 Good morning, good afternoon, good evening, and welcome to a very special mini series here on OpenShift TV. We have teamed up with the Call for Code for Racial Justice Team over at IBM. And we are going to do a, I think eight or nine episode, I forget, sorry, numbers are hard for me. Many series about all the projects that the Call for Code for Racial Justice Team has been working on over the years, or over the past year or so. So let me shut my mouth and hand it over to the one and only Sabine, who will walk us through what's to come. Awesome, yeah, thanks so much, Chris. So my name is Sabine Distillion. I am currently the product manager for Call for Code for Racial Justice. And indeed we have been in existence for a year. We have seven solutions. So over the course of seven episodes, as we'll call it in this series, we'll be able to dive a little bit deeper into what reform and technology can provide as a way for transparency and accountability when it comes to racial justice for Black and brown folks. So Call for Code for Racial Justice, like I mentioned, has seven different solutions that are currently out available on the Linux Foundation as well as in our GitHub. And so today what we really want to focus on is Fair Change, an amazing team that I've been able to work with in the past couple of months and understanding how can we provide upstanders with the ability to really stand up and stand out when it comes to police accountability. And we're gonna go ahead and share a little bit more about that. But what I wanna do initially is to share a video so that we can understand the situation a little bit more for what this type of change can look like, just give me one second and hopefully it will actually play. Hopefully. That's always the thing with these presentations. I'm like, do I have the audio right? Is everything right? Time will tell. Yeah, we'll do it together. All right, so I'm gonna share my screen, optimize for a video and share sound. I think I can do that pretty well, and let's go. It'll take you long, but you're not black. Remember, we only kill black people. Yeah, we only kill black people, right? All the video to see to be seen, black people get killed, that's what you have. In 2019, although African-Americans made up less than 14% of the population, they accounted for more than 23% of the just over 1,000 fatal shootings by the police. And the reason I stopped you is when you came out of the barns with no offense to you, but you're a black male, okay? No, I'm not gonna lie to you, all right? I'm not saying that at all. The reason I stopped you, I'll explain if you let me finish, all right? In this area, we have a number of drug dealers. I'm not saying you're a drug dealer. They come up from other areas that don't live anywhere over here. I am, I live here. I know you, you... In the UK, black people are nine times more likely to face that when searches. Also in the UK, black people accounted for 3% of the population with 8% of deaths in police custody. And we know of no successful conviction of a police officer for the killing of someone ever since 1972. What agency are you with? I'm the second term. Okay, all right. Thank you, your tag didn't come back. Never seen that before. I'm sorry? Yeah, we're good now. So it was... We ran a tag. I've never seen it before. A Florida tag. It's never come back to anything before. So that's the reason for the stop. What was the tag run for? I'm sorry? What was the tag run for? Oh, we run tags all the time, whether it's the traffic lights and that sort of stuff. That's how we figure out if, you know, cars were stolen and that sort of thing. Also the windows were really dark. I don't have a tint measure, but that's another reason for the stop. You guys have clients on here? Yeah, one second please. Actually, this isn't my... San Francisco, the black population has shrunk over several decades to just 5% of the city's total population. But 26% of all police stops carried out through a period of six months were black people, marking the widest racial disparity in police stops. So I think that that video really served as a way to kind of give some context into the major issues that we're seeing about inequitable contacts when we're talking about black and brown people by just living their daily lives. And so fair change is really going to focus on how do we hold police accountable to this measure, empower people who want to say something and do something, do so in a safe manner. And then how does this, you know, provide some possible implications for policy and training for the future? So I'm gonna go ahead and share my screen again so that we can take you all through a deck that we prepared, but we still are gonna have this be very conversational and talk about, you know, what call for commercial justice is in level setting, but more importantly, what fair change is doing at this point in our journey as an open source solution and project for people to adopt and to contribute to. That's the video we just played. This is kind of like a quick introduction to the team. So you'll see many of the faces that are on the left hand side are also the ones that are gonna be involved in this conversation. And so I can actually pass this off to Kailini to help level set us and, you know, kind of give us a little bit more context into this project. Yeah, are you able to hear me? Yeah. Okay, yeah. So just on this slide, as the being said, it's just our team. Basically what we're trying to solve is how the police interact with members of the black community, but not just only the black community. However, we were focusing on the black community just because they do have a higher percentage of being mistreated, basically. Yeah, that was basically just the focus of the overall focus of this. Yeah, and I would love to ask like Kailini, and this is gonna be something I think everyone can speak to, but why specifically did you get involved with this project? Yeah, I mean, one is because I do have family members that have been directly affected by mistreatment, friends, peers, et cetera. And I actually wanted to dive into it and make a change myself versus telling, trying to go out and tell other people to make a change. I feel like the change sort of has to start with yourself. And I think that was one of the biggest reasons why I actually got involved. And then, of course, this is something that has been going on for years and years and years. And once again, last year, I saw where it was sort of like a trend that popped up again, where it was sort of like, oh, black lives matter once again, and then it's gonna fade away come a few months or a few weeks later. So just to sort of stop that trend from steadily popping up and just to remind people, like this is an ongoing issue that sort of needs to stop now before it gets worse and worse. Right. And Tessa, I think that I would love to also hear the context, especially from someone who's living in the UK, why you were engaged in this project and also what it means to you. Yes, I have a legal background and outside