Stanford Webinar - Forecasting Disruption

we would like to take this opportunity to officially welcome you to today's session forecasting disruption how to think about the future in a rapidly changing world with Bill Bernett and Cynthia Benjamin now we'll turn it over to our presenters for introductions thanks Annette that's great um happy to see everybody here we're gonna have a really interesting conversation about the uh the future of you know technology in this crazy rapidly changing world so um we've got a couple of amazing pres well one amazing presenter and then just me let me let me introduce Cynthia Benjamin she is the co-founder and chief strategy and Innovation offer officer of together senior health which is a digital health care company working in the um Alzheimer's and Dementia space she's also been a lecture at Stanford for a bunch of years um has taught a couple of different programs a fantastic class called me 101 visual thinking but currently a class me 297 that is called forecasting for innovators and she's going to be leading us through some forecasting uh strategies U for this particular webinar thanks Bill um and let me introduce Bill Bernett um bill is uh an adjunct professor in the de Design Group at Stanford um he's actually been the executive director of the uh the design IMPACT program and undergrad program for gosh a long time B you're GNA have to remind me how many years about 15 about 15 years um and before that uh Bill had a distinguished career as a design leader a designer and a design leader at Apple at counter toys at several startups um and so has a depth of experience in in uh design and design education he's also a co-author of a book called designing your life which has uh come out came out of Stanford but really resonated deeply um across a wide swath of folks from people um thinking about what they're going to do coming out of college to uh what they might do in their oncore career um and then a second book designing your new work life um so belill H really happy to to share this webinar with you yeah this is going to be a lot of fun um you know in the designing your life curriculum we think about five-year Futures and that's actually what we're going to be talking about here but we're going to be talking about it through the lens of design thinking and also technologies that are impacting our world today so for those of you who you've probably heard of the phrase design thinking or maybe human centered design is what we used to call it um we have uh started the David Kelly who started the D school at Stanford our Institute to teach design thinking basically to the world said design thinking is all about unlocking potential and the creative confidence of of our students David's book creative confidence that he wrote with his brother Tom Kelly uh was also a big hit um and you know this idea of design thinking although the D school started in 2006 our programming design goes back to the 60s all the way you know back to even 1957 when we taught the very first class um uh in design and it's always been a mixture of design art psychology sociology we like to think about designing and designers way of thinking as as a as a powerful problem solving tool it's a process we say you don't start with a problem you start with people you start with empathy and really try to understand deeply what are the what are the issues that people are facing and what are the ways in which you might solve some of those problems you know we're going to talk a lot about technology and Technology Futures today but both Cynthia and I have share the opinion of lots of startups you know start with a technology first and then go try to figure out who needs it in the design thinking process we would do the exactly the opposite first we try to understand what's the real deep human need and not just the need that people describe when you talk to them but what what's really going on past what they say and do to what they really think and feel so we start with empathy we redefine the problem we come up with lots of ideas because we know if we have lots of ideas we'll have better choices and then the whole idea of prototyping of Designing little experiments to to to tweak the future and see what it's all about prototyping and testing is the strategy for building our way forward so design thinking it's kind of the undercurrent of everything we do in the Design Group at Stanford it's a really you know it's interesting it's a it's a dynamic approach to problem solving because we use lots of you know techniques like brainstorming and mind mapping and we'll talk about some of those today but it's also using prototyping and and Rapid cycles of iteration and experimentation to figure out how to increase the innovation of outcomes but more than that it's a really great approach to problem finding and you know one of my favorite quotes from Peter duer the sort of business Guru you know management Professor um is um there's there's nothing quite so foolish as doing something very very well that never needed to be done in the first place and that describes a lot of the technology startups we see in Silicon Valley that start with some cool piece of technology and never find a need for it so problem finding is where we think there's the highest leverage when we reframe problems based on human needs and we use ethnography empathic observations and other techniques that we borrow from anthropology and sociology to truly understand what users need and what's the best problem to solve and because of that we believe it's been it's become a new perspective on value creation because when you can match a human- centered need to an actual technology and into a market that's that's large and robust you have you know a really fantastic way of creating Innovation and value creation So today we're going to talk a little bit about this idea of forecasting and design thinking because you know the needs and design principles that we use to create startups or new products or or new actions in the marketplace these change over time and certainly we're we're in the period right now with things like AI chat GPT robotics automation where where things are changing rapidly and so the needs of of people consumers organizations uh everybody the needs are changing rapidly over time and if we don't have some way of putting kind of a structure around this or at least a a framework around how we think about the future we can we can really fall behind and so forecasting changes and tracking technology we think is really critical to any any design or innovation strategy and that's why for oh I don't know know you and Paul Sappo have been teaching this class for over 