Now, this is something close to your heart, Jim, welcome to Forkast.News. Previous to this, you were the chief software architect at the U.S. Centers for Disease Control, the CDC, where you led modernization initiatives of the CDC’s public health systems. So what’s happening on the frontlines in terms of what researchers need in their hands to get in front of this infectious disease that has now spread around the globe? What are you doing about it?

Jim Nasr: Hello Angie, thank you for having me on your show, I appreciate the time and interest. So it is a very rich topic, about the coronavirus, but to be honest with you it’s certainly not an area that I am by any means an expert. Over the course of my tenure at the CDC and since, I have worked with a number of very talented epidemiologists and public health specialists and physicians and other folks in this space, I understand essentially the germane ideas behind public health data surveillance and infectious disease tracking. But I’m by no means an expert in the coronavirus specifically.

However I think as this event unfolded and we heard news through various media outlets about this, it became evident that there was need for information and particular information that could be trusted. And really, to be honest, it was a complete coincidence how we kind of got into this, because essentially one of our customers asked a question. And before we knew it, we just delved into the question a little bit more — could we use our technology to perhaps get the data from whatever sources we can and then visualize it? That’s really how it got going.

Lau: That’s a tool that’s in place right now and there are a lot of similar tools out there. What makes yours unique is implementing Hedera Hashgraph, implementing a blockchain component to this. How does that shift the dynamic of the information?

Nasr: Yes, that’s a very good question. The thing specifically about Hedera, and which is also part of our philosophy is really building real-time systems. I think we’re in a world where if you look at pretty much everything that we do as a consumer on our technologies, it is in real time. If you look at WeChat or Facebook or any one the tens of thousands of applications we use yet, sadly, we’re somewhat conditioned when it comes to health care that our data isn’t really that real-time, it’s not that usable. And certainly it’s not necessarily what you could trust — it’s very opaque. There are many reasons, not least because they’re cash-cow businesses benefiting from this.

So we don’t believe in that, we think that technology and mentality [should] counter that, and be real-time and be trustable. So all of this really has pointed us to the Hedera path for a couple of years now, we’ve been a proponent of theirs and a partner of theirs since really the very beginning. And the more we have done, the more this collaboration has seemed really relevant to both parties and important because we’re building real applications in the context of what we believe in for health care, and they are continuously improving the infrastructure. So those are the reasons why we chose Hedera.

Going back to your question about the information itself, it really is not us collecting the data directly — we’re not the WHO or the CDC — but what we do want to do is that when we display it, we want our viewers to be assured that we have not manipulated the data. The data has come from whatever sources we say. So the clinical data is coming from the WHO and the CDC. We have Google Trends data from Google, we have Twitter data that we’re displaying. But all of that has a provenance, a computational data provenance and computational trust. So it’s not very sophisticated in terms of a use case or a business model or anything like that, but nonetheless the simplicity is; you can trust the data that we’re displaying. That’s really all we’re trying to do.

Lau: Right now there’s an equivalent app out there, the Johns Hopkins tracker. But what we’re depending on is that they’re not going to lie to us. The credibility of that entire institution is placed in front of the audience or in front of anybody who’s accessing that information and trusting that information, that because it comes from this institution, it is correct. I guess what you’re saying is that it doesn’t matter who you are, if you have this blockchain cryptography that makes zero doubt about the provenance of that information, that should be equally trusted. Is that right?

Nasr: In a manner of speaking. I think what is important is this; if you are using blockchain and using it correctly as we are, you can show that data provenance, and it can be interrogated by anybody on demand. So what that shows is that what we say is accurate the way we say it. What it doesn’t guarantee and really nobody can guarantee this, is that the point of origin data collection is accurate, that the data, for instance, that the CDC or WHO provides publicly is accurate.

However, what is important to us is showing the data provenance because if the data isn’t accurate, and at some point later in time there is more accurate data that essentially supersedes it, we can show that. We can very specifically and directly show that forking of the data as opposed to having that data magically be corrected, and then the bad data basically just be forgotten about. This is something that I’m sure you are also very aware of.