IBM, I am a magistrate. And I have family members who are quite regularly stopped in London because of the car they drive or how they look and that sort of thing. And the issue is how that makes a person react. I don't think anyone can really appreciate what it's like, how you feel when you're stopped and the power isn't yours. And how you react under those circumstances can actually bring you before people in the court. And I think it's fairly well known that in terms of balance and ethnic balance, there are a lot less black magistrates or Crown Court lawyers or whatever. And sometimes you're brought before someone who will try to understand, but really can't because they're not in your skin. And that makes a difference. So that was my interest in becoming involved in this to highlight the issue, to also help in terms of educating and just getting the message out that says it really can be anybody who gets stopped for whatever reason. And it's important for people to know that. And I think the team has done a fantastic job of this and I'll continue to support it for as long as we're making way. Awesome. Thanks so much for sharing that. So I'm gonna hand it, you're kind of bouncing around a little bit, but I'm gonna hand it back to Kylie to also set the stage for why Fair Change was created and its intent and purpose. And then we're gonna move on to a little bit more of the technical deep drive into the underpinnings of Fair Change. So Kylie, can you run through us with this a little bit more? Yeah, so basically why Fair Change was created. Firstly, I do wanna start by pointing out that the statistics on the screen, they're taken from the US, Canada and the UK. And it basically just shows sort of how much blacks make up the population, like the percentage and then how much they're killed or either stopped by the police just to put into context or why it was sort of created and to show the disadvantages that the black community does have over the remaining of the other communities. So I think that was sort of a big reason why it was created. We all have heard of police incident sort of taking the wrong turn and yeah, Daniel. Yeah, I think that was one of the, some of the reasons why it was created. Perfect. So give us a little bit more context into what is Fair Change. I know I give like an overview like it's gonna be able to do this, but what is it actually? Yeah, so it's just a mobile application where upstanders are able to record and upload videos of police incidents. And we're sort of hoping with the shared videos they're able to support victims, even police departments. They're able to, the videos are able to support police departments and aiding and improving their training to better ingrain basically proper reactions on how to handle various situations in not just generic situations in all communities, right? So that's sort of what it is. Yeah, that's a fair point. So it's a mobile application available for Android and iOS. And I think we're gonna get a quick little demo. I know that James is gonna share his screen so he can go a little bit more in depth with this, but this is gonna be kind of the fun stuff in the nuts and bolts of how this was created so you all can see it in action. So James, I'm gonna stop sharing so that you can go ahead and take over. Thanks Sabine and hello to everyone watching. I'm James Stewart. I'm a member of the Fair Change team. I've been for almost a year now. Fantastic team to work with. And I'm gonna just put a pause. James has been at IBM for 20 years. He celebrated 20 years at IBM this past week. So I mean, he doesn't look it, but 20 years goes a long way and we're really happy that he's putting forth the effort in this team. So I just want to do a random plug for that. Thanks Sabine, thanks very much. So what I'll do to start off with is just take you through some of the architecture and then we'll go directly into the demo and you can start to see the solution in action. So I guess the whole ethos really of call for code or all of the call for codes is around open source. And I know that hopefully the audience with us are big on open source as well, just as we are. So that was really what we focused on in terms of the architecture, choosing open source technologies that hopefully people are familiar with. There's the support there from the community if people have any issues. We also wanted to provide a free entry point. So everything you see on here today at least has a kind of free tier available either on the cloud or there's options to run some of these elements locally. We did actually have it up and running on OpenShift at one point as well. So that's certainly doable. I thought it's best to mention that seen as we're on OpenShift TV. And on the left-hand side here, we've got our users which could be upstanders, could be people who find themselves in a scenario. In the future, there may be other user groups as well. And the mobile application, we chose React Native because we wanted to keep a single development path. We've got support for iOS and Android. You'll see that in just a short moment or two. On the right-hand side, now when we collect video from the mobile application, we store it on cloud object storage, on IBM cloud object storage. Of course, you might have other cloud object stores that you could connect into this. That is encrypted by default. And then for a lot of the other data that we capture, the location, the timestamp, over time sort of additional information around any particular incident, we keep that in a cloud and database. And again, we did work with some alternatives like MongoDB as well. So some of this, there's a few different deployment options for. And then in the middle, you'll see we've got this Node.js component. That's the API. Now, if you think about what's happened, especially over recent years and people being able to capture incidents on their phone, we know that we're not the only app out there who aims to do this. But where we do see a challenge is that because all of these different apps exist, actually all the data sits in different silos. Some of it still just sits on an individual's phone. Some of it might be in someone's email account. Some of it might be on another cloud or a site somewhere. And that prevents a problem for the people who are trying to actually tackle social and racial justice. And actually by bringing the data together through this API, we think we can actually really help with the future analytics and the reform that we really want to drive through Fair Change. So that's why the API for me is really the glue that holds this entire solution together. And means that other people can also send their data into the Fair Change platform. And then we've got the React web app. So again, you'll see this in a minute, but we created a web, a map for you that shows where the incidents have happened. And that is powered by Google Maps as well. So without further ado, let me go into my demo screen here. I'm just gonna go back into my Cloud Ant database because it kindly logged me out. But if