Live from Santa Clara, California, it's theCUBE, covering Open Networking Summit 2017. Brought to you by the Linux Foundation. Welcome back. We are live in Santa Clara at the Open Networking Summit 2017, I've been coming here for a couple of years. It's a lot of open source going on and storage for a long time, a lot of open source going on and compute for a long time and networking was kind of the last one that we had Martin Casado on. Earlier today, he said it was 10 years since he started Nacera and now it's a billion dollar revenue run rate inside of VMware. So I think the software to find networking is pretty real. We're excited to this next segment. Scott Rainovich been co-hosting all day. Good to see you again, Scott. We're kind of shifting. We're going to add to Open Networking. We're going to add to Open, not compute, but Open Stack. Can I get them all mixed up? We were just open compute projects a little while ago. So infrastructure is all in family. All right, so our next guest here representing the Open Stack Foundation is Eduko Vanksa. Get that right. She is the ecosystem technical lead for Open Stack. Welcome. And Lisa Brinanti, you've seen many times. She's now officially the Open Stack ambassador, which if you follow her on Twitter, you would have known that a long time ago. For the US. For the US, excuse me. There's several others globally, but for the US, yeah. So first off, welcome. Thank you. And what is the Open Stack team doing here at Open Networking Summit? So Open Stack itself is a multi-purpose generic cloud platform. So we are not just looking into enterprise IT use cases, but also trying to address the telecom and NFV space. And this is the conference where we are finding many of our ecosystem member companies represented. And we are also learning what's new in the networking space. What are the challenges of tomorrow and how we can start to address them today. Right. Because the telco is a very active space for Open Stack as well, correct? That's been a good market segment for you. Yes, it is an emerging area. I would say we have more and more telecommunications company around, and they are also more and more involved in open source. Because I think it's kind of clear that they are also using open source for a while now, but using open source and participating in open source, those are two different things. So this kind of mindset change and transition towards participating in these communities and going out to the public field and do software development there and collaborate with each other and the enterprise IT segment as well. This is what is happening today and it is really great to see it. Right, right. And you've seen more and more telcos participating in the Open Stack summits. There was an NV day, I think, even going all the way back to the Atlanta summit and certainly in Barthelona, Ildiko was actually doing one of the main stage keynotes, which was very focused on telco and some of the main sponsors of this upcoming summit are telcos. So there's definitely a nice synergy between telco and Open Stack. Now why do you think the telco is just the one that's kind of getting ahead of the curve in terms of the adoption? Scalable, low-class clouds? I was going to cut it. Right, and we had John Donovan from AT&T said today that they're either rapidly approaching or going to hit very soon more than 50% of software defined networking within the AT&T network. So if there's any questions as to whether it's real or still in POCs, I think that pretty much says it's in production and running. We found, I'm doing a lot more of the, to also run the Open Stack user group to the San Francisco Bay Area and have them for the last three years. And if we're not talking about Kubernetes or Docker and Open Stack, we're talking about networking. And tonight actually we're going to, the Open Control team is talking about some of the stuff they're doing with Open Control and containers and sort of just to piggyback off of this conference. And next week as well, we're talking about the network functionality in Kubernetes at Open Stack, if you want to run it on an Open Stack Cloud. So it's a huge focus and the user group can't get enough of it. And your guy's show is coming up very, very soon. The Open Stack Summit. Yes. Oh, absolutely. May 8th through 11th in Boston. Like right around the corner. Yeah. The incredible moving show, right? It keeps going and going and going. Yeah, yeah. There's going to be 6,000 plus people there. There was just some recent press releases about some of the keynotes that are happening there. There's a huge focus on, I keep calling this the year of the user, the year of Open Stack adoption. And we're really, throughout the meetups, we're really doing a lot to try to showcase those use cases. So Google will be one that's on stage talking about some really cool stuff they're doing with Open Stack, some machine learning, just really intelligent stuff they're working on. And that's going to be a great keynote that we're looking forward to. Harvard will be up on there. And not just big name foundation members, but a lot of use cases that you'll see presented. So why do you think this is the year? What's kind of the breakthrough that it is the year of the user, would you say? Well, I think that just the reliability of Open Stack, I think enterprises are getting more comfortable. There are very large clouds running on Open Stack, more in Asia and in Europe. And I don't think we can probably talk about it, particularly some of the telco related ones. But the adoption is there and you see more stability around there, more integration with other, I don't know we call them emerging technologies, the light containers, like AI, like IoT. So there's a big push there, but I think enterprises have just, they have adopted it. And there's more expertise out there. We've focused a lot on the administrators. There's the COA, the certified administrator, Open Stack administrator exam you can take. So the operators have come a long way and they're really helping the customers out there get Open Stack Clouds up and running. So I just think it's seven years now into it, right? So we kind of turn the corner. So there have been some growing pains with Open Stack. So what can you tell us about the metrics today versus say three or four years ago in terms of total installations, maybe breakdown of telecom versus enterprise? What kind of metrics do you have there? I'll let you take that one. We are continuously running a user survey and we are seeing growing numbers in the telecom area. I'm not prepared with the numbers from the top of my head, but we are definitely seeing more and more adoption in the telecom space, like how you mentioned AT&T. They are one of the largest telecom operators on board in the community. And they are also very active showing a pretty great example of how to adopt the software and how to participate in the community to make the software more and more NFV ready and ready for the telecom use cases. We also have, as Lisa Maria just mentioned, the China area and Asia are coming up as well. Like we have China Mobile and China Telecom on board as well or Huawei. So we have telecom operators and telecom vendors as well around the community. And we're also collaborating with other communities. So like who you see around OP NFV, Open Daylight and so forth, we are collaborating with them to see how we can integrate OpenStack into a larger environment as part of the full NFV stack. If you look into the Etsy NFV architectural framework, OpenStack is on the infrastructure layer. The NFV infrastructure and virtual infrastructure manager components are covered with OpenStack services mostly. So you also need to look into that how you can run on top of the hardware that the telecom industry is expecting in a data center and how to onboard the virtual network functions on top of that, how to put the management and orchestration components on top of OpenStack and how the integration works out. So we are collaborating with these communities and what is really exciting about the upcoming summit is that we are transforming the event a little bit. So this time it will not be purely OpenStack focused but it will be more like an open infrastructure event. We are running Open Source Days. So we will have representation from the communities I mentioned and we will also have Kubernetes on board, for example, to show how we are collaborating with the representatives of the container technologies. We will also have Cloud Foundry and a few more communities around. So it will be a pretty interesting event and we are just trying to show the big picture that how OpenStack and all these other components of this large ecosystem are operating together. That is going to be a super cool part of the summit. Summit is May 8th through 11th and on May 9th, the CNCF, the Linux Foundation actually behind this, the CNCF Day, they're calling it Kubernetes Day and the whole day will be dedicated, there will be a whole track dedicated to Kubernetes, basically, and so they did another call for papers and it's like a little mini-conference inside the conference. So that's kind of what's saying about the adoption and of other technologies. I'm sure the OpenStack Foundation is putting those numbers together that you asked about and probably Jonathan and Bryce will stand on stage on the first day and talk about them. But what I think is more interesting and where I would encourage people to go, there's a Super User Magazine. Super User does a great job telling the stories of what's happening out there and some of these use cases and who's adopting this technology and what they're doing with it. And those stories are more interesting than just the numbers because you can do anything with numbers and statistics, but these actual user stories are really cool. So I encourage readers to go out to Super User Magazine and check that out. So like, Lego uses it. Yeah. There you go. I had to check real fast. They do a good job with it. Yeah, yeah, yeah. Lego Alligator. So you talked about this day with the Lynx Foundation, is there increasing amounts of cooperation between OpenStack and the Lynx Foundation, given all the projects that seem to be blossoming? Yeah, I don't even know that it needed to increase. There's always been nice synergy between the two and so we know very well was on the board of both. The first woman on both boards, she was my colleague for many years at Hila Packard. She's still on the Lynx Foundation board and there's been a lot of synergy between those foundations. They've always worked closely together and especially things like the Cloud Foundry Foundation that came out of the Lynx Foundation has always worked very closely with OpenStack, the OpenStack Foundation and the board members and it's all one big happy family. We're all open source. Yeah. You talked about the enterprises being, they've been