15 years in the Design Group we really support the notion that we have to not just think about what do people need today but what's going to change as technology evolves in the next five 10 even 50 years so that's what we're going to be talking about um and and Cynthia why you know you're the you're the expert on this on this subject why should innovators you know and people who might want to come to the workshop we going to be running in March um people who might be the CTO or the person in charge of the Innovation organization at their company or somebody who's um an entrepreneur thinking about uh the application of new technologies why is it important for them to think about their future well for uh it's really important for a lot of reasons if you want to uh be competitive if you want to bring real Innovation out to the marketplace um you know everything is connected right it's both obvious and and not right A lot of times we think about our Innovations in isolation like if I just do this cool thing you know better mouse trap will you know people will beat a path to my door but in real life everything is connected and so it's important to think strategically about the future um and and you'll have a real Advantage if you understand the context of your Innovation both how we got to this place the history of it and possible futures um the one of the reasons that we apply design Thinking Tools here is um the very first thing youal Bill talked about in design thinking it's it's these are are pro tricky problems without a lot of boundaries and um and design Thinking Tools can be really helpful in that context um and you know if you want to build Sustainable Solutions that are around for a long time not just for today it's important to think about the context of of your your Innovation um and you the biggest problems are pretty complex if you want to have real impact in the world applying these kinds of tools to to bring some boundaries to the problem to think creatively about Alternatives and not just build on the first hypothesis that pops into mind um these are these are great tools for for thinking that way um and then lastly this this last bullet it's kind of important the future can have a range of possible outcomes right a lot of times we think about forecasting in the same way we think about prediction and it's not about predicting the future because that's you know we don't have a crystal ball and in fact actions that we take today can impact the future actions that we take tomorrow can impact the future so there are a range of possibilities out there um not just one and so if we're thinking strategically about um how we want to play in the future how we want to win in the future how we want to influence uence the future it's important to understand that range of possible outcomes and that cone of uncertainty that um that I'll refer to again later um and and then you can decide where you want to play and where you can have a real Advantage um so let me just put a little bit of a framework out here that we'll talk through today and I'll talk through an example as well um a lot of times when we start uh thinking about forecasting um we will pick we will Define a central question and what I mean by that is like what's the area that you want to be thinking about um a lot of times we think about oh what's the world going to look like in 20 years which is an interesting question but it's it gets so many variables that that it's it's hard to to wrap your head around much less make some predictions about that can be useful so um we want to make this useful we want to make this something that you can take away and take some action about if you're thinking about you know 20 years from now what's the world going to look like that that that's hard to that's an interesting conversation but it's not um not anything that you can really bring into today and take action on so we want to focus on some boundaries about what is you know what is the question that we want answers to um in this particular exercise um the next thing that that we spend a fair amount of time doing in class and obviously we won't spend a lot of time today but talking about the context of the space that you're looking at figuring out how we got here um and and doing some research doing some background and or bringing in experts who know the space that that you're playing in it's important to understand the context so that one you don't reinvent the wheel um which we see a a lot of um you know people come coming out with some great Innovation turns out somebody already did that and in fact maybe they failed a few years ago and you could have learned something if you had just understood what happened with them um uh so so kind of getting getting the lay of the land um then look around for what are the drivers of of change in the space what are the key elements that are going to drive change in the space that you're interested in and pulling out some insight into you know which which ones are important which ones are going to have the biggest impact where's the biggest uncertainty in the space going forward um and and pulling you know pull extracting those out so then you can think about what possible outcomes could there be what what are the different Futures that could happen in my space um which ones are most likely and and putting some structure around that can be helpful so that then you can think about your options and take action why do you care how will you participate in these Futures if the the vast uh range of possibility um uh if the range of possibility is vast how will you manage that how will you learn about the future what should you be looking for between here and there to understand which of these possible Futures is likely to emerge so we have this structure that we use um in the class that bill referred to um me 297 forecasting for innovators and you know we'll take St students through this week by week and we work with we work in teams um and it's a great way to both explore a new area if students want to explore someplace new or to go deeper into an area of expertise um so I'm going to take you through this process and we're going use an example as well so the first thing as I mentioned is about a central question broadly defining the space with a Grand aspirational Vision um and characteristics of a good Central question are are to make it interesting essentially you're not hypothesizing a future but you are thinking about what's a good question to ask that's going to stimulate thinking and thought-provoking it depends on this it depends on that um uh it might be a hypothesis but the point is to generate generate learning at at this first