you focus on the left-hand side of the screen, we really wanted to create something that was very simple to use. We went for two real user stories. One is for an upstander who witnesses a situation and thinks, look, something just doesn't seem right here. I'm going to stay safe, but I'm gonna film this just in case something happens or maybe something already is happening that just looks wrong. The other situation is someone who's actually in a situation themselves. And we're very conscious that that's not always possible, especially if someone's got their handcuffed behind their back, for example, they can't get their phone out and start filming. But when they do have the opportunity, we wanted to provide that function as well. And you'll see that it's got a very simple look and feel. We focus more on the kind of path to getting the video recorded and uploaded in as few clicks as possible. We also want people to be able to come in and update the code with additional screens for the mobile app, additional features, additional functionality, and maybe even give it their own sort of look and feel. So if I- The thing is that, essentially, this can be customizable for someone. If they wanted to kind of make it feel a little bit more, I guess, branded, or if they wanted to change it up a little bit, there's opportunity for them to do that within the code. Exactly. You can almost think of it as a bit of a blank canvas. We wanted to provide the underlying functionality, but really let people use their own imagination, their own sort of thought process, and come up with their own requirements in terms of what else the app needs. We do have some thoughts on that, I'm sure we'll get into as well in a little while. So you can see here that as soon as I say I'm, in this case, observing the situation, it uses the native camera functionality. You can see that it's picked at my location straight away. You can see, or you can't see my watch, but there you go, 18 minutes plus six in the early evening in the UK here. I've just started to capture the video, and then as soon as I stop, it gives me the option to delete or to submit, and if I was to hit submit, that would go, as I mentioned earlier, the video to cloud object storage encrypted, and then the other information, if I go over to the right-hand side of my screen, goes into this cloud and database. And actually within our Git repo, we've included an example of an open source database that aims to capture the same type of incidents that we're interested in. So you can see here just a couple of examples from that open source database. So you'll find I think around 600 incidents. I mentioned earlier that we also have the API. So you can see here we've got the ability to fetch incidents either in groups or individually. We can post incidents, and we also have an API to upload the video. Now by default, we don't envisage giving anyone access just anybody who comes to the site access to videos. We want to protect people's privacy. There are a number of reasons for that, mainly around the safety of either the upstanders or people who appear, but certainly if authorities or the person who actually recorded the video wanted to retrieve it to be used as evidence, we do provide that functionality. The URL that's created actually expires after 60 seconds, so it can't just be shared around. Then I mentioned that we have this kind of website with the map, and you can see here these come from the open source dataset. All we're showing is really the location, the timestamp, and a brief description of the incident. But actually this in and of itself is quite useful in terms of people understanding what's happening in their local community, whether they're members of that community, whether they're NGOs who work with the community or whether they're police officers. And you can imagine if we're able to capture information from lots of sources, how we could really populate this view. Now we've built some search capabilities in, so I can go, I'm in the UK, if you haven't already guessed by my accent, I'm actually located up here just north of Derby, and I just loaded a test incident a while back just so make sure that everything's working, but you'll see there's no incidents currently recorded in Derby itself. Now what I'll do just to finish this part of the demo is just post an incident. So I've got this example one that I've given the geo-coordinates for Derby. I can execute that and all being well, I can go in and just do a quick refresh, head back over to the UK. And those of you who are eagle-eyed enough will have spotted that there's a new pin in the map just with an example incident that I recorded there. So that's the main demo, Sabine. I'll stop sharing and hand back to you. Yeah, that was one, I mean, I've seen this many times before, but I think it's always just so interesting to see the process again and again, because I think it allows people to see in real time how this project really works. And I think that you really spoke to, what are the other use cases for this solution, not just saying if I wanna be an upstander and I wanna record the incident, but I also wanna be able as a police agency to understand what's going on in my community, what can I do to provide better training practices? And I think that that's gonna be indicative of where we see a lot of conversations going forward when it comes to improving what the relationships look like, between police and black communities. So I'm wondering, did you come up with any policy ideas or some initial ways that you would export initially that helped you build up your solution? Mike, what kind of fostered this direction that you all went in? Yeah, I mean, there's a lot that kind of played into it, really, Kailini and Tess gave a really good background in terms of what the problem is. I think most of the team have experienced the same or similar problems as well. That's why we all came together. I was aware of some groups in places like London who actually will go around with phones and film, stop and searches just to help protect the individuals that are there. And I'm also aware of some of the applications that exist in the US as well. And it just sort of, as a team, we just came up with this idea, what if we could kind of crowd source a lot of that information, bring it into one place and then really let the community and by the community, I mean, the black community, other communities, upstanders, people who have a strong sense of justice and of course developers, as well as the NGOs and the police who we wanna work with, if we can come together and collaborate around that data to really drive the change that we're looking for, that's when I think it becomes really powerful. But we needed to kind of start with the base functionality and set that vision that people can then collaborate with us and really build on top of that. And I think definitely there need to be some policies and management in place to make sure that the platform is used in a responsible manner by everyone involved. And those are all things