Hello everyone and welcome back to Conversations with Tyler. Today, I am here in London with the great Jessica Wade. She is a researcher at Imperial College London, well known for her work in chiral materials and ramen spectroscopy. She has written a children's book on nanotechnology called Nano. In the public eye, she is best of all known for having written over 1900 Wikipedia entries as of February 2023. It will shortly be more and those tend to focus on the history of women in science. Jessica, welcome. I'm so excited to be here. Hello. Let's start with women in science. We will get to your research, but your writings, why is it that women in history were so successful in astronomy so early on compared to other fields? Oh, that's such a hard question and a fascinating one.  Caroline Herschel was quite big on polishing the lenses that Herschel used to be able to go out and look at and identify comets and was so successful in identifying these comets that she wanted to publish herself and really struggled as a woman to be allowed to do that at kind of the end of the 1800s, beginning of the 1900s. And I think actually it was just that possibility to be able to access and do that science from home to be able to set up in your beautiful dark sky environment without the bright lights of a city and do it alongside your quite successful husband or father. So after astronomy, women got quite big in crystallography. So there were a few absolutely incredible women crystallographers throughout the 1900s, Dorothy Hodgkin, Kathleen non-stale, Rosalind Franklin, people who really made that science possible. And that was because they were provided entry into that and the way that they were taught at school facilitated doing that kind of research. So I think I find it fascinating they're allowed. But if only we'd had more, you could imagine what could have happened. So household production, you think is the key variable plus the ability to be helped or trained by a father or husband? Yeah, house and that ability to be able to access it and do it and the way that you're taught at school and what you're taught at school. In the early 1900s, I can speak for the UK, but I'm sure it's common around the world. Women were taught science in a really big way. A much bigger way than they're taught now in chemical sciences and physical sciences because men were learning Latin and Greek because that was recognized as important. And then society realized women getting really good at these things that could potentially have huge implications. Push the women out and push the men back in and you have this really big disconnect between what women wanted to do and could do and then what they were allowed to do by society's perspective. As late as the 1990s, one can read in quite serious science books, the notion that maybe women were good at astronomy early on because women more generally are good at making careful observations. Should we regard that as an offensive stereotype or just giving women credit for credit as due or that kind of generalization? How do you look at it now from your vantage point in 2023? I think those kind of stereotypes aren't very useful. I think it's looking at the way that society has trained women to be. You know, the words that they're told, the advice that they're given from a really young age, the way that they're taught in school, the kind of support they get from their parents and teachers to pursue different subjects and that associates particular personality traits with them that men probably have and do have just an equal measure. But because of the way that society nurtures and kind of cultures us, we're pushed into these kind of fields. So undoubtedly you might see more women in astronomy because of what society's done. But it's not a biological reason for that. It's just a societal one. So yeah, I find I find those I don't even think you have to look back to the 90s. I think you probably still find quite a few academics publishing on this now. But if you design a scientific study destined that you want to be able to show that there's some biological difference between men and women's abilities, you'll be able to design the study in such a way that you show that because you're so biased in the design of doing it. And if you go out and ask people and look at a general population without taking into the account what society is doing, of course, you're going to see these quite vast results at the end. And then, you know, you've already made your conclusion. So I find those stereotypes not particularly useful. I'm very happy there are lots of women in astronomy. I wish we use those stereotypes about men as well, though. Are there any such stereotypes we should be willing to accept or even embrace? So one reads also, well, Jane Goodall did better with chimpanzees because she was a woman, maybe chimpanzees are more trusting of women. I have no idea, but all the stereotypes go or just some. Another fantastic question. I think probably the stereotypes about, you know, what it takes to be kind of a great scientist or a great athlete or something like that, you know, that hard work, that commitment, that dedication, that enthusiasm, that curiosity, that I'm fine with those kind of things. I don't want people to be stereotyped by their gender or their ethnicity or their physical ability. I want everyone to have the same opportunity and then to just be able to work out exactly what it is that they love and how they're going to make the world better. How would you distinguish between productive and unproductive ways to encourage women in science? I would say unproductive ways to encourage women in science, which happen a lot, is constantly telling women in science. There aren't any women in science.  So come and be a woman engineer. I don't think that's a particularly useful way. I think the way to do it is to make sure everyone has the same educational opportunities. You know, make sure we have fantastic physics and math teachers in our high schools and all our high schools, not just the expensive high schools, make sure they're getting the same kind of career advice and kind of research opportunity. There's quite a lot of evidence that shows that particularly people from historically excluded groups feel more like becoming a scientist if they're introduced to the world of research and see those chances that they could have. And then we're giving people the same support throughout their career. You know, the same access to lab space, the same kind of access to scientific funding, mentorship, thing like that. That's really useful and productive. Telling women that they're different or telling women that they have to kind of become more like a man. You know, here's 10 fantastic steps on how to give a great presentation like, you know, that power stance stuff. That's not particularly helpful, right? But actually giving people that opportunity, that funding, that space and that support, that is really helpful. So as you know, science plays itself out in a lot of different venues. There's nonprofits. There's for profits. There's universities. There's governments on the whole. Where where is discrimination against women been least bad? And where has it been the worst? Okay, all sectors. I think probably it's it's pretty bad across all sectors. I would say access to education and opportunities in education is obviously massively varied worldwide, but very challenging for women in particular parts of the world to access even basic education. But the West, the UK, US. I think probably I don't know.  I think that if you look at the support women get throughout their careers in academia, the opportunities they get to build their own big research groups while simultaneously taking on caring responsibilities because women still disproportionately get that in society, it is really challenging to succeed and be a really successful professor if you're trying to do all of that other stuff as well. Probably in financial sectors, in private sectors, you might get more flexible opportunities to return to work. I know that the pandemic has had a huge impact on the ability of women to come back to work because of the, you know, chance to work flexibly and things like that. So I think probably the private sector has done an awful lot of the work that academia and, you know, public civil service should be starting to do and is kind of leading the way. But I don't doubt that there's still huge discriminations and issues around sexism and racism within the private and the kind of corporate sector as well. And then, you know, government is a completely different issue because you don't even get, you don't only have the internal politics of what's going on and who gets promoted and who gets to be the public face, but also how the media is portraying those people and the impact that that has on the general public's perception of them.  