routine work that humans find boring, without doubt new types of work requiring skills will evolve. Jobs that aren't replaced by technology are going to change and humans are going to have to redevelop and redefine their skill sets. And this is going to have an impact on worker mental health. So if machines can do the least stimulating, the least satisfying jobs in the workplace, the positions of value will increasingly be the ones involving more human-oriented traits such as interpersonal skills, creative reasoning, etc. But this may result in people spending a greater proportion of their working lives on higher functioning and more stressful tasks. And additionally, we anticipate that automation will enable employers to more frequently deploy automated worker surveillance and time management systems. This could also cause stress for workers. In Australia, sedentary behaviours are observed across most industries and can lead to chronic disease including depression, diabetes, cardiovascular disease. Chronic disease is the leading cause of illness, disability and death in Australia. Sedentary work is increasing and will likely further increase as new technologies push humans away from physical work. As we look into the future, we see a trend towards a service-oriented economy that coincides with a growth in white-collar occupations. And white-collar occupations are often the most sedentary, associated with higher risks to health. Telework's increasing in popularity. This means employers increasingly have very limited visibility or control of the physical workplace. There's also a complex relationship with mental health. If it's not managed correctly, teleworking can be quite stressful. It can make the employee feel a further or greater distance from the workplace and from the employer. There can be increased workloads. There's a number of issues that come with telework. The gig economy, so we all know about the gig economy. It operates under an entirely different business model to that which we are used to and in particular that which traditional work health and safety is used to. There's a lot of discussion about whether gig economy workers are contractors or employees. Under the Australian Work Health Safety Laws that's pretty much taken care of. They're either going to be a person conducting a business or undertaking or they're going to be somebody who is under the control and direction of a PCBU. The test for Australia will come in relation to workers' compensation so we are eagerly watching the US and England in particular who have had some cases come before the courts. But as with the other mega trends there are mental health impacts for the gig economy as well. There's a precariousness inherent to gig work that we know can cause significant mental health impacts. Aging workforce. Since the 90s there has been a steady increase in the number of older people participating in the workforce and this trend is likely to continue. There's some very interesting implications for work health and safety here. Firstly, those aging workers in the workforce are going to need more support from the healthcare sector to keep them fit and healthy to participate in the workforce. In Australia that accounts for 13.5% of our national workforce and it has the highest rate of workers' compensation claims for serious disease and injury. That's the highest rate of any industry in Australia. Also older workers are in the main more likely to encounter age discrimination, bullying and mental health issues. This brings me to the last or the final mega trend. So the rising issue of workplace stress and mental health issues. So each mega trend I've described will disrupt and change the face of work health and safety in Australia over the next 20 years and all have a potential impact on mental health in the workplace. The most important thing is that work-related stress and mental health issues are increasing in the Australian workforce. They cost more, it takes longer to treat people, it takes longer for people to return to work. This is a significant issue. And these issues are common through the six mega trends that I've just galloped through. So at Safe Work Australia we asked ourselves does our current legal framework provide adequate guidance to employers regarding mental health in the workplace? The legal framework does provide guidance to employers in the workplace but the feedback we were getting is employers wanted more information about how to comply with those duties and those responsibilities. As a result we developed the National Guide to Work-Related Psychological Health and Safety and it sets out very clearly what the known causes of psychological injury in the workplace are and also talks about what employers PCBU's can do in the workplace to try and prevent psychosocial injuries. I talked earlier about a desire at Safe Work Australia to move beyond mere compliance and work towards embedding work health and safety best practice in all Australian workplaces. I'm emphasising this because by focusing on best practice over compliance we keep the most important thing front and centre and that's the inalienable right of a worker regardless of their occupation or how they're engaged to a healthy and safe working environment. So I've talked a lot today about challenges and opportunities of the changing face of work. I think we all now stand on the threshold of one of the greatest opportunities for work health and safety. We know that designing work safely from the outset is the most robust way of ensuring worker safety and it makes workplaces more efficient and more productive and work is right now as we speak being redesigned. What an unparalleled, unique and exciting opportunity for us as work health and safety professionals here in this room to actively guide in this change and collectively redesign how work is done ensuring that worker safety is always placed front and centre. And that's the challenge for everyone here today. Thank you.