You are listening to the HumAIn Podcast. HumAIn is your first look at the startups and industry titans that are leading and disrupting artificial intelligence, data science, future of work and developer education. I am your host, David Yakobovitch, and you are listening to HumAIn. If you like this episode, remember to subscribe and leave a review. Now onto the show.
Welcome back to the HumAIn podcast. Today, I have a return guest speaker who joined us last year in 2019 when the world was very much work from office. But now, as we are fast tracking throughout 2020, as we re-imagine the world and we re-imagine education and we re-imagine work, we’re looking at the “work from anywhere” world.
And so our guest today is Alberto Todeschini¹ from UC Berkeley² in the MIDS program. He’s a course lead in Artificial Intelligence. We spoke a lot about data and AI last year, but there’s so many new topics on our mind this year as we’re again re-emerging from COVID-19. So Alberto, thanks for joining us and rejoining us on the show.
Thank you. Thanks for having me.
It’s always a pleasure. We speak a lot offline about where we see the world moving, and one of the big trends that we’re seeing as we re-emerge is governments partnering with private organizations, basically public-private partnerships, and it’s around everything from education, society in the world. But one of the big areas you’ve been putting a lot of attention and energy towards is the future of environment. What are some things that you’re starting to see?
One thing that I’ve noticed recently, is that there’s probable lots amount of money flowing from governments around the world into stimulus to get us back on track after COVID. So an example from the European Union, for instance, is 826 billion US dollars, but we support. Is it for earmarks or environmental and sustainability and social activities? So this has been interesting because in the last few years, a lot of this is about the environment, about energy and about agriculture have really been penetrated by data science.
So we can see some evidence, for instance, from new emerging technologies with satellite images. Of course they’ve been around for a while, but there is an illusion. For instance, spatial resolution has improved massively, then poorer resolution has improved massively and our techniques of analysis, all sorts have improved massively. So I’m pretty optimistic actually, coming out of this big dark cloud. First half of 2022 will be some good news.
We’ve been looking at many years as a society, at these ESGs or these environmental and economic societies and sustainable goals, not only from the UN, but just where is the future? And one thing that we’ve seen a lot, it’s amazing to see that so much money has been set aside to look at the future, because what we’ve seen as we re-emerge from COVID is that there were some early promising signs of how pollution can taper off. Especially when we reduce some of these, let’s call them the bad actors of big pollution, like having cars in our city and having factories running.
We always knew there was pollution, but how much was it? I don’t think many people were aware till they could start breathing again. You and I were talking offline, some of these cities, they’re beginning to have some serious conversations about the change of cities.
This is one of the wonderful things that are actually emerging in the middle of all the gloom. So on the energy side, in newer energy technologies they’ve been around for a while, but they really have become mainstream recently, such as wind and solar. They are intrinsically data-driven. So you need to squeeze every last percent of energy out of this massively capital intensive works.
And there’s a lot of machine learning that goes into that. And regardless it is, it was really inspiring to see. How many people started walking again, with social distance and taking the bicycle instead of public transport. And we’ve seen a number of cities proposing new measures to pedestrian and cycle friendly zones in the city center, including Paris, including Milan, for instance.
And as you said, people are just enjoying the clean skies and quiet. So this is wonderful. Because it’s also a way to produce massive amounts of data, So we can expect, now there will be years spent by thousands of PhDs, plus the research, all the data that we’ve generated in the first half first quarter, a special point 20, atmospheric data, social data, employment data, and then, the longer term health data, for instance. So basically, that’s the opportunity, and for many of us who increasingly want to make a positive impact.
When we look at these pollution levels of big cities, I can speak to New York city where I’m based. And there were statistics that in the first few weeks, as we move through COVID somewhere upwards of 25% particle reduction is what we saw in the air. And that is incredible, not just for you and I to breathe and to live and walk in a walkable city.
But to think there’s been #statistics in the past few years that have clearly shown links, that the more pollution you breathe, the lower the IQ or the lower functioning of the brain. So, less pollution means not just the healthier earth, but also healthier human beings. And there’s going to be sounds like a lot of new startups on new initiatives emerging in this space post COVID.