stage so we're going to talk about robotics for this example here today um and a question that people might set might ask would be what does the future of Robotics look like which is interesting but that's kind of a researchy question and it's kind of boring how about a question instead of when will a human marry a robot so and I like that question because it it makes you kind of stop and think for a minute like what what would that mean what would that look like and and it could could stimulate a fair amount of debate some people might think well that's pretty close in some folks might think well that'll never never happen um but what it does is is it it kind of gets you thinking about what the next questions are oh and and the next question should be about context like how did we get here um understanding how things have changed in this space um design TP and the design tools that we use typically solve problems for today and can be super useful about need finding understanding users um understanding the issues but in designing for tomorrow some of these design tools allow us to understand the history of this space the technology that is in place today um and the rate of change which can be actually pretty pretty important when we think about Innovation and Technology we're often optimistic that this is gonna this is going to happen really fast but you know some of these questions about robotics that we're looking at here today in this example are the same questions we were asking 10 years ago and 10 years before that um and so the rate of change is really important um change around some of the Technologies is is pretty rapid the rate of change around some of the cultural factors some of the the ways that we use robotics it can be much slower and and when you think about how those are connected or linked together um that's where you really start to understand what are the factors that could either accelerate or potentially impede adoption of this technology that we're working on the other reason I look at context don't reinvent the wheel oftentimes there's some things out there that you may not have been aware of that you could build off of or leverage or learn from so the next piece um is where we're going to spend a little bit more time here today so thinking about driving forces and the drivers of change we like to think about three types of of driving forces I'm going to start at the bottom here instead of the top um technology um technology is where a lot of change happens and it can be quite rapid um and that's where a lot of innovators kind of focus heavily on um but we might also Overlook some use cases uh or culture these are the things that that that need to align to bring adoption to adopt change um over time um and all of these things will feed into the The Innovation going forward so um let's start let's start here talking about technology um let's go back to the example that I brought up of a central question when will a human marry a robot so technology that needs to be in place for you know imagine imagine yourself out there in the future or one of your children or somebody coming to to the place where they would consider miroring a robot what are the scientific breakthroughs or the technological advances that that need to have happened um to make a machine functional as a human partner that's somebody you'd want to want to marry so let's Bill let's chat a little bit about about that here what what are some of the technologies that you think might need to be in place to to to marry a robot well um You' probably want to have uh certainly some kind of a you know a physical instance of the thing that it wasn't scary or weird um you'd probably want to have something you could talk to you know we wouldn't have to type input or something like that you could talk and have a sort of a normal conversation of some sort um and you know if you're thinking about a you know a life partner um versus just a robot that you know cooks and cleans or something thing then um I kind of I mean I kind of I'm kind of a hopeless romantic I want something with a little soul with a little bit of uniqueness with something you know interesting or curious for me to learn about because I don't want I don't want a machine machine is predictable I want something that's a little more well human yeah yeah so yeah there are a bunch of technologies that would need to come together to even create something that we could start to think about partnering with over time right and some things you know as as straightforward as sensor technology like can this thing make its way through the world does this thing recognize that I am its partner right so Vision Technologies communication Technologies speech language um battery power like does is my partner going to get plugged into the wall or is my partner going to be out in the world with me um Mobility things like you know some Bas some some basic building blocks of this thing that could that that I could partner with so there's a lot of technology that would need to be in place here for sure um so let's think about use cases then so use cases I what I mean by use cases are these kind of intermediary products or services or functions that would need to come together to create a desirable life partner so like so Bill you mentioned you know empathy but um you know some kind of companionship right there's that's or or um you know intimacy right that's a use case that would combine some of the technologies that one might expect in one's life partner um you know a household support service is another use case like you know picture the robot in in the Jetson right so wouldn't it be awesome if we all had that that you know the kind of characteristics of a household household support person other other use cases what do you think Bill well how might we use robots in this interim period yeah well you mentioned Mobility I mean you know I want to I want to travel with my partner I want to get on an airplane and you go places I wanna you know I want to rent a car and I want them to be able to drive it or maybe it'll be an autonomous car and they can just you know Jack in and tell it where you want to go but if you think about um if you think about all the emotional aspects of companionship um it gets pretty tricky to you know to think about creating a machine that has that kind of emotional depth yeah yeah it does it does and so let's actually start let's think also then about some of the cultural drivers of change like that would that what are some social or political or legal or regulatory issues that might emerge as we think about people marrying machines so this is where things get really you know pretty