My name is Mrdul Mishra. I work with the Fidelity Investments senior director there. It's a financial services company, and you can make it out by the legal statement. So whatever I say, don't invest based on whatever I'm going to say. The topic I'm going to talk about today is explainable artificial intelligence. The interesting part really is, I think, Donald Trump, possibly a couple of days back, started blaming that Google is influencing too much of their decisions. Artificial intelligence, if you look at typical day since you started, whether it was Google Maps, Twitter, Facebook, whosoever used any kind of social media, there was some part of it. But that is possibly still the easier one. But now, considering it's being used for who gets parole or who gets into the jail, or it's being used for ultimately who gets elected as the most powerful person in the world, it becomes that much more important to figure out what's really happening. There are doctors who are getting replaced by it. There are key decisions that who gets the loan or who doesn't get a loan getting made by AI. So it becomes that much more important to figure out why a certain decision is being made. So what we'll talk about today is why, what, and how. And considering we are in financial services, there is a lot of very regulatory requirement that if you are making a certain call, you should be able to explain it. So we'll get into a bit of detail about it. So we'll talk about what it is, why do we need it? Why do we need it now? And then we will talk about some of the approaches. So one of the most interesting things I heard about AI with a lot of business leaders, which we keep talking to, was that it is helping us making our decisions better. But is it helping us making better decisions itself? Can we actually probe into those decisions and then figure out, is it really helping us the fair decisions which is actually good for everybody? And I have a bunch of data scientists which work with me. One of the most common conversations we have with them is, okay, so something need to be predicted, whether it's something on the text, something on a prediction for a particular stock price movement, and they will say, okay, so we need a bunch of input data, then there is a black box, and then magic happens, magicians comes with a prediction. The magicians are called data scientists here. And most of the time, there is a black box. There is a miracle somewhere occurring into it. And most often, nobody has a clue. So if you go back and say, hey, I think the accuracy is not right, they will say, let's try some other model, or let's figure it out if we can add some more features into it. But nobody is very clear in the way how it was really working. In investment management, like the way we work, there was a lot of quant models. Investment management changed 30 years back where most of the investing is now quant driven. But most of these models were fairly predictable. They were very linear model.  But now what has started happening is there is a lot of confusion about why it's happening. And what really, when we say XAI or explainable artificial intelligence we mean, is really AI which can be understood by humans. And I made the understood highlighted there because it's not saying explain it to individuals. It's saying understood by individuals. I mean, I have a daughter who goes to six standard now and it's quite funny because she will come with an answer during her math problem and a lot of times we'll say tell me the steps because you possibly have figured out the answer but maybe you haven't got the concept. And we are the guardians so we have to figure it out. The same way in my view we deal with AI. We say, okay, you've got the prediction right but actually explain it to me, how did you get to it? Which is in a way we human are like my data scientist colleague called human agents take that higher view of pedestal that we know it right, why don't you tell it to me? But before we go any further into it, I just wanted to question that notion that we are actually the higher ones. A lot of you actually followed the AlphaGoes and Lee Siddhal's conversation. I specifically want to talk to you about match two. There was a move 37 into it, which was supposed to be the match move which literally broke Lee Siddhal's any confidence into it. I just wanted to take you back on 10th of August when that game was getting played and because this is happening in India we are not encouraging smoking. Lee Siddhal go to smoke and AlphaGo just to play it don't think about the open FZ will be zero or not. So, Aja sees AlphaGo plays a move 37 and Aja puts a stone in the board. Wow, really, really, really good. Yeah, that value. That's a very surprising move. I thought it was a mistake. When I see this move, for me it's just a big shock. What? Normally human will never play this one because it's bad. It's just bad. We don't know why. It's bad. But it's a little bit high. Yeah. It's fifth line. Normally you don't make a shoulder hit on the fifth line. So coming on top of a fourth line stone is really unusual. Yeah, that's an exciting move. I think we've seen an original move here. That's the kind of move that you play go for. Hey, interesting stuff. That's fifth line shoulder hit. I wasn't expecting that. I don't really know if it's a good or bad move at this point. The professional commentators almost unanimously said that not a single human player would have chosen move 37. So I actually had a poke around in AlphaGo to see what AlphaGo thought. The point really, the couple of times and these are the leading co-players in Korea, in the world really, which actually couldn't figure out why did the computer do that. I stopped it there because there's a bit of discussion that when they did the analysis, they figured out there was one in 10,000 chance that that move could be played. It was never played by a human being ever. And the point really here is that the AI has reached a stage where we humans possibly are not even able to comprehend it and could come with a better decisions. But this was still a game of go. This was not life or death. It was not somebody's retirement earnings and you were making a call whether you invest on to it or not. When we talk about those decisions, whether you have cancer or not, that is where the explanation is required. But why I wanted to talk to you about that really was that AI has reached the stage where we possibly humans are not at the higher pedestal which we think we are and want explanation. So let's talk, why do we need explanation?  This is a Siberian husky. How many of you have dogs? And if you're a data scientist and you want a dog, typically what you will do is you will write a classification algorithm which will have computer vision into it and it will look at all the passing puppies and try to figure it out. If it's a, that Siberian husky is a very similar to wolf looking actually. If you look at it, even though it's a puppy, when it grows it becomes very much like a wolf. So if you write a classification algorithm which tells whether it's a puppy or it's a wolf, this is what comes out. Let's say your prediction algorithm is doing pretty well for one out of six cases, it wrongly classified it as a wolf and it was actually a husky. In every other case it was doing as expected so it was predicting correctly which actually is a dream, honestly, if you can get this level of accuracy right. There is a problem here and this was one of the most talked about in a lot of the explainable AI circles last year was that when they started looking into it how is it actually identifying whether it's a wolf or a husky, they realized that actually it was looking at the snow around it and what it actually created was a snow detector. So whenever it found that there is snow into it, it actually realized that it must be husky because dogs don't really do it, be there on the snow. Now there's something fundamentally wrong. I mean, there was another example. There is an AI company here which does radiology x-ray analysis and they trained a lot of images based on which to figure out if there is a malignant tumor into it and what they realized was it was giving 98, 99% accuracy but when they started looking into it, they realized actually it was looking at annotations which the radiologist has actually done so it was actually because the training data had those marking. It figured out if there is marking into it then it must be malignant which is not really the objective because then it is figuring something else out. So it is fundamentally something wrong unless you figure out how it's doing in that sphere, it becomes very important to do that. But there are four different views why we should look at explainability. So one of it is if there is a user he certainly need to figure out if his loan got rejected, why did it get rejected was that his saving was not enough, was that he has taken too much withdrawal, what could he do really to get it? But the second one really is from even from a data scientist perspective actually figuring out what really is happening and not just do hit and trial because there is actually a project called deep patient and I just have some no idea what's the love with the deep part in everything which they do where they figured out that people who have asthma and pneumonia they actually survive better and they started actually going down the thread saying that hey what does asthma has which is giving this higher chances of survival for pneumonia patients and then they realized actually what was just happening was there was more care being taken because if you have asthma, asthma is not really helping you with pneumonia but if you have just gone with the correlation and say hey asthma patients get better out of pneumonia it's actually giving absolutely wrong. So if you're a data scientist you should go deep into it and figure it out why did it happen. In a regulated industry like financial services I absolutely love GDPR when they started saying all the data subjects which is you and me have a right to go back to a company which has made its decision to explain it. I never thought myself as a data subject in this world but so far this is where we are going to be and there's going to be undictated someday. So if a regulator comes in regulated industries you have to go back and say exactly why was it done so there's really no choice and most importantly if you wanted funding whether it is your business or your boss you really need to understand how it works. I have been part of a lot of these conversations where we explain certain recommendation and the business person will be sitting there and then say okay these make sense explain it to me why did it happen and the funny thing will be he will say whatever made sense anyhow I would have done it so what's the value add the one which doesn't make sense which are counter-intuitive explain it to me why did you recommend that and you're like hmm let's try something else so I think it's very important even from a perspective of selling it that we get that part right. Before I go any further I think it's very important to know that explanations are the humans are not very logical creature all the work which has happened in behavioral sciences behavioral finance proves it that we think we are all rational minds but actually we are not we don't spend as much time with family as we want we don't invest for our future we all want to be getting up early and go for a run but most of us don't do eat that extra candy at the dessert at the counter so the learning has been always that you know what the way people will look at explanations is that it need to be contrastive which is if there has been a certain decision if somebody's loan got rejected and what we figured out was that his saving was only 5 lakh the next question will be ok so if it was 10 lakh would that have approved it how many of you have watched Roshomon Effect there's a 1954 couple of you great it's the classic Japanese movie those of you like black and white Japanese movie and it's there's one killing of