- 2 months ago
Food security is no longer only a question of yield, it’s a challenge of resilience, sustainability, and scientific innovation across the entire agricultural value chain.
From precision machinery and regenerative farming to AI-driven biological discovery and genome engineering, this session brings together leaders working at the intersection of agriculture, data, and life sciences. Together, they will explore how next-generation AgTech is reshaping food production and what it will take to build scalable, climate-resilient food systems for a growing global population.
From precision machinery and regenerative farming to AI-driven biological discovery and genome engineering, this session brings together leaders working at the intersection of agriculture, data, and life sciences. Together, they will explore how next-generation AgTech is reshaping food production and what it will take to build scalable, climate-resilient food systems for a growing global population.
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TechTranscript
00:01Transcribed by ESO, translated by —
00:43All right, ladies and gentlemen, we're going to start right now, if you want to have a seat.
00:49I'm absolutely delighted to be with you all today to talk about a topic that is very close to the
00:58hearts of the people who are on the floor.
01:02I'm going to be actually having the pleasure to share the stage with three distinguished guests this afternoon.
01:10Inbel Becker-Richef, managing director of Microsoft AI for GoodLab, Miguel Molina-Romero, CPTO and co-founder of Orbem, and
01:21Hila Cohen, deputy head of WFP Innovation Accelerator.
01:28Before I hand it over to them and ask a few questions, I was actually very impressed this morning when
01:37I personally entered the VivaTech about what was written everywhere, which is basically, we do not predict the future.
01:46We host it.
01:49And basically, hosting a part of the future of the food security is what I propose we do for the
01:56next 40 minutes together.
02:00For more than seven decades, actually, the food system was based on the concept of pretty much optimization, right?
02:09It was about to feed the world, it was really about producing cheap, fast and enough, if I have to
02:16summarize it.
02:17And then, the concept of food security was somehow derived from this reality, which means that what mattered the most
02:27was really producing enough, being sufficient.
02:32The reality is that the model was really built around scale, productivity, yield improvement and global trading integration.
02:43But a few things happened and the reality is that this future has never been as present as we've seen
02:50it this year.
02:51We've seen climate shocks, geopolitical tension, supply chain disruptions, we've seen it all.
02:59And at the same time, we see increased, rising consumer expectations.
03:04So, the reality is that food security, and that's really a discussion we would like to have today, is that
03:10food security is not only anymore a concept of optimization.
03:16In our perspective at PwC, this is really a concept based on four pillars.
03:21Now, when we look at food security, we look at it in terms of sufficiency, as it was before.
03:28We look at it in terms of integrity, so it's not only a matter of is there enough, but there's
03:35also a question of what is inside.
03:38And there's a concept of longevity, which is sustaining the whole value chain.
03:43And finally, there's a fourth concept attached to it, which is really sovereignty.
03:49And we will be talking about sovereignty because sovereignty encompasses two elements.
03:54One is really being immune of disruption, and we all have in mind Hormuz and the implication of Hormuz.
04:02And at the same time, limiting the dependencies, dependencies and power dynamics.
04:08So, sufficiency, integrity, longevity and sovereignty are the four things, the four elements that define in our perspective food security
04:16in those days.
04:19Having said that, there's an element, which is really the elephant in the room, which is technology.
04:23And now the key question to us, to all of us, is really how technology can help deliver better food
04:32security.
04:33And the approach behind that, it's technology in a way, help us consider the reality beyond trade-off.
04:42You know, historically, when you looked at food security, it was really about having enough or is it qualitative enough?
04:52And so there's always been conceptually a question around, you know, do I produce enough or do I make it
04:59like very much qualitative?
05:01Technology helps us go beyond the trade-off. You can have it all, basically.
05:05When you have the convergence of satellites, AI, low-cost sensors, computing power, for the first time we go beyond
05:12those trade-offs.
05:13Now, the question, and I'm going to open the floor with this, it's not anymore necessarily a question of technology.
05:22It's also a matter of adoption. How do we make sure that this technology, as it goes very fast, doesn't
05:31serve only a world of giants?
05:34You know, how do we make sure that the level of adoption of technology is strong enough, is spread enough,
05:40so we make it really a solution that benefits to the entire, to most of the stakeholders of the value
05:46chain?
