Dole

The European edition of the Fortune 500, ranking companies by revenue.

Fortune 500 Europe

The first-ever European edition of the Fortune 500, ranking companies by revenue. 

F500 Europe Dole pineapples are seen in a supermarket

Dole ranks 364 with $9.2 billion in revenue (up 43%). The Ireland-headquartered food and consumer products company has 37,422 employees and made a profit of $87 million.

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Dole (DOLE): Company Profile, Stock Price, News, Rankings

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Dole (DOLE): Company Profile, Stock Price, News, Rankings | Fortune

As AI takes hold, so do the risks for the next generation. In this important conversation, filmmaker and children’s rights campaigner Baroness Kidron joins WeProtect Global Alliance founder Baroness Shields, OBE to explore how AI is impacting childhood – and what we must do to protect it.  

Who’s Protecting Our Kids from AI?

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Scott Doorley, Creative Director, Stanford d.school

Brainstorm Design 2023: Living With Emerging Technologies

When change is constant, the path ahead is full of uncertainty, the way we think about new technology will, will help unlock its vast promise and unearth its perils. Scott Doley is here to share new ways of thinking about and making the most of our ever emerging tech. Scott is creative director at Stanford D School and an expert working at the intersection of design and media. Please welcome Scott Doley. Thanks so much. I really appreciate the time. Uh Your time is valuable and uh I'm excited to talk for a little bit. So I'm gonna talk about emerging tech and uh I'll get into it in a sec, but I just want to share one thing before I do. Can I be honest right now? Um I'm a little nervous about giving this talk. Uh It doesn't end in the way I give a lot of talk, it doesn't end in the way they normally do. It ends kind of unresolved a little bit. And I'll be honest, I'm slightly uncomfortable with that. Um In fact, it ends with the sentence that is, that's an open question that I think we have to solve. So it's really really unresolved at the end. Now, I think that's ok. At least I'm trying to convince myself that's ok because I feel like we're in a moment right now where things, uh, don't resolve themselves quickly and I think we just have to get used to living with that. I think maybe that's the point is that we have to cultivate the skills to, to live in this unresolved world. Now, I've tried to fill it with lots of the talk with lots of practical takeaways. So I hope you won't be disappointed. But why don't we just dive right in? So I, as I mentioned, I'm going to talk about emerging technology. And often when we talk about emerging technology, we focus on the second half of that phrase, we talk about the technology that makes perfect sense because the technology that we're talking about, whether it be synthetic bio Blockchain A I is very powerful. But there's something about that first part, uh the emerging part that I think is worth spending a little time on because I think it's affecting us in an equal way. It's the technology. Just that constant change itself is kind of pushing us in ways that we're not used to. In fact, that word didn't used to be put in front of technology, it used to be new technology or just technology. So why is this uh emerging? I've got three questions to answer during the talk. One is about how, how that makes us feel the other is how we think about it. And the last is what we might do about it. So let's start with the first one. How does it feel? So, so to me, there's something particular about how emergence feels that we'll talk about right now. This is a graph on the bottom of the timeline. It's roughly the last century on the vertical, on the left hand side, that's the percentage of Americans that have adopted a new technology. Now, this is done for lots of technologies. We're looking at how fast do people in America adopt technology? Up to 80% of the population. We're going to look at the phone right now and start with all the versions of the phone. So first we've got the landline, landline starts a little bit before this graph. You can see it kind of has a little bit of a down slope. The slope is kind of a curve. Now let's go to cell phones. Um and I'm not talking about smartphones, I'm talking about dumb phones, the flip phones and brick phones and the like that starts off with a little trickle in the eighties. You know, these are the car phones, the big mobile phones, but for the early adopters, then it really does start to pick up and in about two decades, you're up to that 80% level. It's a little bit off the chart, but you're up to that 80% level. And then lastly, let's look at smart, so smartphones pose a similar pattern to the cell phones, but the uptake is a little bit quicker at the beginning and then it kind of rockets uh in, in under a decade up to that 80% level. Now, if we went even a step further and got to like the chat interfaces like clad and chas GP T um that would be just a sliver. It's not, I don't know that it's up to 80% yet, but it's on track to just be a sliver on the right side of that. Um So how does that make us feel? Is the question? Well, I work with a guy named Glenn Fajardo, kind of a brilliant guy and he has a framework that he uses to think about how that adoption feels and most technology starts as a nice to have. So you think about when the iphone came out, which was the first, you know, popular smartphone, it's kind of nice to be able to open up the maps and pinch and it was cool to have music in your pocket along with the phone and messaging, but it wasn't like a mandatory thing to do business. Um Over time that moves to what you can't