Okay, we should be live, we check things, just share it quickly, tweet us, we'll start in a sec, we don't know if there are any questions, if you have tried Balikales.com, you can provide your feedback real time. Pop this in the chat as well, please provide your feedback. If there is just, by chance, if there is no feedback from human, we'll get some feedback from chat GPT. Let's start a new chat, we'll do 3.5 first, then move to 4. We have both open and running, we have GitHub Copilot running in the code. We have finished this one earlier this week, the pretty basic, a real EEG, sorry for the ads, a real EEG can select your channels, the 16 channel EEG recording, an intracranial with seizures, you can scroll through the file, you can select your window size, you select here, yeah, this is not great, don't like those controls, they're not fun at all. Let's say make a note to use, what is this called, control shift C button, yeah, those spin buttons, make sure to use spin buttons only if absolutely necessary. Let's do it step by step, we're not getting all over the shop, this is the tool that is working, now we're doing a similar one, it looks more like this, the main difference is that it also has a wavelet denoise option, now we really have some, so it's going to be a Flask application, so I can share it with you, you can play around with it, provide your feedback, now the problem is, just start with 3.5, there's quite a lot of problems, but I wish there was a way to move from 3.5 to 4 in a more seamless way, so we don't get to the 50 messages every 3 hours prompt limit, what we can do though is let the GPT do its thing, well mainly because it's running faster, just so it gives us more ideas, regards how we can improve the code, so this will give us a description. Right, that's right, now we don't need the breakdown for now, now this is the actual Flask application, it does its thing, now we'll have the styles CSS, but we'll deal with it later, let's do those, see what it suggests. Right, well that's actually interesting, let's see what it says. We have a wavelet selection option, a wavelet type selection, now with GPT4 that's the one that I actually expect to generate better code, might start populating it slowly, but surely it's also getting a breakdown, so we can already have that, the wavelet selection. The noising level, the level of denoising, thresholding is another critical parameter, adjust the threshold level or multiply in your denoising code to find the optimal balance between noise reduction and signal preservation, you may need to fine tune this parameter. And that's an interesting one, we might edit as well, what else we'll get. So this EEG is probably the cleanest signal you could possibly get, because it's being recorded directly from the surface of the brain, it's coming from an implant, the other unique thing about it is that it has epileptic seizures in it. So we're actually trying to optimise for those, my mouth is barely moving, it's not very great, I don't have the playback feature at the moment. One thing I noticed with GPT4 of 3 or whatever, actually needed to run for longer, for it to do something useful, as in clicking the stop generating button can yield all sorts of weird results, many to the fact that it's losing context, lazy loading of data, what's that? Let's ask it the same question, we did GPT3.5, let's see and compare the results, this is back to 3.5, what else is it suggesting? Visualise denoising, to assess the impact of denoising more clearly, instead of creating separate visualisations that compare the raw EEG signal with the denoised signal. This can help you visualise the noise reduction more effectively. This is not a bad suggestion, it's actually a pretty good suggestion. So let's load a flash application and see what it looks like at the moment. Right, this is what we have, and yes, considering, we could just plot both of them, another option would be to have options for both displays, we have say red and blue, well then the problem would be how do you do those in different colours? I guess we could do another tool later that just has the time domain, it's comparing side by side the noise than the original signal. It's important to strike a balance between noise reduction and preserving meaningful signal components. Yeah, these values are currently not displaying anything, make sure signal noise and mean square error are showing values. Okay, let's move to GPT-4, so we have that, it's the same wavelength selection. Decomposition levels. Decomposition levels, the level of decomposition can play a significant role. A high level of decomposition might capture more of the noise because it removes some of the original signal. You may want to experiment with different levels to see which gives the optimal balance between noise removal and signal preservation. Okay, that's pretty much similar to what the GPT-3.5 said. 3.5 surprisingly doesn't have a thresholding section. Thresholding, the thresholding technique and the threshold value can significantly impact the denoising result. The thresholding you're using, multiply asterisk nb, sqrt, to asterisk nb.log, then eg.data is a common one based on the universal threshold. However, there are other thresholding methods, such as soft and hard thresholding, and you can adjust the multiplier to change the threshold value. Yeah, probably want the original to be grayed out in the background. Make the regional eg signal and the denoised time domain. If the noise is original, eg signal is displayed, is grayed, and the denoised signal is in color. There's the denoise on by default. Okay, let's do step by step to change the code so that this should be simple. Start with a simple task, change the html. In your JavaScript code, inside the DOM content loaded of EndListener, you can set the check property of the wavered denoise checkbox to true. html, no default option selected, which is unusual. Okay, so we changed it in the JavaScript, it should be fire. Adjust the default value for the wavered denoise parameter in the get underscore data function to true. So those are different options, is it? Yeah, I can just use the, just modify the front end, the JavaScript, check it. Yes, so wavered is on by default. Now next thing, yeah, make the original eg signal and the denoised eg signal in the time domain. Make sure if the denoise is on the original eg signal is grayed out and the denoised eg signal is in color. Yes, let's do this. Next, so we need to do two things. One is modify the back end to always send both the original and denoised eg signals. Modify the front end to display both signals and adjust their appearances based on the denoised checkbox state. All right, so in the back end, the Python code in get data, the data based on the original and denoised signal. Right, so we have a response data. Okay, so there's quite a few changes. And let's create a copy of a Python script just in case we stuff something up. Generate the whole, generate the whole, we should say regenerate, then complete the get data function. Okay, let's see. So we have start second, window size, that's the same, calculate the indices using define the sampling rate. That's the same. Extract the segment from the full data set channel. That's all the same true log wavelet denoised, by the way, not using frequency scale yet. Even though I'm pretty sure it's working okay. Yeah, but it's linear. Yes, it's, I don't know what's talking about. It's a leading problem. To work okay levels. The same validate waveforms. Okay, we have some changes there. Yeah, we don't actually need to do this, do we? Chains and fire original in G data, the trend. Okay, let's move it, let's move it long quicker. Otherwise we'll never get anywhere. I think that it didn't miss anything major. And it's ending with return JSON file. So we can replace this whole thing. Yes, we need to modify anything else. This regenerated function takes into account the default ON state for wavelet denoising, and always sends back both the original and denoised EEG signals. The original EEG signal will be greyed out if wavelet denoising is on, and the denoised EEG signal will be in colour, blue. If wavelet denoising is off, the original EEG signal will be in colour, and the denoised signal will be greyed out. Okay, that didn't work. Don't get any errors in that terminal. It's real loud. Type error cannot read, but you know what I'm using. Okay, so the Python code returning response data. Let's check that. Lotley newplot is called data. Response JSON. Okay, what's going on? Give me generic stuff. They regenerate this response. I don't like it. No, it's like it was working as second goal, right? So let's check the error again to update JavaScript. It seems to be more specific response. You need to ensure that your JS code can handle and display both signals on the same plot. I currently don't have an update plot function. Can you do the whole thing to update this JS? Because I wouldn't know how to do it. That's what I have you here for. It seems to be specific. You need to update your JavaScript to reflect those changes. Yep, need to plot both signals. That makes sense. So this one has yet to... Wait, how is it different from what we already have? Why do we have newplot twice? Doesn't make sense. Signal X, signal Y, signal name. There should be two signals in there. So that's the raw EEG. Wait, where is the original? There should be original and denoised. This modification uses the map function to transform the raw underscore signals array from the back end into the format required for plotting with plotly. It then passes this transformed data to the plotly, new plot function to render both the original and denoised EEG signals. Right, so the both included the rest of the plotting code. I don't have anything. Ah, this meant to be the frequency domain. So that would remain the same, at least for now. Yeah, let's check. Right, let's check this out. Looks like our one is not... I don't know, this is the trend as well. Right, so this is showing both. Let's reduce. Doesn't make much difference, does it? I'm not sure why they're not exactly overlaid. Where is the trend? Yeah, one. Okay, the trend should apply to both of them. They can barely... Yeah, so that's what it does. This filter order is for the frequency spectrum. It will change the levels. This kind of indicates what the trending does. The problem that the frequency spectrum is playing the same tone. Just changing the colors, what? Yeah, that's where the denoises playing up. Probably better to be removed. Might want to add more levels to check what difference does it make. Let's make it 5 and max 10. Yeah, this trending makes them overlaid. Yeah, this is the effect of the levels. Now, the problem is, as you can imagine, that during seizures it's behaving not quite the same. Yeah, it's not quite clear what's happening with the colors. When you switch, the wavelength denoises off. Understand, when it's on, it's fairly clear what it does. Now, the original is also before the trending. And the blue one is detrended and the wavelength denoised. That's why you see offset, DC offset. Yeah, so this can be a bit misleading in the sense that you can only see the denoising working well when making the window size smaller. And you can actually see the difference. It's not working well during seizure. Yeah, so this is what it actually does, just kind of smoothing the signal in different ways. Yeah, this is the epicenter of the seizure. Sorry, not the epicenter.  