05:47That's really where we wanted to start the discussion. And with this, maybe I will start with Hila,
05:55asking you maybe about if you could bring a bit of perspective on what does WFP Accelerator do,
06:01and also your perspective on this very fragile environment that we've been seeing over the last few months.
06:09Okay, thank you so much. So I'm part of the United Nations World Food Programme.
06:14We're one of the largest humanitarian actors in the world. We support people in emergency situations,
06:21people affected by war, by climate shocks, and by the rising cost of living.
06:27And sometimes communities face these triple burdens together.
06:31We, you will see us anywhere, you'll see the UN responding to an emergency, it's probably us, not only supporting
06:39WFP operations,
06:40moving food around the world to complex locations, but also providing cash to families.
06:48So just for you to understand our logistics operations, we manage a fleet of more than 120 ships on a
06:58daily basis,
06:584,000 trucks, and 80 airplanes moving food. And on a yearly basis, we give around $2 billion in cash
07:06to families.
07:07So the need is out there. We, on a yearly basis, on average, support 100 million people per year.
07:14Our function, the Innovation Accelerator, was set up to help WFP integrate innovation.
07:21We are very operational, so our teams already innovate on the ground.
07:25But there's a different level and aspect. It's how can you embed a startup into your operations?
07:32How do you help a supply chain experts, solving logistics problems, embed AI into their operations?
07:40So we imagine that we are a corporate venture arm and R&D team for the World Food Programme,
07:47leveraging the expertise of our colleagues around the world.
07:50So, and what we see, what you ask about what's happening right now, part of our job is to understand
07:57what,
07:58to understand the problems and then understand what are the priorities that we focus to help the organization in times
08:04like these.
08:04Yeah. I'll stop there.
08:06Thanks. Time like these. We've seen it all this year.
08:09We've seen it absolutely all. Energetic crisis, geopolitical tensions, supply chain disruption.
08:17In Bal, in this world where we see a multiplication of shocks, how does technology respond?
08:26Hila was mentioning the ability to bring AI solution embedded to, you know, those different realities.
08:34From your perspective, and I know you launched something called Rapid.
08:37Can you walk us through a little bit about what Rapid is and how you position yourself in this world?
08:44That is very uncertain.
08:45Great. Thank you. So maybe I'll step back for one moment.
08:49And I'm here representing actually two organizations. One is Microsoft's AI for Good Lab.
08:54This is a philanthropic arm of Microsoft working on social good issues.
08:58So really bringing in a team of data scientists and partnering on the ground with a range of organizations,
09:05of NGOs, of governments, working on a variety of issues from food security to biodiversity to fires to lower cis
09:13language models.
09:14I also sit here from NASA Harvest. NASA Harvest is NASA's food security and agriculture program, which we founded in
09:242017.
09:25And the focus is really on how do we bring satellite data and technologies and AI for translating that into
09:32evidence and working on food security on agricultural across the globe.
09:37And so with applications from understanding how much food are we producing, where might a drought impact food production and
09:44by what quantity to supporting insurance and index insurance applications.
09:49But one of the things that we had a lot of requests around were conflicts and wars, for example, where
09:58we need information about what's happening on the ground.
10:01Yet we don't have access at scale to be able to understand what's happening.
10:05And one of the core examples that I have is actually the Ukraine.
10:10We were contacted by the Ministry of Agriculture of Ukraine when the war started to ask if we could help
10:16support understanding what the implications of the war were on agricultural production in Ukraine,
10:22how much of their cropland was under occupation, how much is being produced on the occupied side versus on the
10:29government held territories.
10:30And so satellite data really became the only way to be able to do that.
10:34And we're still actually doing that today.
10:36And in fact, yesterday released our numbers for this season for the first time to the ministry and working very
10:43closely with them.
10:44And so we started to get these kinds of requests that were in Sudan not talked nearly enough about.
10:50And I think Hila can talk a lot about that and about the tremendous and the famine that's happening there.
10:55The Tigray crisis or so this list goes on and on.
11:00Similarly, when we have extreme weather events like droughts, like floods and again where we need to have information very
11:07rapidly to understand what the scale is of the impact.
11:11Again, satellite data become really critical.
11:13And the third part of requests that we are getting and we're getting was around market transparency or lack thereof
11:20where you could have a large producer that can have a large impact on agricultural markets,
11:25but maybe there isn't transparent information or timely enough information about what their production is.
