Technology Predictions and Megatrends
[Music] hello everyone welcome to the next hul Paka Lab podcast from research to reality today we are talking about technology predictions and mega Trends and I have great honor and pleasure to host two amazing technologists Mary Baker hi Mary hi and Kirk bastier hi Dan uh so Mary and Kirk uh can you please introduce yourself I could never do uh sufficient introduction to all the contributions you have made Mary sure I work at HP Inc which is one half of the company that broke off from hulet Packard Enterprise where Deon is and I work in the 3D business unit there the 3D print business unit and I've actually worked in many different parts of the company both in research and in the business area and also at startups and in Academia a variety of different different places I've Had The Good Fortune to work on many topics and in many kinds of organizations Kirk how about you uh thanks de uh my name is Kirk preser I am chief Arc fellow and vice president here at huip Packard livs part of huip Packard Enterprise the the other half of the collegial twins that came out of hulet Packard I've been at the labs here for 10 years prior of that uh I was 25 years in our compute business units uh so back in the day if it computed and had an HP logo on it everything above the laptop was my technical remit number sounds smaller when you split it into so how did you both get into this business of predictions well Deon you asked me if I would be interested in it and it sounded fascinating and potentially very useful and it's also just a general rule of mine that if Deon asks something you make all your efforts to say yes and Kirk you I so I think for me uh you know especially both being in the business unit and the labs everyone everyone always wants to know what's next and it might be how to tell a customer what to invest in it might be to tell your kids what they should be studying in school and so first in the it and the international we for devices and systems we had I began to understand and participate in Road mapping exercises and then with the both the tech predictions and the mega Trends is trying to understand the broader implications as we Rise Up from low-level technology road maps into understanding the implications okay what if if this comes to pass what are other things we should be considering and to be able to again to provide that guidance whether that's here at work or it's at home excellent uh Mary you were specifically working on technology predictions so what are technology predictions sure technology predictions are way of encapsulating our understanding of how Technologies are changing and in such a way that the recognition of those changes we can put to direct use and and this um we hope will be a benefit to people and our world to understand ahead of time what is going to happen in industry in uh healthc care in National Security in all sorts of different areas it helps to know what's coming down the pike toward you and the more accurate your predictions and the sooner you have them the more of a strategic Advantage you have so it's a very useful thing for us to do if we can do it right and how many predictions did we make and how do we describe them I think we ended up with 21 predictions we started with a lot more than that because it was quite a process to go through to winow it down to 21 um and we have a wealth of information about the different predictions and how we think they're going to play out over time but we also describe them in terms of a slide for each prediction where we talk about what are the problems that the technology where predicting is going to try to solve or what are the demands it's going to try to address and we look at how it will do that what are the Inhibitors the obstacles what are the opportunities uh and especially Market opportunities thank you Mary and I'm now a little bit confused what is the difference between technology predictions and mega Trends can you explain to Oscar sure so when we think about megat Trends we should be thinking about multiple things coming together it's a Confluence it isn't just one individual technology Trend these are going to come on sometimes it establishes technology for a long haul sometimes it's just a blip and so when we talk about megats we want to take one step back and understand how things come together the technological the social the economic the political to come together and reinforce and reinforce and pull a couple things together the things we'll see with the mega trend is you'll see the constituent analy both as a sum as an aggate that Confluence as well as individually they end up influencing each other and that's how they describe this long-term Trend the other thing we think about a me mega Trend we don't think locally we do think globally what is something that really has a global implication that will change the way that we do things how we pursue as we say as UL Pac Enterprise we are here to advance the way that people live and work you know advancing the way people live and work that ends up being a mega Trent and what are the megat trends how many are there so we looked at three Mega Trends uh digital transformation sustainability and then artificial general intelligence and those are sort of organized by maturity so digital transformation I think we all perceive that that is something we've been really into can I create a model can I create a computerized model can I model how systems complex systems work so that was that first thing again we'll see that really permeate the way that people uh uh approach their business and their personal life and then beyond on that we look at that next one sustainability right now understanding understand that energy footprint energy uh implications of everything we do and then now looking forward to artificial general intelligence as Things become even more evocative more creative taking over more knowledge uh worker roles how will we then take advantage of that bring everyone forward I think that's the third big Mega Trend and you've been both of you were talking primarily about technology Mega Trends I know you've been active in World economic Forum there are other kinds of Mega Trends can you explain how technology relate to those yes so we we think about those technology Mega Trends and then how they impact the economic Mega Trends the uh ecological meat Trends and the social and political Mega Trends you know we think we can imagine uh and if you talk to anyone they'll always have their particular technology or their