This is where the seizure is happening. Yeah, but it's hard to see what's going on with the denoising. Yeah, it's not too bad, but don't particularly like those buttons. Let's see what it says if we, you know, spin buttons. Alright, let's streamline the JavaScript code to make sure unnecessary operations are avoided, especially with regards to spin button or any other interactions. No, that's not what I meant. Can we replace spin buttons?  Drop menus are not great, but okay. But those are horrible. Spin buttons be replaced. The exact nature of the replacement you're interested in depends on your specific needs. Yeah, sliders are better. So in HTML, you don't like drop-downs, text, no custom. Well, no. Can we try sliders? Slider control instead of spin button. Yeah, window size. Okay, window sizing port. Yeah, this one. So replacing it with a type wrench. It's the same ID, but it should just work. Why the label is right in this one. Update the event listener to display the current value of the slider in the label. Okay, window size. Is it just called input? No, window size label we're doing. So it should update that number 10 when you're changing the window size. It's going up to 100. Yeah, it's all messed up a bit. Yeah, when I display, all spectrum should be turned on by default. The trending is moving the signal around zero. This is working okay. The number of levels is really only visible when you turn the trending off. Select, say this one, and it's channel should be a one second. Yeah, so that's what the level is doing. Yeah, refresh the page. That's the default view. Yeah, channel seven is default. That wavelet is default. Yeah, I'm not sure that's some sort of bug when you deselect this. I'm not sure what's happening with the colors. I would expect it to do something else. That's how the trending work. This filter order is actually only affects the frequency domain. It's not clear from here. You can choose to show the whole spectrum. Those three components should be at the bottom. We should rearrange the page. We should have channel number, window size. Can we do something crazy? Let's try this before, but it didn't really work.  We pop it into chgpt2, so it will pop this scene. We'll think for some time. Let's see what it says. The provided front-end design seems to be quite functional for the visualization of EEG data, but there's always room for improvements both aesthetically and in terms of user experience. Yeah, that's right. Yeah, we have a color theme, actually. The thing about this stasis is that we have this standard styling for our pages. We have a global CSS file and a local one. In the local one, the CSS should be only applied to the specific components on this page. Everything else, like text background, things that will be taken care of by the global CSS file. So we'll have two of them. Yeah, so that's the global one and the local one in the static folder for this specific web application. So this is a bit painful to debug because it will look different in production. So yeah, so the color palette consists in spacing, typography, key interactive elements, legend, graph, improvement, mobile, responsiveness, yeah, we'll have to sort it out later. Instructions, there are some instructions in the bottom. This one. Yeah, we also want to change the layout. Should we do it first or should we have all the controls in one place? Let me know what you think. So in essence, because generally speaking, these three, there will be more related to the wavelet transform that reduces noise. Then we have the overall things like the channel, select and window size affecting the whole thing. Yeah, this one is not, the training is not affecting the frequency spectrum, which makes sense. Now it does a bit. This filter is only affecting the spectrum. That's how sharp the band pass filters are in the spectrum domain. All spectrum is affecting the spectrum, is adding that extra line frequency scales also only affecting the frequency spectrum. So in theory, all these from filter order. Okay, let's sort it out. Filter order, all spectrum and frequency scale should appear next to each other and frequency spectrum chart. Yeah, we have to say out below or something. Yeah, on different screens it will appear differently. I kind of don't really want to spend too much time on it. Yeah, it would be easier just to have all the inputs in one place. Then kind of doesn't make sense. Again, because this filter order only affects the frequency spectrum. I'd also like to remove, so we change the window size. Can we use co-pilot? But that pilot is just not anything whatsoever. Nothing useful at least. All spectrum. Why was it filter? Yeah, I want to change. Let's make sure the original signal. All spin buttons be replaced by sliders. Okay, CSS, HTML. So we have control group. That doesn't make sense. Grouping and layout. All spectrum and frequency scale controls horizontally. You can achieve this using CSS flexbox or grid layout techniques. Position these controls directly above the frequency spectrum chart to ensure they're easily associated with the chart. Style each control to be of similar height and maintain consistent margins between them. This will present a more cohesive look. Consider adding light borders or subtle shadow effects to each control to provide a hint of depth. We don't want a hint of depth. For sure, don't like it. Make the frequency spectrum chart update in real-time or with a slight delay as these controls are modified. This gives instant feedback to users about the changes they're making. That's already working fine. Clearly label each control. If space becomes an issue, consider tooltips or drop-down hints. As the screen size changes, especially decreases, these controls should stack vertically above the chart. This ensures a good experience across all device sizes. Let me change the window size input with a slider. We did it in the HTML. Now we forget to do this in JavaScript. Update the event listener to display the current value of the slider in the label. We know. Window size label. Size label. This one goes window size. Let's click out there. In the event listener section a window size input can add this. Let's see what it does. It's changing that now. It's a bit... I sure want this to be changed. This is better. Now we want it to be displayed top. In CSS back in sec. We're going to sound check. Can't hear anything. Sounds okay. Okay, let's finish this. So we're changing the spin buttons because we don't like them. HTML. This number. How many of those do we have? Two. Filter. Filter order. And levels. Just replace them by range. And now the window size. We should have... Yeah, get rid of play. Right. So. Many ranges. Levels. Window size. And of course. The file scroll. Now. Levels. The label goes first. Size. That's working. Okay. So that's HTML. Installing. You can style sliders using CSS to match your design. Here's a basic example for styling. You can use JavaScript of endlessness, similar to how you capture values from spin buttons. This. Check box. Check box is replaced by buttons. Again. Check. Boxes be replaced. See if it gives us some options. Toggle switch. So I want a toggle switch or a button. Right here. Toggle. Doesn't work, does it? Yeah, well nice to have icons. Icon's in there. Okay, so. Replace when it denies the toggle switch. That won't work. With a channel script. Channel select. Filter. To replace this. More specific. Toggle switch. Is this? All for the switch. All. Yeah, I'll change the colors in sec. In channel script. Yeah, we have a different name now. And to replace. We'll be replaced by a visually appealing toggle switch while retaining the same underlying functionality. We'll still use that. Set. If. Fault. Not at all. Then.  Rest, is it? And remove that. Is it error? Of course. 20. It's called denoise toggle now. It's not doing anything right. It's not giving any errors. Anything else seem to work. But that's okay. It's a nice little button, but it doesn't stop working. Yeah, we should know. I have no mention of where the noise changes to toggle. Can get rid of that. Change. Doing much. Yeah, it's not changing the trend through filter. All spectrum. This is not an agate request. Right, this should be changed to toggle. It just remained the same thing. Right. And in html this is not a check box. It should be passed in the get request. It was changing the colors. Right. That number should be in span and wavelet denoise in get data. And we might not need that. It looks like it's passing in the get request. Like everything else. Okay, let's do this quickly. Let's actually try GPT-3 for that. We're probably going to hit the limit pretty soon. The 50 messages per 3 hours. Let's say this is for reference only the code and do not confirm reading the code and don't generate anything else. This will be pretty amazing. I suspect that confirmed I've read the code. That's pretty amazing. It actually worked. Confirmed. That was the html. That was the JavaScript. We added the html prior and we have the python code and confirm reading don't generate anything and same here and now wavelet denoise button it doesn't work. What's it called? Slider? Toggle. Toggle switch. Let's see what it says. The provided CSS contains styling for a toggle switch. Switch class with a slider. There isn't any JavaScript provided to handle the behavior of the switch. Why not? For the wavelet denoise toggle switch to work, you typically need html. We have the html element. JavaScript to handle the toggle action eg. I'm pretty sure we have something in the noise. Then integrate the toggle state into your flask app request when getting data. Okay. That's what we had before. Anyway, so that should be fine. However, from the flask code you shared, it seems that wavelet denoise parameter is already expected in request. Therefore, ensure the toggle switch in your front-end correctly sets this parameter when making a request to server. Check if the html and JavaScript for the toggle switch is properly set up. Ensure that the state of the switch on, off correctly modifies the request sent to the flask server. Make sure the flask server correctly processes the wavelet denoise parameter and applies or doesn't apply the denoising accordingly. I'm going to do this for me. See above. Is this specific stuff or generic? You have the code. You have the code above. That's getting annoying. It's the problem with the name or something. Come on, are you choking me? I just gave you the code. Funny. So I have this that in html this and in python I think it's the order of things. Flask this case we need to consider. Ensure that the JavaScript code that initializes the checkbox and sets the event listener runs after the html is fully loaded. Yeah, we have the