a samurai and people look at it from different perspective each one of them they are telling the truth but everybody's truth is different and the point really is that if you are talking to different people in the group what you really realize is the way they are looking at that information is very different it's very contextual so the same explanation doesn't work at the level of the person whom the decision is impacting versus his boss versus the executive always it focuses on the abnormal so it's not whatever they were expecting nobody actually asked why did that happen so ultimately the point really is that anything which looks abnormal need to be explained what we learned really was that good explanations actually in some way are coherent with people anyhow what believed whenever we start challenging what they believed and a lot of cases where what happens is that there was a certain way certain decisions were being taken done whether it was a call to talk with a particular dealer or a broker or how trading gets done selecting a particular exchange humans have been doing in a certain way the moment model starts coming back which is contrasting with what they were doing explanation becomes that much more important and my learning really was it doesn't need to always need to be truthful it's good if they are truthful lot of times it just is a simplified version of reality because the real decision making is so complex that it is just not possible to be truthful in the legal sense of explaining all the causes of it it is good enough if you cover most of it so I was saying that in investment management industry which I work with we have been doing quantitative investment for 30-40 years now I mean from like 1980s that has been the fad and most of the time those quant models the way they used to work was kind of a linear model this is from one of the Mackenzie report and what they show that line which you see the green one how typical linear regression models used to work which was very monotonic very predictable how the answers will be but once you start getting into lot of those machine learning models what you start seeing is those graphs in this case it's a churn analysis for I think one of the telecom companies where the way relationships are coming out cannot be linearly represented like it so the representation itself has become very complex and I remember I mean not too long back maybe 10 years back the factors which we used to look for predicting where the market is going was as simple as let's say PMI which is purchasing managers index or we just used to look at inflation data what is coming out the job numbers which is coming out and we just based on that used to go ahead and predict where the market is going to be now with the big data and being able to capture everything any of these models typically runs into 100 to 200 factors now to just predict that same thing which was being done with three or four factors so both that we have more complex representations and we have lot more features has what really made it that much more difficult now the way we put internally the view on this really is that there is a choice to be made there are on one side interpretability concerns on the other side there is accuracy and like they say you don't get everything always there is always a choice to be made in terms of whether you want more accuracy or you want more linear model which is more interpretable but actually what we are trying to do really is when you show a graph like this everybody says hey we want best of both so what we really trying to do is can we start moving some of these approaches to the more of right where we still get an accuracy which is higher than linear model and still try to get interpretable it is still not there as it was easier with the earlier models but you are trying to get it but the other factor which plays the role here is the whole computation power so those of you who did the cap theorem in college possibly remember that you can only pick two of these if you really want a deep learning model and which need to be interpretable we really need to figure out what those different weights were and possibly give the sample feature set which all possible values the computationally it becomes so intensive that it is just not feasible to do it so there is really a choice to be made between three axis not even two which is what you want more accuracy interpretability and how much computation can you really throw at it so far that was the context I was putting in terms of what why do we need it and from here we will possibly move on to how it has been moving before I start talking about specific ones I have to say that this has been an area which research has been behind the adoption of it industries possibly have moved on a lot in terms of using AI without figuring out how do we explain it it was a lot like when electricity came everybody built it but they never thought about building circuit breakers when somebody's electricity plastered the whole grid they said you know what I think we need to do circuit breakers so lot of this is happening is still coming out of research still is something which is happening in the universities still coming out from the research wings of the large organizations and not necessarily something which is a productionized version of it which is available there are two broad buckets of it one of it is if we can explain globally how it's happening which is look for the model look for all the predictions and possibly explain it at the global level the second one is local local interpretability where you're looking at a single instance you're looking at a single prediction figuring out if for me coming from my office to this predicted 55 minutes why did it predict for me rather than saying everybody why the prediction was really that much and what we have seen really is the local interpretability is possibly slightly ahead if you're trying to do global it's still that much more challenging how many of you have heard used lime before yeah so lime has been possibly the most popular at least the most common one which has been talked about in at least one and a half two year part of it fairly simple concept you take it you perturb the input data which was there go ahead and use that to figure out how it gets done which lime we will talk about a bit more later but the more interesting one which has started coming is the counterfactual explanations the interesting thing which we figured out recently was like in US the credit score were always supposed to be explainable if somebody gives FICO which gives the credit score in US has been using neural network since 91-92 and they anyhow had to go back and explain it to it if they said your credit score is 820 why did they come to it so there was they had couple of patents which expired I think some time back which actually was explaining part of it and that gives one of the approaches to look at explanation like FICO's reason report the other thing is actually look at interpretable architecture and actually with the very start of your problem definition itself figure out if is it worth going to something as complex as a deep learning model or just we stay with something which is more interpretable because in some cases maybe you have to take it twice itself and then there are the future of it which is coming in terms of disposable latent features like lens so lime has been a method for fitting local interpretable model that can explain single prediction of any black box machine learning model so it is model agnostic in a lot of ways it doesn't care what you did with internally they are based on local surrogate model so what they try to do is if the representation which you have is very complex and what you are looking for is a specific area where you need explanation what they do is they say let's define a local surrogate model for that specific area which because it's trying to focus on a very specific area it could be a lot simpler version than the complete model of it and then they generate a data set consisting of different samples which are there and that data set they train an interpretable model is weighted by the proximity of the sampled instance which you were trying to explain so they look at how close is the sampled instance of what you were trying to explain and then use it and one of the cutest example which they have which possibly gets used a lot really is a Labrador playing a guitar which gets explained and the way they have done really is what you see down is they have created many versions of it they have perturbed it great different parts of it and what they show really is that the probability of each one of them matching to it so in this case the face of it kind of gives away that it was a Labrador if you just look at the body of the guitar it was giving it's acoustic guitar but if you look at the neck of the guitar it says it possibly might be electric guitar and it gives that higher probability it's slightly confusing picture because the body of the guitar is acoustic but the head of the guitar or the neck of the guitar is electric but what it is trying to show really is that if I'm telling you that this was a Labrador playing an electric guitar why did I say that? which is very useful in a lot of scenarios as we were talking about it works for other cases it works for text inputs it creates separate data sets for the text input which are there perturbs it and then creates which one of those features actually resulted in the final prediction really it's pretty good for localized explanations if your need is being able to explain a specific prediction and I think it's possibly the best to get started with if you need it I think it's possibly the simplest one you get going in a day or two humans interpretation is pretty good it doesn't try to be the most complicated interpretation so it's not exhaustive but it figures out what are the most important features which need to be used for explaining it and because it's not exhaustive it doesn't work if you work in an industry where everything need to be explained to auditors or regulators for each and every decision it doesn't work in a lot of those scenarios the counterfactual explanation this is I think fairly intuitive way it works lot of work was done in Microsoft research they did some work earlier this year I think DeepMind published a paper late August on to it to say how do you how you can start using it there are a couple of GitHub projects which try to implement it currently the way I find it very interesting it really tries to be the way humans think about it so once you find something once you find I mean in Bangalore if you stay the traffic is the most biggest thing to worry about if I have to go back home there possibly are three routes and if it says take it YMG road I will always think hey but YMG road why can't I just go and take the outer ring road and possibly go it so it just really for every prediction says that if X had not occurred or something else would have happened what would have been the output which is very human way of thinking so if you're looking at a prediction and there are 20 feature sets education level it has age it has gender it has the race of it most time what you're trying to figure out really is that if the gender changed is there an angle to it is there if the age was slightly more will that change it which is very intuitive way of thinking it and it kind of tries to simulate that which is very interesting so the way it works is fairly simple we change the feature value of an instance before making the prediction change and that tells how much was the impact of it again it's used for very instance specific predictions that's an example which gets used a lot in the counter factual explanations and the way to read this is that you're trying to predict students average grade of the first year at the law school based on the GPA before they joined it so what you see as column 2 is the GPA before they joined the school the law school entrance exam which is column 2 and the race and 0 being white and 