That’s a great thought. That’s something I’ve been thinking about a lot lately. So we’ve seen companies born, and that’s thriving after 2008, a period of huge crisis. And then you see companies like Uber and Airbnb. They came around and then eventually fried. It was a time with a lot of financial hardship and all the people needed some extra cash, and they could make that extra cash by driving around or by renting the spareable. Now with COVID, we’ve been forced essentially to experiment.
And we will see more experimentation around the livable cities for instance. And it will be again, as you said earlier, private and public, and we will see maybe new experimentation around transportation. Certainly, there’s a lot of appetite for resilience, for community resilience, maybe at the city level, but also at the regional level and national level.
And again, along these changes would be hopefully based on data. There’s a lot of interest in logistics. Again. So why is it that we can all have months after we needed them? We can see less reliable disinfectants or things like that. So then once again, logistics is a big optimization problem. It’s a big problem about collecting data and figuring out optimization. So at the end of the day, it’s math? So this is another area of great opportunity that I see.
The logistics, I can just recall during the COVID times how I had to wait for some Amazon packages to take almost 30 days to arrive because they were non-essential items. And that shows how congested the logistical system became with supply chains. So, absolutely. There’s going to be some emerging startups that are saying, ”Really, do we need to go through so many pathways to get to our end consumer?” Or can we go a quicker process there? And perhaps that quicker process can also reduce the carbon footprint.
So perhaps we’re not moving through as many trucks or airplanes, or maybe even some of those vehicles are going to be more environmentally friendly. We’ve started seeing everywhere from Berkeley to New York City, these little self-driving mini vehicles that can bring you your sandwich, to take you at local buildings, but there’s even been talk of electric air taxis and all these ideas, some of them more futuristic, but a lot of it around clean energy.
This is something I’m really passionate about. So we’ve seen, with the shock of COVID and the shock of the price of oil and recent bonds, we’ve seen a lot of oil and gas companies and coal companies gone bust. And we’ve seen the investment moving elsewhere to renewable, which is certainly more future proof.
So one of the things that I saw has been floating around for a few years, but this will probably make it more visible and more directly relatable to quality of people is the idea for distributed warehouses. So you may not work in Manhattan or downtown Milan, for instance, where you could work in super vulnerable places.
So the idea is basically, imagine you have a shed and you have some objects in there, and they are guaranteed by the reputation system, which is the same that works pretty well for Uber or Airbnb and Lyft and the other ones. And you have a few essential items. So, instead of having big warehouses out there, you can have these self-driving cars coming sooner or later, in any case drones are coming and the little robots will be released.
So imagine you have this large distributed amount of important items, your toothpaste and toilet paper, and whatnot, stashed in gardens and places like that. So this was floating around a few years ago, but it’s suddenly much more interesting than when everything was running smoothly.
And I do fully expect things to start running smoothly again soon. But if you talk to the epidemiologists, they’ll say, well, there will be another one. As a matter of fact, it could be a lot deadlier. So it will be nice to have this distributed way of storing large amounts of essential items. Maybe not the perishable ones in gardens and sheds and little boxes around the counter side, but also around the suburbia. Well, maybe not downtown Manhattan. And so I will do it everywhere else.
It’s so interesting, thinking about distributed as the new normal. Traditionally we think everything must be in person. It must be synchronous at this moment. And we’ve seen how society is moving more to not only remote, but potentially, even as you’re calling it, this work from anywhere which is more distributed and in the supply chain space that is similar to cloud systems. And cloud systems, we think about, Oh, you have these big data centers, but then there’s edge locations. So you can get the parcels quicker. And it helps, especially in areas that are less dense.
What’s similar is that we’ve definitely seen as some of these locker based systems, like these Amazon parcel lockers or UPS lockers, where you can get those. There’s items and I could see multi-use there. Maybe some of them do have those essential items that you need to get when you can’t get to a store and they’re available, multi-use. And this makes me think a lot about what we’re talking about here, about the future of cities. We’ve been thinking about the future of smart cities for years.
And of course, in 2020 at the start, CES was talking about how 5G is going mainstream. And we’re now seeing that, slowly but surely. The Samsung Galaxy S12 Ultra is coming on the markets. We have the iPhone 12 coming on the market. These are 5G-ready devices with blistering speeds. And they’re definitely baked with AI applications all around. What are we seeing around these smart cities? Whether we’re thinking of Milan, whether we’re thinking of Berkeley, whether we’re thinking of Manhattan.