It’s really all to do with transparency in health care. And you see it many times in the context of, for instance, clinical research where results are not reproducible. The reason oftentimes is because people have chosen to reproduce the good results and not the bad results, and the bad results have somehow disappeared. So we don’t believe in that. I think if there’s bad data, so long as there’s provenance to it, we can publicly demonstrate that and we can correct it in time. But then that auditability does not go away. That’s really it, I think ultimately it’s showing that from whatever source that data is retrieved from, that from that point on, it’s not manipulated by third parties like us who are effectively just displaying that information.

Lau: No, I get that, it happens to audiences in breaking news all the time. You have a figure in the early stages of news that is from a few sources of information, and then the numbers change — the number of victims or the number of people affected fluctuate and change and it’s hard to keep track of what was the right number and what was the wrong number. I get that. I also get the fact that right now there are so many agencies involved here that this is really fragmented information. Even being able to have that consistency in real-time to know, OK, what is the latest correct or at least reported figure [is hard].

Now, what I want to actually dig a little deeper into is, unfortunately about the accuracy of information and the fact that at the source of origin, that the original point of report cannot be verified or validated until much later. That’s kind of the scenario that we are experiencing right now with the doubt that has unfortunately really risen in China as to the accuracy of the official reporting. Is there a scenario in which blockchain can kind of circumvent that and allow individuals to share their information? And so you may have one or two [erroneous bits of] information, but they can’t all be lying. Is there some point in the future where this could actually be in the hands of people to report what’s happening to them?

Nasr: Yes, absolutely. I think this is a very important topic because I think this is really what I think of as not just future possibilities, but where we should shape the future. So I’ll give you an example; currently with our coronavirus tracker we’re surfacing tweets. You can see positive sentiment, you can see negative sentiments, you can see what languages [are being used]. You can also see specific tweets that have surfaced over the last hour or so. That’s all kind of being serviced on our tool.

But you can certainly argue that the information could be manipulated, could be bots, it could be influenced by all kinds of people and other forces outside of the individuals that they purport to be. However, imagine that if we had a blockchain enabled Twitter and let’s just say for now, it’s specific to infectious disease outbreaks. So it’s not for all kinds of social events, but just for that and then people are authenticated. There’s some degree of authentication, not necessarily divulging all their personal information, but such that essentially you eliminate the bots and that kind of truth manipulation. But now you are on the blockchain, and I think the whole concept behind blockchain — and I’m really referring to public blockchain — is really in my mind a combination of three different pillars or undercurrents.

One is the actual distributed ledger technology, which is interesting, but not by any means the most interesting. The second concept is really, which I think is very interesting, is this idea of value creation attribution, which is that if you create value, for instance, solve the mathematical challenge that results in the finality of a transaction, you get some reward for it because that requires computational power, that requires electricity and such. So that’s the second concept, this idea of what people refer to as token economics. And the third idea is this idea of a distributed kind of computing culture that you are effectively trying to remove one central authority and distribute it across many different people and if you like, crowdsource the culture of this.

So if you look at it in that context, [imagine] the concept of, for instance — it is something that I proposed three years ago when I was at the agency — a public health coin or like some kind of a public token and that was used as a gaming [type of] incentivization. Essentially incentivize people [to use this token economy], for instance, in the case of an infectious disease outbreak or a hurricane or whatever, to accurately report data, because the data is very valuable.

It is valuable to researchers, to governments, to third parties for all kinds of reasons. Then you’re now providing incentives to not only have people engaged and provide good data, but also through the same mechanism, you can create a disincentive for gaming the system. That’s because the rest of the nodes, the rest of the participants can verify and audit in that information in real time. And because it’s in the blockchain, they can provide counterpoints, a view to essentially spit out bad actors.