that, again, both in terms of what the policies look like, but also how do we build the code to support those policies are really important to us. Yeah, I think that's a great segue actually into just diving a little bit more into, from the developer standpoint, when someone really is seeing the solution and they're saying, I want to understand a little bit deeper, where can I find out more information? How can I get started and contribute? I think being able to go through GitHub repo is gonna be our next point. And so, Vaz, I'm gonna bounce that over to you to share with everyone. We have a quick question from the audience if you wanna answer it. Who has the IP rights over the video and other data uploaded? Is it completely open or are people expected to build their own data sets? I'm kinda curious how that works. It's IP rights over content of videos that people record or are you talking about the code itself? Well, the IP rights of the video recorded, that's upload. Oh yes, so I wouldn't necessarily think that so much as IP as a recording that's used to somebody who's an upstander or somebody who's a person who has a safety need making a recording because of that safety need more than anything else. And they're doing the recording, they're providing it for academic purpose, they're providing it for the ability of activists, they're repiting maybe a civilian review board possibly with notification police itself, if that makes sense, those sorts of purposes. I don't think the app at this point takes a legal position and that would vary depending on where the application gets deployed. IP rights are very different in the UK versus the US, for example, let me read the dates a little bit. So I think this is covered by the Apache 2.0 license. We have had some discussions about the possibility with external organizations as well as lawyers, other lawyers about the notion of adding additional licensing terms and that could be covered because that's not really actually covered by the Apache 2.0 license. And Apache 2.0 can be extended beyond that. I don't think this is like do recording, make money off it or something else like that. No, it's definitely a research kind of purpose, right? Yeah, definitely better, provide feedback but also make it so that there's provenance of videos known, right? It's clear what the provenance is, it's clear that it's not been tampered with, it's clear they can be used for legal purposes and so on and so forth would be the point, I think more than anything. It's a great question though. Yeah, no, thank you. One we've never been asked so far as I know. So that's great, that's great. So hopefully you'll be able to see my screen well enough. I can't get rid of these, these a little bit of the video here but what I wanted to say is, first thing, as soon as you come in here, it's super easy to find, just go to github.com. I'm assuming most of the people who'd be on OpenShift on TV would be pretty familiar with GitHub but if not, just go to github.com. We do have some people who might be here who aren't actually quote unquote technical but who can make major contributions to the application. You can make it, the learning curve is not so big that you can't make important contributions via GitHub and there are a lot of solutions in GitHub where it's used not just for code, it's used for content as well, like websites and so on and so forth. So that's a major thing that you can do even if you're not a techie and you're listening in, join from some of the first thing I would say is as soon as you come into GitHub, it's just make sure you start a repository and click watch or something like that so you can follow along and so we'll know that you're there and we can reach out. There's also a Slack channel and other things we'll be talking about. The way the repository is arranged, kind of important is we've got this solution starter. It's a pretty well-structured read me but it goes a little bit beyond a read me with the videos and architectural documentation and so on that anybody with development, the relevant development experience should be able to follow the instructions and deploy the application and see what's there and get a guide to the code, the architecture and so on and so forth. And there's a lot of steps in here. Obviously, I'm not gonna run through this and answer this being a question but you'll see it's pretty nicely laid out with code examples and everything else like that. And that means it's able, you're able to actually take the repository and not only deploy it and see how it runs but also be able to extend it. And I just wanna give one example of that is we've had some discussions that come up occasionally this notion of linking in with a first responder capability. Like, it doesn't necessarily mean police. It might mean you see an incident happening and you wanna make sure a mental health professional from a city could be involved or something else like that, right? So 911 doesn't let just route to the police also routes to other services like hospital and so on and so forth. So a PSAP registry is something that exists. And a lot of it is accessible via structured data and maybe APIs as well. That's not something we currently have but would be something that'd be possible for someone to actually take the repository, fork it or contribute back in and both of those would be options. Obviously, if we're deploying this in a particular locale, like a civilian review word for a large city, for example, that sponsors the application, they're gonna wanna extend this a little bit maybe integrate it in with their own data sources or other such things like that. And so this would provide that capability for them to do that. Also you could fork and provide different cloud capabilities or other such things like that. So I'm not gonna go through the whole structure but just to say it's well, it's very, very well structured by some amazing developers. And so I'm talking about bare work more than anything else with the backend, the mobile and the other pieces parceled out as well as the research. So there's a lot that can be done in terms of a web content as well. And then we'll talk a little bit later possibly about the issues but the issues are pretty self-explanatory about what's in there. And we've gotten parceled out by a good first issue for different users of different kinds who could really help with this. That's sort of an overall tour of the repository without diving deep into it. And hopefully answers your questions Sabine. I think there's a lot of... Yeah, so like who, I know we were saying like that there are opportunities for technical and non-technical people to get involved. So could we maybe just explain a little bit more about what does it look like for your ideal contributor to the project? And I would almost say that like there are several ideal contributors. So you've got ideal contributors who understand because they're activists and they've done research or an academic or somebody like that who's deeply involved in these issues, right? And many of