Another trend that I heard several years ago and I thought it was tried. Some people tried it, but it never particularly worked, but it could work now with the #technology Ijust mentioned, 5G, this distributed system and the ability to communicate incredibly quickly and also to do, technically speaking, inference on the edge.
So you’re doing AI with your phone instead of moving data around as much as possible. One interesting thing that I had, again, after a few years, not heard about it would be to fear. Imagine a startup, there were a couple, but I don’t think they ever went anywhere. And let’s say that you own a hammer. If you lend the hammer to your neighbor, it’s not like it is going to wear out just because the neighbor is going to nail 50 nails.
And maybe you use your hammer a total of a half an hour every quarter and the way I see it, they hammer that way. So, imagine that, again, on the topic of distributed and also resilient infrastructure or visual infrastructure, imagine that you know because of this app your neighbor has a hammer and the neighbor knows that you have the one screwdriver that you need.
Well, wouldn’t it be great if we could figure out the way that I can just borrow that hammer that I only use once a year or once a quarter or a few minutes even there? So this is different from what I mentioned earlier, where it could be about selling things. There’s a small box in your garden that has some toilet paper, some disinfectant, things like that which can be picked up when you want. It’s more about savings stuff. It’s more about communities sharing, sort of the things they were willing to share such as tools, especially the ones that are not going to expire. The hammer, a saw.
And naturally you need some pretty robust technology to make that useful. People don’t want to write up the list of tools that they have. However, if I can just take a picture of a few things that I have, and my phone knows, yes, this is that kind of hammer. This is that kind of saw, this is that kind of a public drill without me having to punch in everything. Then that could be useful.
We actually had a similar project with some of my students where the idea was, you have a fridge and you have some ingredients, and you do want to cook, but you don’t know what to do with what you have in the fridge. Or maybe you just miss one of the things. Now, sure. You can keep a running database where you input everything that is in your fridge: ”I have one garlic. I have an old onion.
I have some expired tomato paste. I’m going to do it. It’s difficult now, but we’ll get there eventually soon enough. And just take a couple of pictures and we’ll tell you with the computer vision what’s in your fridge. And then with that, you can cook this and you can substitute this ingredient with that ingredient. So it’s like, let me open the fridge. What can I have reasonably healthy today? But we tell you, why do you have to keep up this mental accounting of what you have in the fridge?
It’s so incredible to think about the industries that are being disrupted with technology, especially the on-demand economy. Speaking about both grocery and physical products, as you talk about some of these failed startups. One of them, one of my friends’, Ryan Delk, led Omni in San Francisco, and they were doing that where you could put literally your hammer or your drill bits into storage and rent them from friends or colleagues. And maybe the market was premature.
Maybe not there just yet, but I love the grocery side because especially during COVID I have amped up my cooking skills. I have made a new famous dish every week. Whether it’s beef or some of these other really classic dishes taking the nom. But sometimes I’ve thought, why do I need to buy all these ingredients? it can be very expensive, especially when you want to just make one part of a meal.
It’s so interesting though, to see the future of grocery as we’re leaning into this topic. There’s been much said about the Amazon Go stores that had launched and a lot of these augmented #AIproducts like Caper, where you can have a shopping cart that you can check out from.
Back in January of 2020, which feels like a lifetime ago, but I was actually in Milan as I was finishing up New Years’ and I got to go to that futuristic AR supermarket that they talked about when these MIT professors had helped design. And it’s just incredible to see the technology. There’s so much innovation happening in Europe.
That’s true. So the market in Europe is pretty fragmented. Partially that has to do with language. So, pretty much most European countries would speak reasonable English, but that’s not absolutely not true for the entire population. So there’s an issue with scaling Sydney, but there are a lot of regionally successful startups where the less developed certainly are the world leading companies that you see coming up again and again. In Silicon Valley and thereabouts.
So, growing up with one foot in a city in the Alps and one foot in a village of 200 people in the Alps. It’s interesting to see both of them. And I lived in places like Tokyo for two years and London for six years. And now the San Francisco Bay area, Berkeley, for six years. It’s been interesting to see the cultural differences. One thing that I enjoy about the village is that if you need something, you need flour because you are going to bake, but guess what? You don’t have enough of the right flour or you need that hammer that we talked about, you know exactly where to get it.