pretty tricky like would it be legal Mar a machine right yeah if you think about the legal thing I mean we assume that when two people get married they can give consent I want to marry this person I'm not being forced to do so I want to marry this how can a machine give consent we don't have I mean doesn't that require of Consciousness or intelligence um and uh you know I mean I think you know you look at some cultures like Japan where robotics has been adopted for you know elder care and other things they might be more open to this but I think in the US um people would be kind of freaked out if I was you know sitting at a nice restaurant having dinner with a robot and why why would that and if the robot actually has you know free will to marry you as opposed to being your servant um if they don't have free will like it starts to open up all sorts of interesting interesting kind of cultural societal questions um yeah one that robot for divorce yeah would a robot file for divorce or what about procreation are you you going to have children with your robot whoa what does your legacy look like will you even need a will because your robot might live forever and you obviously won't you have a human body so all sorts of interesting questions start to emerge around this kind of cultural side of of you know of this question whereas you know if you're just thinking about the technology side you might think yes we could physically build a robot that you could marry but but wow like you know what's the setting of of this the culture so I think this this is a great way to think about um you know what are some of those underlying drivers of adoption or something that might impede adoption of Robotics in general so even though you know we're focused on this question of you know Mar human marrying a robot we're also eliciting all sorts of questions that are relevant even if I'm I'm not looking at marriage but I want to understand the future of robot otics in general because all of these things will come into play as we as a society adopt you know more robotics into our world um this this this stuff has come up in in like factories right where robots are working side by side with human workers and the human workers are unionized and the robots are not and then there's all these debates and is it even safe to work next to a robot because the robot you know has no no sense of you know the human being fragile so it's really really I mean I love this forcing question because although miring a robot may be a little bit extreme you can easily you know kind of down select to to situations we're already in where robots are working Amazon wants to have all their factories full of robots you know but there's still people there so how do we how do we navigate these important you know like cultural and use case issues right right you know there also I think some great examples out there of of places we've gotten stuck in this technology level right thinking that technolog is going to drive change all on its own you know you we're talking earlier about um uh you know the VR glasses right Google's doing these glasses Apple's done the glasses um snap has done these glasses and it's this really cool technology but nobody's adapted them and and and I think it's because one there haven't been real good use cases for them there are some very Niche use cases around um you know kind of medical Robotics and things like that where that could be really relevant but there aren't a lot of use cases so people haven't started to use this and getting and gotten comfortable with them and from a cultural perspective we kind of as a group of people have not yet decided that walking around with you know with computers on our faces is comfortable or useful or or societally acceptable um so no matter how great that technology might be it's it's not it's it's not adapted well and it's a perfect example also of Looking Backward in technology people think you know Apple's Vision Pro wow it's brand new or the Oculus that you know Meta Meta stuff is based on the Oculus headset but you know I had friends in the 80s who started a company called face spak face space fake space labs and they were doing VR with two CRT te's literally two two televisions on a balanced boom that you could put your face in and you could have the exact same experience you're having today and all that's happened is the technology got faster it got smaller it got lighter but still you know in whatever that is 50 years nobody's come up with a reason that I want to do this VR or AR stuff and that that it would be acceptable in our culture to be wearing you know like I said a computer on my face yeah so we got a long way to go we got a long way to go so let's pop back to some methods here and and um think about what you do with with these drivers right so there's lots of ways to think about generating this list of of drivers of change one is discussion like we're having another might be a a tool like an idea map that we use a lot in in design and design thinking B you want to take just a minute and talk about what you know how you might use this kind of tool sure IDE maps are sometimes they're called called mind maps are just a great way of really you know Loosely exploring an area and being um very know um you know using using your both your intuition and your sort of creative mind to kind of quickly map out all the ideas that are connected so you have something idea in the center this case it might be Robotics and and autonomy or Robotics and a robot that you can marry and then off of that you you brainstorm a few uh options and then off of that you brainstorm options off of each of those and as the Mind map gets bigger and bigger it brings in more and more of the different domains and it's not limited to just the technology piece you can have you know a whole a whole part of the map might just be around the um the use cases a whole part of the map might be around the cultural or social issues and it's just a great way of a team really fleshing out all of the connections and interconnections between uh the central idea and lots and lots of other ideas it's a great way to get teams brainstorming to together as well yeah great um and so here's an example in this uh example that we've been talking about where human Mir is a robot so what we did was start you know with an idea map and generating lots of these different elements now I wouldn't expect anybody to to actually read all the little tiny things on this on this screen but I wanted to share this kind of as an overview in terms of like how you might use an idea map to start generating things put them up on a wall and then you can start to group them and we