us on the call know people like that who can make an important contribution just via recommendations or by identifying issues that could be features in the application or something else. Another really, really ideal user or somebody who can help with the web content or other push messages or things like that could actually make sure we get this to the larger open source community out there. If you think about police violence or policing issues, if you don't wanna look at it as police violence but you think about the larger issue of people who are getting confronted on the street and feel safety is an issue. They want peace of mind. That's a societal issue that we've discovered from people who talk to us about the application exists all around the world. An open source movement should be big enough to handle the various locales where these issues come up and the law, the applications would need to be adapted to each of those cases. So an ideal user would be somebody who's passionate about it and actually able to advocate for adoption of this by an NGO, by a non-governmental organization, by something like a civilian review board, by some sort of organization that could actually sponsor this in a location where it could actually make a difference and then share back those assets into the larger open source capability is what I would say. And then finally, just an ideal, just the skills we mentioned around things like React and Node, Cloud, OpenShift, deployment DevOps, things like that would be really, really, really important. The main thing for me is probably everybody I've met who's had an interest in this application is an ideal contributor in a sense because the ideal thing is for the open source movement and this movement, Black Lives Matter and beyond that, protecting black and brown people and just in general that are policing to take this on. And it's ideal that everyone who can contribute does. Right. And just to show what this actually means or can practice, we're even able to partner with American Airlines where they focused on getting a group of developers to come in and go after some of the issues and provide some ideas on what they think would be great ways to move these solutions forward. And so these are, we're talking about like beginning developers talking about distinguished engineers who are able to really focus their skillset whether you're a beginner, you're a more advanced, there are ways for people to insert themselves from a technical perspective. But even if we're talking about for someone like me who's non-technical, I was like an English major in college being able to provide the context around community and engagement and what youth activism can look like and saying, well, have you thought of this? And I think that that's gonna be the consistent kind of way we interrogate ourselves and saying, what haven't we thought about as being a way for fair change to be used from a policy perspective, from a learning perspective and saying that there really isn't a single answer that's gonna work. But again, when we look at for non-profit it's gonna be for on a case by case basis on what is it they're trying to solve for and address and that's what we're really looking for or to you in the next couple of months. So definitely thanks for sharing that, Favre. Yeah, I just wanna, I'll just add really quickly, we've heard from a couple of kids who would like to actually use this in their classrooms when school resumes for them to be able to address these issues and expose them and do a development exercise at the same time which is I think really, really awesome possibility. And I do think the societal level discussion that just talking about these features and what will give people peace of mind that they will be able to prove what happens and people will know that people are able to prove what has happened can make a huge difference. That's what I've heard from a lot of people. I know my own family where racially mixed family has had a number of incidents, right? And an app like this would have really, really come in handy on pushback from things that have happened both from police and police being put up to harassing our family even though they didn't want to. So I just think that there's tremendous potential and a wide variety of contributors. And since this kind of thing needs to be adapted to local law and the specific purpose that's going to be tried in order to promote that societal level discussion and address it at the local level, the ideal contributor is anybody who can contribute. Right, awesome. So everybody out there in the ethers there's a place for you here. Exactly. And I think that that also kind of like leads us into when we're talking about you from like a co-perspective type of the new innovation that we see within this project that we're working on. I know that we've been doing some digging doing some exploring this and you know what can we do more from an analytics perspective? How can we incorporate AI? Like what can we do to advance this even more? And I think that James is gonna share with us some things that we've been tinkering with, some ideas we've been playing around with. And this information is going to be shared within our GitHub repo, but this is something we just wanted to really share with the audience and explain a little bit more on like what are some ideas and capabilities we think can be forthcoming. Yeah, thanks again Sabine and thanks for that as well, Bos. So yeah, like Sabine mentioned, what I'm gonna show you now is not yet in the Git repo it's kind of hot off the press. Some of you may be familiar with the technology. Up until recently it was known as Gracun it's just changed its name to Vatical. You can kind of think of it as a knowledge engineering platform. I've recently used it in a project with my client where we were actually looking at issues like deforestation and human rights issues like exploitation in supply chains. And I kind of saw some parallels with our project and I thought, hey, we could maybe make use of Gracun for fair changes, a way of helping really add more context to the data that we're capturing. So this is the language that you use to develop in Gracun. It's called Gracal, a great name in my view. And again, this can run in a containerized version I've just got it running locally but for my other project we've been running this on OpenShift. Again, get a plug in there for OpenShift. So basically what you do is you define a number of different attributes and then you define a number of different relations. And the great thing about Gracun is that it gives you the opportunity to not just define a relation but actually to add a subrelation to that and then another subrelation. So you can kind of daisy chain these different relations together. So I've got a few different relations in here around employment, for example, is just one an assault which would obviously be something that gets captured within our app potentially would also be another relation. And then I define a number of different people or entities. So