So I think probably we should all be learning from what works well in the private sector and also what doesn't work and trying to emulate that. If I think of 20th century history from my naive distance standpoint, it seems to me it was the commercial book market where women make a big breakthrough. You have Margaret Mead, you have Rachel Carson, you have Jane Goodall, which is in 1971. And the buyers of the books, they don't seem to care if the book is good or interesting to them. And then you have big advances for women in science that it's led by for-profit incentives, basically. That's really interesting. I wonder if it's still the same today. I wonder if people still in that commercial book market world would still celebrate and see the achievements of women scientists or the achievements of women and take them as seriously as the achievements of men. I still get the feeling, despite, you know, you having a huge amount more writing and popular opinion around the need for more women scientists or the work of women scientists or the history of women scientists, it's still a very specific type of person who'll go into a bookshop and buy that. You know, not every man who's quite biased or opinionated on these issues will go and buy that fantastic history of women scientists book, even if they exist. So I think book sellers and book marketers can do quite a lot of magic in that space, but we have to make sure it's being read and excited everyone, exciting everyone. Now you're on Twitter, but my anecdotal impression is that social media in general have swung some of the bias back toward men who, for whatever reasons, are more likely to be vocal on social media in terms of celebrity and science. Do you agree, disagree? I think social media has been extraordinarily powerful for connecting people from groups where they are marginalized, you know, from people from historically exceeded backgrounds coming together potentially they're the one black physicist in their institution, but they can come on social media and find a whole bunch of other black physicists and get that confidence and that voice to be able to go out, give that amazing presentation, get that big research funding and start doing their own thing. So whilst I'm sure you've got the kind of cult of ego and these, you know, professors with their super labs and their lack of actual basic support for PhD students and Twitter perpetuates that ego, actually the magical parts of it, the magical parts of any of these social media, for me, is uniting people who before didn't feel like they had a voice and saying there's actually this amazing neuroscientist there. If you go to Canada, you can meet and connect with them. People changing their research fields, they're changing their institutions where they work, and they're really getting more opportunity, you know, after the unjust murder of George Floyd, there was a huge outcry and support from the black academic community to come together and to do more to support black researchers. There was these movements set up, which were kind of black in chemistry, black in physics, black in neuro, and they galvanized a complete different change and approach to funding scientific research, you know, scholarships that have been made available. And that's happened within the last few years, just because people came together on social media. So yeah, there's the egomaniacs, but then there's also this kind of beautiful stuff happening as well. And, you know, I hope that that continues. How will artificial intelligence affect gender participation gaps? I suppose it could affect it well. I guess it depends with all of these things, though the data that the artificial intelligence is going to be trained on. And you've seen it with chat GPT, I suppose. And I'm sure you've had a few conversations at university about how that's going to change the way we have to set exams and get a lot more creative because these these AI tools can now pass exams. Are you right? I think if you give the data in the correct way, potentially it could give relevant advice. I've seen it kind of hilariously. Some American scientific funding is now requiring EDI statement. I don't know if you do yet. An equity, diversity and inclusivity statement on a research proposal. And you can sit down as someone like me who really cares about this a lot and really harrow over how to articulate yourself in the word limit, right? And really think about all of the stuff that you've done and the stuff that you're super passionate about. Or you can just ask chat GPT to write you an EDI statement. And actually, you know, if the person who's evaluating it at the other side can't really tell the difference between the two, then someone who doesn't care very much and can just run this through an AI enabled language model can get the position when I can't. So I think in that sense, it might make it really challenging to differentiate who's actually passionate and who isn't. But it could, you know, I mean, honestly, right now, I can't think of any useful way that it will help it potentially in. But it could make it worse possibly. It could make it worse. You could use it in quite an effective way, I suppose. And this is entirely in my head at the moment. So I don't know if it could be at all useful. But potentially in allocating scientific funding so that it's less biased, because at the moment you have bias about nationality, gender, institution. But if you ask an AI to learn from what has been a successful proposal before and what's gone on to actually impact the world, and then use that and try to get it to assess science funding and who should get what. Maybe it could be useful and less biased there. But again, it depends on the data that we're feeding it. If chat GPT can just reproduce these DEI statements, isn't that an indictment of those statements? Yeah, it's a complete one. But I think having them at all is an indictment of those statements, right? Because it's almost like those, you know, ridiculous entrance exams that used to go to medical school here or graduate school in America. That it's if you're privileged and surrounded by people who help you pass those exams, you get it. And so if you're surrounded by people in your institution who can write your EDI statement, then it doesn't mean that you care remotely about it. Just means you've got someone else to write it for you. In the United States, more than half of the graduating majors in the biological sciences are women. So there's a lot of representation at lower levels. They may or may not go on. The percentage is much lower in a lot of the STEM fields. How much of that difference should we think of as resulting from just preference of the women? We should think of it as resulting from preference as a result of what societies not should them to think they are interested in, right? So because some of it just be legitimate preference, I don't think it's biological. I think it's because of the way you were taught and introduced at school or the passions and enthusiasm, even if your parents, right?   Whereas boys, because they're always taught that these are subjects that will give you huge opportunity and are really excited and do, you know, all these successful men are going on to do them. They just do them anyway. So I think that you see it as being a preference because of the way that society and family has really centered around this fact that girls don't study subjects like physics and engineering, whereas if you gave them all the same opportunity, if we had amazing teachers in schools, if parents were a little less biased about the subjects they do and don't find exciting, I think you'd just see that go in the UK. We have mandatory high school studying of chemistry to get in for medicine. So if you study, if you want to go to medical school, you've got to do chemistry, you probably do biology as well. And as a result, chemistry undergraduate is gender balanced because girls start studying chemistry at high school and they're like, this is an awesome subject, so I'll go and do it at university. If you made physics a mandatory subject for studying medicine, you'd have way more women studying physics undergraduate because they'd realized this is an awesome subject to do. So it's much more about the advice we're giving people rather than biological preference towards a particular subject. So is it zero percent preference? I'm pretty sure it's zero percent preference. But what differences and preferences across men and women on average as groups, would you allow for? What differences would I allow? Probably that men are more likely to be physically aggressive, more likely to be violent and that in no way maps into professions. They're larger and taller and they can run faster. OK, I don't think that I think that, you know, the size difference is probably the one I would like I, you know, I don't want to force anyone to study physics and engineering. I don't want to force any man to do psychology and drama if he doesn't want. But I do want a world where we stop telling people that they are because of their gender, they have some opportunity or some other opportunity. And we just get to a point where we're actually giving people the training and the support they need to go out and take on the challenges that the world is facing. And we we get away from that kind of conversation. And yeah, I don't find it very useful at all. Wikipedia, by the time this episode is released, you'll probably have written significant parts of over 2,000 Wikipedia pages. How should we improve Wikipedia? I think Wikipedia is a phenomenal project. I think, you know, it started more than 20 years ago at the beginning of the Internet, this democratized platform for sharing information and knowledge. It's kind of a beautiful idea now. I can't imagine Wikipedia working if you started it on this form of the Internet. It requires a huge input of kind of public service from volunteers. Every single page on Wikipedia is written by a volunteer and expert in a particular thing, someone who's fascinated by a part of history or a topic. And I really love it.  