used in this case you know the blue ones we started thinking about what were the Technologies and the orange ones were you know what were some of the use cases and and you know applications of Robotics and the green ones were about society and culture but then we started rearranging them on the wall because you the last thing you want to do in a brainstorming session is put a bunch of Post-its on the wall and walk away that's just a that's that's it feels great in the moment and then then you know immediately becomes useless so in this case we started rearranging these and started thinking about what were the linkages what were the the how are they connected um and what were some of the most important um elements that we wanted to consider going forward as we were building a forecast in this space so you can see things were circled there lots of arrows um some things were underlined and they like and and so those were the things that we took forward because to try to build a map with you know with hundred elements here it just doesn't make sense so you try and figure out which ones are the biggest impact and which ones have the greatest uncertainty so the and the top drivers have have both because the things that you know or can predict in you know fairly reasonable ways are going to be the underlying factors in in any future but if you're trying to understand the breadth of possible futures let's look at the ones that we think will have the biggest impact positively or negatively or speed-wise um and which ones have the greatest uncertainty because that's going to kind of give us the breth of possibility in our you know in our count of uncertainty so um we just I kind of skim quickly through this example we took the the items that were circled or squared on that map we started just kind of going through them in terms of impact and UNC certainty so some of the things that we identified and and you as you look at these might think differently so this is a tool for conversation it's it's a you know qualitative tool obviously um not quantitative and there's a lot of of room for discussion here so like which ones do you think would have the highest impact and highest uncertainty we picked empathy like how do you even create empathy from a technology perspective huge impact on whether this is going to unfold how it's going to unfold a lot of uncertainty um learning as well seem you know seem to be a a high high companionship like we talked about earlier um in terms of a use case uh seemed pretty high impact how do we do that what does that look like timing how could that unfold and then interestingly you know a bunch of these things under culture um legal marriage so the the legal elements around how we typically think about marriage and somebody I see in the Q&A ask like what is even marriage should we be talking about marriage in this space is it a what would a legal Union look like as opposed to a legal kind of a human marriage it might evolve to be something different or defined it differently um and this notion of free will uh can you know can a robot can we can we build robots that have enough Free Will and frankly if they have free will will they want to marry us right like if I that's a huge uncertainty and and and you know and a huge impact on the answer to this question so we you know because I'm you know I'm a consultant and a lecturer and all I like to put a little framework on things and so for me it's helpful to kind of graph those so what are the things that have the highest impact and the highest uncertainty and those are the elements that are most likely to tip the future one way or another so those are things in the top right here empathy learning companionship the notion of legal marriage Free Will relationship trust um and when I do this it really helps me to think of to look at things graphically and so it it you know when I look at the things in the bottom left low uncertainty and low impact it's not that they're not unimportant because they are critical but you know creation of a physical body somehow and even what do the sensors development of sensors look like um those are our I wouldn't say predictable but but you can foresee a pretty clear future in development around sensor technology right historically they've gotten you know faster smaller more sensitive so I think compared to some of these other things that's a relatively straightforward I would call that kind of part of the landscape going forward I would assume sensors will continue to get smarter smaller you know better um language I'm assuming that there's that that the language which technologies will continue to to you know get better faster more useful some of these other questions empathy I don't know what that's going to look like right so um so oftentimes it's it is the technology pieces that are in this more predictable part of the the landscape and some of the cultural stuff that is the more uncertain which I think it's kind of interesting particularly for somebody who is a technology person it's like oh yeah there's all these other things so what well how we would you know work with this next is thinking about kind of what order how do how do these things relate to each other um I grabbed the things from that top right the high impact High empathy and kind of laid them out I think we have to figure out empathy before I begin to trust a a machine I need to have trust in place before I could build an actual relationship with that machine um there needs to have some sense of relationships and we need to figure out free will before we Define what a legal marriage or a legal Union could look like so just kind of generally laying these things out and starting to think about how they connect you know what what order they're in and then how they connect to each other stting layering in some of these other factors um and you know we've got physical body Mobility language sensors in here that all need to get get you know dealt with pretty early before we can start to do these other things now um I want to step here for a second because and reference the the workshop that bill you're going to talk about at the end here um as we look at the um expertise of the Stanford professors in the engineering department um and the students that are working today in the you the phds and the labs and the lake a lot of them are making huge advances in these technology areas and some of them in the the kind of the use case areas as well and so you know going deep into these elements gives you a lot more information about how they connect to the other the other elements um and I just would encourage people as they're going deep into these spaces to think about kind