downloader event that should be fine. Ensure that the fetch data and render function is correctly defined and doesn't contain any errors that might prevent the listener from being executed. This one. Yeah, we're not using playback. At the moment all that function can go we have the element by this section. We have a wavelet denoise there. Okay. In fetch and const parameters it wavelet denoise as well. Right, now it's working. Pop, pop, pop, pop. Okay, I think we can run for today. We need quite a bit of progress. Yeah, I want to later change the detrend button also into let's forget what's called a switch. Switch, switch, switch. Should we do it now? Do we have some time? Probably not, but we'll do it anyway. Ah, it's actually working if you click on the text as well, that's handy. Yeah, we need to break down the inputs into different parts. Two, three parts inputs should begin into three parts and spectrum, that's right. Smart boy. Okay. Filter order channel number window size on top of the page filter order whole spectrum frequency scale should be next to each other should be next to frequency spectrum chart then you have trend noise does this have a label should have a label is to give errors, I forgot about it. Yeah, we'll continue this next time let me know if there's any questions is let me know if you had the chance to review this slide and this new tool will soon appear on it as well for you to play with look that's the previous one, just a simple scroll through the data and currently in this one will be essentially an advanced version of it so hopefully we'll finish it next time don't forget to you know what to do on youtube you know, subscribe like, comment tickle the google the youtube algorithm


Hello everyone. Welcome. My name is Katora Brown and I am a foreign service officer. I've been with the department for for over a decade, and I have the pleasure of being the moderator for today's session on data science and and foreign policy. Look, we are really excited that you are all here joining us. I hear that there's over 500 folks that are here for the panel, and we just want to take a moment on behalf of the department of Secretary Blinken and everyone to say that we are thrilled that you are joining us. We are also of course, I'm set that we couldn't do it in person, but that we are going to continue through this process and that we hope to have an interactive session today where we exchange ideas. And we can discuss and and and share questions and the best of our ability, we will answer them, but we will explore together what it means for data, data science in foreign policy and at work at the at the US Department of State. Welcome everybody. Let me just lay out quickly how we'd like to do the panel today. As I said, I'm the moderator and I'm going to few in a few moments I'll ask all of the moderate all of the panelists to briefly introduce themselves. Say a little bit about what they do a little bit about their background, how they came to the State Department. And also a little bit of detail about their jobs. And then I'm going to ask a few questions of our panelists, and I'll ask those questions to try and generate questions for you all. So that at the at the question and answer, we can have a good back and forth. I also want to just flag for people that if you have questions, please use the chat function, because we really want to leave time to address the questions that you have as best we can, and to have a conversation. And so please go ahead. When a question comes to you, you can put it in the chat. So, let me take a moment to introduce myself as I mentioned my name is Kachora Brown I was born Harlem New York and raised in the US Virgin Islands. I've been a foreign service officer for for 10 years and I've served on the Iraq desk I've served in Bamiqomali. I've also served in in Nairobi Kenya, and also in Washington DC. I came to the State Department through a fellowship called the wrangle fellowship, which takes about 20 folks per year. You have to apply to the fellowship and and get into the fellowship as well as get into graduate school, and after two years of graduate school. You are you join the Foreign Service so that was my path as you'll hear, there's many different paths into the Foreign Service. Quickly, what do I actually do now. My formal title is a conflict advisor with the CSO Bureau CSO stands for conflict and stabilization operations. So, I advise the US government, I advise our secretary our bureau and our post overseas about what activities and interventions that we can do in in conflict areas to mitigate and respond to conflict. So that's my, that's my role. Let me take a moment now to share with you a number of my colleagues that come from various backgrounds and I'm going to start with Jeffrey, over to you. Thank you. My name is Jeff Johnson. I'm the chief information officer for budget management and planning. And so I work for the Bureau of Information Resource Management and that bureau is is designated to empower the department to achieve its foreign policy mission by providing modern secure resilient information technology and services. We are focused on collaborative tools that enable mobility and simultaneously protect our information through cybersecurity and and protect our it assets against evolving cyber threats and vulnerabilities. My office in particular, I'm responsible for all the business management plans for the business side of the it investment. So that's about a $2.4 billion global it portfolio that is that annually is servicing across 85,000 people, the workforce of the department and operating in over 300 locations, domestically and overseas. And within that it's a responsibility of taking care of strategic planning, budget formulation, execution of the budget, reporting out to the public on the results of our of our it programs and and supporting the frontline business of diplomacy. And my so that that's a big job and my path to this job was not a I didn't come directly as a as an IT specialist. I started my work with the with the Department of Education working in in the office of Indian education work with Native American tribes on tribal programs and and with that is where I got the bug for data and data analytics. And what we were doing with those programs there was looking at cultural programs that were supporting the native language reclamation and and using using native tools to improve student math and reading achievement. And when I was there, we were having a real difficult time getting school districts to approve to them. And we were able to to create through using a national assessment, a survey that collected information that showed that cultural education does improve reading math scores for native students in fourth, eighth and 12th grade. And that it's in that feeling of empowerment that program empowerment really captured my my my passion for public service, but also captured that that government can do things that improve the lives of the local communities. And so that drove and assisted me with my career and I came over to the department, working for the Educational Cultural Affairs Bureau with their, with their exchange programs the pull by program and other sports related programs. And leading in those grant programs. And from there, I also worked for for the inspector general using technology again to inspect and ensure that we're all being good stewards of federal funds but also meeting the goals and objectives that have been established by legislation and by the executive branch. And that's, that's a little bit about me and I look forward to this discussion and I'll pass it over to aspect to Petra. Thank you, Jeffrey. Margaret, can you go ahead? Yep. Thanks so much, Katara. Good afternoon everybody really excited to be participating on this panel. I want to talk to you all today about data science at the State Department. So my name is Margaret Callahan, I am a conflict analyst in the Bureau of conflict and stabilization operations same as Katara CSO is a functional bureau within the State Department so it focuses on all regions of the world and has a particular its mandate being to anticipate prevent and respond to conflict so CSO implements its mission by deploying stabilization advisors around the world, implementing policy and programs on conflict prevention stabilization and harnessing data analytics and so I fall into that third bucket. So I'm part of the Office of Advanced Analytics and I am lead analyst for the Western Hemisphere but I also dabble in some other countries including Ethiopia and Sudan. A little about my background, I am an applied mathematician by training so I received my PhD and applied math in 2016 from Case Western Reserve University in Cleveland, Ohio. Before getting my PhD, I did a brief stint in academia before deciding it wasn't for me and looking for ways to apply my technical skills in mathematics and data analytics to affect real change in the world. And so I had a few intermediate career steps but that's how I ended up at the State Department. I came in a little over two years ago and I joined CSO as a AAAS fellow so that is American Association for the Advancement of Science, Science and Technology Policy Fellow it's a real mouthful. And I think we're going to talk a bit more about the that fellowship opportunity later but the goal of the fellowship in general is to place scientists, mathematicians and engineers throughout the federal government in order to bring a scientific and analytic perspective to policy making transition. So I recently just like a month ago transition to the to the civil service formally which is really exciting. But my role at CSO is still just in the vein of the AAAS fellowship which is that I use data analysis and quantitative tools to understand conflict dynamics worldwide. For me it's mostly the Western Hemisphere but that's a little bit about how how I came to state and I think is an example of how really there's something at the State Department for everybody no matter your background you don't see mathematicians aren't a dime a dozen at the State Department but we have a role and data analytics is a great is a great place for people with technical background to engage at State and inform policy making. So I think that is it for me back to you Katara. Thank you Margaret. Over to you Patty. Hi everybody good afternoon thanks so much for having me I'm really excited to be here. My name is Patty burner. I guess my path is a little bit different I am the program manager for the foreign affairs information technology fellowship. I'm going to that now I'll talk to you a little bit about it down the road. I work for the Bureau of Global Talent Management. Our focus is to recruit and to retain and to sustain a diverse and talented workforce. And what are the means to do that is the foreign affairs IT fellowship that I manage. The State Department was a little different I was living overseas as a foreign service spouse and I was work started by work with the department as a family member overseas. And when I came back to the states I transitioned into working with the