But we put you in charge. How do you make it better? Or is it perfect? It can't be perfect, right? I think it's a perfect vision. It's a perfect idea. And, you know, from working in universities, we have so much access to knowledge, largely taxpayer funded access to knowledge that people don't have. So we do have this responsibility to take that information and give it to them. Unfortunately, Wikipedia does have huge gaps in its content because of the types of people who edit it. So because you've got a relatively small group of people who edit Wikipedia a lot, do this huge public service in creating content, the majority of them are men, the majority of them are from the Northern Hemisphere. They're mainly men from North America. You have certain gaps in the type of content that's on there, particularly in biographies of women, anything to do with kind of current science is quite badly written about on Wikipedia because lots of academics don't see it as a good time investment. So if I was going to change Wikipedia for the better, not that I think it, well, I do think it could be a little bit better. I would work on improving those content gaps. I'd work on really saying we need more academic people to start contributing their time to editing this. You know what it's like working in a university, getting people to want to teach and not just do their research all the time. Actually, we need to focus on this public service act of giving people access to knowledge, but we really need to start rectifying some of these content gaps about the global south, about emerging science, fixing pages about climate so that we provide non-partisan information to lots of people, but also on kind of detailing the contributions of women to all aspects of society. Now, I focus on science and engineering, but there are women doing awesome things in casting and movies and in writing. And I think we need to start telling that story, too. What if I said something like the following hypothesis? Autistic people very much enjoy organizing information. Males are much more likely to be autistic than women. Autistic people therefore really like Wikipedia. So it's no surprise it's a matter of preference that there are so many male editors on Wikipedia. And that's a kind of scientific claim, right? It could be true. Maybe it's even likely to be true or not. I think before we test that sign, we should probably get data. I think there's probably a huge number of autistic women who would say that actually it's just very underdiagnosed in women, because they socially assimilate to take on the very virtues or the, you know, the stereotypes that you as a woman have to have as a young person in society. And so they kind of put a blanket over issues of autism, but I'm not going to go there because I'm not an expert, but I think that's what they'd say. But actually, I think everyone gets excited about this kind of contribution to open knowledge. I've done, you know, I've written a bunch of Wikipedia pages, but I've also trained a lot of people in how to edit Wikipedia, you know, from from young people in high schools to academics at universities to members of the general public. And they kind of find it awesome this idea that you can research something, pull together all of these different sources, maybe do some kind of history aspect and go through archives and then write something that's actually on the internet. You know, if you tell a high school kid who's used to writing papers that sit in a desk and then eventually get shredded, you're going to write something that the whole world will see. Everyone gets excited about that irrespective of their gender or of their ethnicity. So I think we we should do the study. We should get the data and try and find out how many Wikipedia editors are autistic, but but more just kind of creating this ecosystem where people who get this opportunity to learn and find out awesome facts also feel that social responsibility to give that back and give that access to everyone else in the world, because maybe Wikipedia isn't so important in North America or Europe where we have free and open access to a lot of literature or a lot of texts or we have popular science publishing. But in other parts of the world where they don't have access to that actually having Wikipedia is completely critical. So I wish we'd we'd get away from this kind of blame and and it's just like the women's scientist thing, you know, a lot of people get angry that these kind of topics aren't on Wikipedia. And instead of getting angry, I think you should just do something about it, right? So it takes nothing to contribute and to edit and to learn how to edit and everyone should sit there and and give everyone in the world this access to the knowledge that they have. Will GPT models take significant significant market share from Wikipedia? Because if you type in the name of an obscure female or just obscure scientist into chat GPT or its successors, it will give you a lot of information. It's not perfect, but actually the more obscure the person, the more likely it is to be accurate. I think I don't think it will take away from Wikipedia. I think the kind of beautiful thing about Wikipedia is you can interrogate it quite a lot. You know, you can see who wrote what, when they wrote it and when that reference was added, what that reference is. You have that kind of talk dialogue behind a Wikipedia page. So most people just land on the read aspect of Wikipedia.  And you have a discussion around what is and isn't on the page. I think things like chat GPT are very useful at giving you a kind of very quick answer.  But I think the ability to interrogate it and to look at again, coming back to my earlier points, really where it looked for that information, you know, has it been broad in where it's collected that from? Is it using actual appropriate citations and literature? You can't do that, right? So Wikipedia is still important and for showing people, this person really did the homework on pulling this very non biased page together. And that's why you can trust it. You can keep on interrogating GPT models, but does it at all induce you to rethink what you're doing because obscurity, per se, is no longer the barrier? Like literally everything, everyone is in chat GPT in some sense. So the kind of beautiful thing I think about Wikipedia is that when when I land on Wikipedia, I don't usually go on it to type in the name of woman scientist.  One goes on it and types in climate change or number theory or some kind of thing that they're interested in. And then some or, you know, the name of their high school or their university. And then they look through the alumni or they're just clicking around and they find their way to this page. And I love that like the kind of sleuthy, stealthy part. You're saying these women are here or these black scientists are here or these scientists from Africa are here. And you've just not found out about them yet. But they're learning about it because of the topic that they're interested in. And I worry that if you have something like chat GPT and you go on and you ask it one of these questions, like tell me about number theory and it will just give you the answer about that and potentially the few, you know, big men names in the field, but you'd miss that chance to do that kind of beautiful weaving that you do around Wikipedia that bouncing around things before you land on that page about that women scientists. So I don't think that my work here is entirely futile just yet. And actually, you know, part of what Wikipedia has really shown me is women are just not getting enough awards for science. So I spend a lot of my time not only researching these people, but also writing citations for people to become fellows or get big awards and medals and honors. And I think I can keep doing that even if chat GPT takes over my evening job of editing Wikipedia pages. If I think of my own work, typically I prefer not to know say how many people listen to a particular episode of the podcast or read a particular blog post. It's better not to know. So you write all these Wikipedia pages.  