11:30Again, where satellite data can provide really critical information.
11:34And so we realized there was this real need for being able to develop this, but also that this had
11:39to happen in partnership because this truck touches humanitarian.
11:42This touches development, but it also touches markets and trade and national security, right?
11:48Food security is also national security.
11:50And so how do we start to bring these communities that are traditionally siloed together?
11:55How do we bring in their expertise to drive these kinds of assessments and to co-develop them?
12:01And that's what RAPID is.
12:02So it's rapid agricultural assessments in support of policy and action.
12:05We are going to be launching that also with the World Food Program, with the UN Food and Agriculture Organization,
12:11with the International Grain Council, with a famine early warning system, and the list goes on.
12:17But also partnerships across public and private sectors.
12:20So, of course, with the Microsoft AI for Good Lab, Planet is a commercial satellite provider who is committed to
12:26this cause and to providing information.
12:30And being incubated under Rockefeller's Catalytic Capital.
12:33So we're really excited to be building this international initiative to be able to help to respond to these requests.
12:42Critical is always going to be, and I think you'll hear that a lot on our panel,
12:46that these technologies are co-developed and driven by the needs.
12:50And if they're not, we're not going to have adoption of this, and we won't see the impact.
12:55And so also advice to those of you who are maybe here in terms of startups or researchers,
13:00I think making sure that you're not just kind of understanding and seeing a problem and developing applications,
13:07but really making sure that those are integrated and driven by, because you can have the best solution.
13:12If you didn't develop the trust into it, if you haven't co-developed it with those who are supposed to
13:17use that,
13:18then the likelihood of adoption, which is what you're referring to, is very low.
13:23So I'll stop there.
13:24That's a very, very useful piece of advice, I would say.
13:28And listening to you, I'm really amazed also by the feeling that I had here this year in VivaTech,
13:35which is I think we've really like raised the bar in terms of where we stand from a technology development
13:41standpoint.
13:42What you've just explained is absolutely fascinating.
13:45I mean, this is really like direct application of technology on our most serious and challenging issues that we are
13:55facing.
13:56You know, it's really about technology does really more than measurement.
14:01You know, it can anticipate, give the evidence before the shock.
14:07The ability and the options are absolutely phenomenal.
14:12So I think this is really interesting.
14:13Also, the way you put that in perspective, which is having a way more holistic approach
14:20and, you know, bringing together a community of solvers.
14:23We often use these words in the PwC world, you know, that we believe very much.
14:30Thanks for those first words.
14:32And, you know, back to the Miguel, the introduction, you know,
14:36I was referring to those four concepts of how we could look at food security, you know,
14:42beyond the first concept of sufficiency.
14:44One of it is integrity.
14:47So really what is inside and how we make sure we do not decouple productivity and quality.
14:54I would love you to tell a little bit about the audience about what you do,
14:58what you have developed at Orbem,
15:00because I think this is absolutely spot on on this ability to consider food security
15:05also from a question of a perspective of quality.
15:08Thank you, Jonathan.
15:10At Orbem we have industrialized magnetic resonance imaging, MRI.
15:15So these machines that are in the hospital that you can go and get scanned,
15:19they're very useful for medical diagnostics because the technology itself is truly versatile.
15:25You can use it for many different things and it produces high quality diagnostics.
15:30So at Orbem we question why this technology has to be constrained within the hospital walls.
15:38Why cannot we use this technology for something that is also very impactful for our society?
15:44And we started working on how can we bring this technology into the food environment,
15:50bring it into the production floor where all the food we consume is processed and then served to us
15:58to increase efficiency of the system.
16:01And it's fantastic.
16:03We live in a wonderful technology era because now we have a new dimension to solve problems,
16:10which is artificial intelligence.
16:12What constrained MRI in clinical worlds is that it's complex, it's expensive,
16:18and it's a super slow technology.
16:20And with AI, we have simplified it, we have made it cost effective,
16:26and we have accelerated it dramatically.
16:30What traditional MRI takes to scan 10 minutes, we scan it in less than a second.
16:34And if you can scan in less than a second, you suddenly can see inside thousands of samples per hour.
16:42And that allows us to scan inside objects and see what is inside.
16:51And I'm going to make a couple of examples of the things we work on.
16:56Like, what are the real applications of this?