1 being black and then what it did was it created a counter factual data which is it created a GPA which is quite similar to what was the original GPA it created law scores which is quite different than what was there but it did something very racial it actually converted most of the people to whites to show that actually if you want average grades then there is a very strong correlation that you need to be why it's a fairly racial model to look at but it gives you a picture that underlying model possibly would not have any house stood if it was to be explained if somebody goes to court and say why the GPS score was not predicted right so in a way it gives you an answer that race and possibly your law score law school entrance exam results are one of the key features the implementation of very early stages I mean there are a few GitHub projects which are there we played around a bit with it the interpretation where it works is fairly clear I personally think it's very intuitive to think in that lines it's model agnostic it doesn't do anything specific to a model and it's fairly easy to implement but if you are playing around with it I think it's fine if you want to use it in a production like scenario maybe it's not there I personally thought this was a very interesting concept the reason reporter and this is I mean if you go to FICO and search for reason reporter you'll find the earlier patents which they had on this which have become open now I can give you the way this works really is that let's say a new data point come and credit score was explained what they do is they kind of bin things so they look at different features and then they put scores and then they put bin so what they realize that let's say let's say first feature is the salary of the individual and they will say if you are getting between hundred and hundred twenty thousand dollars your score will be eight hundred fifty if you were thirty to forty thousand dollar it will be six fifty and when they have to actually explain that way they put kind of bins for each and every feature and then when they have to go and explain why was a certain score given they go back and figure out which is the closest user data matching with the what the output has been so in this case eight sixty was the output they realize that actually eight fifty was fairly close the feature bin for that feature one was in that range so what they go back and say is that reason code is sixty five and the user possibly is for that feature is in that feature bin so it rather dealing for individual values which are there it actually tries to put things into bin it's a very useful concept because if you think about a lot of discrete data sets which are there stock prices maturity dates are born it's very important to group them into something which is human comprehensible and something which can be related rather than dealing with each and individual values of it which is a very interesting implementation of it the other thing which we saw was that whatever model does there always will be some human knowledge or a domain knowledge need to be put specifically if you are in a regulatory industry a lot of time data will tell that a certain gender or a certain race or a certain age group has been given certain privileges and data keeps on telling it that if somebody comes back with the age beyond 60 maybe you don't give him house loan because it has never been given now the problem with that really is that if regulator come back and they figure it out that you have been discriminating against people because the age was higher that becomes a problem so what we've started realizing it that you need to still have some rule and in this case like the example which I was talking about if you realize that age has been a critical factor for model to actually score somebody's credit score down you manually flip it either you go back and impute the data and say I will make sure that people above 60 also start getting it or add it to the final score card and say that fair enough let model predicted but I will add some extra points just because if you are in that age group because we have seen a lot of this discrimination based on the data so that's the real world problem because most of the data sets which we get will be skewed in some way based on how human agents have been working on to non-ideal world and going forward if you have to start making it more and more come to what we want the world to be there has to be that domain knowledge part of it added to counterbalance what the data was trying to say. So with that this possibly is the last slide in terms of summary I hope I have been able to convince you that it's a very important for acceptance of model learning machine learning that we are able to explain it it's not only for the users to know or for auditors to know but even for the practitioners who are building these models to know because a lot of times there is something more hidden than what meets the eye and if it gets recognized by a regulator or in the production that's a lot bigger so it certainly need to be a focus area for everybody it's not yet there it's possibly will take a year two year from now for it to become mainstream and get adopted into it a lot of work is happening I mean recently we are talking to sales for Einstein team and they have done explanations on some of the decisions which it tries to make and it will keep on getting better as it goes along but that's in focus area which need to be there and if you are in a regulated industry which makes these critical decision there really is no choice I think before it goes into production you really need to get that act together in terms of making the model screenable so that was all the conversation I had in the slide thoughts questions feedback it's not very good question actually and one of the reason of putting that computation slide really is just becomes prohibitive really in terms of computation to actually add it for every record the way at least we have been looking at really is that there are some use cases where there is no choice and what we make sure is that once the model has been evaluated based on the accuracy part of it we actually make sure that one of the part of QA before it goes into model really is something which is explainable using one of these model I'm not allowed to say which one it works really but there are very few use cases where each and every one of them need to be explained to be explained at that level where interpretability requirements are that high one of things which we have learned really is at the very early stages when we are even having a conversation that what is the business problem we ask this question so ultimately how interpretable do you need could it just be I mean if you're building a model that who will click on your ad really don't care I mean it's okay it's few cents here and there no big deal but if you're going to predict somebody's X-ray is malignant or not interpretability is that very important maybe cost for computation is justified so I don't know if there is a that clear a framework which I was you hoping but that's how we were trying to yeah so I mean the way at least the thinking has been that it should be part of your QA process in a lot of ways especially for those use cases where the auditors might come back and you would have to explain into this should get sued for a specific decision or a life or death kind of conversation so it starts getting very specific to those use cases where there's no choice even though it's computationally very costly it possibly need to be it will delay overall roll out of your model but it is for those industries those use cases it's better to possibly be safe sorry I have a question sorry first of all I have to apologize I join in the middle so I didn't fully see what you present there I'm from the financial services domain so of the techniques which you so in financial services you have to be very clear in explaining to a customer what is that you have to change so that your credit score can improve okay so solutions like lime is not like surgically enough to clearly communicate so of the techniques you have seen is there a clear recommendation we have of being able to explain a deep learning score of what the customer should do to improve the score I mean I think what you should possibly look at what FICO did with the reason reporter and trying to bin it because the point really is when the customers are asking for it they are not really very specifically trying to figure out what your model did more often than not the question is really so what should I do to make sure my credit score goes up or my loan gets approved and what if you come from that angle to figure out which of those should be taken to change the decision I thought that reason reporter does a pretty good job of abstracting the whole problem and then coming back and saying these are the reason quotes you should look back and then if you look at your feature bins it in a ways goes back and says this is what you should work on really so I think that possibly is something worth looking at specifically in financial services thank you give me an example of what you are saying I am not sure Ray we used to have linear models whether it was logistic regression or anything which was explainable this is the simple coefficient you add it and possibly get it but like I was showing you I mean if your representation starts getting too complex which it does in lot of cases specifically deep learning if your feature set runs into 100 somebody backward creating that would be quite a challenge I haven't seen it personally so if it is possible great but I haven't seen it excuse me I have a small question now one of the ways of finding out the explainability in a model is probably using an old technique of AI when in the days of symbolic AI the reasoning and logic frameworks were there so are there works going on we are going to combine them with deep learning models or something called planning and learning and things like being tried or attempted yeah so I mean you are right the world was fairly simple at that point of time an example I was giving you really was that I mean when we used to predict market movement the factors which we used to look were fairly straight forward we used to look job data inflation data what is the confidence level which is coming out and in those cases it was like expert systems where domain lot of people how many of used expert systems before a bunch of people yeah those who haven't heard this was like what 90s 90s AI 70s AI mid 90s AI yeah and in those times it was pretty easy to go back and start explaining because it was in a lot of ways it was coming out of somebody's mind the feature set was fairly limited it was not easy to describe I mean once we get into hundreds of features 200 300 and nobody really knows how they're correlating it's very difficult I mean the only way really is the crudest ways impute a future remove it see the impact impute the other one and see what the impact it are look at the role level and counterfactual do it I don't know if that golden era of explainability will come back because it's lot more complicated word now okay so this is getting into a different range of philosophically way about it but I mean I don't understand how my car works really I mean I expect a functional job of it to do take me from point A to point B it has been working as industry it has reached the level of credibility but if you watch old Hindi movies and all they used to be those scenes where the smoke will come out and you actually open the hood and see where to water to be put so there was a time where you actually need to know it maybe we will reach the stage we will start trusting the decisions which are coming out with AI algorithm and say okay if machine has said it it knows more than it we will get that level of credibility but we are at a very early stages and the decisions it is making are life changing for people so my take on this will be maybe society will accept it maybe regulators will say if machine