I would like you to consider a question. Why is it that wellintentioned good people who are trying to solve problems often make decisions that have terrible outcomes . We said we are going to change the world. Did week . Probably, a bit, probably a bit for the better. I think at the same time some decisions have led us to better consequences. As joy just said we live in a fragile world and as a class of complex and difficult situations, we as a society have yet to figure out. At a personal level i make decisions every day. I i bought this car a wild bac. It is a hyhybrid, i tell you i have nidea if the co2 i get for my 70 miles per gallon has a benefit to all ous outweighs the cost of creating this car in the potential pollution impact of the battery after it gets stored. Maybe if we hadnt done that battery we would explore new technologies that have less of an impact. This is my mom. If i had bought that scarf 100 years ago, fine, no problem. Today i dont know if that scarf was made in a sweatshop using cotton that had pesticides grown on it and there were huge amounts of co2 as it travels froa long way away to the place where i bought it. My choices have actions at a distance and i have no idea what those impacts would be. That is what i am talking g about, you have a new superpower. It is not all negative. The choices that you make have Ripple Effects through the world. It is like a fish in a pond. Where our brains involved and in their pond, everything going okay, a river opens up. Connecting that fishpond. And and our action has outcomes that distance. It is about the actions we take. When we consider those actions, the path through which those actions would become reality, how can we be responsible for the outcomes of our actions if they are invisible . The larger ocean in a small pond, we simply didnt evolve for that situation. I am lucky i went through the computer revolution when i was a kid. Computers were big old things nobody cld use and my mom didnt know the difference between software and hardware. We went through a massive democratization of computing technology. We are in the same cup today with ai data, that new techchnology staff. Ai is done to us. We dont havave control into i. They get a data visualization, and asking them what are you frustrated about . If technology could solve one problem, what would it be . Over and over again i heard a similar answer. This is why i know what i am doing. I have been building Machine Learning applied systems a really long time, over 30 years. I was funded by the human genome project in graduate school, 100 million budget for the government, thousands of Machine Learning models providing learning, who would have known, still with us so many years later. My Machine Learning friends know what im talking about. I believe this background has given me an insight. There has something been missing all these years and that something that is missing and we are coming up from the technology. Instead of putting humans at the center of the equatioi am honored to my backside is honored and mailin worked closely with doug. It is intelligence augmentation. Flipping upside down to bia, puttingg humans at the center f the equation again. When i interviewed all these people i found a decision archetype. What is the decision . It is a thought process that leads to an action. That action in a complex world flows through some stuff. I dont know what buying that scarf is going to do to the world. I dont feel very motivated beusi cant see that impa. Its not visceral and present for me. It doesnt grab my primate brain in a way that makes me think i really need to buy that type of car. I cant see it. The data stack today, the ai stack isnt giving that. This is my dog, im training him toto be a service dog. I had him his whole life. I had this thing happened to me. A trainer teaching me to train a service dog and she taught me about abc and my head exploded. The executives, talking about an antecedent which is the context, behavior and the consequence. This is a universal archetype. Not just one way to think about how we might use ai, and i will ll you about that in a moment. But this is the way to think lowest friction to how humans think. Busy people live in complex environments. They dont have much brainpower to learn about optimization and inference methodology or any of those things. We have to meet them wre they are and the fact that we are not created a giant cultural rrier with people at the head of government and even me. And try to use evidence and data to make sure those decisions have a Ripple Effect that is good. The nsf proposal, they have to decide what crop to plant. If they are productive and they have fewer migrarant workers. And as they talk this through, you hear much about my dog here. There is a behavior. Down the road, my dog is a dog but for us and what makes it special iwe can think through this. That is limited and we need comperelp. And imaginative process. The context willead to some results. If you are a member, remember this template and whahat is co about decision intelligence is because we start with humans, i can teach you something you can use. That is my promise if you stick with the talk. How do we make decisions, i only recently learned this, in a complex world going back for millennia we dont think througthe consequences of our decisions very deeply. We are more likely not to think through and use social signaling, look for someonene o looks successfully and society, donald for prestigious and simply copy the decisions they have been making. That is very effective, hugely successful for the human race and that is what separates us from many other species, we are great copiers. Cultural evolution theory says we develop behaviors and patterns that any individual cant t understand but society like the unconscious process of genetic evolution we use cultural evolution to come up with these behaviors, we are programmed to look at some prestigious or dominant person and do what they do. That was great f a few millennia but the sitituauatios changed. If there is a bad actor here or here and they tell us what to do and they are smart they can subvert our behaviors. They