It’s easier in a village of 200 people, you ask your cousin, you ask your aunt or someone you always know, Oh, if you need the hammer, you go to that person. So that’s not being replicated successfully as far as I know. And as you mentioned so far with technology, maybe because some of the items, not sure about your friend’s items, but they were some of the things that I saw, they tried to solve the problem at the wrong scale.
And one of the things that maybe has changed with #COVID is the sense of locality. We’ll see how much goes back to normal eventually. I know it sounds unthinkable to many of us to think that many things will go back to normal. But I do think that a lot of our lives will go back to normal.
It’s interesting that one of the big things I’ve heard about in tech from some of the leading VCs, especially like Paul Graham, is to do things that don’t scale. If you can build it at a local level, then you can scale it, but you should start small to get big.
This reminds me as you’re sharing these stories, Alberto, on groceries. When you think about it, do you need the right flour? All purpose flour is not bread flour. It’s definitely not the right flour. And this isn’t a distinction. That’s important to make similar to distinction.
When we look at what occurred with COVID, our #datascientists, epidemiologists. Do we know everything about healthcare? This may not be true. We may not be able to translate data to scale in healthcare. And I know as we’ve been flattening the curve, and now it seems that as we’ve re-emerged and reopened the economy that genuinely we’re doing pretty well at keeping with the right PPE and keeping people healthy. And that’s all to be determined over time.
But data scientists and their predictions, I don’t think it went that well. Some people were predicting millions of deaths in the United States and we’ll have to see how that ages on this episode. But what do you think about that with data scientists, epidemiologists and specialists in the field?
That’s a great question. That’s an important question. I want to start with one thing. Yes. We butchered a lot of the predictions. Absolutely. We butchered them big time. However, I was still hoping that people follow the experts next time.
So the most takeaway is to say, see? epidemiologists didn’t know. Or we see all those mistakes. We were promised millions of deaths and we only had a hundred or maybe 200,000, we’ll see in the US how many we end up having, right. We already have above a hundred thousand. I know that people will trust the epidemiologist next time, because it could be 10 times deadlier, easily.
We know something else will come and the chances are sooner or later, you will be far deadlier. So with that out of the way, absolutely. There’s so many problems. So my problem was in simply reporting. So we don’t even have the same definition. What is a death by COVID or is death with COVID?
So if you see how different, even in the same country, different municipalities in different counties are reporting deaths. It’s just very complex or very complicated. And then we saw analysis done by some cowboys, say on LinkedIn or whatnot, at the speed of light immediately in February or whatnot, and they completely butchered it.
And then they kept butchering it. So there’s a huge amount of work that needs to be done postmortem, in the real meaning of the term, to understand, okay, what went wrong with the data collection? So that next time, okay, collect it better. What went wrong with communication between health authorities and political authorities and the general population?
There’s going to be a lot of soul searching that we need to do as data scientists suddenly rushing. Everyone wanted to rush, to find the solutions and find the advice and everything. And a lot of it was pretty poor quality, no rush going forward. It will take a bunch of years of research to figure out exactly.
Think about it. In theory, you would have to go to every single hospital in the country, let’s say the US, and find out. So what was your definition of death by COVID? Exactly. So that person was what, 50%, 40% COVID and 60% for pneumonia? or was it the 55% COVID and then 20% pneumonia and whatever else, something else? We have no clue, maybe individual directors, because individual clinics will know hopefully what they are doing, but we have no idea what’s happening on a large scale.
And without that clarity, there’s no way that we can do any robust and interesting data science. We can have opinions. And your opinions are cheap. And everyone likes to have opinions that certainly we are doing a good job. That’s not the years and years digging and studying.
We’re definitely gonna need to see more collaborations between science, publications and researchers, because like you mentioned, Alberto, we’ve seen tens of thousands of research papers just on COVID-19 and Coronavirus. And that is mind-boggling in two capacities: One, it’s fantastic to look at the collaborative research.
We thought the world was splintering, moving to nationalization, but globalization still exists. And researchers are working all across borders, but then who are all these researchers? How many of them are epidemiologists? These business experts versus the data scientists who may be data experts. We definitely always need to bridge the gap between business domain and technical domain, and that’ll help us, make better research.
We were chatting offline for the show as well that you’ve started to see the movement with tech conferences to go #virtual. And some of these leading tech conferences have fantastic new things, especially with going back to our topic on carbon emissions and forestry and satellites. There is such an incredible wealth of knowledge that people are interested in now because we got to dig away from cities for a moment of time. What are some of those things you’ve been seeing with satellites and images?