particular social or economic challenge that trying to understand understand I really care about the GL Grand Challenge of climate change well then we gave them a map to focus in start with that Grand Challenge work your way through the applications technology work your way through those techn uh Ming Technologies into that Mega Trend so you can either work from the inside out from the mega Trend and then begin to explore its ramifications or you can work from the outside in what do we need to accomplish as a species and then find oh that inter intersection between sustainability and artificial general intelligence or sustainability and uh and that digitization how do all of those things Factor together all of this sounds very fascinating have you done it all by yourself no we were a group of I think 46 47 people from all the seven continents so spread out uh geographically a lot of diversity lots of different areas of expertise very diverse there we aim for a very diverse group because that is critical or you're going to miss something important and the uh the fact that it's all people working on these Trends and trying to understand them means we have all the advantages and disadvantages that you have with people uh so uh we can discuss that more if you're interested but it makes it a fascinating uh project to work on because you learn so much from people whose experiences and perspectives and expertise in some very different areas than one's own so this is how you made sausages or the technology predictions how did you do megatrends did you do the same way it was it was similar and I think you know we had over 40 individuals who came together what I think fascinating about that we had a sufficient sample size sufficient diversity and then when you're looking at the megat trends and we're all providing our guidance it's not just that we're picking one it's you want to look at the distribution what is the peak absolutely is there more than one also you want to see those Tales because sometimes we may not be confident it may be out there on the B boundaries but that can be the most impactful of those and that's where understanding that entire distribution of opinions from this uh Community this diverse Global Community is valuable as well I'd like to agree with Kirk on that that one of the most interesting parts of the process for me was looking at where we disagree and I think you know there's real gold there for for highlighting people's different experiences and expectations when you see where we disagree I know I was an outlier from the consensus on several of them and I learned from that you use the word process was there a process there was there was there's a process that has been worked out over many years and improved each year as we try to understand how to do a better job the next year and so what we started out with with our um 46 or 47 I can't quite remember technologists is we each submitted one or two technological areas that we thought would be important to consider for this this process and then what we did is we voted and Mer well we merged some because there were some that were essentially the same topic or very close and then we voted on the remaining ones to see what the consensus was on how important the the different Technologies were and that way we worked it down to 21 and we each had 16 votes that we could place on 16 Technologies I did notice I don't know if it was required or just happened but none of us placed our votes on the Technologies we submitted ourselves we all placed them on others that we thought would be important to keep on the list and so that way we worked ourselves down to 16 of uh sorry 21 of the Technologies and then we went through a different process where we voted on them using letter grades a through F and we looked at the different Technologies in terms of what we thought their potential impact was on Humanity so a being a good impact F being not so good an impact and we also looked at how mature we thought the technology would be in the coming year uh we looked at how broadly it might be adopted by the market in the coming year but also in one year three years 10 15 years to see what we thought the expectations were for the path that this technology would follow and then of course there were the slides we mentioned before did you follow the same process for the megatrans there was a similar process for the Megatron we started that team of 40 people and then we really identified those three critical Mega Trends the digital transformation the sustainability and the artificial general intelligence from each of those meat Trends we each proposed approximately 20 Technologies and we just again that merging process that that that filtering down to say okay where are these overlaps what is that distribution of opinions from these uh from these 40 individuals we down selected to six per megga 10 and then we went through that voting process that you described uh and then we went through that same a through F trying to understand and impact likelihood how do we uh find those things is we really want to understand really that both of those dimensions of these uh Trends and of these technology predictions Mary you touched a little bit on that um in terms of impact on Humanity but how do you communicate so you got these 21 how did you communicate them to the world there's a wealth of information there and lots of different ways to correlate it so in fact we present lots of different correlations of the information I think one of my favorite is one that graphs the impact of the technology potentially on Humanity what we expect that to be against its technical development in the coming year and there's also U how much market adoption it has and and other aspects that we can that we can graph but understanding especially the impact on human ity and how advanced this technology is and how how quickly it might Advance further this is important I think very useful applicable kind of technical prediction so this is one of my favorite of the uh correlations that we performed could you give us some examples which one has most impact on humanity is it the one that will have the largest chances of success right right well I think the one that came out as having the largest potential impact on Humanity was remote healthc care and I think there's lots of reasons why that can be very helpful going forward especially giving some of these these trends like aging populations in many places and so forth um and that had I think uh I think we rate it as being kind of