Do you like it that way? Or do you wish you had a way of measuring the efficacy of your output? I think sometimes it's useful. You can you can get page views. So sometimes that's useful as a kind of motivator for why people can get page views. Yeah, you can. I mean, I don't look at them because you prefer not to know. Well, I prefer not to know. But also that's not why I'm doing it, right? Like I just want these stories there. But I think sometimes if I'm trying to get particularly academics, get excited about editing and I'm like, well, there's 15 billion people who look at this every month and we did this Wikipedia edit on last time and a million people have already looked at the pages. Then they're like, well, I'm going to go on and write about the science I do then. But I do think that the thing I find amazing and isn't the kind of Wikipedia data and the numbers that come back but seeing how these people are then celebrated in the public eye and there was a phenomenal is a phenomenal mathematician that I wrote about called Gladys West, who is 91 now born in Virginia went to a historically black college in university, studied maths, became a high school teacher for maths before working for the US government and doing the calculations that enabled GPS. So she worked out how far from a perfect sphere the surface of the earth was so that they could put satellites around it and help us with navigation. And when I wrote about Gladys West, it was kind of the beginning of my wiki editing world is 2018. And there's very little about her online. You know, she was 90. She'd done all these things in the 60s and 70s. And she was is an extraordinary woman and but very little about her and really little honouring her and celebrating her. Now her Wikipedia pages up. She's in all of these lists of top women in the world. She's been inducted to the US Air Force Hall of Fame. She's won a medal from the Royal Academy of Engineering. Every time I see people talking about GPS, they're like Dr. Dr. Gladys West, the mathematician enabled this. So I don't want the metric from Wikipedia that tells me how many times that's been viewed.  And now we're starting to celebrate them. So I like that kind of I guess it's it's enabled by Wikipedia that the world is starting to honour them. A lot of the problems of science funding, I think, stem from the fact that bureaucracies ossify over time and once dynamic institutions become just very difficult to work with. Should we expect the same to happen with Wikipedia, which, of course, is a non-profit? I think it's interesting. I think you've got kind of I don't know if you've I don't know if you've had Wikipedia people on the podcast. Jimmy Wales, of course. He was a great episode. OK, he's just cool, isn't he? So cool to fangirl massively. But I'm going to listen to that also on the way home. But I do think that you've got an extraordinary culture in the Wikimedia Foundation, who are the people who facilitate Wikipedia. They're very global. You know, there's only about 200 people who actually work for the Wikimedia Foundation. They're very young. They're very enthusiastic about open source. They're very forward thinking in what this encyclopedia should be. And they're always pushing boundaries, you know, changing the interface, changing the graphic design, all of these different things to make the user experience better and the editor experience better. So I think that from that nature, because you'll have this push from the actual employees, we just need to do that part as the community that Wikipedia is serving to make sure that the editorship represents the kind of global community who read Wikipedia. So I think if we keep pushing for that, then it doesn't have to ossify and become backwards and archaic. We can we can keep progressing for something that's more and fair and equal and representative for everyone. OK, your own research, you'll be able to explain all of it for us. But there's four concepts I want to put on the table. OK, chiral materials, chiral materials, ramen spectroscopy, nanotech and quantum computing. Yeah. And what you do relates to all of those four, right? I hope so. I hope that I hope so on the quantum part. It's quite exciting. So so. So let's start with chiral materials. Tell us what that is. So chiral material because it underpins everything. We're going to go through all four and then you'll tie it all together. OK, very nicely, very succinctly. And so I work on functional molecular materials, so carbon based materials that can be kind of semiconductors. Semiconductors are received hugely useful for any kind of optical electronic device, solar panels, light emitting diodes. The chirality part is that these molecules can exist in these beautiful and weird and wonderful forms, but they can also exist as non superimposable mirror images of one another. That's what chiral is. So a great example is your left and your right hand. If you put them together, kind of palm to palm, their mirror images. But if you put one on top of the other, that they're quite clearly not. And we see that kind of non superimposable mirror image nature across multiple different length scales in the human made and the naturally occurring world. So you see it in electrons and photons. You'll remember from chemistry, you had spin up and spin down electrons. You drew out a little up and down arrow. You see it in left and right handed light. So light that twists clockwise and counterclockwise. We see it in molecules and we see chirality in things like shells in snail shells in wisteria barks. You see that twist that's clockwise or anti-clockwise. And there's a reason for that, right? Well, it's endogenous to something. Well, naturally occurring life, all DNA in human life or in plant life or anything on planet Earth is right handed. All sugars are right handed. All amino acids are left handed. There's some reason that that happens that life selects for that. We don't, we still don't know the reason that that's the case. And you have a hypothesis for it. The fascination of a lot of scientists. Well, there's one that kind of comes back to the quantum part at the end. But these molecules that I work with are chiral molecules. So they're molecules where well, some of them that I work with are just helices that they're kind of twisted structures where you connect these benzene rings together and because of the ways they're connected they can't lie flat in a plane. So they twist up or twist down. What I was trying to do with them particularly for kind of electronic devices is use that chirality, that shape to control the polarization of light that comes out. So to say if I've got this emissive chiral molecule a molecule that will emit light and it's twisted clockwise or anti-clockwise can we make the light that comes out left or right handed, certainly polarized. And that's really useful for display technologies because it means you can kind of double the brightness you get and reduce the power consumed. So from a kind of technological advantage point that's very exciting just from a photon side. But what's emerging for the reason for homochirality of life on earth is that not only do they emit twisted lights but they also transport up or down electrons. So depending on whether you have a left or a right handed molecule you'll get a preference for up electrons passing through the system with ease or passing through the system difficultly. So it's more efficient transportation with chirality. Depending on the handiness of the molecule and the spin of the electron which is quite kind of revolutionary from trying to control not only charge transport but spin which would enable a whole bunch of new technologies involving in aspects of quantum. But people are trying to push within the chirality community that this could also explain the reason for homochirality of life on planet earth because electron transport is much more efficient if you only have these electrons moving only in one direction and they're pushed through by the shape of the structure. Lots of things like chlorophyll, a chiral lots of these kinds of forms that you have proteins, a chiral. So is that shape that very structure to enable this efficient electron transport that makes things life on planet earth happen more smoothly. So there are various theories of that. I'm not sure how much I'm on board with them yet. But part of the program here is to use these insights to build new semiconductors taking that term rather broadly which are based on different materials and they're more flexible. That's like the end. That's the end goal. Not only giving you this new flexibility so that carbon-based lightweight easy to process, relatively low environmental impact much less so than the semiconductors we use at the moment but also that you get these