in this case, we've got a person, we've got an officer as an entity, we've got an organization as an entity, an incident as an entity. And actually the scenario I'm gonna walk you through is based on a real life scenario we had within the Metropolitan Police in London where one of their officers was found to be linked to a far right organization, hence the entity here, the FR organization. But you can, this is a very basic knowledge schema, but actually this is something that can be built on and built out to capture the entire system if people wanted to do that. And it gives context to the data and it helps us define relationships. And then we can also define these kind of inference rules. And I use the term kind of loosely coded because just because we've defined a rule, Gracan doesn't automatically assume that that rule is definitely true. It actually uses what the data is telling it and it takes data from lots of different sources. Now, Gracan comes with its own UI, which is what you see here. And I'm just gonna start off by running a very simple query, just say of the data that we've got, what are the risks? And I've only put a few different records in here. They're all made up. I'll sort of copy out that before I hit the button. So everything you see, all the names, the places are all made up. It's really just to help kind of set that vision as to what we could do. And so you see here that it's brought up this little block with a high risk on it. And because this has been inferred, Gracan's gonna let me ask it to explain why this risk has been inferred based on the data. And what you can see here is that we've got an officer number. We've given his name as well because quite often that's public information. We don't necessarily have to do that. And we can see that he's got this high risk label. Now I never told Gracan that this particular individual was high risk. Gracan has decided because I put in some dummy data that showed a link between this individual and this far right group that's known to be dangerous. Now what we could then do, and if you think about what we said earlier about linking into other systems, we might be able to go to another, some data that exists in another database and think about, okay, so who is this officer employed by? Which police department does he work for? And so what Gracan has now told us is that, okay, we've got this Borsville PD again made up and we've got this relationship between the officer, he's the employee, they're the employer. And then think now about some of the data that might be coming in either from the Fair Change application or from other applications who are using our API. And this could be inferred based on things like badge number and location and other data. And what we see here is that we've got these two incidents that linked to two different members of the public. You can see the blocks in green are the member of the public who it links to with hidden their identification. We've got a brief description, as I showed you before on the map, you sort of brief description where it happened, what the date is. And we can see again the relationship between this particular officer and the victim, but also the report. And so hopefully that starts to build a picture as to why this could be quite a powerful tool in drilling into information as well as making inferences based on the data that's coming in from different sources. So that's Gracan Sabine and I'll hand it back to you. That's amazing. Yeah, I was like, does anyone else like the audience have a question about that because I think that that is something that when we're talking about the ways that we can layer information and understand what are some red flags, what are some ways for us to pay attention, like what are gonna be the key ways that we want to understand what the data is showing us. It's gonna be important. And that actually kind of brings it back to last week when we had a workshop with a couple of different subject matter experts around policy, judicial reform and accountability. They were able to see Gracan and be like, you know what, that is actually gonna be super, super helpful because again, when we're talking about accessibility, like how could me as a lawyer who sits on a police review board understand what are gonna be some of the, what is this information telling me? I'm not a data scientist, I'm not a technologist, I'm not an engineer. And so how can I make the experience or be able to give them information that helps them to do their job a little bit better? And I think that Gracan, we know when we're talking about putting it on top of the fair change that it stands right now can start to embrace that gap when it talks about how do we make this accessible for the people who need to understand it to be able to do that. That's amazing, I think. What I also think would be great is that, yes, it can identify potential, not bad, I mean, bad actors, yeah, we'll just call them bad actors essentially, but it could then say like maybe, well, these incidents all have this one thing in common or these additional components in common and how we can like maybe use the first responder to kind of short circuit the problem before it happens. Yeah, you're on a really good point there because of the sort of reasoning sort of approach. Think about it as an explainability issue. We've talked a lot about, there's been a lot of work on AI explainability and understanding how AI applications work. What we got here, what we got is a potential fusion of a lot of different data points and you could just get an explanation, not just in terms of risks, but also who's not at risk? Why are things happening? Explain to me why there's something systemic here that I'm not seeing that you can link to some external data. And there are a lot of people who will tell you, a lot of experts will tell you that policing issues are really a reflection of systemic racism or systemic inequities, right? And so pulling together data like that, using something with some explainability capability can really help people see that if you set it up correctly. A lot of potential there, thanks. And to make a point like these, while the teams on there are creating this, they were in their own spaces, right? They're like, we have our 10 group, our 10 team members who are working on the solution and we have that across the seven different solutions that have been externalized right now. And Baz is actually part of multiple teams because he's just that big of a fan. But I also wanna make this point that these solutions, like as we're starting to see the conversations, especially from the feedback that we got from our community engagement is that these solutions have some relations to each other. So while we are using this information to talk about inferences that we can draw from, maybe a police department or a police accountability board that's looking at where are there some bad actors? When it comes to our other solutions, like open sentencing, maybe to be changed, how are we then looking at the ways that we're