using open source for a long time, right? Lynx has been around forever. They're really more adopting kind of an open source ethos in terms of their own contribution to the society, contributions back and participating back in. So you see just increased adoption really of using the open source vehicle as a way to do better innovation, better product development and to get involved, feedback, give back to their engineers to get involved in something beyond just their day job. It is definitely a tendency that is happening. So it's not just AT&T like I can mention, for example, NTT Dokomo who now has engineers working on OpenStack code. They are a large operator in Japan and it is really not something I think that a few years back they would have imagined that they will just participate in an open source community. I've been involved with OP NFV for I think two years now or two and a half. I'm an OP NFV ambassador as well. I'm trying to focus on the cross community collaboration. And the OP NFV is an environment where you can find many telecom operators and vendors. And it was a really interesting journey to see them that how they get to know open source more and more and how they learned how this is working and how working in public is like and what the benefits are. And I remember when a few people from, for example, Dokomo came to OP NFV and they were like a little bit more shy just exploring what's happening. And then like a half year later when they started to do OpenStack contributions, they had code patches merged into OpenStack. They added new functionalities. They kind of became advocates of open source. And they were like telling everywhere that open source is the way to go and this is what everyone should be doing and why it is so great to collaborate with other operators out in the public so you can address the common pain points together rather than everyone is working on it behind closed doors and trying to invent the same deal at the same time separately. So that was a really, really interesting journey and I think more and more companies are following this example and not just coming and giving feedback but also more and more participating and doing coding documentation work in the community. And maybe if I can understand what I think also the question you might have been asking, that there wasn't a ton of Python developers in the beginning and it was really, and everybody's like, how can we get these OpenStack developers in the company and it was a huge shortage and the Linux was a little hanging fruit. It's like, why don't we just hire some Linux developers and then need some Python and that's how a lot of OpenStack knowledge came into companies. So that was the trend and I think enough companies, enough enterprises do see the value of something like OpenStack or Linux or Kubernetes or whatever the project has docker to actually dedicate enough full-time employees to be doing just that for as long as it makes sense and then maybe it's another technology but we saw that for years with OpenStack, huge companies and there still are. Not always the same companies but depending on what a company needs and where they are they absolutely find value in contributing back to this community. Okay and you said you got a meetup tonight? I do, yeah. Give a plug for the meetup. Juniper, it's OpenContrail and we're talking about OpenContrail and containers and it's at Juniper here in Sunnyvale so if you go to meetup.com slash OpenStack, that's our user group. We're the first ones so we got that one. The meetup.com slash OpenStack is the Silicon Valley, San Francisco Bay Area user group and then next week we're at Fam, we're talking about networking and Kubernetes. It's always good to be above the fold, that's for sure. All right, to Deco, Lisa Marie, great to see you again and thanks for stopping by and we'll see you in Boston. It's not before. Absolutely, we'll both be quite busy. We have both four presentations each. It's going to be a nutty week so I'm looking forward to seeing you guys in Boston. Always a pleasure. Thanks for inviting us. Absolutely, all right. Thanks for stopping by. Thank you. With Scott Rainovich, I'm Jeff Rick. You're watching theCUBE from Open Networking Summit 2017. We'll be back after this short break. Thanks for watching.


To this talk on chaos zone TV this talk the rise and fall of social bot research Will be presented from for Florian Galvitz No, my for the deutschen zu shower and höher dieser talk wird übersetzt schaut nach der Übersetzung Ich werde nun zurück nach Englisch wechseln. I will switch back to English now This is a talk presented by Florian Galvitz from the Nuremberg Institute of Technology and he will talk about social bots in Recent years we have all observed the phenomenon of social bots Accompanying different media events and also the media had like waves also showing those social bots Activities in the social media Four years ago already michael found significant shortcomings in the research on social bots and Florian will now deeper show us why the current research is Floored or even deeply thought in this specific field So have a lot of fun in the talk the rise and fall of social bot research Thank you very much for the introduction. So unless you've been living under Rock somewhere in the desert. You've seen Headlines like these are just randomly selected a couple of headlines through Google news. So we have been told that Bots on Twitter are amplifying conspiracy Theories or they are spreading Disinformation before the election or they even half of the accounts tweeting about the corona virus are likely bots and bots are a major source of climate disinformation and they There are hundreds of thousands of them and they even interfere in Canadian politics and in British Politics and Donald Trump has millions of bots supporting him and They are a danger to democracy and they are poisoning Democracy and they are damaging democracy They supported Boris Johnson and they are spreading fake false claims about the bushfires in Australia and they even trying to influence Elections in Germany, maybe so this is You will find hundreds of Headlines like these if you just search for the keyword bots in Google news I'm there behind a lot of many of these headlines. There is some academic Research, most famously the paper by Ferrara and colleagues called the rise of social bots which inspired the title of this talk and Well, they the research that papers that Claim to Prove some influence of social bots on the US presidential elections and the spread of fake news by social bots And this is a paper one of many papers by Philip Howard who claimed that bots had interfered into the Brexit referendum But there are many other issues that are allegedly Influenced by social bots. So for example and health communication vaccine the vaccine discussion. This is a paper from 2018 so before the COVID pandemic and This is a more recent paper Both claim that bots are interfering the discourse about vaccines but they're also interfering the discourse about climate and generally Any low credibility content on Twitter is allegedly Spread by social bots. So by the end of this talk, you will Hopefully learn that the low credibility content is actually inside these papers So what's the social bot? If we look at one of many slightly different Definitions, this is one by Ferrara. So he's the one who basically Created the social bot hype. So we have to believe him So if we listen to him me social bots are automated accounts that use artificial intelligence to steer discussions and Promote specific ideas of products on social media such such as Twitter and Facebook The typical social media users browsing the feeds social bots may go unnoticed as they are Designed to resemble the appearance of human users and they behave online in a manner similar to humans So that's a pretty clear definition of what social bots are supposed to be if Basically, if you look at all definitions of social bots in academic papers This is a pretty precise picture of what the general consensus on social bots is So typically they are assumed to be political accounts influencing political discussions and they have to be automated and They are accounts with human fake profiles pretending to be humans and somehow behaving in a human fashion So obviously at the intersection between political accounts and fake accounts You would find human paid trolls for example, so people who are paid to To take part in political discussions. Also, you can easily find automated Political accounts. So for example, the Fox News feed is political and it's somehow automated. So automatically newly published Articles on the website for example Get tweeted on Twitter. So there's some kind of automation. So this would be automated political accounts. And of course, they're also Or you can at least suspect that a lot of automated accounts With fake human profiles are used with porn or crypto scam So basically to scam individual users on Twitter, but social bots they combine these three properties That's generally the idea of social bots and social bots are At least attributed with a with a They're there somehow People believe that they are able to produce content on their own. So they're come somehow autonomous and the very often the Words artificial intelligence are mentioned in context with social bots So if Twitter is counted with Crowded with social bots where the hell is one? That's the my starting point for my interest in social bots So I felt kind of gaslighted So media is telling me that there are millions of social bots on Twitter And I've spent almost a decade on Twitter and I've never seen this social bot So that's the point where that got me interested I have a background in AI In pattern recognition, I've been building conversational dialogue systems for many years which we call chatbot today and I've never really believed the idea that at the current state of the art you could build Political bots that's it could interfere in current political discussions That seemed kind of strange and implausible to me So if they exist, how do these things work? So I wanted to find one to take a look at the social and actual social bots And I an actual social bot and I started to search for an actual social bot in late 2018 so three years ago So since then I've studied dozens of scientific papers media reports about alleged social bots. Basically, I read all newspaper articles, media reports about social bots that Google News could come up with in various different Countries and I've analyzed hundreds of Twitter accounts that have been accused of being social bots For example in newspapers where actual social bot accounts were named And of course, I asked a number of social bot researchers for an example of an actual social bot And I've performed experiments on using the Twitter API Which involved hundreds of thousands of accounts some of these