16:57Because this is nice, but what do we do with that?
17:00So I don't know how many of you actually are aware of the problems in egg production in the poultry
17:06industry.
17:06In egg production, the eggs are basically laid by the female chicks, the hens.
17:14Males are completely useless.
17:16And when they hatch, they're also not good for meat production.
17:22So basically they'll kill right after hatching.
17:25That is really questionable moral practice.
17:31Because if you can imagine that there is one hen per person in the world, that basically means that we
17:37kill around 7 billion or 8 billion male chicks just to have the females.
17:46We have to stop that.
17:48We look inside every single egg during incubation, and we can tell very early in the incubation process if an
17:54egg is a male or if an egg is a female.
17:57And we do the full end-to-end service to our customers.
18:00We sort the eggs for them.
18:02They send the female eggs back to the incubation.
18:05So only female hatch, and they produce the eggs we eat.
18:11And the males go into animal feed production or biogas production.
18:16We have removed 50% of the waste that was produced before and give it a new purpose.
18:23And we have created, or we have improved the animal welfare of the poultry production.
18:31We are actually the global champion in InnovoSaxing.
18:37I mean, it's a European technology produced through European regulation.
18:41And we're expanding now into more countries.
18:45So around 50% of the eggs that are InnovoSax in Europe go through our systems.
18:51And now we're expanding into other applications.
18:53Go back to food security and integrity, as you were saying.
18:59We are expanding into fresh produce.
19:02This year we're launching two new products, one in avocados, one in watermelons.
19:07They're actually crops that are heavily consumed in Europe, globally, very much.
19:16They're also very intense in resources.
19:19And we can see inside each of them.
19:22Our customers face a reality.
19:24They don't know what is inside their products when they ship it to the retailers.
19:27And because they don't know, they take precautions.
19:34They are very extremely careful to ship only those things that they're sure they're very high quality.
19:42And in that process, around 30% of the production gets wasted.
19:46We can tell them exactly, this is an avocado that you can ship in two days.
19:51This is an avocado you can ship tomorrow.
19:54This is a watermelon that you better don't ship because no one is going to be able to eat it.
19:58We use it for something else.
20:01And then we can produce or we can serve the same needs using less resources.
20:08Again, food integrity with impact in abundance or sufficiency.
20:18Thanks very much, Miguel.
20:20And that's, you know, we'll come back to that in a second question.
20:24But I'm just, you know, just want to make sure that everybody heard two things that you mentioned,
20:30which is, you know, European based, European production, one of the world leader.
20:37It's great to have you also here in Europe and being able to deliver all that and to produce all
20:44that.
20:45So very amazed by this ability to bring technology in this kind of day-to-day life somehow.
20:52You have a direct impact on what we eat.
20:55You have a direct impact on what is produced.
20:57And you touch not only upon integrity, but also in terms of sufficiency in one way.
21:02So very, very interesting.
21:05Thank you for this first comment.
21:07Hila, back to you.
21:10We're talking technology.
21:11That's great.
21:12This is the right place to talk about technology.
21:16But there's also this question around adoption.
21:19And you're very well placed to talk about that.
21:21How do we make sure that we do not create a small private club of giants who will benefit to
21:32those technologies?
21:32How do we create the right conditions for enablement and then for deployment?
21:37Great question.
21:38So first of all, we understand that hunger is one of the biggest problems on the planet.
21:44So also the assumption in the World Food Program and with other actors is that we will not solve hunger
21:51on our own.
21:52So you need to find different ways to work with different actors to address this.
21:56It could be in partnerships with large companies.
21:59But the other sector, in my opinion, is also startups.
22:03There are a lot of innovators out there.
22:05There's people who have a solution to diverse problems that we have.
22:09So first of all, when we work with startups, we really try to identify a problem.
22:15So it's not because an ag tech solution is cool we will work with it.
22:20It actually we have assessed and it will solve a specific problem in one of the 100 countries where we
22:26operate.
22:27And also we check that the startup really understands the realities of our users.
22:33And I think that's a big topic and close to our heart is human-centered design.
22:37You really need to understand the reality of for whom you're solving.
22:41Because the reality of a male farmer versus a female farmer is different.
22:47The reality of a farmer with a big plot of land and a small plot of land is different.
22:53And then also when you come with a solution for those different type of farmers, you need to think what
22:58are their realities.