So I have a couple of projects actually running now, one was pretty simple. It is pretty simple. So you have this satellite imagery about cultivated areas.
Cultivated areas are very interesting because agriculture consumes the majority of fresh workers and about half, depending on which paper you’re reading, it can be about half, 52% of agriculture. Currently it is not sustainable. Purely from the point of view of water. And we’re not talking about deforestation, we’re not talking about runoff of chemicals into the ocean, purely just the water. So if you read the news, look at what’s happening to water in Australia, the Midwest here in the States, the Central Valley. They’re all dry now.
So the better we understand any part of this massive ecosystem that includes rain fed, and includes irrigated land can push the needle to, essentially, a more sustainable and intelligent use of water. One thing that I’m working on that is very interesting is to find this sweet spot, the optimal spot between maximum yield and sustainability, still with water, and still with agriculture, and we’re using satellites for that.
So basically the idea is simple. Let’s say there’s a curve, and maybe it’s a normal curve, the Gaussian. And let’s say that you’re on one side. You’re not watering enough, you’re leaving crops on the table in the soil, and that is a problem because of the quickly increasing population. And yes, there are more calories around and we need them, but there’s a lot of food that is not nutritious as you know. But if you push the other way, you’re using too much water and then you risk ending up with water, stranded assets. Essentially pieces of land that don’t have enough water to be cultivated optimally.
And another thing that has been interesting is that water is also used for electricity generation. Everyone knows about hydroelectric, electricity generation. But thermal electricity produced by means of coal is actually very water intensive, just because you need a lot of water to cool the heat that is generated.
And also carbon capture, some of the main carbon capture technology Technology is very water-intensive. As we increase both the data collection, as well as the predictions, which are two of the main things that we can do with machine learning, we can just use water better, essentially. So simple as that. Sustainably. But also with increasing yields.
And one of the things I noticed is that some people just don’t want to know about sustainability. They want maximum yield today, but also in five years. It will react very well, if you put it like that. If you say, sustainability, what do you mean? Well, what we talk about is finding the sweet spot, the optimal spot, with optimal use of water for businesses, for profit, and also while respecting the balance and natural resources out there.
This maximum yield conversation leads into a very interesting bet that we’ll be talking about as we get further into the show. So everyone definitely stayed tuned about thinking about tech trends, but, as you’re sharing in five years versus today, yield is a little bit more challenging to predict. And as we’re moving into this internet-first society or digital-first society that we’ve seen as a result of COVID one thing is, data’s gotten a lot more spiky.
It’s gotten a lot more volatile and we’ve seen that there’s been so much data collected with contact tracing apps and movement of people and trading and the finance and quant world. Where do you think data’s gone? Is it getting spiky, especially with #machinelearning?
Absolutely. To give an example, how Zoom completely exploded in popularity? And as soon as it started going viral, this has completely dominated the market. And yes, I know some other people are still using Skype and whatnot and Google Meet, fine. But Zoom, which I’ve been using for years for my online purposes has completely exploded.
I’d be interested to see the actual increase in usage in the last six months. I wouldn’t be surprised if it’s the next, possibly more. Now Zoom is a verb. Now, you zoom your grandparents. So clearly that was only possible because it’s a technology-first company. You cannot scale certain types of businesses equally fast in six months, you cannot start producing from 1 million cars to 10 million cars for a car company, not even Tesla can do that in six months, it’s just not going to happen.
So absolutely, as we move towards collecting ever greater amounts of data, those companies have to make good use of that data. And by good, we’re speaking about business-wise here, specifically. It’s not a judgment about privacy or anything new. We’re talking about commercial business at the moment. This is going to dominate WhatsApp and Amazon in the last few months, sure. Even Nike, Amazon, scrambled a bit with logistics because of the incredible spike of users, as well as because of physical distancing measures of employees.
What’s happened to Netflix? A huge increase in usage. So these companies that are, from day one, data-driven companies, are all thriving and they’re becoming ever more unmatchable. I don’t even know what a competitor of Amazon looks like. You know you are number one when you cannot even fathom someone else catching up to you. Sure, in niches. Yes. But not in general online commerce. Even though Walmart is doing fine, Target is doing fine, but it’s just not keeping up with Amazon.