civil service on the civil service side so I've worked with the family liaison office on advocating for family member employment and sharing resources and information. And then when I came across this position with the foreign affairs IT fellowship, it really caught my eye have a background in education. I'm passionate about creating a more diverse and inclusive workforce for the department so it really spoke to me and I've been now in this position for about a year and a half so I look forward to telling you a little bit more about the program in a few minutes so thanks Patara. Thanks Patty. And finally, over to Aubrey. Thank you Katara. Hi everyone, my name is Aubrey Paris and I am a science technology and innovation policy advisor in the office of the science and technology advisor to the Secretary of State, and that's a mouthful so we often call that the staff's office. More on that in just a minute. But how did I get here. Well I'm from New Jersey, and I have a very broad science background we can we can say that so as a scientist I double majored in chemistry and biology in a very interdisciplinary program at our sinus college in Collegeville, Pennsylvania, and immediately I started that up with my PhD in chemistry and material science at Princeton, also back in New Jersey. I clearly have a trend here. During my graduate studies and my undergraduate studies I also had a great passion for science communication, whether through writing video podcasting all different platforms, and this this passion for translating science and technology topics for non scientific audiences and seeing how science and technology topics could most effectively be appreciated and then applied in the real world. So science policy and the State Department seemed like a pretty exciting place to take that after my graduate studies. So I like Margaret joined the State Department thanks to a science and technology policy fellowships program. Mine was sponsored by I triple e USA, which is the Institute for electrical and electronics engineers. And this was for me a two year fellowship program in the State Department to focus on science technology and engineering diplomacy. So, in the office of the science and technology advisor to the secretary, my primary responsibilities I categorize in two different buckets. On the one hand, I am working on recommending courses of action and contributing to policy discussions related to various science technology and innovation topics ranging from biotechnology to areas such as data because data is not just something we we use to inform policy we actually make policies around it as well. Another bucket is really related to public diplomacy and innovation writ large and public diplomacy and outward engagement with various public especially international audiences is something that's also really informed by data. That is how I fit into my office my office as a whole has an even broader scope. So we work with and collaborate with offices all around the State Department as well as our many missions overseas to anticipate trends in emerging science and technology and think about ways in which they're going to affect foreign policy down the road so that we can be proactive and and create the necessary policies regarding those topics. We also work to build the capacity of the State Department to deal with and work on science and technology topics through, for example the fellowship programs and others that Margaret and I have already mentioned. Finally, we engage on science and technology topics through public diplomacy through conferences like this and through multilateral and international organization settings. So, I think, I think that'll do it for me in my summary so back to you Katara. And so, to everyone who's joined us on the zoom call, what I hope you've heard from us is that we come from all different backgrounds. There's not one path to the State Department, and that data informs the wide range of all the activities that we do here at here at the State Department. So, one question that I have for the panelists and I would like Jeff to start on this one. When, when we say data science or data analytics, what are we really talking about when we use that term for data, data science in the form Okay, great. That's a that's a good question. And when you're on the outside of the Department or outside the federal government. Sometimes it's hard to, it's we're influenced by by entertainment and by social media and and and think that there's a lot of things that are in our hands and available for us to to have these cool tools that we're carrying around all the time. The reality is that the federal government as well as the Department of State is still still working on how to how to how to grasp and how to take care of a large segment of data that we have across various functions and how do we use that and how do we use that in a predictive model. Can we utilize data that's collected to be able to predict whether there be turmoil or or a an insurrection in a country and be able to determine any sort of supply chain challenges so that there's there's a lot of we still need to do it in order to get there, but we're beginning to build those building blocks. And we have the Center for analytics that was put into place recently within the department that drives our dashboards and executive dashboards and and working level dashboards that are helping us understand a lot of areas where we're working towards utilizing more mobile technology laptops iPhones iPads and being able to issues to employees and allow them for greater flexibility and mobility to meet various work requirements. The use of AI or a data lake is really important. And just give you an example. I talked a little bit about my meandering river of a career where I've been to various agencies. Before I came back to state I was at Health and Human Services and I was in charge of the grants programs for HHS grants are the largest funder across the federal government they include overseas as well as domestic grantees and there's 26 other federal agencies that use grants. One of the areas that we're just getting a handle on is using common definitions of terminology. When you look across those federal agencies. Nobody even had the common definition of what a date of award was everyone had a different idea of what that meant, and that makes it very difficult to do any analytics once you don't have a common set of definitions so that is one of the areas we struggle with internally just to get those common definitions. But now that we have those common definitions all of a sudden grant making agencies across the federal government can start looking at larger issues and being able to connect Department of Justice data with HHS data with HUD data with education data and provide better programs to local communities. And that is where I think we want to be is our mistake also is to create these data lakes where we are able to utilize that information grab a hold of that information and be able to drive good policy making decisions. But that takes a lot of a lot of work and a lot of opportunity for growth there. One of the areas that I think is students you can look to and your universities are eligible for this is there's two programs. And we're patty's going to talk a little bit about other programs, but I just want to plug one one program that I'm in charge of. It's the virtual student. The BSFS program. This program is your any any undergraduate is allowed to apply through a PhD and it's specific programs across the federal government where you can actually go in get an idea of what we're looking for across the federal government to to resolve a problem. And you apply for that. And once you apply and you're selected you'll be working with the federal agency for a 12 week sprint or three month sprint to resolve or to find some solutions. So that's a fascinating program BSFS dot state dot gov. It's the largest longest running program that covers over 60 federal agencies with that program. And then there's one other program that you could look at it as an undergraduate is the opportunity project out of the Census Bureau where agencies put up a an idea of problem statement and then universities and colleges can take that. Create a team and come to the federal agency from the data sets that we've been given the public data sets and say this is how you resolve the issue. And that's happened recently with with environmental controls. So groups looked at plastic usage and how to track plastic that are in oceans and they're hurting our food supplies through the fisheries. So there's a lot of real opportunity out there to use data and unique and different ways. And the one way that you can think about as you're thinking about your career is using these project based opportunities to begin exploring which federal agency want to work to. We would love to have you here at the Department of State. There's a lot of agencies that are also doing international work across across the government. Thank you Jeffrey. Margaret I'd like to to ask you the same question there about when we talk about data science what do we really mean and can you share some tangible examples of the things that you've been working on and how you have incorporated data. Over to you Margaret. Sure. Thank you. I'll mention just what how I use data at CSO which of course is very different than how data is incorporated elsewhere in the State Department but I think we use it really interestingly so of course CSO Bureau of Conflict and Stabilization Operations. Our goal is to anticipate prevent and respond to global conflict. So for me in my job that means typically using a wide variety of data sources and methods to understand conflict dynamics and also mitigate current conflict and prevent future conflict. So part of the reason we need to do this is because conflict looks different in different parts of the world. So I think a lot about the Western Hemisphere. In my role as lead analyst for Western Hemisphere and in Latin America and in Central America for instance, conflict is often social conflict. So when I say conflict, we usually mean like conflict and protest events so any political events. And I'll talk a little bit more about that but send in Latin and Central America conflict is often like protests or riots and can involve gangs or other arms, non state armed groups as perpetrators of violence against against unarmed civilians whereas in places like Ethiopia and other countries that I work on regularly conflict is often driven by ethnic grievances. So we use data to help us understand what is driving conflict like the drivers and factors of conflict. And one of the data sources we use is called Aklid. So it's the armed conflict location and event data set data project and that it's open source. It's available online if you can Google it and check out their dashboard. And I believe to download data you need a license key but but you can kind of poke around and see what what they track so it's an events based data set that tracks conflict and protests globally. And it is a data set that we use pretty