23:00So I want to bring an example of a startup that is in our portfolio that's been very successful on
23:06its own, but we also champion it through our program.
23:09The startup is called Ignisha.
23:11They operate in more than 10 countries.
23:14We work with them in Mali and in Nigeria.
23:17And what Ignisha does is they can give hyper-local weather information to farmers.
23:24Their information comes from assessing satellite imagery.
23:28They leverage AI to understand exactly what will be the weather in a specific location in a few days.
23:35For the farmer on the other hand, all this complex information arrives on their simple phone in a very tangible
23:43manner.
23:43It tells them expect rain in the next few days, so take the following action.
23:49Again, depending on the season.
23:50Plant the seeds or harvest your crops.
23:54And that's what the amazing thing is because if you think about it, if you think about climate shocks,
23:59a lot of farming practices come from tradition.
24:03You learn from your family, from your community, when to do different farming milestones and activities.
24:10But the world is changing around us and also the weather is changing.
24:14So that is why you need to give this support to farmers to solve this problem to address climate shocks.
24:21Now, the other thing is, again, human-centered design is the way that information appears.
24:27It's not what type of information, but how.
24:30We need to think about literacy level of communities, access to phones and things like that.
24:35So sometimes the information will come with imagery or very simple language and or through radio.
24:42And I think, again, all about human-centered design.
24:45It's about you can create the most sophisticated system.
24:49But as we talk adoption, you really need to make sure that when it arrives to the hands of your
24:54user,
24:55they can use it on a daily basis.
24:57And so this is just one example.
25:00And it shows, again, AI.
25:02I think this is a topic that will come in many panels.
25:04But again, it needs to be relevant.
25:07And for us as an accelerator, we've been doing this for over 10 years.
25:11We've had 500 teams in our portfolio.
25:14And really, every time we check is, are they solving a specific problem?
25:19Do they know their user?
25:20And what is their funding model beyond this?
25:23Because we will be a relatively generous grant maker in the impact sector.
25:28We can give $100,000 per startup, depending on our program.
25:32But also for scalability and, let's say, business model, we also need to think what happens
25:37the day we stop financially supporting them.
25:41Yeah.
25:42And I think what is interesting is that, you know, you all in some way are the different pieces of
25:50the puzzle to make it work.
25:51You were mentioning that we need to step away from isolated approach and go for more holistic ones.
25:58You know, bringing capital, bringing expertise, having the right products.
26:03I think, you know, combining those forces is absolutely the direction of travel we want to take in order to
26:08make concrete results.
26:11Talking about a company that is making concrete results, Miguel.
26:15You know, most agricultural intelligence sits in the US or in Asia when you look at the level of investment
26:23in AI.
26:24But as I said before, you know, you're a deep tech that generates and owns a vast proprietary data set.
26:31You're based in Europe.
26:33What's the kind of next step for you?
26:34What do you need in order to scale, whether it's from a regulatory standpoint, whether it's from a capital standpoint?
26:42What do you need so next year you make another big announcement about where you stand?
26:49That's a very good question.
26:50Let me take a step back here because also urban comes from probably a place where there are a few
26:58outlayers.
27:00We hear, we talk a lot in the AI community about we have to deregulate, we have to deregulate.
27:07And that is true.
27:08There are so many regulations that is stopping us to make progress.
27:13And yet there are other regulations that prepare us for the future.
27:17And I believe this is one of the cases where that was very important to us as a company.
27:22We just started, we weren't the first one to try to solve this problem.
27:26We certainly end up building a very competitive product.
27:30But the adoption was driven by regulation.
27:35And in this case was regulation that was pushed by France and Germany and a few other European countries.
27:41Still not European-wide regulation.
27:42And that's one of the things that we really need.
27:46The fact that they pushed for it, and of course the industry, the poultry industry was scared.
27:51Like, you know, if you now tell me that I cannot kill the males, that's going to cost me five
27:57euros per male.
27:58That basically is going to skyrocket the price of X.
28:01And no customers want that, right?
28:03So we need technology for this.
28:05And they put the regulation, they put in also funding, and we capitalize on that.
28:13The fact of this is that through this regulatory pressure, we have created, as you said, a global European player
28:21in a very specific industrial sector.
28:24And we're expanding into other sectors.