Not to get into the full philosophy behind this, but I can assure you that the technology for sure is there to make this happen. It’s just a little bit imagination and a little bit of mobilizing the right people to make this happen. But in smaller pockets, it’s already happening. Then what you get is information that you can trust to a large degree, regardless of whether it’s coming from an authority like the CDC or from individuals on the scene.

Lau: One of the things that the CDC and WHO researchers and scientists around the world are tasked with right now is battling to control the contagion. Knowing that, and working alongside your ex-colleagues at the CDC, how important is just having the right information and understanding the scope of it, and the accuracy and the transparency of the reporting? How important is that when they’re in the labs trying to figure it out?

Nasr: It’s incredibly important. I have a lot of respect for the folks that do work at the CDC and in particular the public health specialists. I would say from my experience, these folks —perhaps unlike the stereotype of what you may imagine for government employees, these are extremely talented, extremely dedicated people who focus their entire life on this mission. So the data being timely, being accurate, being complete as possible is huge to them.

Unfortunately, and again I know this in many ways, people like myself in the technology space have not really helped in this kind of area. They spent a lot of time just verifying data, cleaning data, reformatting data and things like this. None of those things to an epidemiologist is of that much value. The value that they provide is in the modeling, is an analysis, their recommendations and the timeliness of their communication to the public.

That’s the value, they should not be spending 60, 70, 80 percent of their time, which is a very accurate figure, on just cleaning data. But unfortunately, what happens. And I’m sure you probably remember the Ebola outbreak a few years ago and at that time — this is public information — the CDC really got a black eye for over a number of actions or lack of actions or timeliness about this. But in my experience, a lot of that really was to do with not being able to get data moving fast enough and clean enough to the right people to actually do the analysis. So it is very, very important.

Lau: Well it’s important, it’s critical and it could potentially save lives. Right now, you’ve created the start, the beginning. Where it can go could be an incredible new future in the fight against these new coronaviruses, of which this is likely not going to be the last. It’s just the kind of world that we live in right now.

But I think what’s incredible is that while it has spread globally, knowledge has also spread, and so some real action is being made and people are taking it seriously. What does a future look like with this potential new tool? Do you think that something like this, if this were to happen again, if we had the reporting in place, how quickly do you think that we could really collaborate as a global medical community and fight this?

Nasr: I’m an optimist and I think about these things, particularly things that I have some degree of control or influence on. So certainly this is a path that I see us repeating. In fact, just over the last few days, as people have seen [HashLog], people have brought to our attention some additional use cases. For instance, tracking similar kinds of not so much an infectious outbreak, but public health issues in Africa. A couple of African countries where there is a real relevance in terms of the actual treatment side. We have been already working a lot on substance abuse, particularly the opioid crisis in the U.S. using mortality data.

So again, I think with this coronavirus tracking, some of my colleagues in the medical space, particularly public health space, have been inspired to look into other areas and other things we could do around this opioid tracking. I think this is really the beginning of a number of related types of tracking exercises and use cases. I think that the bigger concepts around effectively crowdsourcing, accurate and trustworthy data will take some time. Certainly no one entity or government or technology… it’s a combination.

However, I think as history has proven, you do need a catalyst. You do need some people effectively to go make the investment, put themselves out there to try and drive some ideas to then generate that momentum and reverse the inertia. I think I certainly see us, Hedera, and some other folks in this space, good folks, as being part of that.

Lau: Well, it’s almost like you’re adding more muscle to the front lines if you are reducing people’s work from having to clean up data, reducing their workload 80 percent of the time on literally administrative redundancies that could be taken care of technology so they could actually get to the work of science.

Jim, thank you so much for sharing what you’re doing right now, helping us understand the importance of data and when numbers don’t lie, and the importance of transparent reporting. I’ll leave it off there. And with a familiar goodbye that we often share these days here in Asia; stay healthy, stay safe. Thanks, Jim, CEO of Acoer, thanks for your work and thanks for joining us. And thank you, everyone, for joining us on this edition of Word on the Block. I’m Forkast.News Editor-in-Chief Angie Lau, until next time.