experiments together with Michael Kryl Who was mentioned in the introduction who has been working on this problem One or two years longer than me So the total number of social bots I found until now using all these different approaches is zero So I couldn't find a single social bot that fits the definition of emilio Ferrara So that seems kind of strange. So where does this apparent mismatch come from? In order to understand this, you have to take a look at the methodological basic basis of all these scientific papers And basically it boils down to two different methods. The first method is the so-called Oxford Criterion named after the University of Oxford, Philip Howard, who defined heavy automation as accounts that post at least 50 times a day So basically he counted the the tweeting frequency of different accounts. Everybody who tweeted more than 50 times a day was defined heavily automated and referred to as a bot So that seems kind of strange And the second approach and the more common approach nowadays is An automated tool called a botometer Which is You can use it. There's there's a public website where you can enter a twitter account and press a button And then you get a score somewhere between zero and five or between zero on and one It depending on the scale you use and it basically and and The researchers typically use the api. They feel a long list of Twitter accounts into botometer for each account They receive a bot score and then they use a threshold typically 50 percent So 0.5 on a scale of zero to one And if the bot score is larger than 0.5, then they simply assume it's a bot A similar there are similar tools that basically work in the same manner But botometer is by far the most popular tool of this kind So in both cases no manual checks are performed whether the accounts Identified using these rather crude methods are bots or not And even more interestingly the names or the user IDs of these alleged bots are not published You will won't find any bots in all these dozens of research papers And if you ask the authors of these papers For the actual bots, they are routinely routinely withheld. So they won't give you the data They will give you some flimsy excuses about data Protection laws and privacy or they somehow Accidentally deleted the data or they didn't store the data or whatever So pretty much like if you ask That kind of the dog ate my homework type of excuses Okay, let's take a slightly closer look at the way these Researchers produce headlines. So so that's basically a certain perfect recipe for for Creating a headline in the New York Times. So you Um Decide which political issue you might be interested in really You can come up with any topic. You might be interested in let's say you're interested in gaming So you will you want to Find create a headline about gaming and social bots in the New York Times. So what do you do you? Look for gaming related keywords on twitter And you identify accounts that That tweet about gaming then you Can come up with a long list of of user IDs of twitter accounts That tweet about gaming then you feed them into about a meter use your threshold 0.5 for example, and you Get a list of bots and a list of humans And then the New York Times will publish a headline Researchers nearly half of account tweeting about gaming are bots Okay, so now skeptical people like me Might want to take a look at the actual bots to verify your claims So obviously it's more useful to hide this data But um journals don't seem to be interested in the actual bots They have never questioned the validity validity of these claims even without looking at actual bots So they will believe you and they will publish this in the New York Times So um the first Criterion That's used for this type of papers is the oxford criterion. So the 50 tweets per day criterion. It's pretty easy to to Show that it's not very useful. So you find very Large twitter accounts celebrities who tweet more than 50 tweets per day like journalist gren Glenn Greenwald or Corey doctoro Was a blogger and author with a very large following Or you on his cars for example a german member of parliament who tweeted up to 300 tweets per day Donald trump himself tweeted more than 50 tweets per day on six days in 2020 and so um all right at least in a very short period of time in 2020 so I'm political activists who have more time than presidents or members of parliament obviously tweet a lot more My favorite account on twitter is actually a guy called erie glucksack. He's a canadian engineer and retired college instructor he has Been tweeting at rights above 300 tweets per day over a period of several months And he's always ranting about liberals in canada and he he hates just in trudeau um another interesting experiment i performed with with uh Was about the k-pop band bts extremely popular and um a german radio reporter made some derogatory remarks about the bands and the the k-pop band the the bts fans were extremely angry about this and um They created more than three million tweets in a period of four days with the hashtag buy-on-three racist buy-on-three is the the um radio program involved and they um So 500 of those accounts 500 different accounts each of them fulfilled the oxford criterion and um the maximum was 344 tweets on average per day and I looked at the top ranking accounts in this list and none of them showed any signs of automation that there were real people they were They were tweeting pictures of themselves and they Everything was consistent. They're coming from different countries. So those are real people not bots um another easy way of Uh, the second criterion was criterion that's often used for the bot search is the bottom meter Bottom you can try it. Uh, the the link is given at the bottom of the page And you can simply enter the name of a twitter account and the bottom meter will return a score So for example, um, so those are all bots according to bottom meter. So for example tim cook is a bot The pope is a bot. Uh, the new gem chancellor olav schaltz is a bot former um chess world champion garrick asparov is a bot Auschwitz museum is a bot Joe biden is a bot The brazilian president rio balson arrow is a bot the Very well respected germ virologist christian drosten is a bot but also his counterpart A retiree economist Who is basically who doesn't believe in the corona virus? He he is also a bot. So Basically, if you just randomly enter account names chances are very high that you will run into bots according to bottom meter um a similar Analysis had been performed by um michael kyle in 2018. Um, he fed all the twitter accounts of um members of us congress into bottom meter and um, you can see that basically it's a It behaves like a random number generator with a normal distribution pretty much around the threshold that's usually used for um for discriminating between bots and humans so, um If we want to use the same approach um The the bot the social bot researchers use for identifying But we can find interesting stuff. We could find ufo's or we can find any kind of Of stuff we want to find And I want to show how we could find unicorns. Let's say we want to find you We want to find unicorns in africa. So we would train a kind of phototrap for unicorns and And we want to deploy that in the serengeti to find actual unicorns So for training the unicorn, we have the same problem the social bot researchers have We don't have actual unicorns to train our Our classifier on so we would use Unicorn like Animals like a white horse for example, or we would use toy unicorns as As a training set for unicorns And we would use some other animals like a cow a pig a cat in the dark as non unicorns And then we would would train our classifier on this data and then we would move our trained classifier to africa and then we would Find lots of unicorns. So for example in this case the zebra would get rated would get a 75% Unicorn score because it looks quite similar to this white horse And also this white egret would get a very high unicorn score because it has this pointy Pig and it's white. So it looks a lot very a lot like a unicorn So now if you want to convince people that you actually found Lots of unicorns in africa Some people might want to take a look at your pictures, but obviously that would Be bad for your Claims. So obviously you you would want to hide the actual Unicorns you would find you would simply Rely on the results of your unicorn classifier and people who who Complain you would tell them why we have almost 100% recognition rate In our on our training data. So you believe us That's exactly the way the bottom meter people argue If we take a closer look at how this kind of classifiers work, well, basically Statistical classifications or neural networks or in the case of bottom meter is a it's a Random forest classifier any any of these classifiers basically places each of the Observations in a feature space. So the dimensions might be the the whiteness and the pointiness of the animals and So the unicorns and the non-unicorns They form some kind of cluster in the feature space ideally And the the training the classifier will create a class boundary that Can perfectly discriminated between unicorns and non unicorns on your training data or and very similar data But in reality if you now deploy your classifier To africa or to the real world you would find lots of Unicorns and lots of non unicorns depending on the the class boundary chosen by the Classifier so it would still produce 100% recognition rate on your on your Training data, but it seems far stretched to believe that this is actually a unicorn or this is a unicorn So if you now remove the training data, you see that's basically You get some kind of unicorns non unicorns depending on the class boundary you trained But it seems outright ridiculous to believe that the animals labeled as unicorns will be actual unicorns Or even that the relative amount of the unicorns that result from this approach conserved as an approximation For the true prevalence of unicorns, but that's exactly the way those spot researchers argue So there's another problem if you think that what I told you so far is bad for social bot researchers, it's even worse because Now you I have to Explain you some fundamental ideas of of pattern recognition so in Let's first take a look at the approach So we the the idea people used to come up with claims like 50% or 15% of the accounts are bots They feed the list into the Into the classifier and they come up with five bots and eight non bots for example And now they calculate the relative amounts of bots like 38.5 percent in this case Now they claim that 38.5 percent of the Of the accounts are bots, which is the so-called a priori probability for bots or the prevalence of bots Or the the priori probability And the the fun part now is that this probability Is already part of the decision process that's used by the