has said it it's move 37 we don't know whether it is good or bad but human just don't get it we are not there yet I mean that is more like a fundamental major for calculation how yeah yeah yeah no I haven't actually no I haven't but it's called as shapely okay I will certainly look at it correct correct yeah H2 is doing some great work absolutely in that area there will be vendors here so yeah maybe with no comments on specific ones cool can we put some methods rather than manually? AI to explain the AI yeah so a lot of this is in a way generating even if you use Lyme in a lot of ways it uses a surrogate model which generates those explanation but the point really is this is for human consumption so if finally you have to convince a user you don't want him to game whatever machine is giving you at least at this stage we still need that kind of verification to be there I agree I mean yeah it's you need to be certain level of tall before you try achieving it and if you're not verging your model and data then yeah some way to go totally agree somebody was saying something there some comment feedback yeah yeah I mean fairly valid point and the funny thing is somehow we humans have this urge to understand everything it's not like we understand so if you go and listen to the news market goes up they will say oh the market has gone up because this data came back and because of certain geopolitical tension and if market goes down the same reason will be used we have that urge I mean I remember when Trump was getting elected everybody was betting on Hillary to win and we were saying if Trump wins it will be a disaster it's two year and we can give reasons he gives reasons better than I can give I think there is more psychological reason to ask for justification rather than really a need to understand it and I get your point I mean in some way we don't really understand a lot of complex system once that level of trust gets built maybe nobody will ask it's just a commodity but if you watch any news channel I think all the experts are trying to give justification for any and everything but the world is just too complex to be explained in those soundbites so I think it's more a psychological urge than that technical thing really cool thank you


And thank you for reading my article in this month's Envision Magazine. Now, as promised, I wanted to give you guys a little walkthrough of the incentive-driven goal planning that we use here at Spexy and kind of give you a few examples of the best way to utilize this. Jumping right in, you'll notice that for the entire year that it has six different focuses that you have throughout the year. The reason why is because we want to give your team two months to be able to implement this new way of thinking, this new strategy of whatever your focus is and to really make it a habit. Because once your team is able to make it a habit, then you have a really good opportunity to be able to move on to something else and not have them drop off on that one focus from the previous month. And since we're in March now, you might go, well, we have to wait till next year because we don't have January, February, not true. This is meant for you to use every single year and you can jump in this month or you can go ahead and start next month, however you like, but the whole idea is to make sure that you are doing two months at a time for any of your focus-driven goals. So on the first page, you want to enter in what your focus is going to be for those two months. So maybe one is your anti-reflective treatment percentages. And then maybe another one is your new patients. How are you guys going to go about getting new patients on there? Maybe another one is you want to move people from plastic or poly into Trivex. So maybe that's going to be your big push. Maybe another one is your sunglasses. Maybe that includes plano and prescription suns. And then maybe you want to do multiple pair sales, right? Really focus on multiple pair sales for two months to see what your team can do. And then maybe another one is not necessarily optically related, just something that your office has a metric on that you can grow with. So maybe for one of them, you want to do something like a retinal imager, like an optomap and selling that in your office because you have statistics on that from the past. If you grow that, what would that look like for your office? So that brings us to the next section. Now, I love this quote, knowledge is having the right answers, intelligence is asking the right questions because this is something that's really, really important because so many people in leadership and optical will come to me and say, well, Kayla, we tried to set up this goal and it didn't work out. It's a problem. Mary didn't do her job or so and so didn't pull their weight or so and so got upset because so and so got a higher incentive than they did. Well, I personally think that everything should be set on a team basis. This is a really great opportunity to have everyone on the team take part, not just the sales team and the optical because if you think about it, every position in your office can absolutely kill a sale. Therefore, every position also has an opportunity to actually complete a sale and to help a sale thrive. So if you have your front desk person on board with you with being able to get more anti-reflective treatment and they're empowered with the knowledge of what anti-reflective treatment does and when a patient comes in and they say, yeah, I don't love my glasses because I have so much glare at night, they can say, oh my gosh, we have this anti-reflective treatment that we're using and you should definitely talk with the opticians about it because not only is it really fabulous with helping with your glare but it also is really great with preventing scratches. So I'll make sure and put it on your chart so that they know what to talk to you about it because it's really fab. Great. And then if the patient has it, awesome. Maybe they just need a better one. If they don't have it, awesome. The fricking front desk person just sealed the deal for ya. Now, the rest of this is pretty self-explanatory. The biggest thing that I want you to focus on is completely understanding.  Okay, let's just make it easy on ourselves. And let's say you want 10% growth. So that would put you at 110 anti-reflective treatment sales, okay? And maybe your percentage is higher. Whatever your percentage of growth that you're wanting is, make sure to give your team an actual number to be able to run a metric on, okay? Because once you have an actual number, it will allow for them to statistically in their head, you know, track how they are doing. And also in one of our previous months with InVision Magazine, we had a goal tracker to actually have your team be able to track the monthly goals that you guys have in place. So make sure and check that out if you need to. But the rest of this is pretty self-explanatory. The biggest part is make sure to come up with a statistical number, like an actual whole number, not just the percentage. And then make sure and come up with the incentive value. Sometimes it's monetary, sometimes it's not. Sometimes maybe you guys are having a really awesome sunglass sale and you tell everyone that they can get a Plano set of sunglasses if they hit the goal for that month. Oh my gosh, that's super awesome. So make sure and have everything detailed out. And make sure and have every sort of, kind of the ins and outs, right? The little asterisks that you would normally have on a deal. Make sure that you have that all laid out for your team before actually implementing this new goal-driven strategy and incentive to the team because if you get it right, I'm telling you you will no longer have a team that's unmotivated. They will actually be really excited to perform. So go ahead and get started and I will see you next month for April's Envision Magazine. See ya.


The close sustenance of the human body and the human life entirely depends on the system that runs the nature. It entirely depends on the systems that are working for the human life and for the life of every living thing. And if that system is damaged, well, the human being will perish. Because we entirely depend from these things. We depend on water, we depend on air, we depend on food, we depend on the space, we depend on how the environment is sound, with the right temperature, with the right weather, with the right conditions for us to survive. And that's what the planet does for us, create the right conditions so we will be in a harmonious environment. And so if we don't have that, there's not going to be peace and there's not going to be any reason to live in an enjoyable life. Life will be crazy as it's going that way pretty quickly. Life will be very confusing for most of humans. And it will be no longer life, but just surviving at all costs, which has become a magnet in insanity. Hello everyone, welcome to Simulation. I'm your host, Alan Sakyan. Very grateful to be on site at the Somatic Sanctuary in Ojai in California. We are now going to be talking about ancient wisdom. We have Mamma, would you want to join us on the show? Hello. Hello. Thank you so much for having me here. We're very, very grateful to have you. I was very fortunate to be introduced to you teaching the ancient wisdom about last month. And since then I've been very interested in continuing to learn and embody this wisdom. And we came down here for the workshop that you had a two-day workshop at the beautiful Somatic Sanctuary. And it was very powerful again. And I'm very grateful that you were willing to sit down with us. And I would like to give some background to those that don't know. Mamma Luijuan is a gifted native and then maestro from Colombia, a master in bringing the ancestral wisdom to all of America and the world. He is a vibrational healer, holistic educator, yogi and shaman of the light. He holds the unique distinction of being the only mamma born outside of Sierra Nevada of Santa Marta, Colombia, authentically ordained by the highest-ranking Kogi, Mamma Jacinto, who recognized and tested him over a 15-year period and was surprised to see how exceptionally accurate Mamma Luijuan was in his way of working with Aluna, the spirit of the mother. Mamma has dedicated his entire life to spiritual training and the work needed to help transform people from all walks of life to recover humans' righteous functioning as part of nature on Earth. He has also been doing silent service across the USA to reharmonize the forces and spirits of nature here in California and around the entire country for 25 years. And you can find the links in the bio below to koginkasewalunafoundation.org as well as the Facebook page Koginkasewaluna. Mamma, let's start things off by asking you, what is this ancient wisdom that you are teaching? The ancient wisdom of what we call the original wisdom of the mother. The mother refers to the power that has manifested everything into creation from the spiritual dimension to materiality. And so the original living wisdom of the mother is that that originally was passed to the first original ancestors, the first spirits, sons and daughters of the mother. And with that the mother has established from the very, very beginning, from millennia right from the very beginning of the creation, has passed this ancestral wisdom that is all about how to behave, how to function, how to get along with each other as a spirit. And how to be able to co-create and maintain the reality in which we would like to live. And essentially how to get along with the environment that sustain us, especially in this dimension, in the human planet. How we can really function with nature, which is extraordinary basic and extraordinary essential. It's something that unfortunately is forgotten. The wisdom that we're talking about is the wisdom for the whole humanity. It's universal. It's the origin of functioning. It's the origin of getting along. It's the origin of holding harmony, balance, integrity. And integrity is the original wisdom that really is critical for maintaining