28:26If I try to generalize that, what I've observed, the pattern is regulation is useful if it helps us to
28:37strengthen our strengths.
28:39If we believe that the world has to be more sustainable, let's create regulation towards that more sustainable world.
28:45And put in the means that we create companies, that we create champions that are capable of building that future.
28:51This is very close to my heart.
28:54I believe this is possible.
28:56We are an example of this.
28:59But we spend a lot of time talking about deregulation.
29:02I think we need to also look at the other side of the coin here.
29:08When I think about what do we do with the data we generate, right?
29:11Because this is one of the key occasions where we hold a massive amount of data.
29:16We see around north of 100 million MRI images per year.
29:21This is more than the whole healthcare system globally produced.
29:26This is massive.
29:28What can we do with this data?
29:30And I would love to see less fragmentation.
29:33Whenever we go to the customer, you said we have to talk directly to the people on the field, understand
29:39their problems.
29:39The way I see their problems, and I spend a lot of time with them, is that we tell them,
29:45okay, you can eat this, you cannot eat that.
29:47And we give them all that information.
29:48But then they also have another machine somewhere else.
29:50And then also they have the satellite data.
29:53They live in a very fragmented world.
29:55Can we give them more integrated solutions?
29:59Can we help them to be more effective in the way they produce?
30:04Because it's, again, not about producing more.
30:06It's about producing more effectively.
30:08And I believe we have an edge there, but we need to make it real.
30:15Maybe it's a regulatory thing.
30:17I don't think it's regulation in this case.
30:18I think it's more on creating a cohesive place for really discussing what does the industry needs and serve it
30:28to them.
30:29Thanks for that.
30:30And by the way, among the things that the industry needs is, you know, keep injecting capital.
30:36The flow of the capital injection is massively growing, right?
30:42You need more and more of that.
30:44And we're saying if you just make the analysis for where the capital injection sits in the different part of
30:49the world,
30:50you go back to the US, you go back to Asia.
30:52And so the reality is how much in this part of the world are we willing to keep investing in.
30:58And maybe a question to you also in Val is there is no question of the use that we can
31:04do of satellite data.
31:08And the reality is someone has to build this data lag, this data layer, right?
31:14But if you invest, you need to get a return out of it.
31:17If you want to get a return out of it, you're investing into data development, but you also want to
31:22have the ownership of this data.
31:23So it's kind of a complex situation to balance, you know, I mean, keeping the investment flow, but at the
31:30same time having the ownership of the data.
31:32How do you relate to that in what you see on a day to day?
31:36Yeah, I think that's an interesting question.
31:39And I'll start by saying that satellite data for many countries, including the Copernicus program here in Europe, is free
31:48and open, right?
31:49It's tax driven data sets.
31:51And so I imagine most of you know that we have hundreds of satellites going around the world all the
31:56time collecting data of all of our environment and our atmosphere continuously,
32:01both in kind of the visible what we can see and in various wavelengths.
32:07And I think but that's still just data.
32:10That's not information.
32:11That's not going to tell you how much food we're producing.
32:13It's not going to tell you where we're producing that food.
32:15And so there's a lot of work that's required to convert that data with models into information and into analysis.
32:22To do that properly, we need to have ground information coming from the ground, from farmers, from understanding if I
32:28want to, for example, map maize,
32:30I need to understand what maize looks like on the ground, all the different ways it looks like, what I
32:34might confuse maize with to be able to produce a map.
32:37And so I think there was a time where there were a lot of companies and startups and organizations that
32:44thought that that's where the business model should be.
32:47I'll do a startup and there were loads of them, including forecasting yield or making crop type maps.
32:52And I would argue that that's probably not the right place.
32:56And I think what we need to talk about when we talk about these topics is what should be public
32:59good and what should be then the data that we have as public good that we can build on top
33:05of for services.
33:06That if we didn't have that data, none of the other layers and information services could be there for.
33:11And I think there's a lot of those core information.
33:14And we see in countries that have that information, then private sector and public sector and governments can rely on
33:21that and will know that I'm going to know what crop type is.
33:24You know, if you look at U.S. or in Europe or many other countries, I can rely on that
33:28information.
33:28And therefore, I can provide, for example, insurance services or assess that for using and providing credit services or for
33:36farmer advisory as I was talking about.
33:38But if you expect each one of these companies separately to start to collect that data on the ground and
33:43then to build those models, we're doing a disservice to everybody.