classifier. So for example, uh, um, uh Random forest classifier like bottom meter will include this probability and will learn this probability based on the training data So, uh, if If the bottom meter people use 50 percent bots and 50 percent non bots to train bottom meter The classifier will have incorporated The information that 50 percent of the accounts are bots and uh, the optimal classifier with the lowest possible recognition rate and this is what the training process is trying to achieve Will always adjust the threshold in a way that it will Will will conform to this equation in order to produce good results on the training data or on similar But this is circular reasoning. So to estimate the number of bots using this approach, you have to know it beforehand So this is it doesn't make sense. It's simply impossible to use a statistical classifier to, uh, to Determine the prevalence of bots or of unicorns or whatever In reality in if with bottom meter Um, uh, there's typically a curve like this. So depending on the threshold you choose You get a percentage of bots that are classified a percentage of bots or a percentage of accounts classified as bots So the standard threshold many people use is 50 percent But if the accounts of bots is the number of bots is too high to be credible The researchers typically choose a higher threshold, which would give you a lower percentage of bots If you want more bots, you can choose a lower threshold if you want to uh, want Few bots you can choose a higher threshold. But so basically the the results the researchers present are based on their guess of what And uh, uh the prevalence of bot might be in this area. So it's can It's uh does not really make sense So far we have falsified the methodology used by social bot researchers using examples Of human accounts fed it into the different method and also we have shown that it can't even work in theory So there's one secret That's remaining. What do the bots look like that these researchers claim to find in the studies? So the accounts they prefer to hide when we ask them for the list of these accounts and we've spent a quite a lot of time trying to get behind This question and to find out what do these actually the accounts look like They might find in their studies So the first study we took a closer look at Was about the german election in 2017. Um, the authors claim that The share of social bots among the followers of seven german parties increased to from seven to point one percent to nine point one nine percent during the election campaigns So basically they they claim that roughly ten percent of 38 000 accounts following the largest german parties were social bots. So more than 80 000 accounts Following german parties are social bots. That's interesting. So I asked the first author for examples of actual social bots and He gave me four accounts which didn't remotely look like social bots So that seemed kind of strange and he also seemed to be fully aware that there are no social bots in his sample So, um, we try to replicate this study A couple of months later. So we basically we downloaded all the followers of german parties We fed them to through about a meter. We used the same threshold These authors had used and we for the first time we had a look at the actual bots that show up in this type of study So now we can't look at we found 260 000 bots We took a random sample from these in this case 109 accounts. I spent a lot of time looking at those accounts very carefully Those are they are ranked by the bots because so this is close to the basically the maximum value a bottom meter can produce and Um, those are all the accounts you can check them if you want if you believe any of those are bots We couldn't find any bots So for example a dense cafe in air forward this guy Or we found a forest in southern bavaria or this guy complaining about the noise produced by motorbikes in gels and kechen and It took me a quick google search and I could find out exactly at this day There was a motorcycle event in gels and kechen at the at the amphitheater in gels and kechen So they those are real people with real ears Complaining about real noise. Many of these accounts are very inactive. So basically the opposite of what what social bot researchers make you believe About the about the properties of social bots. So we couldn't find a single social bot in this list. So some more of these accounts So for example Probably kaira miller probably she asked microsoft for for help and the The one that only tweets tweet she all she produced with this account and it resulted in a Bot score close to five like four point five six four so close to the maximum awesome a blogger a doctor a politician Former regional chairman of the political party d linky. She got a bot score of four point four in a scale of zero point five no bots the second study we looked at closely claimed that they they found Very large in a number of social bots in Vexy spreading vaccine critical information kind of 200,000 social bots and I asked adam done the first author for the list of the For bots of his bots and he actually gave me the list of that for a very first time We had the precise list that was used to produce this kind of paper and also again We sampled A random sample of 121 in this case of the 200,000 bots and I took a very close look at these 121 accounts and we could not find a single social bots and those are just nine of the 120 accounts. I analyzed You can see those are the doctors. This is a very high-ranking A doctor at the world health organization A medical student from rando A professor from texas He's a Working at a medical technology company in Nigeria Medical intern From saudi arabia A health professional from california. I think a postdoctoral researcher and And on rna viruses data Operator it professional from india so People from across the the world many tweeting under the real name many with impressive professional credentials and they simply These social bot researchers simply claim those are all bots. So this seems kind of strange Uh, so if we take a closer look at this list of 121 one accounts a lot, you can Check the accounts. They are all in our paper. So for example the world association for medical law was rated a bot or this pastor from Boston was rated a bot but None of them seem remotely automated This is one of my favorites tail or timothy Tweets by a girl called taylor who is seriously in love with a guy called timothy musk with whom she is engaged So those are two of her tweets and the bot score is 4.39 for close to maximum or this low Laura james She even tweeted pictures lots of pictures of herself. She tweets a lot about unicef. She was really rated a bot Okay, so In this year two other papers came out two other interesting papers Okay, okay Okay Okay, so there were some problems with the slides, but seems the problems seem to be solved. So the um, the uh in 2021 two papers were published where Researchers use bottom meter and they actually checked The list of Bots they they got very much similar to what we actually did and in this obviously in this in this paper They took a very close look at 500 Accounts and they fed them into bottom meter and they also manually checked them if they could be automated Or if they looked automated and it turned out that bottom meter labeled roughly six percent of the uses as social bots But none of them account looked like a remotely automated. So they simply ignored the bottom meter labels as rubbish And another paper very similar It was just the preprint was published a few weeks ago And they also use bottom meter. They used their standard threshold of 0.5 and So 86 accounts were labeled Bots, but actually none of these was a social bot Only one of them was automated. It's automatically shared article from an external personal blog So that that doesn't make it a social bot is it might have been automated So we ignore the people basically turned out that the bottom meter scores are Absolutely unreliable and have nothing to do with reality So now we've seen so basically we can ignore the existing social bot research based on on the oxfuck criteria Or and we can ignore the research based on Bottom meter, but there are some other methods being used Where people claim to find social bots So this is a headline from the times of london army of twitter bots follow top politicians such as niggler distortion and a few others and when you ask the There's no The the people how do you how do you know it's bots? And that is actually this guy He he Sorry, okay, still some problems with Problems with the slide stream, but hopefully I think I won't change anything now. Okay, so the This guy explained on twitter how it worked We downloaded the latest 1k followers of seven politicians and checked numbers of users with exactly eight digits in usernames So these guys assume that bots are Usernames with eight digits like mic 2648 1564 So they assume that the bot many people believe this but it's actually complete bullshit because Names like these are automatically assigned to newly created accounts by twitter at least since 2017 So you can if you just create a new account With a common name you will automatically get assigned a name with these age Digits attached So if you're familiar with twitter you would you have a possibility to change the name of your twitter account But most people aren't aware of this feature. So they simply They look like bots for the rest of their days on twitter What about accounts posting the same stuff very often claims are made about bots With screenshot like the one on like like this So different accounts posting more or less the same message and typically those are so-called copy pastas and where people ironically Make fun of some Or a tweet they don't like by posting it over and over again. Sometimes they They post it Over and over again unironically or different accounts post the same message. It's pretty hard to Understand if you're not familiar with the meme meme Culture on twitter this guy for example, all these accounts Are on the same side of the discussion But he doesn't get the joke. So he he believes those are bots Actually, those are his friends in this in this political issue And and then you find reports like the one that's a year published yearly by the computational propaganda research project in the oxford internet Institute and they give you colorful lists of countries where bots had been identified in the year and obviously the The the whole list if you look take a close look is not based on actual bots But it's based on news reports about actual bots. So that's a kind of In a process that will continue to go on forever because Newspapers will report about this report and the reports about the report will be Will lead to further bot bots in or bot Claims in the newspaper. So Uh, the best uh, there's a very nice claim by a germ journalist in a very different