of what either what are the technologies that underly them and or what are the the cultural factors that that need to be in play for adoption so after after we kind of lay these things out let's build some stor stories let's get to that um that cone of uncertainty so you know you can you can lay these out and start thinking about that you know the top piece of this gets us to legal marriage so let's say the first things out there are you know robots around sax and intimacy some might say that some of those exist today right household service Bots um you know maybe next thing is uh you know is starting to build some relationships with these um AI you know friends um skin motion pain replicated fully mobble humanoid um because most most of us when we picture a human miring a robot it's a humanoid robot you're not marrying a box right it's unlikely that you could have all of these things in place with you know with with with a big metal box um but then what happens when you've got a fully mobile humanoid um that maybe has free will well maybe robots are going to start doing things independently because they have free will they might want to be citizens they might want to vote right they might want to have Choice um and probably at that that's the only point where I can imagine legal marriage kind of being redefined to include being married to some kind of artificial intelligence and that's you know that's a a a it's a reasonable story it's a rational story um and it's an outcome that when you understand the elements of it is not it's not out of the realm of possibility flip side of that is when you start thinking about how some of those elements might turn out differently um you know in terms of of some of the elements that we've talked about realistic conversation has got to be in place high capacity batteries have got to be in place but what if we get to a place where that uncanny valley Still Remains and we're not able to build these humanoid robots that are that are good enough so that we start to to kind of back away from the notion of of robots as human and start moving towards robots that are embedded in our environment which is also a a a a future that could make a lot of sense right you walk into your home and you don't have a humanoid service robot you just walk in your home and say do my laundry home it's just you know go make this happen world around me um and so the robots are not humanoid at all maybe they're just embedded around us and we and and they they start to become of our world and and so then kind of trust issues evolve a little bit differently um and maybe they're so embedded in our world that we don't need people anymore in a lot of places first grown adult with no other human contact you know there have been some sci-fi books and movies written with this future in mind and it's it's also plausible given what we just talked about all of those elements if they don't turn out one way they might turn out a different way and combine in a wholly different way where we are here for the robot as opposed to the robots being here for us and so you know building out these stories gives us a sense of the the range of possibility um and you can you know you can look across these and see uh See kind of a baseline future where robots are are starting as service elements for us then we start to build relationships with them and then they find some kind of Independence and it's that that that range of things around Independence can be kind of scary but you also can see how it starts much earlier to move towards one side or the other so as we think about you know range of possibilities why do we care what can you do with this information right where does your company fit in um are you working in a technology company that uh will enable any future going forward which would be good to know um are you working in a space that kind of will depend on one future or another um you know when we talk when I talk with my students a lot of them want to know you know I don't like they'll come at this and say I don't like this particular future I don't want the world to come out where you know we are here for the robots so what can I do today to influence the future what can I do today if knowing that this is a possibility um how can I think about influencing the future or playing along in the future or leveraging the future um but knowing that this is the range of outcomes and that these are the things that are likely to unfold um can give you a real leg up no matter how you want to play in this particular space so I'm gon to wrap up there on the Robotics and the forecasting um and see questions or I just want I wanted to jump in on a couple of things here because it's such an interesting idea um there's a comment in the CH chat about oh hey they already have companion robots in Japan and that's true nothing like what we're talking about but it is one of the things I would put on the chart they got little dogs that you know run around and bark they've got little companions but it's also interesting because um Japan is going to be a super aging Society in the next 10 years a v vast number of Japanese are over 55 or 60 and in other parts of Asia the the home care for your for old for your older you know adults for your your parents um has been solved by importing inexpensive you know caregivers from different parts of the world I I used to have an office in Hong Kong many people in Hong Kong have um you know Hospital helpers that they brought in from the Philippines from Indonesia from other places and that's how they take care of their Elders Japan because of cultural issues has decided not to do that they don't they don't bring they don't allow that kind of immigration so instead they've turned to robotics as a solution but it's a really interesting sort of extreme case right where the obvious solution is to go find some really compassionate caregiver to take care of grandma and instead the Japanese for cultural reasons would prefer um to offload that to a robot and there was even a fun movie made about this where the there was a robot who was sort you know helping a an older guy Age and and um and so you know the the the cultural issue there is critical the other one that I that you brought up which I think is really interesting to think about is trust I'm not even sure I trust my bank with my financial information because they get hacked all the time I'm certainly not sure that I trust you know some of the big companies in Silicon Valley with my personal data which they seem to like to sell all the time and somebody's going to make and sell this robot and I really want to know what that maker you what the you know robots are