seeing maybe how lawyers are interacting or public defenders are using information that's coming through their database and how they're being able to record the ways that there may be some inequities in the ways that people of color are being treated as they're going through the judicial process. So these solutions, while they can have like a group of them and you know, if you're like, I wanna get it all, you know, you wanna get the package for judicial reform, like you can do that. But these solutions really are able to play off of each other's strengths and saying, well, you know, how can I understand this information a little bit more if I wanted to show what it looks like in the state of Washington? Or if I wanna create a police database of an officer moves from Florida to Washington and says, I don't know why Washington is on my mind. But you know, you have a history of behaving poorly. You know, what is the system that we're now trying to build to be able to, you know, keep people informed of that because public defenders are gonna need to have that information. Criminal justice lawyers are gonna need to have that information so that they're able to give their clients, you know, the full benefit of the doubt. So I really encourage everyone to like really look at, you know, the different repos that we have right now and you'll slowly start to see, you know, a common thread which I think is indicative of just how IBMers are really looking at what racial justice looks like in these systems that there needs to be ways that we have like a unifying way to connect, you know, what police encounters look like, how we move through the judicial process when it comes to even like the hiring process when we're talking about policy, it all matters. And so I just really wanna drive that point home. Thank you. Yeah, that's very important. So I'm gonna share my screen again. I think that the conversation today has been amazing but I mean, of course I'm not biased. And so I really wanted to, you know, kind of drive the point home a little bit more about like what we talked about, but also like leaving room for people to continue to ask questions. And I know Chris, you'll be able to, you know, prompt us with a little bit more of that information. I don't want just being aware of the time but I wanna do like a quick recap of, you know, what it is that we talked about and you know, bounce that over to Jolith to capture for us. And then we can talk about, you know, ways for people to continue to get involved. And then, you know, the more amazing things that are to come from fair change. Yes. Thank you so much. So I know that was quite a lot of information. So recap would be quite handy to just refresh our memories. So just to kind of recap on what our key intentions are we throughout this whole journey, we definitely always made sure to keep in mind that our key intentions are to enable transparency, reeducation and reform as a matter of public interest and safety. We, as we've heard our mobile app is there to capture information around incidents that happened between the general public and the police. But I also want to kind of mention that it could also be used to capture other types of incidents as well. But obviously we, as Kailini has mentioned already, we focused on incidents between general public and police. And then also very important, I wanted to mention the significance of it not only being there to support complaints but also to kind of capture data and enable long-term education in terms of policing and all of that. And then for our users, James has mentioned or hinted towards us focusing on the general public for now but we definitely also throughout this journey we've interviewed other key stakeholders, for example, ex-police officers and NGOs and support services that we definitely want to include in our further development of the app as well. And very important to also keep in mind that we want to kind of incorporate functionalities to cater for individuals with neurodiversity, for example. So that's also, yeah, there's more to come, so to speak. So to speak. And then Boss has gone through our GitHub repo and shown the different GitHub issues that we've documented already. And I think I'm just gonna quickly hand it over to Boss to kind of highlight one or two of the issues so he can, yeah, explain it a bit further if you don't mind, Boss. No problem, thanks, appreciate that. So those issues were listed on there but just so you know, we've got 16 current active issues in this repo. We've gone through multiple, by the way, a lot more issues than this. We did some forking and moving of the repo around to try to make sure we make it more available for the development community. So that's why the number is 16 currently open. The, one of them that's really, really important is this advice, guidance and news on the website where we're really trying to scale this up so that there's not just the app having the coverage in the places where the app would be deployed but that we would get sort of the societal level discussion that comes with that, the local discussion, the right organizations involved in coming up with solutions that link to the community, the police, the other first responders or whoever needs to be involved in solution that make people feel safe and have them realize that they actually can be safe and deliver that to them. So to do that, you have to have a lot of content. You have to have a lot of outreach. You have to have guidance. You have to be able to teach upstanders, for example, when to record what to do, how to be safe and so on and so forth. News, these sorts of things can really help. And so there's an issue for that. There's an issue around, there are other issues. There's one around upload confirmation. You know, one of the things we've discovered in some of our research and going through many hundreds of prior videos and that's a really hard thing, watching all these videos and sort of coding and seeing what's going on in them is there are some cases where people are at risk or have actually had their cameras turned off or the recording turned off or they've lost control of their device and been unable to get out what happened to them for several years and the community only finds out much later, if at all. And so this notion of an upload confirmation or being able to take the video as it's recorded and put it in a safe place off the device, the ability to start the recording and not have your thumb print held against the phone fingerprint identification and then have somebody turn off the recording. Those sorts of things could be really valuable. And that's covered in that upload confirmation story. And then the use of AI, this is where we really need some AI practitioners and data scientists and the like, as well as guidance from the professionals in these various organizations on analysis of the incidents and what could be learned from those incidents that can really help. And Sabine really talked about that in a really great way. You think of, for example, over-policing