can influence us to make decisions to benefit them, they are smart about the situation. We cope with this big ocean that is fundamtally different. There is new fish in the way of thinking through problems at a societal and crowd level. These have complex system dynamics. Large companies, large artists get 90 and massive inequality. Action at a distance, intangibles are important too. Money, size, price. We tend to overlook happiness. We built a decision on what hadnt had one known feedback loop that involved something tangible. We must talk to the sociologists, cultural evolutionists to understand those soft factors. Decision intelligence creates a roadmap for how to do that. The other thing i didnt say is the future is no longer like the past. The black swan, the problem when we assume the past and future are the same and we dont realize the situation, all thswans used to be white, the black one i believe ai which im going to tell you about can solve this problem. I grew up in appear go of technology optimism. We were all sharing our code and the internet was going to democratize reality. Remember steve . We have a dream but i dont think we have realized that dream. I ink decisi intelligence will help us go there. I think we have created a number of links in the chain, data machine, learning, collaboration, the internet, social media and one more link we need for a lawn nonlinear impact. We will start to talk about that little practically right now. How do we do that . We start with people. We dont say where is the data. We dont say we cant do this ai likthing. Data is great. There is a huge amount that is no data set whatsoever. We are good at knowing how actions lead toutcomes and your homework is to go home, ask a friend who didnt come to this talk how they think about a complex position or the promises they talk about actions, the intermediate effect and that will lead to some outcomes and they will talk about the context. I sit down with a Diverse Group of experts, old, young, gender, rarace, and say what are the outcomes . I know so Many Companies with big projects that never sat down and brainstormed through the outcomes, okay . I consult with Many Organizations and say what are you trying to achieve . The list of outcomes is different for each person. You dont nd technology to get better. You just need a brainstorming process when you think through what are the outcomes we are trying to achieve . Is at higher revenue . Net revenue after two years . Is that a military advantage . Do wwant a military advantage that doesnt create a backlash that will hit us, what are we trying to achieve . Make sure you ask that question, brainstormed through the action. Many folks dont take the time to have an open brainstorm whwhere they allow bad ideas a funny ideas for the actions that might achieve those outcomes. Move all the blood to the creative side because when the blood is in the creative side or analytical side over here you dont have room for the creative side. Spend some time being creative and spend some time being analytical. As we democratize ai this is the pattern. I saw greta. We have a Climate Crisis in the way we solve this is really simple, stop worrying about analysis. At the very least pay for some trees. There are organizations all over the world that will take your money and buy trees. There will be more biomass and ththat will sequester some carn and if enough people do this, i nt know if she said t shke i havent send any money to a Tree Organization yet. I cant visualize how the money i might send leads through a chain of eventss to some outcome. If im going to use ai, i want an interactive, fuexperience. This is what i think is the future of ai. It looks like a video game and i hope we can do some of this, we can walk through these spaces and what are we doing in these spaces . We are experimenting with actions we might take and letting the computer help us understand the chain of eventss that sets in motion, valuable at a personal level and highly valuable at the organizational level. Lets see if this wos. I have a lot of fun counting immunity. There is no purpose whatsoever but to show this. What is going on . Trying to make the decision as to how much money to sequester carbon. As i changthis decision this data is telling me about the future that puts in motion. I change my decision, changes the number of trees, heres the biomass, here is the total atmospheric carbon. There is a chain of eventss. Linda ritchie is the expert in the background who has done some research. Barry hayes might have done some research. Each expert has an opportunity to say our actions connect to outcomes and i cannot only change my decision but also change whether samhan is right and who o i can trust because can see different people, different experts claim different things. Ultimately i can click on a name and go to a site where i can see where they are making their case, a model for how buying trees leads to outcomes that can help us and it will be like wikipedia. A site that is curated that we can use to understand the situation. This looks like a Business Intelligence dashboard, like stuff we have been building for a long time. Let me tell u it is not. We are not looking at a data set here. We are looking at the future. Really summarizing it to understand it. In the background depending on our choices we have a physics engine generating the implications of those choices. There is a lot of forest going on and as i change investment or use ted browards opinion i can see how my decision interacts with the situation as they characterize it. This is a universal pattern, an example e of something you do your head 500 times a day Large Organization with understanding the impact. These are Machine Learning models here through triangles. We might have built a machin learning model that detect whether a Computer System has a current intrusion happening right now. Machine learning is widespread with an intrusion detection and gives us the score, goes up to 95 . There is an intrusion happening right now. Heres the type of intrusion. It has some spaghetti in it. Is that spaghetti how you are thinking of things . We are using invisible