us company that sold me my compion I really want to know what they're going to do with the data that's generated with with that because the probably the most personal data is the data about the person I love so wow I mean it's just I mean again it's an extreme question but I think the extreme question brings out all these interesting combinations of of you know what's culture what's technology what's a use case and that's the kind of stuff that I think really drives an interesting conversation about what's the next five years the next 10 years going to look like and at the rate of change that we're seeing right now with things like chat gb4 and and other AI you know implementation starting to flood into the marketplace we're we're at what we think is a point of incredible disruption and that's why we put together um this webinar to talk a little bit about casting but also the um the program going to run in March for two and a half days live on the Stanford campus aren't you dying to get out of your office now that coid is over and finally go to a live thing where we're gonna have amazing uh researchers showing us what they're doing in robotics and autonomy and Ai and other things so that we can build for your own organization these kinds of um forecasting tools to get you walk away with a forecast for the next five years for what you think's going to happen happen in your organization and particularly this idea of the cone of uncertainty what happens if everything goes great what happens if everything goes south I think that's that's exactly the kind of way we should be thinking about the future so I think um Anette are you gonna can you C question well first first and foremost thank you and Cynthia for such a an a fascinating discussion I think a lot of folks were um very engaged uh so we will open it up to questions short if you haven't submitted yours please do so in the Q&A box if you have one um WR on your console um now let's go into some questions the first the first one we have here what are the key drivers of change in our world today and how might they evolve in the coming years that's a that's a big question really really big question and and I would suggest breaking it apart a little bit right um you know you can see how putting some constraints around the initial question can allows you to go deep and then kind of surface back up to questions that are relevant like a lot of these questions that came up are relevant to society in general and understanding kind of how this world is going to evolve but we didn't get there by starting like starting with that huge question like how's the world going to change it's a valid question for sure but it's not a not necessarily a useful way to get to answers right so I would suggest coming up with some provocative question here and I'll bet when we started this folks were going yeah yeah pickle pick a question and then go for it but then when you do this you realize that how a a provocative question like that can really help you kind of go deep into an area and then come up with some answers that that are more broad yeah and just to add to build on that I think the the the value of asking a good question for instance if I'm a policy maker and I'm thinking about you know public policy uh in the city of San Francisco for the next 10 years um what are I what are my drivers well it's the economics of the of the of the region it's you know um that's certainly climate change and how that's going to impact you know um the region both for for like where is it going to be safe to live and how many seaw walls am I going to have to build and blah blah blah but when but if I have a if I have a focus if I have a point of view or a lens to look through then I can figure out what the drivers are to say what are the you know what are the mega drivers for the world for the next 10 years um I'm not sure you can get any traction on that question because you end up with generalities like well economics and social unrest climate change World Peace you know yeah useful you can't you can't solve the problem so I think this is where diving into a particular focus and then fleshing out a cone of uncertainty could raise the next level of questions and then doing it again and again you know you'll end up with five or six of these kind of cones and forecasts and then perhaps you could synthesize something down to say well you know if if if I am the President of the United States my number one priorities need to be X Y and Z but even that is going to come through the lens of what's good for the US rather than the world so I think asking the right question is is is critical you know to get to something that's that's actually actionable yeah you know and let me give you another example so some other questions that we have posed in this class are um you we wanted to look at healthcare for example pretty big topic and the question that we posed was um uh will will I or will the students in the class um live to be 120 years old will I live to be 120 so it's a somewhat provocative question um it's pretty it's fairly General but specific to healthcare so that really allowed us to dig into healthc care in an interesting way and you know what are not just longevity Technologies but what's going on in you know biotech and social services and what else is going on in society that will kind of accelerate or impede longevity in these questions and it got us to a lot of really interesting questions about um you know about retirement and social policy as well as you know technology behind um you know the field of longevity and other health care issues so by asking a a a question with some boundaries on it um in a provocative way it really allows you to open up and and go go deep and then open up I love that um thank you I think the next one is a is a great question around um applicability of this methodology and um this uh this participant would like to know what is the role of a design leader to apply forecasting into corporate strategy um I I love that question um I think the role of a designer can be to both you know provoke and put some boundaries on stuff um you know I think good design often um thrives with a little bit of constraint and kind of focusing on that central question encouraging people to um put some constraints on their questions instead of you know what is the future of Robotics like encouraging people to to to put some you know something down that we can all kind of discuss and rally around um and then bringing some of these design tools into play Thinking about encouraging people to think about Alternatives and alternative futures um encouraging people to think about the human side of these questions