space and especially to preserve this planet. Unfortunately that wisdom, there is no wisdom only for the indigenous, our indigenous people of the world. Not only a wisdom for the kogis of our ancestors, the chipchas of the ancestors of the Sierra Nevada, the kogis and others. That original wisdom, the original wisdom of the world is for the entire humanity. We are only some of the groups that preserve it and we are only some of the ones that are still practicing and applying it. It is not that this original wisdom is strange in the great sense of the expression for the entire humanity. When you see Native people, Americans or Native Africans or Native from any part of the world, when we look at them, even if it's slight differences and a little bit of controversial stuff, they essentially do the same. And when that wisdom is lost, which is the wisdom for the entire humanity to behave in a beautiful dimension and planning like this, when that is forgotten and undermined and neglected, we create what we have right now a complete mess. So this wisdom is what we are here bringing and telling the whole world, especially this is the mission that my mentor, the great mama Hasinto, put me to do. And we pioneered 15 years ago with him and bringing that to the world because it was so critical and it's so critical. The human being recovers the original wisdom of the world to be able to function in this environment and consciously responsible for the planet. One of the best ways I think I've learned from you about understanding this is what sustains us. It is the planet that we live on that sustains us. It is the nature that sustains us. Every breath we take, every drink of water that we have, every bite of food that we have comes from this planet. And when we become disconnected from that, we see so many of the issues that have arisen in our world. And I think that's a beautiful aspect of this ancient wisdom and like you indicated, it's ancient wisdom from all of the indigenous tribes appointing at the same thing that we have in this case lost. I want to ask you about that embodying that remembering of what sustains us of this ancient wisdom. That is the conscious living and functioning? The basis of the original wisdom is actually very self-evident and extraordinary practical and functional. And the best extraordinary proof of the original wisdom is just the functioning of the body. If you see the body, it has many organs, many systems, many intelligent, extraordinary, special functions. The body functions in a very cohesive, coordinated, harmonious way. Even though every organ can be doing a number of functions, they are developed for the entire benefit of the whole system, the whole organized system. The body shows how it's to work in unity, in harmony and in balance. So if the organism that is functioning in unity, cohesiveness and balance, then nature will come to them the same way. Well, nature is life force. People think that nature is trees and rivers and all those are only the material manifestation of the workings of nature. But nature is life force. Life force is a conglomerated group of forces coming from the cosmos and so forth and so forth. So the close sustenance of the human body in the human life entirely depends on the system that runs nature. It entirely depends on the systems that are working for the human life and for the life of every living thing. And if that system is damaged, well, the human being will perish. Because we entirely depend from these things. We depend on water, we depend on air, we depend on food, we depend on the space, it depends on how the environment is sound with the right temperature, with the right weather, with the right conditions for us to survive. And that's what the planet does for us, create the right conditions so we will be in a harmonious environment. And so if we don't have that, there's not going to be peace and there's not going to be any reason to live in an enjoyable life. Life will be crazy as it's going that way pretty quickly and life will be very confusing for most of humans. And it will be no longer life but just surviving at all costs which has become magnets in insanity. If we destroy the environment in which we live, which is lack of consciousness and conscious responsible behavior, so then we are all compromising the most essential elements of the human being. And that's what this original wisdom says. If you don't preserve harmony, balance, order, peace and sound environment, the human being will be crazy and that entirely depends on nature. We don't do that work. Give the example of the body and how beautiful the cohesive system that is and if there is an organ failure that happens, well the body is injured in that process and that is in a sense what is part of the systems. These functioning systems on the planet are experiencing these injuries that the humans are not functioning cohesively with nature, with the system that sustains them. And now you're indicating to us that it's become like an allergic reaction of the planet and that the amount of people that are living in a non-harmonious way with nature is so many. Now how do we deal with the allergic reaction that the planet is giving us right now? We instead are to be part of the harmony and part of the very harmonious functioning of nature. Nature has given us the opportunity to embody a spirit. Our bodies are coming from the workings of nature in a very extraordinary, amazing way. The body itself is a piece of art and that is the original wisdom of millennium, the original wisdom of the earth and the original wisdom of the human race is right there in the body.  If somebody comes to mess with your body and touch it and even just do a little pinch or something, you will react and you will act defensively. What about if we do the same with the system that have provided our bodies and that's exactly what we should do, protect the environment, the mother, our own lives and bodies, provided our sustenance, we should protect it and we should do what is right. In our wisdom, the wisdom of the ancestral land of Colombia, it is all about how to function, how to get along with the system they sustain us. The best relationship of the human spirit should be with nature to begin with. Otherwise you can get along with superior dimensions or superior levels of consciousness of celestial realms or anything like that. We are here to master the experience in a beautiful environment that was designed for us to master consciousness, to master wisdom, but we are doing the opposite. And we, to matters worse, we are basically attacking our own mother, destroying it. The damages that we are causing to this planet are completely out of proportions, are extraordinarily unthinkable, inconceivable. The damages that we are causing to this planet cannot be repaired probably in millions of years. What nature took in time and process and improvement for thousands and thousands of years, we are designed in a couple hundred years. And if we don't change our ways, we all end up in a very catastrophic end. And I know alarming anybody, but this is the message. It's coming to the point that many people know already that we already have passed the tipping point and which is probably there's no way back to recover, to repair. But we still can stop becoming enemies of nature, stabbing and destroying our own mother, the mother of our own life, the system that sustained and provides for us. This is exactly for us what is insanity. And so this is the alerted reaction.  It's like a house. If you see some box around, some incest, as I explained before, well, you're cool with it. Especially if you are pro-life, kind of a freak. You're life, you protect the ant that is around there. Two ants, you say, well, probably it's the father and the son. And then you say the whole legion of ants comes to you. And then one night the ants are at your bed. So you say, no, I had to start spraying. And so nature can become very allergic and reactive to us, which is the case, because we are intruding, invading, destroying the organs of functioning and recovery and the organs of balance of the earth just to make profits. Which is okay, you know, there is a level that it should be intelligent and not blind to make profits and to make business. But to the point that people should respect it, do not cross the line in the line where we are already causing extraordinary damage that is practically beyond repair. We should not cross that line. And my message here is also for the ones who are making profits and destroying nature, I'm not going to blame anybody because I can point fingers to anybody. But remember that probably they also had children and their new generations and money doesn't guarantee the good future of anybody. What guarantees the future of every single human being here in a lower status, in a high class, is harmony, balance, and has good environment that is coming from nature. So I really, I will really ask to these people, whoever is that, please, we beg you to reinvest the money that you have taken from nature to repair it. Please do that. Please. And you're not going to do it because of your own set of beliefs and, you know, system of beliefs, of your convictions and everything, but I'm telling people there is still, and I'm speaking to the people who still can hold a level of consciousness. This is not about in what side you are. If you are in the right side, in the low side, in the higher side, in the high class, it's about the whole humanity that let's reinvest and return to nature. Otherwise you will see what happened. And it's happening right now. It's not only what people are doing in manipulated nature. That's only another consequence of the same, same disaster. The disaster of the human race is one. Eight billion people, that is dysfunctional, how to get along with nature, including the ingenious heads and the ingenious geniuses of the planet with very few exceptions. The billions of years of evolution that it took for the planet to be able to sustain us and then in just a couple hundred years, the ways that it seems the irreparable damages that have been caused need to be healed. And you requested for those that have made profit off of the planet and other humans to please reinvest back into the nature that sustains us to guarantee a better future for us all. And also I want to see what your thoughts are here. Every child being born in full connection with the full potential to be connected to nature, to spirit, and then there is a lot of deceptions and manipulations that can, the fragmentation of the spirit, and then will you please teach us about that process? Yeah, once people are caught in an artificial system, that is actually, it's deceptive because it's artificial. And it's also deceptive because it doesn't get along with nature. If the system will get along with nature, it will be not that deceptive and it will not be that dysfunctional. It's that simple. But people have become so desensitized and so on sensitive and so unconscious that the system of artificial malfunctioning is completely predominant and the human race is just moving in the system that it doesn't have any level of connection and any level of functioning with nature. And so children who are born in the same system unless somebody comes and brings consciousness because it's not to remove children from this dysfunctional system. That's already something really, it's a wrong view, it's a wrong perspective. It's to bring children to come and get along with nature so they will be able, the new generations, by being educated in the wisdom of the world and the wisdom of functioning with the system that sustain us. So they will probably are the force that will create the change. But it depends on the educator. Who educates the educator and the functioning with nature? Probably the ones who know the wisdom of the world and the wisdom of the original wisdom of humanity. That's exactly what we're doing. So the question of deception is a system that is completely artificial that has no way to get along with nature. It proves that in this system, look I'm not an activist I'm not a pro rebel or something like that. That's not what we do. We're not here to politicize or spiritualize politics or politicize spirituality.  