mechanisms today, words and text which is inherentlyly linear. We need a blueprint like this. It shows how Machine Learning sits in. We send intrusion information to the police and investigate the intrusion and that will flow through the cost and benefit and impact some outcomes. If i call the police every time it might be crisscrossed. I tried to call the police only when it is necessary. This is a decision model, part of a a big nsf project, got 23 phds, finishing up the proposals this week, cross your fingers at we win this. It will be a National Center for excellence in ai and agriculture. What is important is i didnt have to explain decision intelligence to anybody. I simply sat down with my diverse team of experts and said what is a typical farmer trying to achieve . At first they said they want to be profitable at the end of the year. After brainstorming, is that all . They wouldnt take any action that will put them out of business. That is the second goal to balance against that and we talk about the action farmers might take, make choices about how to spray their crops, the choice of crop, this gives us a map to understand how the Machine LearningTechnology Fits together because a couple models tell us how precision spraying will impact the yield and another model says the amount or type of diseases or contaminants based on our spraying and these a sensors farmers have on the field that they can use with ai to interpret the sensor data to know if there is a pathogen, as earlymorning as possible so that we can spray little as possible to achieve our goals in c cost and longterm viabily and a climate pollution point of view so it is kind of spaghetti but haviving the spaghetti on paper is better than what is going on right now which is invisible in peoples heads. This becomes an artifact and we talk about divine thinking, we designed a decision, a decision is something we can move on, pretty radical but when you do it you realize we can bring engineering best practices through decisions, you can continuously improve it. It acts as a blueprint, my stakeholders built this. It connects them to the ai people so they know where they fit in. We had been working comments or so before we began the diagram and i dont think anybody knew how it fit together and might have to explain it, we have a map. You know how it fits together and where the ai will go. What is going on with decision intelligence . Those of you who have known me a few years now that it has been quite the slog, flyining l over the world trying to talk, sometimes theres 3 people in the audience trying to tell people this story. I am happy to the extent this matters, gardner has decision intelligence. I consider it t a big accomplishment. There is an article by ibm, google trains 20,000 people, shes the other big evangelic and then theres a bunch of companies that have started in specific areas, pure tech and water company, curriculum labs, medical devices, these are a people who recognize if they go beyond the Machine Learning model, put it in a decision model surrounding the Machine Learning model that connects from actns to outcomes that will help them be more successful. It is really cool. I love that get that this is how kathy defined di. Discipline ofurning information into bter actions at this scale, a slightly different way of saying it but it is the same thing. If i make this decision today which leads to this action what will be the outcome tomorrow. Lots of people have different approaches. This diagram is mine. Other people have different approaches, some people dont come protected, sociologists and economists and m more. What is common to all of us is we have taken seriously the action to outcome task as the core way the technology can science interact with humans. We also made it to hollywood. Who knows what show this is . What is it . A good place. This is ted denson. Im not going to do the spoiler. If you havent seen season 3 this is episode 10. I recommend yotake a look at it. He basically discovered di by the end of the serie was the big reveal, the mystery. Which is so cool. Whwhat does ted have . Who knows who this is . That is janice. What is she . As she human . Now. She is in ai. Here is ted tryiying to understand why there are all the negative unintended consequences and heres janet helping him. How cool is that. I dont know if they read my book. And it is so important to the future. With great power comes great responsibility. You have the ability to take action as an individual and as an organization to have giant impact. I am an optimist. I believe we are in the beginning of a solution renaissance where it is not just a ai, but all these technologies come together under a common blueprint, system dynamics, complexity, computational neuroscience, cultural evolution, all these fields, many originally viewed as soft fields that lived within their little silos, deconstructionists of thousand years of being specialists. We are entering the age of synthesis and those of you who are neogeneralists know what i mean by this. We are the experts, we focus on the outside these boxes. It doesnt matter if we know the math with operations research, we know what goes into it and what comes out of it. In some version of di, how to glue that to gather to crystallize solutions where we understand the solution to water impact poverty. A solution to poverty impact the status of women and those impacts hit all of us, they had governments, they hit democracy. We call these the Sustainable Development goals. The ly w way we can solve them is to have a new approach to understanding how actions bounce around through the whole world and ultimately lead to the best outcome. Thank you. [applause] we need chairs. Do we have a chair transported . The shock that you finished under the time. One question, do you have a particular case study that shows how this works in actice . The example i showed was farming. We built an additional model, the subsaharan african country, it was a pulmonary study, in two places. You also had to stimulate the police. That is not enough for some assistant to take a vicious cycle of conict. How long was this . The causal change is for 5 minutes