ignore, right? So when the technology gets to, can't ignore stage to just actually function in society or in your work, you can't ignore it. You have to either just do it or decide specifically to opt out. Now what's happening now is the distance between nice to have and can't ignore is getting shorter, right? You can see that on the graph. Let's look at one more graph. This one's about A I, this is how fast the A is uh on, on different tasks can learn to be as good as a human at that task. So you can see, I don't even, this is a much shorter timeline. It's about 20 years. I don't have to get into all the details. But if you look at say like handwriting recognition which begins on the left has like a similar kind of slope to the landline as you go to the right, which are newer things coming out. Now you get to language understanding that's like a straight up with a little hitch and then a straight up, right? So it's following that same pattern. I think this is creating a certain type of feeling in us, this quick adoption that distance, shortening and the change in the improvement happening. And it's putting us in a situation where we're never up to speed, right? We're never up to speed. And if you take that and make it into an acronym, we have N for never ut si think you can see where this is going. It's nuts, right? It's making us nuts. Now. Now in American slang, uh there are a couple of definitions of nuts that I think are useful here one is that it's mentally disorienting. So, uh, if someone's playing a song that I don't, like, I might say that song is making me nuts. Right. It's not making me feel good. The other though is kind of the opposite. It means extremely alluring. So, like, if I have a song that I love, I might say something like, oh, my gosh, I'm nuts about that song. I'm nuts about that band. Right. So, on the one hand, you can think of the mentally, um, disorienting folks as being the, the pessimists and the extremely alluring folks as being the optimists. Um, but either way it doesn't really matter, the mental state is still this excited mental state and I don't know about you, but I don't make great decisions when I'm in an excited mental state. When I'm sort of mentally frustrated, I eat a lot of sugar and things I shouldn't eat when I'm overexcited. I make a lot of rash decisions that I shouldn't do. So, I think this is actually an issue that we're kind of like hyper, hyper, excited. Next. How do we think about it? So, how do we imagine what's to come is the question that I have. It's a really interesting question because we're actually not that good at this. You know, we don't know what the technology is going to do. We can't really totally understand it. So, what we have to do is take old mental models and put them on the new technology and see what comes out. So let's look at generative A I, again, there are lots of metaphors. I've been kind of collecting. This one is a representation of a calculator. For words, this one is particularly popular with some of my students. A calculator for words suggests that, oh, this is a tool we have it under control and it does our busy work for us. That's sort of what that metaphor reveals. On the other hand, I'm giving a lot out in the media that there's a, it's like these are like nuclear weapons, right? We there, there's an existential threat here. We need to have some treaties around how fast this moves, there's a political solution to it. And so that like highlights kind of the threat and the power of it. Now there are tons of other ones. Electricity has come up fire manufacturing. I've used one which is Margarine that maybe it's a synthetic thing that in the long run is going to turn out to be not so good for us. Who's right? Who's right? Which of these metaphors is right? The answer is, who knows? Because we haven't seen what it can do yet. And I think I would add, who cares? Because to be honest, it's not really about being right anymore. I think when we're in this never up to speed moment, what that means is we have to operate in ignorance. And so what we need to use these frames of mind for is not to make sure that we're right or wrong. It's actually to find the space that we're missing. And so the main thing is, it's both right. It's all of it, but we shouldn't get hung up on one too much because when we get hung up on one too much, it narrows our field of vision and we end up being stuck in that metaphor. So I think the goal here is just to switch switch frames of mind. OK. So now we're coming, coming to the end, what do we do about this right now? What or what now? What happens next? How are we going to make sense of all the opportunities and all the perils that are here? I've been playing around with what I call rules for emerging tech. I'm really interested in like, why are we lumping all these technologies together again, synthetic bio Blockchain A I? Why are we saying these are all emerging tech when we didn't say tech was emerging before? Um So what I'm looking for is a way that we can have a framework that allows us to have what I call the ability to respond. So the ability to respond is very similar to what my colleague, Sarah Stein Greenberg was talking about this morning in teaching students to be able to be adaptive learners. It's about, you know, developing the capacity to learn how to learn this has kind of become a phrase that's used all over the D school Cortland Butts who does equity work with us uses this phrase Lisa K Solomon, who does futures work with us uses this phrase. So in very different areas, this phrase is, is popping up. And I think the interesting thing is if we look at the peculiarities of this technology, it can help us get ahead of it. So I'm sure there are like 42 of these, I've come up with three. I'm still not even