We only follow wisdom and we tell people to say look if you don't stop behaving and building an artificial system we all will be destroyed. As simple as that, it has happened before. It has completely this behavior of being smart and trying to outsmart nature with inventions, with technology, with science. It's not the first time that great civilizations have completely been banished by the power of creation because they just went too much.    We don't know how to do that. And we now have the conviction that science and technology is going to repair the problems that we created in the first place. No, it's about the system of malfunctioning. If the system malfunction and it doesn't get along with the system that sustained us, so then that's the catastrophic event of a human being. So the question of deception is why we are so convinced. This is exactly the deception. Why we are still so convinced that what we're doing is just fine just because we are barely sustaining a system of malfunctioning that, well, it's okay and somebody or some, you know, very, very reduced group of people is benefiting from that system. That doesn't mean that the system is not dysfunctional. The system and which is where it's wrong is completely dysfunctional and it's going to collapse. Whatever is dysfunctional and it doesn't get along with nature, it will collapse. Simple as that. And sooner or later, it will collapse. Simple as that. And we don't want to prove that the system is right through a very catastrophic event.  Bye-bye, everybody. This is exactly the deceptive. The deception lies in the fact that we insist and insist that the way we operate for centuries, especially the last century in this life, that that's a system that functions at work just because, you know, probably for some work, conveniently, but that's not guaranteed, it will not collapse. So while we don't avoid the collapsing of a system that is dysfunctional, and we correct it, it will be great for the ones who are on top and good for the ones that are low. And we will continue. The deception lies in the fact that we are still completely freaking attached to a system because it brings us profits and benefits and pleasures and, you know, power and all that. But it's a dysfunctional system. Completely. It's no wise. That's why we are here to say to return to the original wisdom and save what is dear for us is the planet, the functioning of the planet, and let's get along with it. It doesn't matter if everybody is different and want different things. Nature is nothing but a very, very big variety of things. And however nature, no matter how different is everything in nature, everything from the tiny to the mighty works in harmony. They are high mountains. They are low valleys and rivers and caves, and they function in harmony. Just as in this society, high people with high power, with high money, with high sophisticated knowledge and information. There are low people that doesn't know anything. You know, the tree has roots and they have flowers on top. And still in nature, everything functions cohesively, harmoniously. This system can keep the high ranking people and the low ranking people, but it still can function, getting along. As the laws of nature, the law of the high, the lower should be the stronger, you know. The stronger part should be sustaining the weak part. Isn't that the way it's in nature? Now the opposite, the weak and the deficient sustaining the stronger, it will collapse. A tree is not sustained by the leaves and by the flowers. A tree is sustained by deep, deep roots. This system pretend that the lower, that the weaker sustain the stronger. It will collapse. And its civilization is not guaranteed. There have been collapses in the past and the disconnection from nature and immature playing with god-like technologies is a recipe for disaster. And will you teach us about this relationship? I think this is a really great way of explaining it that the older brother carries this ancient wisdom and that the younger brother is out in the world creating, engineering, building, toying around and making all these cool things. But when the younger brother is disconnected from the ancient wisdom and doing that, it's again a recipe for disaster. Will you teach us about that relationship? Completely. The question of the younger brother and elder brothers and younger brothers, it comes to a very simple thing. An elder brother is an obedient brother. Somebody who is stuck, you know, stick to the rules, follow the principles, is rigorous, is reliable to the power as the beginning has been. And the younger brother is a younger brother but is a teenager. You know, like, you know, poisoned by ideas, poisoned by curiosity, by rebellion, by great, great creativity, it's vivacious, it's crazy, it's very thrilled, it's outgoing, it's just out there exploring the space, murder, broken down the atoms and getting crazy building, buildings that are just thousands of murders about so he can reach in his class the souls of God and say, hello, look how great I am and all that. That's the younger brother. He has tremendous ingenuity, creativity, curiosity, in vain so cannot think that are cool and sometimes are really ingenious. He has also his own wisdom to keep going in his own life and everything but he went crazy. So older brother including us, the ones who call wisdom that we were born in a country that honors and respect nature, most of us that are from my generation we are completely conscious on nature. I was born as a campesina, as a country boy and I learned from the land, from the way we were living the nature is our mother and I am in this business of spirituality ever since I know myself. The real spirituality is first you are the spirit nature is life force that is the spirit you should get along with honor, with dignity, with respect like you respect your grandmother but younger brother put the great mother in nursing homes and he go about his entertainment and his inventions and discoveries those in here the grandmother the grandmother dies in a nursing home that's exactly the disaster. Younger brother never lend the wisdom from the ancestors from the elders and that's why he goes about his craziness and that craziness is expanding like a pest like an infection, a pandemic and that will bring us to destruction that will destroy the younger brother the entire planet it has happened before because the mentality of the younger brother which is not in the mind, is not in the brain is in the spirit this curiosity, ingeniosity is he is thrilling instinct to discover and to find out, to explain is ancestral, is in the spirit and it has caused already many problems it's not only in this planet but in dimensions and it's in different times in the planet and the cosmos the younger brother has gotten crazy and it has created all kinds of things but also I'm not saying there is only a younger brother also the elder brothers have been thrilled by the younger brother's attractions and he also has felt and that's why you see many of the elders also fell into the same trap and you can see here in America and other places of the world there are no longer real, real people holding the original living wisdom of the earth and humanity and that's why people doesn't, it's completely forgotten with very few exceptions our race, if it doesn't have what you call the tutorial very clear eye on top of the younger brother he will get crazy, he will lose sense of proportions he will go so mad and crazy that to the point that destroys everything that's the reason why we come and tell what we say and I've been doing this for 50 years very intensely right now for the last 25 years look at what is happening fortunately I gotta tell that there is people who is getting it there is people probably like you they are really, hey, this is serious there's no longer a stop the game of madness, destruction and uncontrollable policing stop it it's time, we're not gonna have much time to repair right now we can only stop and correct, we're not gonna correct anything because it's probably not gonna be time for that the conscious living that we can embody for the process of healing it's within us, not outside of us and outside of us is where we sometimes find the deceptions, the entertainment and the drugs and so many of the things outside of us, but on the inside of us how do we heal from the inside our connection to spirit and nature and then how do we go out into the ancestral lands for healing as well and go on that process there are sacred spaces in nature the spaces with the water system with the rain system with the reproduction of vitality and the reproduction of all the vigor and nature is repaired constantly and the high mountains and caves and fountains on the ground currents of water and caves and the very original rivers and the snow peaks and the ice lands and all that in the Johnson Road rivers and oceans and mainly in the oceans, nature is repairing and renovating, nature is recreating, nature is recycling and everything if we mess with those sites and we damage those sites, it's like in your body you leave this damage and then your kidneys are damaged and then your stomach is damaged and your lungs are damaged and then it becomes a systemic damage, what do you think will happen with that then the whole body will collapse isn't it probably will less, so what we're thinking that by causing all these damages to the system of the world and we're going to repair it is stupidly wrong and so the human being being disintegrated because it's captivated by a system that is dysfunctional and probably it's not intended that way but it went that way for the lack of the other part, the wisdom that it tells you when is enough when enough is enough when you need to stop being foolish thinking that you're a genius the most foolish thing in life is that you believe that you're a genius when you are screwing yourself and screwing many others, that is called the worst level of stupidity that's exactly what is happening in this planet and then also and we're going to repair it we'll figure it out, somebody else from another dimension and the aliens are going to tell you what to do when it was simple from the beginning keep the harmony, keep the system recycling functioning, do not damage the structure of the planet, energetic and material structure of the planet don't damage it, so we will be able to receive the forces of the cosmos and you don't have to mess with anything else and you can have a great life there with money or without money but still you can have a great life there is more than money power and more than power is domination and all that, oh really? well that way you have a hell because then you start destroying nature and this is exactly the cause of this integration and the spirit that we were talking about since human has completely forgotten the first is the spirit and it's part of life force life force is the spirit, so we don't care about anything we only care about what we can see but the unseen, the invisible the supernatural, that is not that supernatural it's weird but doesn't mean that it's not natural and it's like every single human being probably is weird to himself because you are first a spirit and a body and the most essential thing in your life is your spirit isn't it? part of life force but if you start considering that you are first a spirit then you say I'm getting crazy, no you are probably re-naturalized, you lost the natural sense of perceiving yourself as a spirit and unfortunately people only record the sense of a spirit when they're going to die I'm going to die in a dying bed and then you rediscover something that you lost for the rest of the beginning of your life, on the entire life you lost the sense of being a spirit and then that is there to remind you, to prove you that you are the spirit because something is leaving, what is it? something is getting out, something came into the