context That describes what's going on If I found an institute to combat public health hazards caused by hedgehog bites And provide this institute with staff positions Then I will get a study every year warning about the growing dangers posed by aggressive hedgehogs Anything else would be rather stupid on the part of the institute's stuff So that's pretty much describes what's going on with all these Research institutes involved in Investigating social bots So to conclude social bot research is fundamentally based on the misclassification of human users as social bots A malicious interactive social bots don't seem to exist at all After years of studying the output of social bot research We have yet to see a single credible example of a social bot And somehow the research is involved in this type of research by all its basic academic Standards, though they make claims that are not supported by data and they withhold data Which would allow us to verify their claims And the public has been misled over the non-issue of social bots for years So um michael cryland me we Published all we wrote all this down in paper The name is the rise and fall of social bot research You can download it at the link on the slide and you It has all the lists of bots in the appendix so you can take a closer look and Try to find social bots if you uh in those lists if you if you like. Um, thank you very much for your attention well, thanks so much flurian and um Yeah for your talk and it seems to me that indeed the field of social bot research is in a very problematic state To me it also seems just for the sake of realistic thinking and discussion The work you do and michael cryl is doing is really important for all of us So we and maybe you or all the scientists need to provide a clear base for discussion And media coverage such that those topics are actually kind of um talked about reasonably So we collected some questions from our audience And um, maybe I'll go through these questions one by one. The first one would be Um, yes, you talked about those social bots and like what is a bot and what is not a bot? But um, shouldn't the question rather be about the effect of such accounts Rather than whether they are click workers people which too much time in their hands paid influencers or automated accounts so saying being a bot or being Acting in kind of those political ways or acting like a bot. Isn't that actually the same or like the effect Is important would you agree with that? Well, it's um We are not the ones who made the claims that these automated bots exist So first of all before we talk about the Effects of stuff we would have to first have to talk and do they exist at all? There are many both social bot research can take but can let's talk about the effects not about the existence Because but first of all we have to read out this belief which I think it's a it's a it's a conspiracy theory It's a fairytale.   So, um First of all Michael and me we're trying to get uh to make uh get Make let people have a realistic view of what's actually going on on twitter Now the the question whether accounts are maybe paid by Some malicious actors To influence discussion is a very different question So we we have been looking at automation. I'm I'm a computer scientist and uh, so my my, um, I'm not, um The right person to me to analyze the motivations why people might be Tweeting on twitter a lot but my Impression is that the very active accounts on twitter like the uh, the canadian account I mentioned in the talk Erie Gluck, I don't believe he's a paid actor He's he's a retired professor and he uh engineer he He has a lot of money He he's certainly not paid for being a political very active on twitter He he is acting out of intrinsic motivation same holds for all these 500 accounts that tweeted Hundreds of times about the about the the k-pop band They are not paid actors. They are people who really Who are angry about stuff or people who are really trying to To to to change things by being very active on twitter So my general impression is that people have a tendency of overestimating the problem of malicious fake accounts people The default assumptions should be actually those are real people with real Real intrinsic motivation Another question we have is um in your slides you had this circular reasoning Example or maybe this kind of fundamental flaw of circular reasoning. Um, and the question would be from this person Is it maybe? Like circular reasoning maybe not rather resonance with which would be a valid method to get a result kind of That the results actually resonate with their With the real world such that in the end you would kind of confirm that there's something resonating With your findings. It's a bit hard to ask this question, but maybe you got it I think I think I get I get I believe I got to get more of the questions going out. So maybe the the idea would be to So you To start this to use this method you would have to have a guess for the the the prior probability of bots So you could use this iteratively and hopefully end some and at the real value But actually I believe it will certainly Either it will Explode and go to 100 or it will go to zero from all my As I'd say 25 experience in pattern recognition. I don't think that this approach is remotely capable of Estimating the real probability by using it it iteratively or something like that So I don't know that I don't think that's that will work the interesting part about this This equation is Any kind of classified use it is so even humans use it. So if if I have the If my task is to label bots or whatever in a list of accounts And I have some expectation of the real prevalence of bots. I will include this information. So how how So basically the the the problem is If we don't know the prevalence Can how can we even estimate it? And the only way to do it was it would be if these two Posterior probabilities which basically tell us how much does the do these features? How much does these do these features? So for example the tweeting raid Look like a bot and if these two distributions are very different So for example, if bots tweet 10,000 times a day and humans only it tweet 10 times a day Then we keep it can keep these two apart And these two probabilities which we don't know are very Unimportant but if these two distributions look are somewhat similar. So if so think let's Think of we're trying to estimate if it's a man or a woman based on the on the on the height And of course if somebody is 1.75 meters it can be a male or a female It's very hard to discriminate So these distributions overlap and if these distributions overlap we can simply cannot count male and females based on without having Without knowing in advance which which are the two classes what the distribution is So this approach even if we there's no way to make it To iteratively use it Unless we have a very clear Identifier for humans and but so for example if each of the bots has a label that says it's a bot Then we can discriminate the two classes Another question that is similar maybe to the effect question that we had in the beginning Are you not worried that your research will be abused by those employing rooms full of humans to do bot-like posting to just claim there are no problems at all and just Just giving this as an excuse saying like look at those researchers. They claim there are no bots at all. So Like what we do is a good work or something like that Well, first of all, I'm I'm a researcher. So I'm not interested in what people might Make of the results I have. So I'm not trying to produce results That might be useful for somebody or I'm not afraid of producing results that might Might come handy for Parties in political discussions the whole bot research often very often involves Very Polarized political discussions. So sometimes people like me because I Tell the right-wing people. They are not bots. They're real people and then in the next discussion I tell the left-wing people they're not bots and they like me because I tell them they're not bots so At the moment I start to think about The the effects that some people might might like about research This would be I would would no longer be a scientist, but obviously we're not talking about people Getting paid for for tweeting. So obviously we are only interested in the claims about social bots So the automated accounts interfering in political discussions using fake profiles. So the pay trolls I don't claim they don't exist. I know they exist especially in Venezuela for example or in Mexico or in russia. They're very valid Very credible reports about Pay trolls even insider reports by people who have been working in this kind of setups So I'm certainly not claiming that there are no humans trying to to interfere in political discussions Yeah Maybe a follow-up from another attendee. How can we incentivize this replication work? For those studies you've shown and you kind of try to replicate as well Or at least got some information out within the scientific community for this field Is there kind of something that the general audience can do or maybe something that researchers need to do In order to put more focus on replication in this field Which seems to be a bit flawed and needs a lots of replication. It seems Well, it's I think The replication issue is a big issue in all scientific fields even in computer science A lot of the research for example um New topologies Designed for neural networks which work in certain setups in certain But it no longer work in slightly different setups So um replication is a big issue in in all scientific fields But I think it's a very huge issue in social sciences social sciences So I'm a computer scientist. I come from a technical field. We're used to very strict standards. So we're used Uh, we nobody Uh would dare to publish something without being ready to to publish the raw data as well So the idea of publishing results without Being able to hand out the raw data is a huge It is basically scientific misconduct in our field So in social sciences, obviously people seem to be a little bit more more relaxed about about Reality and about truthfulness and I have a feeling there's a kind of cultural mismatch. They they'll It turns out that a lot of studies in social sciences are not replicable and The problem seems to be extremely Prevalent in social sciences. Yes Maybe last question A couple of people ask the variations on the same question In your opinion, is the lack of evidence for social bots sufficient to prove that social bots do not exist Or not in any meaningful amounts. I mean like that we didn't find them doesn't mean they don't exist I mean we can build one for a proof that they exist But uh, do you think that um kind of the lack of evidence is um prove for maybe That they do not exist at all or not exist in a in a large quantity Well, basically, um The the interesting, uh, maybe you're