33:46And so I think it's really important question also to think about that balance and look at what should be
33:51public good domain that's going to advance us all as a society and is going to help both the public
33:57and private sector.
33:58Of course, they're important questions.
34:00I think, again, today satellites can see everybody's fields everywhere in the world.
34:05OK, if I'm going to go and now collect data on the ground and harvest and understand what your yield
34:11was, then we better have an agreement.
34:13And you better know that I'm collecting that data, what that data is for and having that consent and having
34:18that integrated into the consent.
34:20So I think there's a lot of topics and questions about how we collect that data.
34:24And they're really important ones.
34:25But I think there's also place really for a lot more public private in working together and partnerships to look
34:32at how do we do this properly.
34:33And I can give one example.
34:34We're working very closely now with the Kenyan government.
34:37This is a project led by the Kenyan government for the Ministry of Agriculture and the space agency there to
34:42start to develop these kinds of core data products about crop type maps on every season.
34:48And yield estimates and having this kind of system owned by a government.
34:52So it wasn't a grant that somebody came, showed a really cool technology and then is gone because you have
34:57you've actually done a disservice at that point.
34:59But really looking at how do we transition this kind of information and systems and tools so that that supports
35:05both food balance sheets and trade decisions to early warning to disaster response to farmer advisory to insurance companies, et
35:13cetera.
35:13And so I think this will be a really exciting model, of course, looking at how do we leverage?
35:17I think if we look just even a few years back to what our capabilities were with satellite data versus
35:23where we are today in the advances in AI and machine learning applications, it's massive.
35:28And I think one of the things that we have to think about today is how do we make sure
35:32almost any of you can go on a computer today and generate a crop type map or a deforestation map
35:38for that matter or anything else.
35:39I think what we've got to do today is make sure we understand transparency about, you know, garbage in garbage
35:44out for a model.
35:45So really understanding the uncertainties, the assumptions that have gone into these kinds of products and making sure that both
35:51as a consumer and as a provider that we are holding ourselves to those standards and we know how to
35:56understand these kinds of products.
35:57And I think we'll see more and more of that across the board with this kind of tools and availability
36:03to provide global information at scale, especially using satellite data.
36:08That's a very important point. You brought the element of transparency.
36:12And I think sometimes we speak probably with two less around transparency, but technology actually is a fundamental opportunity for
36:22us to see things that we didn't see before.
36:25So there's, you know, this question around how do we trust this model and trusting a model is also the
36:33more we'll spread technology, the more we'll have also need to audit those models, making sure that we can trust
36:39the data behind it.
36:40So I think this is a very, very fair point.
36:43Maybe I'll add one more thing actually is accountability as well.
36:46Yeah.
36:46And I think, again, if you're a researcher and you're providing a model of yield forecast and you publish that
36:51as a paper and you got that wrong.
36:53Okay.
36:53You got it wrong.
36:54Maybe you have to retract your paper.
36:56If you're going to provide that data to a government, to World Food Program, and they're going to go on
37:00the ground and now decide on where their services are needed most or not, there's a lot of accountability.
37:07And I think we ought to be thinking really carefully again about that and the transparency and in the information
37:12and services and tools that we're developing.
37:15Probably an additional short question because everybody came to this room and saw the question, which is how can technology
37:23deliver food security?
37:24And can technology deliver food, better food security?
37:27So as maybe a concluding remark, two minutes each, can I ask you your thought on this one?
37:35So I think there's different things.
37:38If we want to create food security, we need to create an equitable world where everyone has equitable access to
37:46food.
37:47We don't have a production problem.
37:49There's enough food on the planet.
37:50The question is how does it get distributed equally?
37:54How do the people, and one piece of information we didn't mention, the people that grow our food are some
38:01of the poorest people on the planet.
38:02So how do we also make sure that they get the income that they deserve for their hard work when
38:09they feed us?
38:11So that's one point.
38:12The second point, I think there's different drivers of hunger, as I mentioned in the beginning.
38:16There is mad made conflict or war.
38:20There is climate shocks.
38:22And also if we don't address those, then all the technology in the world won't help us.
38:27But I think there's an element where technology can help us.
38:30Technology can give us information, as Inbal mentioned and as Miguel mentioned.
38:37We, for example, have a platform called Hunger Map Live.