often it's very rich it includes information on where conflict and protest events take place who is involved specifically what occurred. And that is the data source that we employ very often and we use certain data visualization tools to just understand how conflict is trending in in certain countries or regions. In addition to Aklid we use other other data sources that give us a sense for the factors and drivers of conflict. We use economic data we use data on countries levels of democracy levels of political terror. And we do all of this to understand the trends in conflict in certain parts of the world and anticipate where new conflicts may emerge. And all of this helps helps the department prioritize, particularly where programming should be implemented where funding should be invested. It helps drive the both CSO and the and the State Department as a whole's priorities on mitigating conflict and you know increasing stability worldwide. So that's, that's a general overview back to you Katara. Thank you market and Aubrey. What are your thoughts on this topic. Thanks. Thanks for the question. If it wasn't clear already I think what my answer to this question will really indicate or underscore or drive home the point that data is used in so many different ways around the department which I hope is really exciting actually to our our listeners here today, hopefully gives them lots of fun ideas about how they could engage with data if they were to join the State Department. So I think from the perspective of the staff's office on the side of using data to make policy and programs. I can give some some examples of where this pops up in our day to day work. For instance, over the past year, my colleagues in my office have worked collaboratively with other functional and regional bureaus across the department as well as many of our missions to create AI related or artificial intelligence related strategies for our missions in different countries. And I think one thing that most people recognize about artificial intelligence or AI is the vast amount of data that it requires to to implement effectively. And there are a lot of implications of where those data streams are coming from and how we are using that data in terms of how effective that eventual AI will actually be. So that's one one example. Another in in my own work. I work with many folks across the department on biotechnology policy. And so you can think about biotechnology from a lot of different perspectives but just one example here with much relevance to is genetic information, whether for, you know, people or other living things. And what that means for things like data privacy, or who owns genetic data and how should it be shared, or maybe it shouldn't be shared in different, you know, circumstances. Bioethics is another place where all of this comes full circle because what are the ethical and moral questions associated then with how data is collected, how it is then shared and then eventually how it is used. On the programmatic side right I talked about public diplomacy I think it's also important to recognize that we use various sources of data to inform the public diplomacy programs that we put into place. And then once they're complete we use metrics and data, a ton to assess how effective they were at accomplishing our goals and then how can we learn from that data that we've now created based on our past programs to influence our future to make them even better and more effective at accomplishing their goals. So that's really using data to make policy and programs but again I really do want to underscore that we're also at the State Department making policies and programs about data. So talking about these questions about data ownership data data sharing data implications, you know how should data be protected. And this really does require a deep understanding of what data are how they're collected and how they they can be protected or not and what that means so there's a huge role for data scientists or really scientists of any type that are familiar with working with data to be able to answer some of those big questions and have a really important say as those as those policies and programs about data take shape now and in the future. That's really interesting thanks Aubrey. What I'm hearing is that there's a, there, there are broad sources and methods to the to the collection, but also to the use of data across the department that that that data helps to inform policymakers to make decisions, but then, on the other hand, as policymakers we are actually making decisions about data and how we use it. And, and, and how we share it. So, if I wasn't already in the foreign service and working for the State Department, or in the civil service, or had a fellowship, I would think to myself, these sound really interesting. So what are some actual tangible examples of fellowships or opportunities that our students on the call can pursue I know that we've talked about some but I just like to spend some time right now, going over a few a few tangible examples so that you guys that are here with us can walk away with at least a couple of examples of how you can get involved with with the State Department as a student as a graduate students, or even as a recent graduate. And for this I'm going to ask Patty to give us some more details over to you Patty. Yeah, I mean you're just been hearing about all the wonderful and amazing things going on in the in the State Department. Your best resource is to go to careers.state.gov. Because you can find lists and information about all of these some of the fellowships that Aubrey and Margaret mentioned. And I'm going to talk about one in particular because it's related to information technology, but there are intern programs there are, you know, paid internship programs there's fellowships. There is coming into the State Department in the Foreign Service and I'm going to talk about the one program to one of the programs that that puts you in that direction. There's also a myriad of civil service jobs. I think most of us here are with the civil service so there are many, many opportunities so I just highly recommend go to the careers.state.gov website. At the beginning, Katara had mentioned that she was a wrangle fellow and the program that I managed the foreign affairs it fellowship was modeled after the wrangle and the pickering fellowships. I'm going to highlight it and talk to you a little bit more about it, because it is a fellowship that is specifically geared toward students who are in an IT related major, and I'll talk about that in a minute too because that's a that's a broad umbrella. This is for undergraduate and graduate students so I want to talk a little bit more about that and highlight it's a growing program. There's a lot of focus on in the department so I just I'm going to share a few slides, just because I think that will make it a little easier for us to just see it I'm just going to take a few minutes here. It's okay I'm going to share my screen. Okay, just to double check and everybody see that okay. Okay, perfect. Okay, so I'm just going to give you a quick overview this is a few of our fellows here in the corner. So the, the foreign affairs it fellowship program was developed to attract and prepare outstanding information technology students for a career as a foreign service information management specialist so that's the key of this program is this will lead you to the career this is one of those paths that we talked about our different paths in, but based on the fundamental principle that diversity is a strength in our diplomatic efforts, the program similar to the Pickering and Rango fellowships value varied backgrounds including ethnic racial gender and geographic diversity. So minority groups which are historically underrepresented in the Department of State women and those with financial need are encouraged to apply for this program. I'm just going to talk a little bit about the specifics just so you have an understanding. Some of the benefits of the program. There's academic funding up to $37,500 annually for tuition books fees living expenses, you know funds to cover, you know, transportation to and from school. So it's a two year program so it really adds up on there are two internships as part of the fellowship. One is domestically here in the Bureau of Information Resource Management that Jeffrey spoke on a little bit at the beginning, and also the opportunity for overseas internship at a US Embassy or a consulate. There's mentoring and professional development opportunities throughout the two year program, and the best to top it all off is at the end, you have employment in the Department of States Foreign Service. There's a five year service obligation and in a minute I'll just touch on, you know what what the position is. One of the biggest benefits is it gives you that foot in the door it gives you that start of a career information management specialists, they serve their country by maintaining secure reliable information technology tools and resources. And that ensures that the State Department and other federal agencies and Americans overseas, you know can effectively communicate and they can protect us interests abroad. I like to say that you know the information management specialists are sort of like the backbone of the of the department overseas, making everything work and making communication and technology possible. So for those of you who are interested, which I'm sure there's many I'm just going to talk a little bit about how to be eligible for the program. The next cohort won't be selected until 2022. However, the application will open probably around September of this year. You must be US citizen to apply. We have two fellowships we have one for undergraduate students. So those students would be entering their junior year in 2022 in fall of 2022. This is a cohort model so you sort of have to follow along with the time scale. It could be possible that maybe you're a community college, and you're going to be transferring to a university or college junior senior year. So as long as you're going in as a junior in 2022 you'd be eligible. The graduate program would be that you're entering the it related master's degree program in fall of 2022. You don't need to have completed in it undergraduate degree. This could be your first experience with information technology related degree. So when I talk about it related degrees I just want to stop here there's, there's a huge umbrella of this. Many of our fellows are computer science majors. We have some who are majoring in data science, cybersecurity information management. You're free to contact us if you're not sure if your major would fit into the eligibility requirements and we're happy to talk to you more about your programs. You do have to have a minimum 3.2 GPA on a four point of scale. And so, you know, you do have to obtain a maintain medical and security clearances and suitability requirements you know as part of the Foreign Service requirements. So just to give you something to look forward to in the future. This is the