kind of new functionalities like generating really twisted lights or generating really highly spin polarized electrons that can enable you to go out and do things that are more useful for the kinds of technologies we're creating. So if you could create some kind of chiral molecular thin film that at room temperature could spin filter electrons can that enable some kind of quantum tech thing to happen much more efficiently without the huge infrastructure that we need at the moment to enable and to kind of enlarge these quantum properties. So we don't have to do it at cryogenic temperatures. We don't have to have extraordinary pressurized compartments to be able to do this. We can just do it on a bench top with some kind of molecular material. So that's the end goal. Not only to take a technology that already exists and say, hey, we can do it more efficiently but give it new functionalities that we couldn't before by controlling the shape of the molecule. So there's even a possibility maybe speculative there could be biological semiconductors broadly construed even biological parts of quantum computers. Am I mishearing you? There's a part where we learn from biology and could use it in some kind of quantum realm. So we'd learn from something like DNA we'd learn from the topology of DNA this chiral shape and we'd use it to filter electron spin or to detect photon spin and then we'd use that to enable some kind of quantum sensor. Definitely that I wouldn't all have to be super cold. There's not, it won't have to be super cold. That's a very exciting thing. If it works, if we can kind of systematically produce these chiral structures in a really ordered and beautiful way. If we do the science to get it exactly right and have the theory behind what's going on at the moment, there's huge excitement because people have these experimental results and they're like, whoa, let's go and change the world. But the kind of backup theory for why these processes are happening is still not there. It's still not got a kind of universal agreement. So I think molecules will provide us a whole bunch of new opportunity in quantum that we've never seen before. So the spectroscopy part of what you do, spectroscopes, you can use them to judge like if food is rotten, if the painting is authentic, if something is an explosive, and what do you use them to do? Yeah, spectroscopy is a huge encompassing and wonderful term as you've just illuminated in those examples. Basically, normally spectroscopy is, you shine a light on something and you see what light is transmitted through or reflected from it and you work out what that thing is because you're looking at the electronic structure. Raman spectroscopy, which is the type that I'm particularly excited about and you can use it on paintings, is a vibrational spectroscopy. So instead of looking at electronic energy levels, we're looking at vibrational energy levels. But long story short, you sign a laser on a molecule or on a material or on a painting. You make all of the bonds, the chemical bonds within that structure start to vibrate. So if there's a kind of carbon-carbon stretch, that will start to vibrate and do these word in wonderful stretches. And then that, as a result of that vibration, scatters the light that goes back at a slightly different energy to the light that you shine on it. And you get this Raman spectrum, we call it, but you get a spectrum, which is a kind of extraordinarily molecular fingerprint over all of the different chemical bonds within your structure and how they're arranged and ordered with respect to one another. So I can then take my molecule, take my material, put it under this laser, find out exactly what's there, but also how kind of ordered and arranged these things are. If I'm trying to make something for a quantum application, I want them to be super well-ordered and super well-oriented and I can't ask the molecules what they're doing. They're way too small to see with an optical microscope, but I can use this vibrational spectroscopy to work out exactly what's going on and I can do it in situ. I can find out what's happening when I apply charge to it or heat it up. So you can work out a huge amount just from this interaction with light. Raman spectroscopy is just, I love it because it's so versatile. I can shine, my friend does, we did our PhDs together. He did Raman spectroscopy for solar panels originally. He's called Joby, I should say. He then went to work for NASA on the Mars 2020 mission, doing the Raman spectroscopy for the Sherlock instrument, which is on the Mars rover, which is out there at the moment, collecting data from Mars and looking at the organic signatures from their Raman spectra. He's now in the Natural History Museum, looking at microplastics that are found in birds that are washed up on the beach using spectroscopic Raman signatures of their kind of exact molecular packing and confirmation. So it's just this technique that takes you to all of these wonderful places centered around this amazing vibrational effect which we can't see. So it just seems like magic to me, which I just really love. So this could make nanotech more effective, possibly. So it's actually a really fantastic and perfect point. We use it at the moment to optimize the way we process these materials. So I've got amazing chemist who's made this beautiful molecule. I want to turn it into a thin film to put into a device. I'll work out exactly how to do that really efficiently by doing some microscopy, but doing a lot of the spectroscopy to work out, how do I perfect the recipe to put it into that device? If we could do that kind of in line in manufacturing processes, which you do a bit in organic semiconductor industry, then you'd have this really efficient way of creating a technology where every single time this is what the molecules are doing and that's how we're gonna put it in. I'm sure they do it in display manufacturers already, but that's kind of how it envisages. So let's say this research program goes fairly well, not utopian well, but say 90th percentile well. 30 years from now, what will we see or what will I use or what will I have? That will be the result of this. Or is it 50 years or how do you think about that stuff? I think kind of five years from now or probably even less because display manufacturers are so extraordinarily quick the way that they innovate. You'll see chiral molecules being the active layer of your LED display. So if you've got an Apple iPhone or I think Nintendo Switch has an OLED display or if you've got a massive OLED television at home, you could kind of double the efficiency of those displays by just using something that emits certainly polarized light. We're working on that a bunch in academic research, but display manufacturers are on that too. So kind of five years you'll have that and your power consumption, you will only see it in that your battery won't be drained as quickly because you won't be pushing all of this power into generating light from a pixel, which isn't very efficient because you'll have increased that efficiency. I think probably kind of 10 years from now you'll see quantum technologies that are enabled by molecules and particularly by using the topology and the shape of those molecules to make them more efficient that can do this room temperature operation and probably chirality will have some big role to play in that. But like with all areas of science and all areas of any academic aspect that we're studying and probably lots of conversations you've had around these tables, there's a lot of jargon, there's a lot of words, chirality is an important and useful word for me. It means a lot of different things to people in the quantum world. You know, you can have chiral electrons, you can have chiral phonons. So probably it will be hugely important, but what particular aspect of chirality I'm not entirely sure yet. But in terms of a new item, so we can make screens better, we can make batteries last longer. Maybe it's too early to say, but what new good or service could we expect? Again, assuming things go fairly well. I think a lot around optical communications and encrypting data transfer and things like that, you know, if you can harness circular polarizations of light, you can multiplex the way you send data, you can make use of left and right handed channels, but you can also encrypt the signal that you're sending because only the sender and the receiver know what to expect based on the kind of chirality of those patterns that are produced. So I think probably in some kind of encrypted optical communications, you'll see this, but again, not know entirely that that's what's happening, but making efficient and more efficient and more kind of more impactful technologies like that. We will entirely have the particular aspect that I'm really excited about at the moment, other than all the other work I do because I love everything I do, but is trying to use chiral structures to be able to detect really