body to run the body, to run the life of the human and something get out, therefore you are a spirit and so when you lost sense of spirit you lost sense of spirit, you lost sense of consciousness when you lost sense of consciousness you lost sense of functioning and sense of purpose it's so simple, that's the wisdom and that's why the human being is disintegrated now, when the spirit is not functioning with the body harmoniously with the sense of purpose then that's what people is wounded as fragmented as fractured, as afflicted tormented, because all of this the spirit doesn't have a chance and that's why people are unconscious because there is no spiritual presence and they call spirituality all kinds of practices and all kinds of things, yeah those things are good and nice, I practice many spiritual things for most of my life but the first spiritual practice is that you recognize that you are a spirit directly and if you lost that that's why people are unconscious where there is no spirit, there is no consciousness how do we recognize that we are a spirit it's so natural, it's at hand like you recognize that flower and then you see the flower right there and then you smell it, the essence of that rose is the spirit body and essence, flower and essence that's exactly the same thing that the human is is body and is essence the flower is the body the essence is the spirit we are always together, we lost that consciousness I say wait to support you healing that will heal the dysfunctional systems that are how we are dysfunctional with nature right now and then what would it look like then for us to be at our full purpose because it seems as though we have with this great dysfunction many of us have a lack of daily purpose, daily meaning doing something that we find very meaningful every day so when we are fully embodied with spirit then we're surrendered and we get to achieve our track of our divine purpose part of deception in the human reality which is very actually discouraging and also the cosmicity is that the purpose of a life of a human being is not what the spirit has a grip on but it's the purpose that the official system has it imposed upon him in the mind and in his psychic and whatever it is not in the spirit so the purpose of a life of a human being is agree upon in the spirit by the means of intelligent power throughout a very very clear conscious agreement with the power that has created us delivering to being as a spirit we have a clear pure purpose in the spirit that is completely forgotten and it is not the same for every single human being once again here is the body the leader has a purpose to do 380 functions in an astonishing way probably more for the benefit of the body there is something still like people I want to do my own thing but even if it's your own thing it should be for the benefit of the whole for the benefit of the collective as the body indicates the heart does its own thing on its own but with the purpose and the benefit of the whole everybody can do something as long as as far as the collective and the reason because this went wrong is because that's the the national consciousness in the spirit and that's the agreement to function for the benefit of the whole there is no suffrage but it went wrong because the system of deception has imposed the poopers to the human being there is also artificial art the system is it doesn't benefit the collective it benefits the system but not the collective simple it's a beautiful way of looking at it all of the different cells in the body like humans on the planet how they all work cohesively in the body for the functioning and if with a on a civilizational level if they can also work cohesively with their individual purposes then in balance with nature then that can be a beautiful beautiful look you're living the original living wisdom of humanity the original living wisdom of the human race the original pure wisdom of nature you are every single instant as long as you're in a body as a spirit you are living in on it the wisdom which is keep the body alive is no different that the wisdom runs in nature and runs the entire system of nature you are there on it as the most extraordinary proof the functioning and the life of the body there you go and then you're asking what is the wisdom it's not in the books it's not in the you know data on the collection of information the wisdom of this planet of this dimension which is the reflection of a celestial original wisdom of the spirit is right there in your body and the spirit is coming to work with it as it's coming to work with nature and people is completely unconscious when they have health issues and real serious diseases and challenges now they see that the body doesn't function and then probably the spirit gets completely disintegrated now they have a problem and that's probably the only time that they pay attention couple other thoughts on the way out I want to I want to hear your thoughts on this so when we tap into the cohesion of of being connected to nature on a moment to moment basis we feel expansive we feel beyond we feel all that is we feel mother we feel the source the spirit and if we can hold that on a moment to moment basis you said that that was grace yesterday you said that was grace and if you can connect with grace on a moment to moment basis then that can be one of the best ways to live consciously and function consciously the first thing we tell the state of grace is that you the spirit is part of that perfection we are part of the mother power of part of the of part of God and the spirit we are part of that we were born and created as a part of God and that's the first level of grace if you're consciously you're part of the power of grace so then your consciousness will be recovered some of the many spiritual practices of this world especially in the younger brother they supposedly are pointing out to it but yet people don't change their own behavior when they discover and they have this direct very simple natural experience that you are the spirit part of the great great power then your behavior will be completely changed and that's exactly the original wisdom since probably people have gone so far away from the power and we did not follow the most important law function in which is reciprocity reciprocity means to correspond one and another in a loving association you call love was reciprocity if we don't reciprocate with the power that has created us we call the mother power we have to correspond with the mother power the first level the way we correspond to the mother power is fulfilling the agreement that we came here to fulfill and obeying the natural law function and created by it we did not create the laws we did not create the principles of function and they were created with the creation itself if we will loss how to correspond with the power naturally functionally where we will malfunction with everything we don't correspond with anything we take, we take, we take we don't care therefore the natural law the original law of reciprocity is the power that holds harmony integrity and balance if you don't reciprocate with everything and then things will collapse it's like would you have a relationship with somebody you give and give and give love or you take and you take and you take and you take the so-called love in a relationship but you don't give back what kind of relationship is that the real relationship between humans between nature between power the power of creation that we call the mother power is based on reciprocity you take you give back in every possible way is that what we do we have a disposable planet mentality yeah we use in abuse and then we dispose extraordinary unconscious and irresponsible and there's big delinquencies you use this word that we have to pay our taxes that we're delinquent on the taxes as in the connection to nature that we've been disconnected from fragmented from well the taxi thing is translated into the Django brother terminology to make that not that weird more connected with the dysfunctional system to follow which is the monetary system the financial system the money system is like yeah pay the taxes to the ones who you know are the organized system of finances and supposedly the system that runs the budget for everything to maintain everything but it's to maintain a system it's not to maintain nature so the system of monetary financial stuff if part of the budget is in best the to repair nature and to maintain nature so in other words pay the taxes to nature the same pay the same way to pay taxes for everything it's great that you pay taxes because it's part of you know the collaboration and the great part for maintaining a system that is necessary for humans absolutely but part of that budget should be uh dedicated to repair the maintain nature because most of the profits in model most of the business and most of the money is made out of using of using nature and destroying nature and exterminating nature so why now part of those things should be in best in repairing nature it's very intelligent actually it doesn't go against anybody probably it's inconvenient but just for a while people get used to pay taxes for everything taxes well that's amazing it's good because in maintaining a system but it's not maintaining the system they maintain that system that depends out of it and that system that is close the system that really sustain us pay the taxes to nature the same way you pay the taxes for everything and then we will be in balance or at least we will stop the crazy destruction that we are creating if we pay taxes to nature in many various ways versus maintenance maintenance look at this if you have a little machine the lawn machine to cut the lawn and keep it beautiful it needs maintenance it needs to pay the handyman the operator and everything else in it so what's the kind of money that we invest in maintenance and nature if we were taking everything from nature what's the kind of work what's the kind of investment that we do and workers and labor and humans that are completely dedicated it should be a department in this country and in many others that department on nature maintenance and billions should be invested in it and cool continue with your business but you also are investing in maintenance and repairing nature the same thing that you do with your refrigerators with your computers with your sophisticated cars and planes and quantum computers do it with nature and then things will be better I wrote this down in the notes during the workshop that it would be interesting if 10% of every single venture capital fund over 10 million dollars had to go 10% of it had to go towards this maintenance of nature budget around the world I think that would be very helpful things like that also when you say pay your taxes you're making it clear you're not going to the ocean unconsciously taking a selfie and then leaving this is a go there it's not a selfie, it's a selfish you go to nature put your hands take the picture probably before committing suicide because that hasn't been the case and a beautiful setting in nature and you go that's what's so wrong with us that's the title of my next coming book called what's wrong with us this is the level of insanity what's wrong with us I mean could you bother to just go back to the grandmother and say grandma how you doing I love you it's ridiculous to be there or we can only have sex there in all kind of ways and get naked and get beaten by a charge or something like that and then the selfish before committing suicide what's wrong with us nature is there to be honored to be respect not to be only used in the views in a society like this one of the most powerful and yet cynical and pathetic and beautiful world is word in language it is used in the views more than any is abuse that word is exploding in so so so so many ways with animas in relationships with everything verbal abuse, psychological abuse sexual abuse all kind of abuses are levels on that might be true but what about the abuse to nature nobody says anything about the abuse to nature abuse to the