timeline for the next cohort in 2022 we will be selecting 15 fellows, some undergraduate some graduate, but keep your eye out the application will open in September. This actually goes until the following February will announce it on the website, which you'll see at the bottom of the slide there is fate fellowship.org. And also on all of our social media sites so please have a search and you can find us on Instagram or Twitter or Facebook. And then you'll see sort of the end of the timeline is then fellows are appointed into the Foreign Service as an information management specialist and following the timeline it should be in fall of about 2024. So it's a two year program. So I encourage any of you who are eligible to certainly find out more on our website there's a ton of information there. There's loads of information about what it's like to be an information management specialist overseas. And so I encourage you to apply and you know start an exciting career as an information management specialist. So thank you for letting me share, and I will send it back to you. Thanks very much Patty. So just to recap for folks. There's the fate fellowship. There's also the Pickering fellowship. There's the wrangle fellowship. There are a number of other fellowships and opportunities that we would love all of you to at least take a look at. And so you'll see in the chat that was posted. So the best place to go and to look to follow up after our conversation is careers.state.gov that lays out all of the opportunities at all the levels so so so we really encourage you to please look there. And so, and also, we're cognizant of time. And one of the things that we don't want to do is just talk, we want this to be an interactive experience. What I'd like to do is hold on other questions for the panelists and then just see if there's actually any questions from from from those who who've joined us questions about something that one of the panelists may said may have said questions about even more how data is used about how the State Department works. We'll be able to to make sure that we have a good amount of time at least 20 minutes to respond to your question so if we can answer them, we absolutely will. But I want to, I want to encourage people to start looking, or to start asking questions. We already have two, we already have two and please keep them coming. And so the first question is, how is data acquired by the Department of State, and what are its sources, how is data acquired by the Department of State, and what are its sources. So, we already enter that to a certain extent in terms of depending on your job responsibility as a conflict analyst, or as an IT person protecting the data infrastructure behind the State Department, our sources of that data is going to be quite different. And also, the State Department, we say to to acquire that data. There is public publicly available information, like Margaret mentioned, through ACLIN, and many types of other sources that are public. You also know that there's some data, geospatial data or other types of intelligence data, that is collected via classified ways, right, so we have unclassified ways, and then there's classified ways. And so, again, depending on your job, depending on your job responsibility, there's different sources and methods, and of that data. There was a second follow up question that we have here. And I'm going to ask Aubrey to respond to this one that this question Aubrey is, how have the growing fields of machine learning and artificial intelligence within data science impacted the projects and activities at the Department of State. Let me say that again. How have the growing fields of machine learning and artificial intelligence within data science impacted projects and activities at the Department of State. Aubrey, can you take that? Sure. The short answer is quite a bit. The longer answer is, and I should caveat this by saying I have many colleagues in my office who work on this very closely, but what my understanding is, is that much like with any type of emerging technology, those that involve data included. We at the Department of State try to be as proactive as possible when it comes to determining the implications of technologies such as artificial intelligence and machine learning in creating the policies, creating and implementing the policies necessary to see those technologies have their fullest, most beneficial impact in society. So over the past several years, artificial intelligence and machine learning has been a huge priority at the Department that has been collaborated on by many, many, many offices across the building in secure the areas of security of economics of science of bilateral and cooperation, etc. Because these are all places where AI and ML artificial intelligence and machine learning are popping up. And so our department has worked on determining its own strategy for for working with an acting on and making decisions based on these technologies and is now as I mentioned in the process of helping all of our US missions decide how they should be interacting with and acting on these technologies. And it's really important I think something that Margaret said that's true here, just as as conflict has different forms, or implications in different parts of the world, different technologies, AI ML very much included, have different applications and implications in all different parts of the world, depending on what those with different regions priorities are, or, you know, how much they are really able to focus on science and technology as opposed to other other issues such as conflict or conflict. So it's it's very, it's a very important consideration for our current policy activities. And I think that it will continue to be so as we continuously understand from our colleagues out in the field around the world, how these technologies are being implemented in various countries, because that will really dictate and guide our decisions on how to engage with those technologies ourselves or engage with other communities or other governments on those technologies. So it's it's so, I love it as an example of really case by case basis, you know, what our diplomacy means in different parts of the world so it's a it's a broad answer because it's hard to be specific unless you're talking about very specific parts of the world so I hope that helps. Thank you for that. Maybe Margaret, you can take this question. Is data the same thing as intelligence. And if it if it's not sort of, what's the difference how do we explain data versus intelligence over. Yeah, that's a great question and actually, I'm going to combine an answer to that question with the previous question which was about the State Department's data sources so as you mentioned Katara. There's a lot of public data sources and we try to use those sources as much as we can because open source data is unclassified and so it's easier for us to share with our partners across the federal government. And also with the countries that we work with closely so we and when we don't have a particular source of data that we need we are often able to design and fund data collection program so that could be for instance, if we're interested in providing public perspectives and opinions on, you know, it may be a transitional government, we are able to fund programs that go into the field and collect data for us so that's another way that the State Department can share data. I don't have a lot of experience in the intelligence realm, but I think I, I, I, as a data analyst that doesn't deal in intelligence can say that the two things are different, I think intelligence can often come in the form of and is often, I think, classified and so I can't really speak to what that data would entail but I think a lot of the data that we use in our work is generally open source and tells us, you know, about what I spoke about earlier conflict events or other aspects of the kind of big questions that we are interested in perhaps infrastructure worldwide, data on climate, which impacts conflict so these are some other examples of data sources. And if I don't know if anyone can speak any more about intelligence specifically but I would say that intelligence falls under the banner of data but data captures more than just intelligence, if that's helpful. That is, thank you. And I'm going to open up this one to to to both Margaret and Aubrey. Are you aware of any new technologies that or or new new technologies and new data sources to address climate change Margaret you just mentioned that one of the key concerns that CSO is looking at is the impact of climate on conflict in particular. So can you just talk a little bit about maybe what some of those data sources are that you use or if we're aware of new technologies to help us address the issues of climate change over. Well, I knew I shouldn't have mentioned climate change because I don't I don't have too much just add to this I think Aubrey will probably have some things to say but I will say that CSO right now is in the process of looking into what data sources we have available to better understand the relationship between climate and conflict and you know I think we know that climate change impacts availability of resources food and water so that is a you know a kind of a direct line between climate change and conflict and so understanding what parts of the world are experiencing drought or are experiencing floods other things that damage crops and access to clean water. You know we'll be looking for data sources like that that kind of information. And this is just a space that CSO is beginning to really engage in and so it's an exciting time and we'll be looking for new data sources that will also probably include imagery satellite imagery, which is something that we have been using as well for other types of projects so it's an exciting space, obviously a very important question, and I'll I'll see if Aubrey has anything to add. Yeah, thanks Margaret. Well, I think on the technology side of that question. It's really important for us. In my office as well as others in the department to be keeping an eye on different technologies coming down the pipeline and what they could mean for big picture questions like climate change. And then think about what those implications could mean for our diplomacy and security and all that all that fun stuff. So I will put my scientist hat back on for just a second and give one example of a technology that sort of maybe coming down the pipeline that that could be related to climate mitigation. And that is carbon dioxide utilization technologies. So this is exploring ways to take carbon dioxide that is released at point sources or diffusely floating around the atmosphere and and be able to turn that carbon dioxide into something that's actually useful. So whether that be actual materials or chemical feedstocks or even fuels. These are all from the chemistry and material science perspective, real possibilities of things that are being done in laboratories right now. And so this is, I guess, I think it's a personal favorite example, I guess I should say of the type of technology that's really worth watching because it can have both, you know, climate change mitigation applications while simultaneously having economic applications as well you know if you can turn CO2 into something that you can sell and reuse. So it's one of what's the phrase two birds with one stone, maybe. So, so that's one example. That's quite interesting. And I'm quite helpful. So, thank you on that. So, we're at the time where we're going to wrap up and we're going to try to wrap up a few minutes early, but that's because we know that you all are in a full day of panels and we want to make sure that you all have time to transition to the next one. So, instead of doing sort of formal goodbyes, what I would like to ask our panelists is, what's the one thing that you want to say to the over 500 folks that are joining us today about about data and foreign policy, or about data and State Department. What's the one thing that that you'd like to, to leave us to leave with us. I'm going to ask Margaret to go first and I'll come to Patty. Margaret. Thanks so much, Katara. And I really appreciate everyone's time today. This has been a really interesting conversation. It's been very fun for me to hear from my fellow panelists on this.  