As we’re looking at how the world has shifted because of COVID, some of it’s going to be short-term and some of it’s going to be long-term and that Amazon effect is being felt everywhere. But we’re looking at the changing workforce, the changing of living and the digital experience. You’re coining this term that we’re moving into like a work from anywhere space. What do you mean by work from anywhere?
What I mean is that we should not be limited to think in binary terms. So all of the discussion is couched in binary terms. Either you work from the office, maybe 9 to 5, Monday to Friday, or you work from home.
So that’s the first thing that we need to debate. One of the good things, actually, about COVID is that it’s forced us to think about flexibility. Many companies are not going to go full one direction or the other, full from the office or full from home, or they’re going to be a little flexible, certain to be a good thing.
How many people enjoy their commute? If you can stay home every Tuesday and every Thursday, maybe of the work required, would you do that? A lot of people would do that. So that’s one dimension. And the second dimension is, well, where is home? So if you work for one of those companies that allow you to work fully remote, where is home? Are you even going to have a stable home or you’re just going to travel around. And especially for some people in their twenties, for instance.
The danger is that work is everywhere, anywhere, as in the possibility. My boss is not checking, but so long as I’m prompt enough and in a reasonable time zone, I can do whatever you want. That’s great. That’s flexibility, but work everywhere. As in, you always have that connection with work and it’s difficult to check out. That’s the negative effect, certainly.
That is definitely a mental health crisis that’s brewing. And there’s been a lot of the companies out there, who’ve been thinking about the headspaces and cons of the world that have been helping people unplug or disconnect.
But let’s get into something very controversial. We’re talking about tech, we’re talking about tech leaders and there has been this dichotomy or this binary, if you will, where one company leader executive, Jack Dorsey of Twitter and Square has said, “you can work from home forever, we are just going to begin removing our footprint” and Twitter historically has been the company that has not worked from home, versus Facebook.
Facebook, Mark Zuckerberg, has come out saying very publicly numerous times “I’ll give you the opportunity, if you’d like, to work from home”. Absolutely. We need to be an empathetic-first company, but if you’re not in our core Tier 1 cities, and you move to a Tier 2 or Tier 3 city, there may be some compensation changes in store. What is your take on that, Alberto?
That’s been interesting being in #Berkeley and just a few miles from the headquarters of both companies. And I have a lot of friends and former students who work there. So that’s been interesting. I was not too surprised to hear Twitter’s decision, which was applied to Square, another company whose CEO’s check those two.
So that was not too surprising. It was a little surprising in terms of a high profile. They’re still super famous companies. It’s super in the media, especially Twitter. However, if you read the news about Jack and what has been seen over the years, it was not too surprising, it is going to be a very interesting experiment and I’m sure we’ll learn a lot.
And in a way it was not too surprising to hear from Mark, either. He’s been somewhat conservative in many choices. I don’t mean politically, obviously. I mean, in terms of maybe not pushing the envelope with other things, so regarding costs, that’s absolutely fascinating. So I’m pretty sure some people would gladly get a small pick out, possibly a substantial picker to move away from San Francisco or Palo Alto or whatnot.
They move somewhere more idyllic. However, one suspects there is going to be also a fair amount of resentment. So if you are hired in a place that is distinctly cheaper and you grew up there and from day one, if I’m hired remotely, I will make X percent less, but you know what?
Home costs 30%, possibly 20% what it costs in San Francisco or Manhattan, maybe it’s easier to swallow, but if you want to relocate and then have to take pick up, that’s difficult. So if you, if you use two X and then they say, okay, how about we give you 70, 80% X that’s difficult. That’s what I’ve seen out here. It’s all cheaper. And I can walk to work, which is Starbucks or whatnot versus let me take a pay cut now. So we’ll see how that turns out.
It’s a little early. It’s going to be very fascinating to see how many people accept them. To be honest, I’m also convinced there will be lots of people leaving the Bay area. Or other expensive areas in the US and elsewhere. News from this week is that prices are finally starting to react negatively. I mean, rental prices in the Bay area. So that incentive to move may also change a few percent points. Let’s say you pay 10% rent less in San Francisco. Then it’s a fair bit of incentive, less to move elsewhere.