weak magnetic fields, particularly kind of the magnetic fields associated with brain functions. So when neurons are sending signals around your brain, they generate these tiny magnetic fields. If you could use some kind of chiral structure to be able to detect those magnetic fields optically, you could generate some kind of medical imaging system that was much more flexible, again, could operate at room temperature. So I think you'll see innovations in things like medical imaging and also in optical communications. Now I can pick up popular science magazines and they will tell me sometimes we have quantum computing now, how accurate is that? Well, I think you've got some kind of systems with a very primitive number of qubits that can do some kind of calculations, these quantum bits, and they can do some kind of mathematical calculations much more efficiently and quickly than their non-quantum counterparts. I think getting enough, and I'm really not an expert in this, but getting enough of those qubits to work in harmony to actually do anything that's computationally useful for you or I is way, way off where people are currently at. And at the moment still, I'm not sure if you've visited any labs that are doing this or any companies that are doing this, but they have these kind of isolated molecules trapped in vacuum chambers or they have these cryogenic chambers where they've got a hundred different qubits in a room the size of a football stadium, each there trying to connect and interact with each other. I think that's a long way away from what we can imagine happening in our own personal homes or in our companies or in our lives. So whilst people have demonstrated that quantum computation is possible, we're really, really far away from it being societally relevant or useful. And maybe we don't need it right now for the types of things that we're gonna need to do. Let's say we put you in charge of science funding in the UK. Thanks.  Apart from the question of how much should be spent, right? Cause scientists will always want more spent, but put that aside, for any given level of funding, how would you change the system? I would probably try and shift the narrative at the moment from judging people based on their resume or their previous track record. We have a huge amount of institutional bias in the UK. If you work in a few universities, you're much more likely to get science funding than if you work in others. And if you are judging people based on their resume, which we do, we submit our CV, we call them, and also our research proposal. And people often look at the CV first, check where you work, check if you've had career gaps, check all of these things that they're quite biased about. And that impacts their likelihood to kind of fund your science. The DFG, the German Research Council, quite progressively a few years ago flipped it, so they no longer got people to check the resume and just evaluated based on the proposal of the research. And it was much more democratic and fair and gender-balanced because you didn't have that bias creeping in in that. So I'd change that. But more fair, more balanced. Does it give you better outcomes? People are just as innovative, just as kind of creative and just as wonderful at doing that science. I think there was a really interesting paper recently that looked at the impact of kind of institutional privilege on generating number of science papers. And it wasn't that people were making more breakthroughs, it's just that they had more opportunities to make those breakthroughs because you've given them so much money to be able to do it. So I'd get people to judge based on the research that was being proposed and the infrastructural support that they'll get to be able to do it. I'd also think we probably need to have kind of, and I think this is starting to happen. We have a national quantum technologies program here. There needs to be a really serious look about how we create materials and technologies that are actually going to benefit society and not just be these things that we have to cryogenically cool or do it in extraordinary vacuum chambers and get a little bit more creative and forward-looking at looking at new molecular materials and thinking about these new challenges to make sure that we make these technologies. So from a very personal, very, I'm not being very responsible for everyone else working on materials. I'd say we need to invest more in molecular materials, but I'd also say we need to get rid of these biases, things like making sure everyone has equal opportunity to prepare for interview, making sure everyone has equal opportunity to put the time into writing a proposal. I wrote a bunch of proposals last year, which completely exhausted me, but would take a month to write this perfect- Sure, but isn't that totally wrong? Shouldn't we make the proposals three pages? We should make the proposals three pages and we should make sure everyone has the same support to be able to write those. You can be at one- But that will just up the requirement. Why not take away the support and just impose three-page maximum, nothing else is considered. You attach a PDF, but it won't be read. Wouldn't that be better? Well, again, then we're just gonna favor the people who are in places or have this prior history of writing these things and can write these savvy three-page proposals, right? We need to give people the support to be able to write them and give them something I've seen a lot, not only on kind of trying to improve things for celebrating women scientists, but it's just this complete inequality and equity in the way that we give people support and access, this kind of hidden curriculum in academia has a huge influence on the type of science that we fund. So I think, sure, reduce the page count. I had to write something recently for an American funder where they were just like, just write 20 pages. And I was like, what do you mean just write 20 pages? So I think definitely reduce the page count. But I think beyond that, we need to make sure everyone's getting the same opportunity to write those perfect three-pages because at the moment we don't, which is why we see biases in what's coming out in who's being funded. Stuart Buck has argued we should fund basically people, not projects in most areas. The ARC Institute in California connected to Stanford has more or less that approach. Do you agree, disagree? I think it can be absolutely fantastic and transformative. And especially in things that are kind of clinically relevant, having these amazing institutes where you've got clinicians working with basic research scientists and computer scientists and analysts, fantastic. I would say we're still at risk there of creating these little empires where certain people gets huge amounts of scientific funding and other people don't have that opportunity in that seat at the table. So sure, fund people, but make sure that we're representing an equal and fair in the decisions of who we fund. But isn't fairness overrated in the sense that there's meritocracy and there's fairness and there's some tension between the two? And why always side with fairness? Because I don't think we're getting the most disruptive or exciting scientific ideas at the moment from just funding the few big people who've always had science funding. You know, I can think of a few people in the UK who consistently get big research grants and I don't think their labs are producing massively innovative or exciting stuff. They just consistently have this money thrown at them. So I would say the pursuit of fairness is because we want science that is exciting and impactful. And at the moment we're not seeing that, we're just seeing the same people get huge multimillion pound grants. What did you learn writing a children's book about nanoscience? That children's publishers don't want you to write a whole book for a six-year-old about vibrational spectroscopy. I think that I was, I mean, it was just a huge opportunity to be able to write it. It made me very proud to do what I do.  