sure that they're right. These are hunches or hypotheses that I'm testing out, but let's work through those three right now. So we're going to look at the peculiarities of emerging tech. So one is that they continue to grow even after we're done with them. So you can see this very specifically in something like synthetic biology, right? Synthetic biology. It just literally keeps growing after, after we're done with it, you can see it in A I the way machine learning can kind of progress and can get smarter even after we ship it. Um So what does that mean for us, another colleague of mine, KSA Carter, who's the academic director at the B school. And I have been throwing around this idea for a while that actually maybe delivering products is going to look more like shepherding or farming than it is going to look like shipping. Now, we still use this mental of shipping when we're talking about even things like software and I think that's probably outdated. It's even outdated already. Right. Because software development is kind of a dress rehearsal for what I'm talking about with like constant version releases, beta testing, uh, constant debugging that when we push things out into the world, our responsibility is going to continue long after the shipping date. Um, and it, it, it, it seems like that should always have been the case, but frankly, it hasn't. So I think what you could do is if you're thinking about shipping a product, how do you create a nimble team that's going to be able to interact with that product over time? And again, it's already happening. Next one is they seem like us but they don't work like us. And I think this one can be, this one can confuse us a little bit. So they do a lot of human things. You know, if I go into chat GP T or I look at stable diffusion and create an image, it kind of looks like something a human could have made. But the way it actually happens is very different. You know, they get these huge pre training data with uh stable diffusion that's about creating noise and then subtracting it to get the image, which is not how a human does. That. The reason I bring that up is because we get so excited about the capabilities because the capabilities are so powerful, they they're actually lopsided and they have really weird vulnerabilities. So this is going on San Francisco right now with the um driverless taxis, people who are kind of not in favor of this are taking traffic cones and putting them on the hood and that stops the tra the taxi debt in its its tracks. And so it's just like a weird vulnerability that it has. So in terms of, of um putting things out to the world, I think what this means is that we are not just thinking about the features, but thinking about the faults. We're actually designing features and faults. At the same time again, this probably should have been done for years and it's increased in popularity. And I've heard a lot of people talking about it today, but I think that's like the critical shift there. And then uh Sarah and I have actually been talking about this, the side effects come along with the effects. So let me give just a quick illustration of that. Uh This is Carl Sagan, the scientist in 1985. He's speaking to Congress about what was then called the greenhouse effect that we now know as climate change. This is over a century after the industrial revolution. So the effects of the the side effects of the industrial revolution took that long to come into play. This is a similar moment. This is Frances Haugen also talking to Congress about this time, her concerns with social media and how it was affecting teens and then also how it's affecting society. This is less than a decade after the shift in social media that a lot of people think sort of spawned these issues, right? So that distance between when an effect happens and when the side effect happens are getting shorter, I think, you know, again, just recently, um Sam Ullman was in front of Congress talking about the worries about uh generative A I which had only been released with under a year at that point. So they're getting closer and closer and closer. I think you could think of this as a, as a major problem and it is uh as a big concern. But I actually think there's a silver lining in this one, which is that when things are changing at that rate, it's actually easy to perceive what's happening, right? Because you can very quickly see the causes and effects. So it actually makes it easier to act. The other thing is I think it really lowers the cost of investing in a hunch because if you invest in a hunch, you can validate it more quickly if those changes are happening in succession like that. All right. So, um so I mentioned that there wasn't going to be a big resolution and this is the moment of, of non resolution. Um What I want to say is, uh there's, I'll just, I'll just begin with a quote. Um or I'll end with a quote, I guess there's a French philosopher, um named Paul Valerie and he ha he has a quote that just like sticks in my brain. Uh And I repeated it all the time. He was dealing with emerging tech when he said it, his emerging tech was radio in the 19 thirties. And what he said is, can the human mind deal with what the human mind has created? And I'm not sure all the time, I'll be honest, like sometimes I feel like, no, absolutely not. Other times like today, I feel like, yeah, you know, if we can develop this ability to respond, if we can get comfortable, never being up to speed and kind of getting in touch with the things that we don't know. Uh Yeah, I do, I do think the human mind can respond to it and we can be a little bit less nuts, but to be totally honest, uh I think that's an open question that's for us to solve. Thanks so much.

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