That’s right. We saw in 2008 during the global recession, that prices fell upwards of 15%, from a rent perspective. And our early signals are showing that prices for renters in San Francisco are down about 10% and Menlo Park down 15%. So perhaps a similar trend is in store. And maybe that can ward off some of the facts of this suburban sprawl.
Like yourself, I’m in New York City, another big city. And I’m genuinely a fan of this economic theory called aggregation economies, which is when you’re co-located and in these big urban centers where anything’s possible, it just couples, the effect is stronger. One plus one is definitely more than two. It could be three or even 300, which are things I think about. And the challenge is that we, as practicing data scientists and AI experts, in the short-term we overstate a lot. We think self-driving cars are going to be here next year.
Okay. There they’re not here yet. But in the long-term I don’t think AGI will be here in my lifetime. It’s something people know I’ve said in the show. I don’t think it will be, but you know what? I am not Nicholas Tesla. We got to see where that’s going to be. So with that note, thinking about the big picture, predictions, trends, call to action. What are some things you’d like to leave with our listeners today Alberto?
Let’s carry on with a thought about cities. One of the things that could conceivably happen, I don’t expect this exodus, but some dilution potentially. If you only need to go to work, if you feel like it, you need to go to work once or twice a week. You’d like to meet people and see your boss and whatnot. But what about living a hundred miles from work? You wouldn’t want to commute 200 miles a day. But if you only need to do it once a week, maybe you will do that, so it’s a mild delusion though, where the center is still the city.
So similarly, maybe you just go to work on location five days a month and you live a hundred miles, 150 miles from work it’s from SF, for instance, or from Boston or whatever. So it’s some delusion, but the center remains the center. That’s a very conceivable trend. And especially, as you said, self-driving technology improves and sure enough, it’s taking longer than even I posted a famous young LinkedIn, I was so wrong a few years ago, but nevermind.
So as that improves, it’s like, “Oh, you mean I can just read the news for those 120 minutes once a week, one way that I go to work”. But the center is not going to change. I don’t think so, maybe a little delusion, but I don’t expect an exodus at all. What should we do? maybe what we can do and we should do is find ways to improve life in the city, which is what we’ve been saying for a while.
Let’s make them, let’s use technology to figure out how to improve life in the city or make places where we enjoy walking. We like walking, we enjoy local restaurants. We enjoy going out. We like biking around the same fit in the city, livable cities. So maybe that is something we can think about and work towards.
Thinking about what you just shared. I’ve also heard these stories about New York City where the Hudson Valley could be a place where self-driving cars are here tomorrow. So you can live a hundred miles out and commute in, but we’ve even seen in the real world today where I know doctors who particularly live in Florida and commute once a week to a hospital in a different state. Depending on what work they’re doing. So it definitely is possible. We’re going to re-emerge stronger.
The economy is going to rebound. We’ve seen early signals from China that airline traffic, less than two months after they’ve been fully open, is early back to 80% of pre COVID levels. We’re seeing similar signals a little bit lower, but trending up also in the hotel and the restaurant space. So, if there’s one thing I know is that we’re a resilient nation.
What call to action, a message, would you like to share with the audience?
I agree. I’m optimistic. It’s been awful. It still is awful, but I’m optimistic. So what I would say is just look around. Look around your neighborhood and think of things that you want to stay with us. So, yes, we’ve been given a great opportunity to reset a lot of our habits. It was greatly challenging. So how many of us started eating better during COVID? Because our habits usually were kind of destroyed.
How many of us started working out better? Or worse. So we were given an opportunity. We didn’t ask for the opportunity, but we were given an opportunity to change a lot of things to break out of habits. And so, what I would say is, let’s make the most of it. This is really, the most important thing that we can do looking forward to cement that optimism that many of us are actually starting to have. Let’s break the bad habits. Let’s remember the good things that start these new good habits as we can get out there more and more.
Alberto Todeschini from UC Berkeley. Thank you for joining us on the HumAIn podcast.
Always great having you, my friend.
Thank you for listening to this episode of the HumAIn Podcast. What do you think? Did the show measure up to your thoughts on artificial intelligence, data science, future of work and developer education? Listeners, I want to hear from you so that I can offer you the most relevant trend setting and educational content on the market.
You can reach me directly by email at email@example.com. Remember to share this episode with a friend, subscribe and leave a review on your preferred podcasting app and tune into more episodes of HumAIn.