But also that we don't do enough to get young people and parents excited about material science and chemistry. You know, you go into a bookstore and all of the books for kids are about dinosaurs, about space or like gross things about the human body. But they're not like his amazing materials that you can use as a solar panel or potentially will become a quantum computer one day. So I think that it made me think a lot more about that. Like our responsibility is people who work in materials of going out and talking about these things to young people. And you know, the public response to it has been absolutely extraordinary. I thought, you know, non-fiction hardback kids. So it's a really hard sell. Luckily it was illustrated by a phenomenal woman, Melissa Castrion, who's just got this beautiful whimsical approach to illustration. It was her first non-fiction book. And when she was asked to do it by the publisher, all of her illustration friends were like, don't do it. Nanotechnology will be so dry. But I'm very glad she did it because it's completely beautiful and that's probably helped get it into people reading it. And but it's been translated into all of these different languages. It's got all these stars, these American literature, you know, guilds, these library prizes, which I never dreamed possible. But I think it's just because materials are really exciting. And I had to do no work to make that book exciting. She did some to make it beautiful. But I think it's just showing me people in the world want to read about this. Again, to our listeners, the title is Nano by Jessica Wade. Should academia reward that kind of project more than it does right now, which is either zero or negative, as far as I can tell? Yeah, zero negative is right. Probably negative. A lot of people are just like, oh, she's not very serious about the science she does because she does this. I think that academia should reward anything that is kind of taking the science or the outcomes of their research to a bigger audience, right? Whether it's something like going out and giving public lectures, whether it's something like doing a kid's book, that's fantastic. Is there a way to fix that without de-emphasizing peer review? I think some people, yeah, right. My peer review was the editors. But I think some institutions are a lot better at that than others, some institutions in the UK, a lot of institutions in the US will recognize that public service aspect of what you do in promotion and in recruitment and they'll see it as something that's really positive. I can think of a few absolutely phenomenal professors who have really incredible research programs and some very public-facing aspect of their work or some people who work on really huge innovative parts of reforming education. We have less of that in the UK than what you have in America. You could shift it a little bit. We're trying to at the moment, one of our big funding councils has made fellowships where 20% of your time can be on something like policy or like looking at equity, diversity, inclusion. So it's starting to happen. But I still love all the other parts of my job. I love being in the lab and I absolutely love teaching undergraduates. So I didn't write this book because I wanted academia to be like, oh, children's books are really valuable. But it is interesting because I've had so many emails afterwards from academics who are just like, I'm thinking of writing a kids book too. Like, can you give me some advice about this? So obviously a lot of people are thinking about it.  Does that create an imbalance with your colleagues or do they just not know? They're in too much of a fog. I'm definitely not the most famous person.  There are a lot of very awesome people there. I think probably, I don't know. I think probably people think of you, it comes back to the earlier points about it being negative. People think of you and judge you just for that. And so you have to constantly be doing like, I love the science I do. So you're constantly doing this awesome science as well.  You've always got to kind of prove them wrong. So you definitely have that. Whether they dislike me because of it, I'll find out, I'll find out soon enough. I'm currently on one of those awful UK funding works. I'm on a fellowship, which is like a year and a half more funding. And so let's see, right? If everyone's going to push me out for writing this, then more power to another institution that gets me. What did you learn in your year studying art in Florence? I learned an awful lot of, well, I tried to learn a lot of Italian. I was very lucky to have a land lady who was a professor of history of art at a university in Florence and only spoke Italian and I spoke no Italian and was very junior. But also, you get this extraordinary perspective, which you do whenever you're in Italy, about how extraordinarily interdisciplinary and kind of multi-talented these Renaissance masters were. And obsessed with materials, right? Obsessed with materials, obsessed with innovative new techniques for painting, for architecture, for building buildings that you can't feasibly imagine working without a computer or without a huge infrastructure to be able to make it happen. The metallurgy of the doors, the woodwork, the kind of beautiful glass nanoparticles being used long before we'd be able to study and call them nanoparticles. You really learn that this idea that everything has to be in silos, that scientists are distinct from artists or craftspeople, was completely gone then. In Renaissance in Italy, they just didn't have that. You had to do everything. And then you go into high schools now and it's like you have to choose whether you're gonna do the sciences or the arts.  So it taught me a lot more about that. I obviously always knew creativity was very important for being a good scientist because if I'm gonna design an experiment no one's ever done or explain something in a way no one's ever explained it, you have to be quite creative to do that. But you get it so much reinforced when you're in Italy and particularly in Florence that before people could do this a lot and they didn't talk about it all the time, they just did it. Similarly though, they also didn't recognize the contributions of women and there's almost no, you know, Artemisa Gentileschi is one of the only women Renaissance artists or women artists that the world- And that's a bit later too. So and that is a bit later than when all of this stuff was happening and she also had a really hard time to get to being where she was. So you saw this idea of the kind of polymath, this idea that people could do science and art and perfectly well was celebrated but society still didn't value women. Last two questions. First, what is your most unusual successful work habit? Unusual successful work habit. I suppose it has to be the Wikipedia editing, right? Like I go into the lab or teach or whatever research proposal I'm writing every day and then I go home and after dinner I edit Wikipedia. And part of it is this advocacy and this, you know I really want these people to be celebrated and to be honored but I also get this huge chance to learn new things every single night that are out of the kind of little bubble that I'm in of learning about chirality and how that influences technology. I learn about a cool new spectroscopy or a cool new university I've never heard of or what people are doing for this particular type of technique. And then that opens my ideas and perspectives for something else. And actually, you know, I as a scientist and as a material scientist I'm very interested in new materials and new ways to study them. And so I'm always going around the world trying to do experiments with cool and interesting people. And one of the best ways to prepare for going to do that experiment is to write the Wikipedia page of who you're going to be with. So I was last week at this high magnetic field lab in France getting this opportunity to do solid state NMR. So to do nuclear magnetic resonance but of thin films and materials. And it's completely fascinating. Another one of these weird and wonderful magical scientific techniques but just writing the biography of the person I was going to work with and then I was really prepped for going. And if I'm about to see someone speak writing their biography before means I get this. So that's definitely my best work habit, you know. Do you write the Wikipedia page of what it is that you're working on? And final question, what will you do next? What will I do next? Well, I really, really want to make it an academia not just because of, you know, because I love the science but also because I really like this idea that you can try and do these little incremental changes to make it better for the next generation of scientists. You know, whether that's making scientific funding more equitable whether that's really shifting how we teach to make sure that we're teaching in a way that's preparing for this group of researchers to go out and change the world. Not just teaching because it's what someone's curriculum was 10 years ago but saying this is really exciting and this is what we want you to learn about now and you're in the university, you've connected, you've checked in, you want to be here, let's do it too. So the transformative education, the research and also this progressive idea of making it more fair and equal. I want to stick around an academia to make that happen. Jessica Wade, thank you very much. Thanks so much for having me.