in an area and the impact that that has not just on people's safety, but the impact on the school to prison pipeline, for example, people, maybe they're truant, they're late to school or something, maybe they have those specific reasons. If that gets over enforced, suddenly taking people down a completely different path and there's massive scholarly work and data to show that that's the case. And so an app like this that integrates data could actually illustrate the relationship between over-policing in particular areas and its impact on other outcomes beyond direct primary safety to the individual at that moment. And this is the kind of point systemic issues that the activists look at. And these are meant to be exposed as issues in the repo and have a level of engagement via the issues so that people can actually interact around those to figure out what the right thing is to build for these particular local areas or more generally. Thanks, and I think I'm handing it back to Jodeth. Yep. I'll share my screen again so that you... Oh, is it showing? Oh, no, it's not. Okay, there we go. And yeah, I think Bob just kind of hit on, you know, even the ideas for like the roadmap. So if you all need to just access the GitHub URL, you can go ahead and scan that QR code. I'm gonna move to the next slide for you, Jodeth. Yes, maybe just to go over the roadmap items. Yeah. Yeah, so what's to come? So for the Fair Change Future, basically we have several things on our roadmap items list. We definitely want to cater for the different identified stakeholders that I've mentioned just now or that we've mentioned throughout the whole session. And also want to add further technologies to tackle things around situational education. I think Bob has mentioned that before as well. We want to educate the users on, you know, what their rights are or how they should handle certain stop and search situations. And therefore need to build out the content on our websites and stuff as well. And then obviously analytics will be a key and a major part for the future starting with Kraken, but also just generally we want to make sure to use the saved map data for, you know, other analytics for longer-term education, as I've mentioned before, and to make sure that police officers are better educated in, you know, making more conscious decisions as well. And yes, and then also things around evidence packaging is also what we want to build out in the future which judiciary services can benefit from in terms of having more reliable decision-making processes based on the facts that they get from, you know, our mobile app basically. And yes. And then for how can you get involved and how can you stay in touch with us? Definitely join the Slack community and Slack channel that we also, I believe, have links to. That'll be on the next slide. I'll pop up. Yeah. And yeah, just stay in touch over Slack, join our community, go to our GitHub repo, start people in our repo and just watch our repo for follow-up follow-ups and just to stay up to date on the solution and how we're progressing. And then also for anyone who wants to be involved and join us in further finalizing our fair change logo that you can see on the right-hand bottom side of the slide. So we took a first cut at it and tried to, yeah, draft a logo, but we definitely need more help in finalizing it as well. So feel free to post any suggestions in Slack as well. And then that QR code will lead you to the developer site where you can look at the other projects called Corporation Justice Projects that Sabine has mentioned before. And then in terms of sessions, we've had quite a lot of sessions already. We had on the 24th, we've had a crowdcast session where we kind of demonstrated our solution as well. And if you want to go and look at the session, there's a link to the replay. And then we've had another session just yesterday having a more kind of like a technical scrum explaining the architecture in a bit more detail and answering more of the technical questions as well in terms of tools and technologies, et cetera. And then obviously we have our session today. And then in the future, we also plan on having a hackathon. And yes, that's pretty much how you can get involved and stay in touch. Awesome. I think there was a question that actually popped up in the chat. So I can read that out. So the incidents recorded are the videos pictures stored on a cloud or only the device itself? Okay, and then because I think you answered it. Oh, okay, you got it. We touched base on it earlier in the call, right? There's a storage bucket involved. There's some analytics being run against that bucket and all the videos and everything. So having that data accessible is important. Because if we don't, then we won't know about a lot and we won't be able to make this change possible, right? Right, exactly. Very well said. And I can kind of round this out a little bit more. So if you don't know Will Smith, I mean, come on. But I mean, well, I'm not gonna say that because we have a global audience. And so not everyone may know about Will Smith but he's really articulate and hear that racism isn't getting worse, it's just getting filmed. And we really reiterated throughout the call that the goal is to be able to avoid the continuation of incidents like this when we have overpolicing, we have incidents that go awry because of proper handling or just communication with community. And so we wanna be able to provide visibility for our police officers, for our community to understand what's actually going on and add that as a layer of accountability and protection for people who are trying to just live out their daily lives. And so developers really have an opportunity right now to step into the shoes and being able to contribute in a meaningful way so that adopters who eventually wanna bring this into ways of working within the communities that they live in have a way to do that in a safe and effective manner. So this is really gonna be for peace of mind and collaboration. So again, join us on the cloud and the Slack community. Hope you guys can capture this, but also this whole presentation kind of leads back into an actual conference that IBM developers having around data and AI. And so there are a couple of other conversations that are happening that people can interact with. And so we're doing this across the globe. You can see the different schedules. So if you wanna just go to ibm.biz slash defcon dash AI, you can find a little bit more about how IBM and call for pro-forester justice is doing our work and then we can leave it at that. Awesome, wonderful presentation. Thank you all so much for coming. Thank you audience for tuning in. We are running short on time though. So we have to make the jump over to the next show on the channel, but thank you so much everyone. This is a project that is very deeply important to me as well as many others. So thank you for coming on and sharing it with us and we look forward to seeing you soon. Yes, absolutely. See you soon Chris. Take care everyone. Thanks.