familiar with russell's teapot. Uh, he he used the the The the idea of a of a teapot flying around the around the sun in an orbit beyond mars and Claiming that the teapot was flying around the sun in orbit around mars is hard to disprove So you cannot you can Took a very close look at the orbit and he will still not be able to disprove that That or that a teapot is flying around mars and um, obviously we have the technology to send a teapot in an orbit around mars so, but It's uh, and if people claim that teapot might be orbiting mars. Uh, it's very hard. Yeah, we can build rockets We can build teapots. Um, we can send them an orbit around mars and it would be Very hard to disprove these claims. It's very much like social bots Now I believe it's very unlikely that somebody has already launched a rocket with a teapot teapot to to to orbit mars and also believe it's pretty unlikely that people would try to build automated political social bots simply based on my understanding of the technology So building chatpots is extremely cumbersome is expensive and the results are really really bad So if you've ever interacted with a real social, uh, a real chatbot, you know, the those Bots are very limited at the current state of the art. They can't even handle negation. So if you tell, uh, Siri do not, uh, switch on the light, it will switch on the light. So even simple stuff like negations Are still beyond what natural language processing can do at the current state of the art so the idea that of rapidly coming up with a, uh, a chatbot like System that can interfere in current political discussions, which are usually only going on for a couple of days on twitter And then you would have to buy a new one for the next discussion Or you have to to program a new one. It seems very very, uh, Beyond what's possible from a tech technological perspective. So I'm pretty sure these kind of bots do not exist But of course I cannot prove it All right, um, thanks. I think we got some more question, but we cannot really fit them into this slot. Um, again Thanks so much florian keep up the discussion and also keep up your work And, um, after this talk, uh, we will continue here on chaos sony tv with a talk from big alex about Software engineering, I guess and we will see you soon. Um, after a short break. Thank you Thank you


So yeah Veterans Day means to me What it means to me it means a bunch of men and women raised their right hand to Support and defend the Constitution of this great nation. I am a second generation American and All of my family has served this country to thank them for letting them in and again Veterans Day is all of us That have served past present a future You know for me thanking them for leading the way I came in in the early 80s And I'm grateful to Vietnam ever Marines that raised myself and my friend here and We're just grateful for everybody that has served and will serve in the future Veterans Day is a day with a good thanks to all those guys and ladies who raised their right hand For this great nation of ours My name is Javier Morales. I'm an accountant. I did Six years in the Marine Corps in ten years in the Army reserve Ice-tray Montgomery Veterans Day for me is People who so proudly served our country I Work program for Liberty works where we And that reflection gives us new direction on how to deal with our veterans that are coming home That's better Yes, I am Marine Corps veteran I've served three years active three is inactive veterans day needs to be old and after me And they're livelihood So all of us can go around Without the veterans That's why we should never forget the bettons everybody should come out Salute the veterans on veterans day It would be a great thing in the United States everybody hung a flag from their house show support for the veterans


in low-income countries, many donors were involved in regular collections of funding for emergency assistance, especially in South Saharan Africa, and they felt that what is needed is to move to a more stable means of providing assistance to food insecure households in South Saharan Africa. So that is kind of the explanation there. In low-income countries, it's simply because of the initiative of low-income countries in moving in this direction and then kind of funders and donors coming behind and providing support for them. So what part of social protection has shown the best results so far? I think these social protection programmes that have a human development component that try to build assets, productive assets, and the student in a broad sense of not just physical and financial assets but also human assets. I think those tend to have the greatest effectiveness and I think the great likelihood of having a long-term impact on the recipient households. You say that foreign aid have an important but limited role in social protection. What does that mean? Well I don't think that there is an appropriate role for foreign aid in actually financing transfers in developing countries. I think it aids to volatile, I think it's not sufficiently political enough to involve the governing coalitions in developing countries to really make a significant effect, a positive effect on developing countries. I mean, for example, I'm a UK taxpayer, I would not advise anybody to depend on UK taxpayer for their social protection. So ultimately, social protection must be developed out of internal sources of financing. So that limits the role of aid. However, aid has a very important role in supporting infrastructure development and capacity building in particularly low income countries. I mean, to give you an example, Sambia has 50 districts, has two social workers per district that is never going to be sufficient for an effective poverty reduction kind of a strategy and program. So you need capacity development, you need infrastructure development. The other point that is really important is the issue of registration of children because any anti-poverty program requires to know how many people need support when they were born, are they school age, why do they leave, and that is crucial. So supporting, for example, 100% birth registration is really an important step forward. So there is an important role for aid there, but it's limited. I don't think aid should fund actual transfers. But at the same time, you say that foreign aid in social protection is probably the best evaluated, I mean, from the donor perspective. Why is that? I think it's because there is a resistance among kind of voters and taxpayers in donor countries as to how their kind of resources for aid are used. And I think that resistance has been met on the part of multilaterals and increasingly bilateral agencies with evaluations that demonstrate the effectiveness of these programs. So if you, for example, if you want international aid to support microfinance, very few people will complain about it. If you want aid to support small and medium enterprise development in developing countries, no one will complain about that. But if you say, we're going to use aid to support programs that provide direct transfers in cash to families in poverty, there is much greater resistance. And that is really where evaluation has come as a means of overcoming that kind of political resistance to this strategy.


Okay, very good morning. It is Friday the 11th of September. I hope you're doing well I'm just going to run you through some of the main kind of fundamental headlines from this morning and an outlook for the day ahead final trading day of the week and Going to start off with I'll talk about Brexit in a moment as you can see to the side of me but let's start with the charts and One of the main things here was quite a breakdown in US equity indices yesterday Moving through what was an area of support you can see these center charts here in the S&P in the center right a Breakdown of what was a support level throughout much of yesterday's session at around 7 p.m London time and that coinciding with a similar technical setup in the likes of the Nasdaq as well So a breach through their markets were a little heavy The latest that we've had on on US Congress is that Democrats have blocked the Senate Republicans whittled down 300 billion dollar coronavirus aid package As the prospect of passing they're more relieved to households and businesses by the US election date of early November continues to be a Fairly slim prospect at this point in time. So did dampen sentiment a little bit We also had US lawmakers still remain pretty far apart as well one of the other contentious issues at the moment, which is How the US is dealing with China Basically Trump said he will not extend his September 15th deadline for bite dance to sell its US operations To tick tock video on the tick tock video sharing app So differences in opinion of the best way forward with that between the Democrats and Republicans as well at the moment so Yeah, that caused a little bit of attention But yeah, technically we broke through but and I was quite a large cell siding balance into the close Last night on Wall Street But since then pretty quiet overnight Asia Pacific session and we've continued to just reverse course and find a Bit of a footing now as we in the futures market trade quite a bit higher already And you can see that point of break in the Nasdaq We are already back above there right now if we were looking at the current market price action and trading above pivot and actually on the longer time frame was just looking at the The nasdaq 100 on a daily continuation this morning There was that long standing trend line that we were looking at kind of dates all the way back to April So since the initiation of the recovery post that March set off that we had on the pandemic and There was a couple of tests on that point when EU Covid fears when we're materializing towards the back end of July But then we had those mega cap earnings that really outperformed and we pushed on since there We can see previous other tests and around the that trend line Interesting then to where we're at at the moment. Obviously, we've had a pretty decent correction in markets overall Obviously a whole holiday short and weak if you're in the States given the Labor Day holiday But here then we're trapped on a slightly higher time frame between some quite interesting Areas this line here as the 21 DMA the bottom colored line is the 50 DMA So at the moment price activity over the yesterday session was very much caught in between those two areas and on the upside that 21 DMA does coincide with that trend line and you can see back on on the 8th We respected that we respected it yesterday as well So definitely be keeping an eye on that as an upside level whereas on the downside Then you've got the 50 DMA coming in which was also respected yesterday So quite interesting being kind of wedged in between that and then the upside the kind of Dual combination of that DMA