We really come from everywhere, you know, all types of backgrounds. So I would just say, like, if this is of interest to you, if you're interested in foreign policy, if you're interested in doing data science at the State Department. There's tons of opportunities. There's it's very interesting work. It's really important and relevant.  I personally had no foreign policy background whatsoever coming into this role. And have, I think, you know, thrived at State and loved it here. So just really want to encourage everybody to, to look into the various fellowship opportunities and other opportunities that we that were discussed on the panel and and yeah, good luck with your future endeavors. Thanks, Aubrey. Yeah, I guess I would close this out by saying, I'm not sure why each and every one of you chose to join this particular session today, we're certainly really happy that you did. I don't know whether you've chosen to join because you already have a passion for data science or you are pursuing a field in related to data science, or maybe you just recognize that data is part of your life. I mean, you probably use social media have a favorite streaming platform for your TV and movies or have your life on a laptop right. And so, I think that alone is real evidence that data in our lives is only becoming more prevalent. And that means there is a role for data, both acting on it and using it within government and here at the State Department. And so whether you are already studying data science, or it's a passion of yours, or if you have a scientific background of any type. I can't believe this by saying there's kind of to echo Margaret.  I think it's really beneficial to apply just this broad scientific way of thinking and specifically problem solving when it comes to our foreign affairs and our international diplomacy. So best of luck and I think we would all welcome you to reach out to us in the future if you have any questions. Patty. Yes, thank you all so much for joining us today and allowing us to speak with you I think by listening to the other panels you've heard about just the wide range of opportunities exist within the State Department and I don't think sometimes students are aware of everything that's that's going on I mean, you know, highly recommend, you know, spend some time, you know, check out the careers.state.gov website and the State Department website itself to see what is going on what are we doing these amazing initiatives that are going to bring us into the future. And, you know, reach out for us. There are the diplomat and residents that are listed and you can find their contact details. We have recruiters right here in DC who'd be more than happy to tell you about all the different opportunities that the State Department provides so good luck in your future endeavors and thank you for having us today. Thank you Patty. One of our other panelists Jeff has been having some technical difficulties. And we're sorry about that. But I know that if he could that he would want to want to probably, as Patty did encourage you to remember that any background, and there's just a number of opportunities that we have here. And when we talk about the impact of data, it's, it's, you know, it, it, it, it impacts all fields and all issues that we work on so it is pretty exciting. One of the, I think I'm just, I think we have to two minutes and I want to see that we had one other question about combating food, food security. And I think on this piece that I know about is that that State Department, often funds research, and the State Department also provides funding to organizations like the World Food Program, our sister agency, the US Agency for Development USAID provides a lot of funding to the World Food Program, for example, but USAID is also working with farmers from Kenya to, to, to, to places in, in Latin America to devise ways or to use technology to better inform crop development, or to understand or to have a better understanding of the weather and using technologies to understand the weather so that you can plan for flooding issues for example so that's just one very quick way that that technology is being used to combat food security or to address food security. So, folks, I want to say on behalf of the State Department, on behalf of this panel, and all of my colleagues, we want to thank you for joining me we want to thank you for considering the State Department whether or not it's for an internship or whether or not you think that dedicating your professional career to service is right for you I would say it's never a dull moment. And you can join as a Foreign Service Officer, as a civil service officer we welcome everyone and I would say be encouraged that data is interesting, and it is needed and so we need you. And so we hope that you take advantage of the opportunities. And we hope that you consider the Foreign Service and with that, good luck with the rest of the day, and of the Foreign Policy Conference, and hopefully we look forward to meeting some of you guys in person sometime soon. Thanks so much. Bye bye.


I'm glad to see that everybody made it to class, I'm sorry about all the confusion but I'm glad that we're all here and we have a big class today, that's awesome. I guess there's no rain, but there's quits. I do want to make a couple of announcements. I had some of my online students and I really tried to work with them a lot but they asked me if we could push the L2 back one day. So it was due tonight, so September 10th at 11.55. I'm going to now make it due tomorrow night, okay, so that'd be September 11th, Saturday September 11th at 11.55, okay, so it'll be due tomorrow night. I added up there for quite some time but it was due on Monday, of course, we haven't done any of Chapter 3 yet, we're going to do a little bit today, but of course we won't have it all finished by Monday, so the test is going to be the test for the in-class people, the 14-06-01, all of you guys that are watching right now. That test is going to be held Friday, okay, the online test of course is being held Wednesday and Thursday, but what we'll do is make the HAL 3 homework due the same day as the test, okay, or actually day after the test. We'll make it due next Saturday and I believe that's Saturday the 18th, okay, yeah, so that'd be the 18th. So if there's any questions, let me know after class but the test will be next Friday and that'll be over Chapters 1, 2, and 3, okay, and the HAL homework that was due tonight is now due tomorrow night and the HAL homework that was due on Monday is now due next Saturday the 18th, okay.  Okay, so that being said, I'd like to do a 20, a small 20-minute lecture right now before I give the quiz, you know, we can start on some of Chapter 3 stuff so you guys can get some information so you can start doing Chapter 3 homework, okay. Over the weekend, that means that you have a long weekend. So anyways, Chapter 3, electronic structure and periodic law. So essentially we're going to be talking about the periodic table and why it's set up in the way that it's set up. Okay, so there's this guy, this is a painting of this guy. Obviously it's not a picture of him, he looks quite different, a little less austere in his pictures, but in that painting he looks quite grandiose or whatever, but this guy's name is Dmitri Mendeleev. He developed the modern periodic table, so this thing that you see over here. He introduced the concept that properties of the elements are periodic functions of their atomic weights, so what does that mean, periodic functions? That means that whenever you see an atomic or an atom that is actually placed in the periodic table, what you can see is that they're placed in like columns here and all of those columns within one of those columns. So if we look at these guys here, nitrogen, phosphorus, acetane and so on, we see that all of these have similar chemical properties. So in other words, it's periodic function, so every time you go to that column, they have similar chemical properties. So we call those columns families and we'll get into that in a little bit. So in reality, the properties of the elements are actually functions of their atomic numbers. So the atomic numbers, what you see here for hydrogen is 1, so the number that's in the top right corner there, 2 for oxygen is 8, sulfur is 16. These atomic numbers describe how many protons are actually located in the nucleus. This is an expanded version of the periodic table, taking the F block, which is down here, and inserting it in the place in the periodic table where it should be, which is right after 57 and 89. And again, respect to the chemical properties. So let's talk about the elements of the periodic table, the atomic number. So let's look at carbon. Carbon is atomic number 6. Remember, the atomic number describes the number of protons in the nucleus. The symbol for carbon is C, so right there. The name, of course, all elements have a name, all elements have a symbol, all elements have a number of protons in their nucleus. And the atomic mass of carbon is, actually this should say AMU after it, because the units for atomic mass are AMU. Sometimes you'll see U. I can't remember what our book does if it's U or AMU. Does it do AMU? Yeah, I prefer AMU. I really should have put some units after that. But anyways, the atomic mass here is found on the periodic table up here, usually below the symbol of the element. And that describes what is the average mass of any carbon atom that you'll find. So again, how I implied before these columns here are known as families or groups. And they have similar properties. This is showing a picture of the different halogens. In fact, this is chlorine here. This picture here is describing bromine, and this picture here is describing iodine. Notice that they're all diatomic elements. So if you can see the picture, each