mature and uh kind of well adopted but not necessarily at the top of either adoption or maturity compared to some of the other Technologies uh and I I think one of the most useful things you can do with this information is if you look at a technology that looks like it has potentially high impact on Humanity but it isn't very Advanced then that's a technology you would really like to invest in somehow probably in a research environment if there's just a lot that's not known about it yet so perhaps that's a good technology for academic dep departments to invest time and effort in whereas if something is fairly mature uh and uh at least as mature or maybe not quite as or maybe more mature even than its impact on Humanity that's a time maybe at the other end of the spectrum where perhaps it just needs some corporate enthusiasm to push at that last mile to Broad adoption and these 46 people did they all agree on the same Technologies same factors uh for some of them we were in pretty good agreement for others there was some diver mergence so for instance if you look at our level of confidence uh I know I was an outlier in particular on one about managing misinformation the consensus there was that that's fairly mature and broadly adopted I felt quite the opposite I feel like we are still rather helpless in the face of some kinds of misinformation so if you look at uh the lack of confidence across if you look at that by standard deviation I yeah I probably contribut to to that one so excellent and is the same outlook for the megat trends similar we had you know and I really love these visualizations because they are so useful to help you understand and so looking at that technical Readiness uh versus that that adoption impact uh I think that some of them really stood out if we think of that that success of Technology development taking right now and that impact in humanity and and if we think of those in the same why understanding which ones are really Advanced and really impactful uh then again that'll help us understand is this an academic exercise do we need a lot of groups contributing to low-level research or is this one of the case it just needs scale it needs investment and maybe there's something in between maybe it's a candidate for a government to encourage or to regulate finding those sweet spots of cre each of them that's really available inside of these visualizations to help you divine find out which of these things you should be investing in and when they all have these different Horizons and impacts and uh how do they compare to each other technology uh predictions and megat Trends so I think that you could look at the at the both the technology predictions and then the megatrend and do a mapping right to understand okay which of the three megat Trends the digital transformation the sustainability the artificial gen uh general intelligence and how do the individual Technologies then factor in and support them and you can see that inner relationship and you can understand okay given the focus on sustainability oh well then how does the AI how do AI Technologies plac into that understanding how digital twins about uh the sustainable all these things end up factoring in so we think of these megat Trends as both cesing and and um being that Confluence of Technology Trends but they're also helping each other and Inter interacting with each other and again thinking of that bigger lens not just the technology the social the economic impact of these things coming together and can you make any conclusions about the evolution of the skills as a function for example of AI yeah I think and we use our own industry as an example you know recently we did an analysis okay think of it boy there's something you probably recommended to someone who is entering college right now you better be in in information technology or at least have an understanding because it's now permeated click ahead a couple of years and it's now understanding the AI impact across every knowledge role it is a knowledge role so should you be working really hard to gain your system administrator certificates probably not because that is an example of something that will likely be automated we will have uh systems that are being maintained at superhuman levels of performance by artificial intelligence at the same time thinking about that ability to craft that next Generation AI to be the data scientist that is creating the data that feeds into these next Generation AI systems those are certainly skills that we would be encouraging and again whether we're talking about having a conversation with a legislator or a government official about which programs to incentivize or you having that conversation around your dinner table with your high schoolers who's trying to figure out what they should should be pursuing I think that's where we want to understand these impacts at the largest scale and at the small scale Mary uh we are from these two different sides of what used to be HP but we've done all of this work uh within itle e so what is the importance of these professional organizations to this kind of work and everything else yeah organizations like the i e are uh places where you can bring together people of lots of different kinds of expertise and area and understandings and backgrounds so we uh can learn from each other and the result the the collective power then is much greater than the sum of its parts so an organization like the i e can have huge influence where a bunch of us just in one particular field for instance wouldn't really be able to do that so I see the I and organizations like it as being rallying points for the things we need to get done to help improve our world and the prosperity of people in our world and Kirk you earlier mentioned road maps uh do these predictions help in road map standards and other things uh I think they do and I think one thing I'll highlight about the I possess U uh participation things the first thing is that I stands for international right and so having that broad perspective because this is not just about individual technology it's about understanding how they then impact uh large scale uh social and economic system we think of something like that digital twinch and understanding how we move from simple models that that give us that simple prediction and as we look forward into the future suddenly the the simulation is more important than the real system because I can't put a print F statement and debug a cell uh I can't uh do the similar inside of the the fusion reactor of a tach