with the trend line It's something to be aware of with as well If you put a horizontal line a double top now from the eighth and a tenth of this week Would be quite a key upside obstacle now on any further recovery if that was to take take place As far as the S&P is concerned As I said the river had set off yesterday a bit of a breakdown towards loads to find a bit of support around these prior areas That we saw back On 8th on the evening and then that the rally that commenced on the European morning Two sessions ago. So got to that point and we've had a bit of recovery We're just hugging pivot at the moment and the upside levels keep an eye on if we continue to push higher Would be up at around that kind of area of 33 61 3 quarters And they're kind of tracking the move back up if that were to be the case and you've got that double top at 34 14 and obviously the 3400 level and our one on the way if that was to materialize throughout today's session One of the other things then I wanted to talk about was the FX market quick look at the euro And then we'll get stuck into the Brexit side of things Obviously the euro has been in focus this week, of course Particularly given the the ECB meeting and if you you missed our live session yesterday It is available on the YouTube channel. You just go down to the live session recordings Category on the YouTube channel to be able to find it and review it if if you wanted to but yeah The last 48 hours of price action has been pretty interesting You had that initial quite explosive move to the outside when those ECB sources came out Which were kind of talking up the optimism of markets and we talked about this at length yesterday About how that perhaps could have been a coordinated effort by the ECB to through the backdoor Avenue of sources to try and just prop the market up a little bit in terms of its pre-event positioning Just given the the general expectations were that they were going to kind of toe the line and which may have perhaps then disappointed the the doves in the marketplace and therefore could have created quite an aggressive rally in The euro currency and and that did actually end up being the case I mean of that matrix that you remember sharing yesterday. It was pretty much the top scenario, which was the You know not they're not particularly spooked at this point They didn't really make it was a real soft touch in regards to any referencing over the euro currency rate Which obviously a lot of people were looking for and that in itself contributed to quite a large pop here in the euro However, if you look at where we are at the moment, I mean net net we're pretty much scratched to where we finished After this session back on the ninth after that initial source commentary So despite some of the volatility that was seen yesterday, I would say overall It's a fairly contained move considering how important that ECB decision was it's failed to really maintain direction And either way in a bigger picture perspective obviously It's going to be quite interesting to see do we continue to see a push-up to to 120 in the end That obviously is the key area on that long-term significant trend mine which we've Well, it's apparently made quite clear and present They used to be a little bit nervous and concerned about the strength of the euro And although the guard not willing to really be more definitive on that point It's certainly the lack of talking it down does open up the prospect potentially of a further move higher But obviously we want to be tracking dollar developments as much as euro developments to see whether that plays out But at the moment this morning, it's pretty quiet It's basically in consolidation mode through much of the overnight European session on the downside if we said a trend lower today I'd be looking at those initial lows that was seen into the US clothes last night and on the flip side if we start tracking higher Probably be looking at first port of call around here, which would be 118 73 which would be these previous lows and you've got the high here and then just tracking that move back higher then to the the highs that was seen Going back to the beginning of all beginning of September Excuse me third and the fourth on that double top and that area of support that we saw post the ECB Going into the European fix and the effects markets yesterday So let's let's look at sterling then We'll talk a little Brexit And yeah, it's been a continuation of real Pressure for the sterling currency and I'll go into it in a bit more detail on the fundamental side But just looking at the technicals here I've marked it up with the what has been actually a 5% move This is going back this high was printed at the beginning of September So over the last 10 days or so and would be the sterling currency against the greenback has lost about 5% Johnson threatening to leave the EU. This was going into that eighth round of talks Which obviously have finished now as of yesterday and then that resulting in this new internal market bill being issued by Boris that throwing is eJeopardy then the the legality of Deering to the rules of the withdrawal agreement which was agreed back in January of this year and that has led to the EU threatening legal action and so Continuation of downside pressure on sterling finding technically though some support around What is a key area? That's that previous high that we had Back in June before then actually we saw a very meaningful pullback In the period thereafter through that month And so we got back down to that level yesterday brief flirt and run down to what is the 200 DMA? Which is the blue line and that's also been a quite a keenly watched Level as well over the last couple of months of price action So yeah, this ellipse here would be quite key area of support now at this 128 handle as to see where we finished a week I'm quite keen to see and a lot of conversation We had yesterday with some of the traders internally was about you know, how much is it got to go for this to be priced in? And we were kind of looking at a chart much kind of longer dated to encapsulate a little bit of the 2019 price activity and the kind of transition then over from Theresa May over to Boris Johnson and the markets pricing Even before he officially became PM of the risk of a no deal given that his stance was well known And that was when we were trading more around kind of the 120 area 121 when it came to sterling so with all things remaining equal and as I'm going to discuss a number of other things We're looking at in the UK from a fiscal point of view potential monetary policy implications There definitely is room with the the risk of Further material pricing of no deal that this sterling currency can remain Under pressure going forward in the coming weeks. So let's let's talk about some of the fundamentals then on the headline side. So during crisis meetings yesterday Boris Johnson's government rebuffed an EU request to scrap his plan to rewrite the Brexit divorce accord or otherwise that Known internal market legislation which came out on Wednesday And this comes even after the block gave him a three week ultimatum to do so or they threatened legal action against the UK Michelle Barnier said that UK has not engaged in a reciprocal way on fundamental EU principles and interests Significant differences remain in areas of essential interest for the EU and we had pretty much the mirror Statement coming out of David Frost his counterpart for the UK the negotiators though. They do plan to meet again next week in Brussels you can probably In visage then that these talks will now intensify as the kind of soft deadlines in October Which we were initially looking around mid-October some sort of tentative deal to be struck at least in a loose Framework agreement It's probably going to see then week after week negotiations going forward a few other things that have happened just given this this UK Change of stance, let's say particularly that legislation they brought forward in the middle of the week Johnson is facing a revolt by as many as 30 conservative MPs over that particular bill Is that a shocking and problematic number? Well, it's it's definitely going to create some media noise, but I don't really see it given his resounding what ATC Majority has in Parliament It shouldn't really prove to be too much of an issue in terms of the commons But when it comes to the House of Lords, which typically tend to be a little bit more Euro-friendly, I'm sure that they're gonna do what they can to slow down the speed of passage of that bill Which is likely to just zoom through the lower house And that could again be a contentious issue for internally Boris Johnson and conservative parties to manage Couple of banks been commenting on the situation Goldman Sachs said the British government's moves were intended to extract concessions on the UK's ability to diverge from EU regulatory standards while still enjoying zero tariff zero Quota access to EU markets after the transition period ends at the end of this year They're expected the perceived probability of a breakdown negotiations to escalate over the coming weeks But their base case remains a thin free trade agreement At this point in time, I I tend to agree with that statement I think things are going to get a little bit worse before they get a little bit better Hence this is the normal process of Brexit negotiation which we've seen many times before and I do think as what some of the media referring to this game as Brickmanship can go wrong But we've been here multiple times before when it comes to break Brexit and in the end Although sterling must reflect this include in this renewed risk We tend to see a general positive outcome or delay in kind of cliff-edge type scenarios So I don't see any reason why that wouldn't be any different this time round one thing that that some people were looking at was Overnight sterling implied volatility rose to 13 percent. That's the highest it's been since my birthday on March 26th earlier this year and obviously that was right in the middle of the peak of the pandemic route that we were seeing in markets So we've got over the peaks that were seen in June and late July early August And that was that latter one when the the US outbreak was happening in some of the Sunbelt regions Implied volatility gauges for other maturities Or are also elevated including the six month options contracts Comprising then the end of now if you think about the calendar year that encompasses the end of the transition period And that stood now close to its highest since mid-May So some of some of the pricing would be indicative then that things certainly people are positioning themselves to get get worse Essentially more volatile if you think about it, then there's kind of a multiple factors then are weighing on this sterling They've really created this five percent decline over the last 10 