one of these has composed of two atoms stuck together. And when they increase in mass, we go from gas to partial liquid to more of a salt. But the properties of these elements are very, very similar to each other. In fact, their reactive nature is what you really want to think of as being the most similar. Here's another family of elements. Magnesium here, calcium and strontium. Notice they're the nature of the way that they're... And this metal C that we will eventually describe. But notice the kind of shape and chemical or physical properties of them being similar. Those are all the 2A elements there. Again, they have similar chemical properties. So some of the common family names that I'd like you to know are group 1A. This group here, this is the alkaline metals. Group 2A is the alkaline earth metals. I want you to know these because when I say alkaline metals, I want you to know what group I'm talking about. And then group 8 or group 18 over here, group 8A or group 18. We call these the noble gases. Their name implies, I guess, nobility. This is because of their place in the periodic table and their actual electronic structure. This electronic structure that they have actually gives them a very, very stable structure, atomic structure. So in fact that they don't react with any other elements. Which is why they have the moniker who will know. So that's why you call them noble because they're always turning their nose up at all the other elements. And then we've got a group of very reactive elements called the halogens here. That's the halogens. And again, they all have similar properties. If you've ever heard of halogens, headbites, or whatever, this is where that turns. So we describe the groups and families here. But there's another periodic function to this table here. And that's the periods themselves. So we call the horizontal line here a period. So if you see we've got period 1 contains these two elements. Hydrogen and helium. Period 2 contains these eight elements. Period 3 contains these eight elements. Period 4 contains these 18. 5, 18. And then 6 you have to include these at block 2. So it gets more and more and more as you go down. There's regions of this periodic table that aren't really described on this one that we have here. This big version of it. But if you look at the slide, you can kind of see there's a difference in color in the different regions of the periodic table. Notice this purple region covers most of the periodic table. So that's almost all the elements. Those are the melds. Anything that's purple in there is a meld. So this is an element that is relatively shiny and malleable. Malleable is if I take a hammer, I can pound it into a sheet. So that's what malleable means. And they conduct both heat and electricity. Some of the metals obviously conduct that stuff better than other metals.  Well, they just got put on last week. And I was trying to eat with silverware. And it does me every time. So now I eat with plastic forks and mess. Okay. So those are all metals. They conduct electricity, conduct heat, all that good fun stuff. Notice the other two regions of the periodic table are very, very small compared to that big metal region. Okay. The next region I would like to describe is the non-metals. This is shown in green here. Those are elements that lack metallic properties. So kind of opposite properties of the metals. So where we're going to learn about covalent and ionic bonding and that sort of business, the metals all participate in ionic bonding. There's very few exceptions where you'll find them participating in covalent bonding. Every once in a while you will. And those are usually the smaller metals up here. But for a general rule of thumb, anything you're going to see in this class, ionic bonding for metals. Okay. Non-metals, on the other hand, can participate in both ionic and covalent bonding. And it all depends on what they're bonding with. If a non-metal bonds with a non-metal, then it will participate in covalent bonding. If a non-metal binds with a metal, it will participate in ionic bonding. And the difference between ionic and covalent bonding, ionic is the transfer of electrons from one element to another. And covalent is the sharing of electrons from one element to another. We'll really get into this, into the meat of this later next week, probably on Monday. Okay, so if you don't understand, it's no big deal. Okay. But anyways, let's look at a couple more regions. The yellow here, these are the metalloids. Okay, so those are elements that have properties in between a metal and a non-metal. And then the transition metals. So these metals over here, these metals in this region here, those are called the main group metals. Okay, these metals here in this little block here, or big block I guess, those are called the transition metals. Yeah. And they have inherently different ionic bonding capabilities and properties. Okay, so that's why we kind of separate our thinking about it. And again, we'll get into more of that way. Okay, so let's try to identify the group and period of some elements. So if we look at calcium, which is C-A, oh, and I'm never going to make you memorize the names or symbols of an element. I'll always give you the periodic tables that you guys see in front of you right now that have those names and symbols. So if you don't have one yet, there should be a pack of them coming around. And you can do it. I don't think you'll need it for quiz more. Okay, if you do, I'll tell you what it is. Okay, anyways, so let's identify the group and period of calcium. So calcium is C-A, so we've got to look for it on the periodic table. Okay, there it is. So we know its atomic number, remember its atomic number is shown in the top right corner there, that's 20. The atomic number describes what? What does it describe again? The number of protons and the nucleus, okay? And a neutral atom, so any of these atoms that you see on the periodic table here has a neutral atom. Those numbers also describe the amount of electrons that atom has, right? Okay, so here calcium's got 20 electrons, 20 protons. And notice it's in the group 2A, or we call these the alkaline earth metals. And notice it's in period 4, okay? So hopefully you guys can describe that. Cool. Okay, so let's start talking about the electron configuration. So I know we went over all of that protons, neutrons, and electrons in chapter 2. So let's talk about, if we can get on that slide. Okay, electron configuration. So electron configuration is the arrangement of these electrons in atomic orbitals. So remember we describe the electrons as being circling around the nucleus, okay? So this is a kind of, not really accurate picture of what an atom looks like, but that we can kind of start to describe it. And then we'll expand our knowledge of what it looks like later when we understand more about it. So the electron configuration is the arrangement of electrons in the atomic orbitals. So there's this guy called Bohr. His model talked about circling electrons around the nucleus in atomic orbitals. Okay, so you can think about it like this. We'll hear a higher energy orbital there, higher energy orbital there, and a higher energy orbital there, okay? The higher that the energy of the orbital would be, the further the orbital is away from the nucleus. Of course, the electrons are negatively charged. The nucleus is positively charged, so they really want to be closer together. So the further away they are, the higher in energy you can think they are. The more smack they could have if they were going to hit each other. So these electrons could be raised or lowered in energy level due to energy absorbed or released. So if I pumped a bunch of energy into this atom, I could make the electrons jump up and down into these different energy levels. Okay, so this model was revised in 1929. So, well, almost 100 years ago now. And 1926, sorry. And instead of circular orbitals, the location and energy of the electrons moving around the nucleus is now defined by using three specific terms. The shell, the sub-shell, and the atomic orbitals. Okay, so this whole thing would be a shell, okay? So the location of all of these different regions, okay, all of these different electrons here. So you see, you got the shell is the big thing. The sub-shell is this 4F or 4D or 4P or 4S. The orbital, let's see, the 4P has three orbitals in it. And an electron would be one of these dots, okay? So this is just a picture of building up electron configurations, okay? So let's just, we'll do a couple of these and just stop at this slide and get ready for the quiz. But let's build up the electron configurations of the first five elements, for example, okay? So the way I would really like to draw this picture is to put an arrow pointing up and that describes the change in energy, okay? So we're going to try to draw the picture of hydrogen. Hydrogen only has one electron, okay? And its electron is in the electron shell that is the first period up there. This shell is actually the S shell. And in fact, its sub-shell is going to be the 1S. There's only one sub-shell in the S level. So you can describe it as a box like that. So I guess we should say that the sub-shells are S, then it goes to P, which is greater than an energy than S. Then it goes to D, then it goes to F, okay? And if we look here, these are all the S sub-shells in these first two groups here. Okay, then it jumps over to here. These are the P sub-shells here. And then the D sub-shells is in the middle here, the transition metals, and then the F sub-shells. We'll really be only concentrating on the S and the P's in this class, okay? And again, you may think this is all crazy right now. You don't understand anything, but by the weekend this over, you'll figure it out, I promise you. Okay? So the way to build up these electrons is to show each one of these atoms gaining one more electron each time, right? So put one electron in there to describe hydrogen. So hydrogen, if we look at the periodic table, has one proton and one electron, so we only want to put one little line. An electron is usually described by what we call a fish hook arrow, a half-sided arrow, okay? So if we're going to describe the electron configuration of helium, helium has two electrons in it, so what we'll do is put another fish hook arrow like that, okay? When the electrons are in the same orbital, remember every one of these boxes is in orbital, okay? So the whole thing here is the shell. The 1S, that's the sub-shell, is the orbital, and these lines here describe the electron. So that's helium. And what you'll notice is that only two electrons can occupy an orbital at once, okay? Okay, so the first two atoms have electrons that occupy the same orbital, okay? Let's stop there. I know this probably, we're just starting it, so it might be a little confusing.  And I promise you you will have no problem with it. Yeah, so the left side over there is S. S, P, E, S. Yeah, so what'll happen, look, what'll happen here? Think you'll fill up your electrons going one, two. It just goes by the periodic nature of these electrons. Okay.