38:41We just released a 2.0 version of it.
38:43And this is a free tool for anyone who's interested in this topic that maps different drivers and predicts food
38:51insecurity.
38:51You have different layers and you can find that information.
38:54So one, it can give you visibility on what's happening on the ground.
38:58But then you can also, again, if you understand the problem, you can leverage technology to benefit the communities that
39:04you're serving.
39:05So I think technology can help, but it's not the only thing that will help.
39:10Thank you very much.
39:12Miguel?
39:13Yeah, I agree.
39:14Technology alone doesn't solve the problem, but it helps us to accelerate solutions.
39:18And the way we look at the systems we deploy on the field, they produce extremely precise information.
39:24Can we leverage this information to improve our models of yield prediction?
39:32Can we improve our models on, is the next season going to be better?
39:38Can we feedback this information to the crops and do better management?
39:44And maybe we need less farming area to produce the same amount of food.
39:51For us, these are questions that are key to food security.
39:55Of course, we don't work in war areas, but we would love to share the data we have and see
40:04if these models can get better
40:06and can be then translated into this space where their need most.
40:13Thanks.
40:14Inbal?
40:15So I'll continue to agree that technology is, you know, as always, it's in service of humanity and what we're
40:22doing.
40:22It clearly won't solve the problem.
40:24It can help us get there.
40:26And I think if you think about the main drivers of food insecurity is war and conflict.
40:31At the same time, if you're hungry, we have seen conflicts and war also develop because food insecurity.
40:37And so there's a very close correlation there.
40:40I think we are seeing technologies advance very quickly in terms of sustainable production, right?
40:45We also know that we're going to have to move to more sustainable food systems, as you've alluded to.
40:50And I think technologies are going to help us get there.
40:53At the same time, I think today the burden for doing that transition sits with farmers.
40:57We need to understand a lot better what are those transitions that we can make?
41:02How do we make those also profitable?
41:04How do we enable insurance?
41:06Right?
41:06If you look at some of the ways in which you can take a risk and innovate and then also
41:10increase your productivity,
41:11it means that you've got a backup.
41:14And so if we don't have credit access, if we don't have insurance access to many of the world's smallest
41:18producer and small holders,
41:20so those are really critical pieces of it that technology, of course, can help us.
41:24I mean, there's so much work going on on resilient and better crops and seeds and varieties, more efficiency.
41:30How do we make sure that we have better infrastructure for moving our food around the globe?
41:35Because I think self-sustainability for every country is not the answer, right?
41:39We have different places that can produce.
41:42We have different things that we can produce in different countries.
41:44And so making sure we also have the regulations and the policies to enable that are going to be really
41:49critical.
41:50So certainly, I think there's a tremendous amount of promise in technology,
41:53but it's ultimately going to have to come together with also actions of people in the world.
41:59But I think it's important to echo what Hila said, is that we do produce enough food in the world
42:04today to feed everybody.
42:06Thanks. Thanks very much, Imel.
42:08So, you know, just maybe as a concluding remark, hearing you, I mean, reminds me also one of the initiatives
42:15we launched at PwC about five years ago,
42:17which is how we feed the world initiative.
42:20We did that in the context of the sort of how the reinvention of this sector
42:25and how, you know, the frontiers are becoming a bit more blurred between different sectors.
42:31And, you know, we work with academics, we work with active companies, we work with large input and CPGs companies.
42:40And we're bringing what we call this community of solvers because we have the humility to believe that the only
42:45way to make a real impact and decision will be by joining forces.
42:50I will leave you just with this idea, which is what we call the three T concepts, the three T's
42:57basically, which is a concept that you've heard,
43:00but just to make sure you leave the room with them in mind.
43:05Technology, terms and trust.
43:09Technology, we need it in order to move solution faster.
43:15Terms, those are the rules of the game.
43:17That's what we talked about regulation, not in a way to threaten or to limit, but to make sure we
43:23create the right environment in order to accelerate a number of things.
43:27And trust, because through technology developments, greater transparency, there's an element of trust that we both need to make sure
43:37is in place in order to bring more people to the table and facilitate the adoption.
43:43So, talking about adoption, let's see next year when we all gather whether the gap has widened further or if
43:54we contemplate new successes.
43:56But in any case, thank you so much for this panel and thank you very much for attending.
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