but I can do those same kind of things in the model so understanding and being able to predict how these happen and what's important is for us to do this over time and that's another thing I think is so valuable when we repeat this process over time we gain confidence in our ability to predict and that help us answer the question of of where and when where in my computational my business my leadership portfolio will this technology or this Mega Trend uh be impactful and when will it happen because in the end I want to compute a return on investment a time value of money plenty of investment of individual resources and that really is another aspect of these road maps that it helps us understand where there technology predictions or Mega Trends it gives us that understanding over time I like your where and when but what about how is there any ethical question to all that you spoke about certainly there's the the question I can do it the more important question sometimes is should I do it uh and certainly that is an aspect and again that's where I think the mega Trend and bringing in that broader society as well as not just one Society but in that Global Community it gives us that understanding of things like how do sustainability Advance ethical uh uh as ethical aspects of whether it's business or personal or public life it gives us that structure for us to evaluate and understand okay is it possible for me to have a technology that is ethical and not sustainable I would argue no if we can't afford to let everyone enjoy the benefits of technology is it something that we should be pursuing or is should we try and say there you go we've identified a need but unless we can actually make it available equitably to everyone maybe that's a technology Gap maybe that's where we say the current technology was a stepping point but when I understand its full ramifications on a global scale I need to invent something different Mary you worked on these technology predictions for scoring them then predicting new ones first through Thanksgiving then through Christmas holidays there must be something gratifying to sacrifice all these holidays working on this yes there there is certainly with any of these kinds of visionary activities there's a great deal of gratification of course if you get them right if you are able to predict a technology that is useful for helping our people in our world and when it's going to come about and and how it should so as Kirk was saying you know there are choices between what we should pursue and what we shouldn't but it's also how we could pursue these things and when you're right that's very gratifying it's also super interesting when you're wrong when you're very wrong there's a lot to be learned from that and so that's one of the things we do at the end of each year we grade ourselves on how good our predictions were over the previous year there's some accountability there there keeping us honest and that's also a very a very useful process I think it's one of the ones that I look forward to the most to see just how off we were over the course of a year or how much on the target we were thank you Mary great examples so Kirk if you would based on what Mary just said recommend to our younger early career colleagues to do predictions how would you suggest to them to do it well I think I'll I'll highlight something you said as well and and often when I'm talking to Young technologist I I'll I'll let them know my personal experience I look back on my career and my predictions and sometimes you laugh about what you got wrong it's like oh do we really think that that was going to be that important sometimes you'll cry about what you got right and when you really it's going to be one of the one of the challeng most challenging things you'll ever have as a technologist is when you had the technology prediction right but the other elements were in place and I think that's what's so valuable about not just predicting the Technologies but the larger Mega Trends why when I thought that idea I had that idea 10 years ago and now I'm reading about it in the Wall Street Journal about someone who just got an IPO what were those other elements I didn't understand and I think that's where understanding our role as technologist and what really enables us to make that valuable contribution it's not just the technology you have to have that aha moment that's absolutely necessary but unless you have that Ingenuity Plus opportunity plus explaining that to someone else who can make an investment in you that's when it really comes together and so that's where understanding megatrends and Technology are so important to be done simultaneously I'd like to to add to that so if I'm thinking about roping people into helping with future predictions or people just want to get started doing that for themselves one of the things I would suggest is you do step outside your field of expert seek out people who work in very different areas have very different kinds of backgrounds because you will find out things about your own area that you didn't expect there will be overlaps you didn't predict and huge gaps that might be important ways of thinking that you can bring to bear on your field that you didn't know about or or consider and one of the things you'll find is it's it's so true there's there's that saying that the more you know the more you know you don't know and that helps in the area of techn ology prediction because you you need to know when to reach out and bring other people in for example about satellites power and energy blackouts in PA Alto Etc absolutely uh we like to end this uh podcast on a personal note so when you don't do predictions what do you do apparently I show up for podcasts so there's there's lots of things I like to do as Hobbies I uh I do a lot of Designing of 3D print jewelry for both poers and metal and I also design knitwear and and I Garden rather poorly but but I do it how about you Kirk uh so I am uh I used to run until I kept hurting myself and so now I just hike so I do a lot of hiking I I'm fortunate uh at my home up in the Sierra Foothills I am just a few steps away from a a state park and so I can hike 20 mil up the hill to Auburn ride my bike 30 miles down down the hill to Sacramento so I love that getting outside when I'm inside uh I love to cook I am the the cook for the family uh and I must admit I do enjoy a good cocktail as well well great and many insights thank you very much Kirk thank you Mary thank you looking forward to next year's predictions
2024-03-03 05:09