not just the technology side um I think a lot of design tools um are part of this conversation and really can be great um next question um so let's see what questions or Frameworks you use to assess where one's analysis might be wrong my one's analysis might be wrong um let me take yeah go ahead can let me take a whack of that and then you can follow up um that's the the whole idea of this is that we're using you know brainstorming mind mapping design principle somebody said can you use chat to come up with driver sure why not I use chat in my classes all the time as a brainstorming tool chat doesn't know what it's talking about but it's just good at you know randomly generating you know interesting work and interesting things to think about but the whole idea of you know forecasting a cone of uncertainty is there there's no right or wrong there's a probability that the future will be this there's another probability that the future will be wildly different than that and a different probability that will be the negative of that and so when you look at that then you and you think about your own organization let's say you're in a a pharmaceutical company and you're thinking about you know drug drug Discovery and Drug Sy Delivery Systems for the future and where's that going to and how can AI influence you know speeding that up or you're a Energy company you're trying to think about transitioning to the green economy or your uh you know tech company and your you've got some brand new thing that you want to make an app you know that has something to do with AI and and um the financial markets so you take these tools and you start to think about what's going to change in the future and how can my company respond to those changes and what's the likelihood that the worst case is going to happen and what's the likelihood that the best case is going to happen so we're not talking about you know coming again as Cynthia said in the beginning we're not predicting the future we're coming up with a range of possibilities and probabilities that the future can you know can sit inside what I love phrase the cone of uncertainty and a nice part is you know you say you start with the forecast and you so five years out and you've got your cone blah blah blah a year later you're at a completely different point in that cone of uncertainty right and you can start all over again go so these are the things that actually happened this is how my assumptions change what's the new cone so it becomes a dynamic tool for thinking about the future in a structured way without the without getting into you know I'm right or I'm wrong or I'm predicting or I'm not predicting all right I think that's great let's see if we can get in you know another question or two yeah let's let's get into the next one um the next one that I have here is can AI be applied to leadership to a leadership framework in the future will a I become part of EX of executive of an executive team as well what are your thoughts on that certainly could be um andd be surprised I'd be surprised if it if it doesn't somehow become part of the Executive Suite how so is a different question right so um you know using a framework like this I think could really help us kind of tease out what are those possibilities um and then you then you've got your own qu context for asking that question why you know why do you want to know that question because you're an executive and you want to figure that out or because you're a shareholder and you want to invest in more of that or less of that or because you are an employee and you don't want to be you know led by an AI or you do want to be you know you think that's great so the context really matters and and kind of why you're asking that question on you know in terms of what you're going to do with that with that information but I got to tell you I love that um some of the questions here are are being asked about kind of the the framework and so many of them are being asked about the content here and you know and people have some really interesting thoughts about you know robots and Robotics and the future of of Robotics which I really love that that this is stimulating those kinds that kind of thinking and that's that is really the the value in a you know kind of a framework like this to get get you really thinking this is it's not you know you can talk about it superficially oh I heard this in the news I saw that in the news but to really understand it you know having a little bit of structure like this look at all these awesome questions that have come up and and the comments people are making about you know ethics and and you know the legal nature of Robotics and Ai and how that's involved and all these other interesting things so I'm I'm really I'm really loving the the variety of questions I wish we could share these all out one one of the one thing about about every question has an embedded assumption in it so Will AI be part of the Executive Suite um well in my con of uncertainty AI replaces Executives because if most of what Executives do is try to make optimal decisions AI will be better at it than they are now if you're talking about leadership that's a different thing but this is going to force Executives to separate what they do about decision making which isn't leadership it's just management versus leadership ship and so you know to me if you look at the the changes that are coming why would I pay an investment banker 2% of my you know of my fortune to invest for me when I can hire an AI That's going to outperform that that Human by 10% why would I pay a CEO millions of dollars to Simply make decisions about the company when the AI will make better decisions so I think you know in one version of this there is no se Suite companies are run by AIS and more efficiently and with less less Humanity right because they'll just make rational decisions but boy you know that that's a you know be careful of the question the question has an embedded assumption that that the folks who are asking it will still exist when the answer occurs wow well thank you I mean I agree with someone is a very thought-provoking conversation I loved it I hope you all um on the line loved it as well we're at time um thank you Bill and Cynthia for this interesting insightful conversation like I said to everyone in the audience live with us today thank you for all your questions and super engaging participation I want to remind you that today's session was recorded and a link to this will be sent and made available to you all within a week have a great day and um see you all next time thanks so much

2023-11-13 22:02

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