system to the grandmother mother earth that sustains us all what about the abuse the collective global abuse the biggest abuse of all what you don't say anything about it we do we are abusing nature we are exterminating nature the system that sustain us because of the lack of consciousness the lack of responsible behavior and because we have lost sense of the spirit sense of being and sense of functioning and the last thing I think I would love for you to touch on quickly is on a big picture level of what's happening on the planet it is in many ways seems at times that there are forces that are at play on this beautiful planet that are beyond what is here in the physical world and so what is sometimes it literally feels like light forces versus dark forces that are at play on the planet and where do they come from how do the dark forces come within that spiritual fragmentation when we are fragmented disconnected from nature that's where evil comes in teach us about that the spirit of fragmentation the first level is the loss of sense of spirit and then let's say shocking irreparable experiences because of not knowing and not holding ourselves as a spirit just with the characters and personalities no sense of spirit whatsoever so that in itself creates a serious serious fragmentation in the spirit the spirit is inability to come and perform it's real function so that fragmentation causes the others you know this is that because we don't operate as a spirit consciously then we will start creating sub-levels of energy sub-levels of quality and our own development which is levels of energy and density which is coming from mentalizing and mentalizing the lowest kind of energy is mentalizing psyching things out like crazy I'm using mentalizing and I'm using psyching out you know especially with experts the mentalized, over analyzed they cannot be natural anymore have some sense of proportion and common sense that is the most common sense from nature we are a spirit life was a spirit and so when we had lost sense of spirit sense of being sense of function with nature you know so then everything gets crazy and we create a dense operating way that probably attracts the same from other planes from other spaces from other dimensions and then as that is degrading and degrading even more probably attracts attracts and magnetizes something that you can call that forces at place forces of evil forces of that part, yeah but we are calling for it we are the ones responsible for that let evil be there in its own function, God put evil there to do its own function and what we do we don't do ours it should be intelligent and divine evil is there for the purpose who knows the Bible says and some of the accounts of the Bible and your wisdom the wisdom of the most of the Christian world and so now as they say God creates evil for the purpose probably is to prove us if we are faithful and conscious if we are integrated and function intelligent intelligence is part of presence of spirit if we are stupid probably we are attracting that evil take control of us and sabotage us and manipulate us in its own way it is totally up to us we are the ones who bring the problem we are the ones who can solve the problem with wisdom with consciousness and with responsibility we will solve even at the times that we live in and critical times and the times that are completely crazy despair and confusion we can come to senses we can come to terms everybody with his own capabilities and gifts and wisdom and stop the problem if we cannot repair fully at least we can correct and bring a better let's call future for the new generations this is exactly with the ancient wisdom of my ancestors it's necessary in this world of the Janger brother the Janger brother has to stop being naughty and being spoiled and come to visit the grandmother and receive some consoling not only with the psychology but with the grandmother wisdom wow this has been definitely one of my favorite sit-downs that I've ever had on the show thank you so much thank you for having me we are very grateful for you and one moment I'll close the show quickly I just want to say everyone please please do check out the links in the bio below to the KoginkasewaLunaFoundation.org as well as the Facebook page the amount of times that you're traveling around the United States there's an Asheville in Florida in the California so please there are plenty of opportunities to come and partake in this ancient wisdom and we highly highly recommend you do so there's also other videos as well of mama giving talks online so please do check those out and share this type of ancient wisdom with your friends, your families co-workers, people online go and pay the taxes to the ancient mother, to our grandmother to source the spirit to what sustains us thank you very much for tuning in we greatly appreciate it and we will see you soon thank you thank you so much


Okay, happy Sunday. I hope you're doing well and welcome to this outlook for the week ahead Well, I'm going to talk to you a little bit about what happened with the OPEC meeting this weekend We've got an update on the COVID rules in China We've also got interesting commentary coming out of Bank of England and ECB officials Which I can update you on and then for the week ahead We've got Chinese trade data We've also got rate decisions coming out of the lights of the RBA and the Bank of Canada And then we have US PPI of course always a focus for inflationary conditions for US policy and that comes out on Friday But let's dive straight in and let's talk a little bit about OPEC who have responded to surging volatility and really growing uncertainty In the global crude market just given a number of different things at the moment from a growth perspective Russian sanction perspective from a Chinese demand perspective, and they've basically decided to keep Production unchanged doesn't come as a great deal of a surprise This was pretty much in line with what we were expecting This does follow that hefty two million a barrel a day reduction that we saw in the prior meeting The other thing of course that's happening at the moment is to do with Russia So European sanctions on crude exports from Russia They're going to come into effect on Monday This is where the EU will ban most seaborne imports of Russian crude and block anyone else from using the region's shipping or insurance services for the purchases of Russian oil unless it is done So below the price level of $60 price cap The other thing that's really quite key at the moment in regards to oil and China work out the future direction is And the decisions from OPEC is what's happening in China And we have had some largely positive news happen over the weekend where shanghai has eased some of its COVID Restrictions joining other top tier cities like Beijing, Shenzhen, Guangzhou Authorities have moved to accelerate the shift toward reopening their economies And of course this comes this time last week where there was quite an outbreak of a number of protests across the country Just to give it a bit of context pretty mind-blowing figure I saw here of those four Chinese cities Shanghai Beijing Shenzhen Guangzhou if you were to put their Population together as one total figure just those four cities are the same size as the entire United Kingdom So quite a big deal of course a lot of these places are key manufacturing hubs Technology for Shenzhen and the other thing we've seen here of course is for Apple Which we saw some of their production being impacted by these protests and actually what's happening here is restrictions Are also being rolled back in shengxiao city, which is Apple's largest manufacturing site in China Otherwise some other things to update you on and this is some central bank cometary First of all coming out of the Bank of England where according to smarty dingra Bank of England's benchmark interest rate Benchmark interest rate should peak below four and a half percent if the central bank wants to avoid a deepened and prolonged recession For context the Bank of England been raising rates for eight consecutive meetings now The benchmark rate is coming at three percent Obviously the main focal point being to tackle inflation the next meeting coming on the 15th of this month But these comments here of course a little bit more on the dovish side But coming from a dovish member if we just look at the NPC board here The top being the most dovish members ten reiro Dingra and Kunlif man and Haskell being the most hawkish So this type of cometary doesn't come as a great deal of surprise Flip over to the ECB pretty similar really and the head of the central bank of France Francois Villarrois the gal has come out and said the central bank should raise interest rates by 50 basis points So again reinforcing expectations that the ECB are going to slow the pace of monetary tightening Much like in a similar vein of what the markets are pricing for the Fed at this present point in time And then just taking a quick look at the week ahead. What have we got in store? Well, these actual PMI numbers on Monday are all going to be final prints So shouldn't really move the needle a great deal. However, if we skip on into Wednesday We're going to get Chinese trade data November was a month of course that was plagued by Chinese COVID lockdowns as case rates have soared That in turn sparking some of that social unrest in several large Chinese cities and with China being the second largest Global economy its data is going to offer us a bit of a glimpse into not only the domestic Scene but demand as well coming from the likes of the Western world in mainland Europe and North America So that will be particularly interesting data. There's also inflation data coming from China as well The other major thing happening this week is on Friday here You've got US producer prices, which are expected to ease in November providing fresh evidence then for the feds That they're drive to bring down inflation is Paying for issue or coming to fruition headline producer prices are expected to have risen 7.1 percent in November from the prior year and that actually Would mark its slowest increase since May of 2021 Excluding volatile food and energy so the core reading for PPI is expected to have risen just 5.8 percent a step down Significantly from 6.7 percent in October and that would be the slurs pay since June of 2021 Again as far as markets are priced Despite the jobs data that we saw at the end of last week, which saw that quite extreme negative reaction But then recovered into the close on Wall Street Markets are still taking the lead from the comments from Fed chair midweek last week from Jerome Powell Who talked about then come December the increment change of policy tightening is going to be slightly smaller I 50 basis points and that's still priced at around an 80% Probability at this present point in time with that meetings on the 14th So remember this month you've got the Fed on the 14th the ECB in the Bank of England on the 15th So quite a lot to come in the week or so ahead And then on Friday just back to the calendar You also get the December University of Michigan number could be quite interesting US consumer confidence again Expected to soften and these are the preliminary numbers So markets will be keeping in half an eye on those the other central banks, of course I briefly mentioned are the RBA they'd like it to height rates again on Tuesday when they meet money market surprising in around a 70% Chance of around a 25 basis point rate increase and then for the Bank of Canada They come out on Wednesday and markets and economists though this one could be a little bit more interesting They're pretty split on what we're looking out for and whether or not the central bank will opt for 25 or 50 basis point Rate change. So, yeah, that's it. That's everything to look out for this week I hope that was useful. Don't forget to sign up for our free daily newsletter I'll drop the link on the video for this if that's going to be useful for you Otherwise have a good week ahead and come on England playing tonight against Senegal