days or so whether it be uk economic data generally losing a bit of momentum We've had a rise in uk covid 19 cases We've had a tightening on social gathering guidelines as a result of that and we've got fiscal tightening Potentially very close in the horizon and the particular one being furlough finishing at the end of next month and that in itself Furlough is still being used by some 9.6 million people in britain That's being talked about a little bit in the press this morning I've mentioned this before about whether or not russia sunak might have to extend that program I think that that probably will be the case, but in a little bit more of a strategic sector-based way Continuing the program According to the treasury Number two, steven barkley. He said yesterday that extending furlough overall Would only serve to keep people trapped in a job that only exists because of the furlough scheme I can kind of see the point there And this is the difficult thing that the treasury now in the uk needs to weigh up Is do they want a mass flood of unemployment in the millions which is only going to further Not just impede the economic recovery, but it's also going to damage the conservative party's political favorability So do you stump up the cash and keep paying for that but ultimately at some point it does need to finish and There probably is some legs in that argument that there's a lot of people who are just trapped in a job where an employer Perhaps in a small medium-sized business is happy to keep you on because the government's back stopping 80% of your wages But if that's pulled Then some of these companies are going to have no choice anyway, but to let you go So your job's already lost you're just caught in this kind of gray area that's furlough Is is maintaining that that employment for the time being The way they could approach this and probably I think the way that it will work is the treasury might well Extend beyond October for targeted areas in terms of job sectors. So particularly those that have been most hard hit So things like tourism Um hospitality leisure these sorts of things Which have had to go on complete lockdown obviously because of the nature of uh of social distancing Um, so yeah, I mean number of factors then to to weigh on this obviously as things get worse If that were to be the case then um, does that create then more Necessity for the Bank of England Although they've kept things like negative rates on the table does it push us more further down that route? So more reasons accumulating for uh for further softness coming in there the currency going forward But hopefully that's a good overview um Quick mention about covid Uh, I know it's been pretty quiet on this front for uh for a little while But I just wanted to give you a bit of a brief overview In the u.s. The number of new cases still moving down generally the one week rolling average now below 40 000 new deaths Hospitalizations continue to decline as well. So yeah at the moment It's still you know when it comes to this sort of thing Uh, it's really not that much of a talking point comparative to what it was just around A month or two ago, but I still do keep a daily eye on on it just to to make sure That generally two two things one I think it's quite important not just to look at cases Um, and a good example of this is the what's happening in the uk and europe Because the number of new cases in europe continues to increase at this point in time Um, and nothing is suggesting that that will will stop anytime soon So we are expecting case numbers to go up Particularly france spain are the worst hit at the moment. The number of new cases in uk is now accelerating at a faster pace Uh, particularly as well as you know the youth. We've got freshers week coming up um next week I think and uh If freshers weeks anything like I remember back in the day I'm not sure there's going to be that strict to social distancing and perhaps then the reason why the The government made their move This week to to initiate that from monday specifically given the fact that it's 17 to 21 year olds that have been the major issue With the acceleration within the uk in terms of a demographic Uh, but you know kids go back to school the potential transmission then onto their older relatives and so on So things are getting worse on a on a case basis But you know the most important thing here is I'd look at the data as a whole and actually new deaths in europe remain stable Despite new cases have been rising since july. So Could be a couple of factors here and here are a few um And there could be multiple so More young people getting infected and generally their ability to be able to cope with And then fighting off the the virus is seen as more effective than that of the elder generation More testing better knowledge on the treatment hospitals not under so much pressure So, you know, hence the reason why politicians despite numbers going up are a little bit reluctant to implement too strict Or too stricter A movement on curbing the virus due to the high level of economic cost that it would entail to the economy So this is why perhaps there's a bit of a disconnect between you read the press and the numbers going up And yet the economy is trying to reopen and they're moving forward with that plan the push to put people back to work And so on that's because underlying it actually More people are getting it but it could be down to other factors and it's not resulting Intangible deaths in the end. So Yeah, at the moment as long as that remains the case And that latter part doesn't start to pick up in step with the case numbers Then I don't think it's really going to have too much of an impact on markets for the time being But it's something to remain vigilant for of course on the note of covet 19 I did a tweet this morning My twitter handles here if you want to get these crib sheets, but I saw a really great research report from danska bank And here is a great table looking at The vaccine candidates that are currently in phase two and phase three clinical trials and you remember University of oxford astrozenicus one's been the one in focus, of course This week mid week with that that scenario that we saw where they briefly have halted their their latest trial And so that's number one here at the top, but it's really useful to be aware of one of the other nine currently in phase three What type of vaccine are they? How many doses timing of doses you know just to give yourself, you know, if you know Markets are sensitive to a certain issue Then it's prudent. If you're going to be an agile active headline macro Good trader then you should have a base competency of at least having An understanding of these things because these are what markets will move on if a certain headline was to hit the tape On the tweet. So you've got that table the different types of vaccine How soon can a vaccine be ready in terms of timelines against normal Procedure because obviously everything's being accelerated Governments will need to expedite their usual drug approval processes In order to get the vaccine out as quickly as possible And then the vaccine development phases. What exactly does this include? You know, how do we get to the the point of approval status and so on? So it's good to have a little bit of base knowledge on this and for the amplified traders I distributed the full research report to you guys earlier this morning All right, quick look at the calendar for today UK data has already come out and It hasn't moved the pound. I wouldn't expect it to and the the GDP number it comes as no real surprise At this point in time. We're already kind of fully accustomed to what the status really is there So the month-to-month reading was at 6.6 percent. It gets expected 6.7 So minimal change in terms of some of the other data the industrial production Month-to-month 5.2 percent above the expected 4 percent The trade balance was a deficit of 8.64 billion against expected deficit 6.9 billion So it's not really too much to comment on UK construction output deep contraction But not as bad as analysts were expecting but overall minimal reaction in the pound I would not be looking at that To supersede the other factors, which I think are more dominant At this point in time. I think the the fallout of the brexit situation, although I think largely priced in In terms of what's happened this week. I think that is reflected in price That doesn't detract from the point then that there are multiple threats facing The UK pound at the moment So fundamentally from a directional bias. It's still short at this point in time for us Yeah back on the calendar then what other stuff have we got we've got the US CPI numbers They're really the only major feature of this afternoon and you know given the move In policy now from the Fed to move to average inflation targeting Perhaps a little bit interesting, but in fact now perhaps inflation data like this specifically CPI Takes a lower precedence because of the fact that now it's not so definitive that we're looking at 2 The market can run hot above that point and to be quite honest We're nowhere near that at the moment and even though inflation has been picking up As the economy in the US has started to reopen and so naturally then We see the demand start to to pick up once more We are expecting this this pattern to continue albeit perhaps not at such a rapid pace I think the consensus estimate is for 1.2 percent on the on the year-on-year figure But I wouldn't be expecting too much from that as I said We're still away from from 2% And the fact that inflation can run above and below now given the new policy kind of system I don't think that's going to be a real game changer for today Otherwise Baker Hughes rig count usual for the for the oil traders a couple of speakers coming out later this morning ECB schnavel at 9 50 London time ECB's lane talking at 1 p.m And just given the context then of Christina guard speaking yesterday usually would be uncommon for Something to be said explicit that would be any different from what the guard has said Because she speaks on behalf of the ECB But if they felt the need to kind of Reemphasize any points or re-guide the market then these two speeches could potentially provide a platform to do so So worth keeping an eye on And then for fixed income traders reminder You've got the boom bubble shats set futures expiry happening late morning 11 30 All right, that is it. I'm going to let you get on with things if you don't already do so Do not forget to subscribe to the channel had some really great videos this week not just the standard kind of macro briefings in the morning, but Breaking news about AstraZeneca. We've had video about tesla from eddie and one about soft banks So yeah new content coming all the time great to have you guys engaged And with that, I wish you a great weekend. I'll see you on monday. Thanks very much