This is the Army Today, a daily feature from around the globe. Twenty wounded warriors are among over 200 disabled athletes who will represent the U.S. in the 2012 Paralympic Games in London. Chief of Paralympics for the U.S. Olympic Committee, Charlie Huebner, says there's a great need in this country for programs for persons with disabilities. The U.S. Olympic Committee is very invested in developing programs at the community level for persons with physical disabilities to participate in sport. And that could be with your friends, with your family, to be physically active because we know the impact of physical activity on persons with physical disabilities. Eleven soldiers will participate in events in archery, cycling, shooting, sitting volleyball, soccer seven aside, and track and field. There are some unique sports to the Paralympic, but the most part the Paralympic Games are about elite sport and elite competition for athletes with physical disabilities. A swimmer since his youth, Navy bomb diffuser Lieutenant Brad Snyder, who lost his eyesight in an IED explosion in Afghanistan, will compete in swimming at the Paralympics. It means a lot to me to represent my fellow wounded warriors and go out and prove that there are no barriers that exist through these injuries. We can get out and we can have the success that we want to have and we can still represent our great country even though it's not on the battlefield. Lieutenant Snyder, who won gold at this year's Warrior Games in the men's 1500 meter run visually impaired category, says the Paralympics is a great avenue for athletes who are faced with adversity to experience success. The Games will be streamed live on Paralympics.org from August 29th to September 9th. Here he comes as Peacock got enough to hold him off and he dug. That's the Army Today.


Hey, hello there. So like I said, I'm Ron, and I'm part of the developer relations team looking after security, privacy, payments, and identity on the web. Now, what that boils down to is I'm here to give you a little flavor of the implementation detail for one of the advertising-related proposals under the Privacy Sandbox banner, specifically showing you where you and your dev team can get involved today. Now, we've got 15 minutes, so this is by no means comprehensive, but hopefully I'm going to set you up with a base for the patterns that you'll need to navigate the other proposals. Speaking of patterns then, one of the first challenges in this entire effort was defining what we mean when we talk about privacy. And specifically, it needs to be precise enough that it can be used in specifications and help us make decisions about what is in and out of scope for the work. So to do that, we've put forward this potential privacy model for the web, and the key aspect of this is sharding web identity. So let's take a look at what that means. The first concept is that identity is partitioned by first-party site. Now, what that translates to is this idea that your identity on site A is distinct and separate from your identity on site B and site C and so on. And this concept is what drives the work towards making this the default in web platform functionality, along with addressing the areas that allow joining of those identities, which in turn enables covert tracking. However, that doesn't mean total isolation. So composability is absolutely core to the web's success, and that's across enabling advertising, but also things like embedding videos, maps, running analytics, calling APIs, and so on. So first parties need a way to be able to delegate access to that first-party identity to third parties. However, the important point to note here is that it can be allowed access. So it's a privilege that a first party must explicitly grant to the third party. And likewise, that top-level identity is still sharded. So the embedded video on site A is not sharing information with the embedded video on site B. And so that leads on to the final concept, which is a per-first-party identity can only be associated with small amounts of cross-site information. And this is the pattern you'll see in many of the new APIs proposed for these existing use cases. So where previously, there would be a third-party cookie from site C that would be sent with the embedded content on site A and site B, and that would provide a single tracking mechanism or shared identity across all of the sites. And instead, the new APIs focus on using just the information required in each location and only sending the information required to complete the use case. And now, while I've drawn a direct arrow in the diagram there, that doesn't mean a direct real-time link between them. This can also be aggregate information that is separated from the individual identity on the sites. OK, so that was a little bit acrobic, but I need us to have this shared foundation. So now we can talk about how we go from the model to something you can actually implement against. Let's take a look at one of the proposed APIs then, the Event Conversion Measurement API, and see how that matches up with the model. So first a quick overview of the current process and where the issue comes in. I visit a site where I see an ad. The third-party provider has a cookie that they're using in order to track my interaction with the ad. In this case, I like the ad. It's probably one for yet another black t-shirt, so I'm going to click it, and I'm going to head over to the site where I'm going to buy it. Now, this site has a tracking pixel for the advertising service so that they can link my purchase of the t-shirt with my click on the ad and then make sure that all the right people get paid. They can check on performance of the campaigns and so on. Now, this motivation is fine. This is an important use case, and there's data that you need to make that work. The problem though, if we go back to the privacy model, is that we've lost that partitioned first-party identity. The cookie gives us a link that lets us fully join my identity on the site where I saw the ad with my identity on the site where I purchased the t-shirt and, of course, anywhere else I go with that cookie too. Now, let's see what we can do differently with the event conversion measurement API. First step looks almost exactly the same. Land on the site, display the ad, but there's no cookie involved. Instead, when I click on the ad, the API is going to record the click event and just store that on my device in browser storage. Now, when I convert on the target site, I still have the same tracking pixel there, but again, no cookie. Instead, the ad tech platform, when it serves that pixel, is going to issue a redirect with a bit of conversion data included, which is also picked up by the API and stored locally. Then, at some later point, the browser will send those reports over to the ad tech platform. So the key thing here is that the platform gets all the data they need to attribute the clicks, get people paid, measure performance, and so on. But they do it without an identifier for the individual. This also allows the API to build in additional privacy protection, such as delaying the sending of those reports, batching them, and adding a predefined level of noise to those reports.  So you could see from the diagrams for the infrastructure for the whole process remains mostly the same as the cookie version. So what are we adding on the front end? Now, this code is hot off the press, because we've been updating the attribute names as the proposal evolves. But I want you to see the mechanisms involved. I've got an anchor tag there for an ad, so just a normal link. But I've got these new attributes for the conversion and reporting URLs along with a limited attribution ID. Then I've got my tracking pixel here as well. That is going to trigger the redirect to a well-known URL, which is where the service can add the conversion data. Okay. I said we were going to talk about stuff that's real and that you can try, so you should remember this journey from Hany's talk. Specifically, we're going to zero in on the prototype and experiment phase to talk about origin trials. That's the stage that event conversion measurement is at now, along with some of the others, and we've got more in the pipeline there. Origin trials are effectively Chrome's way of allowing an origin, which is your site, to opt into some functionality for testing and feedback. And what I really want to stress is the experiment part. We go to origin trial because we are depending on real-world feedback from developers to iterate on the idea. So this is not like a dev-complete beta feature that we're expecting to just roll through to stable. The feedback we get during the origin trial often significantly changes the API, and may even result in it going completely back to the drawing board as well. So this is where Hany talked about the implementer role, and that is very much our target audience here. Keeping with the conversion measurement example, if you provide a service that includes conversion measurement, or you have a first-party implementation, then you're an implementer. If you use a third-party service for conversion measurement, that's the customer role. So you don't need to take action for the origin trial, but you may still be involved, and I'll show you how. But the key thing here, it's a two-way relationship with effort and time investment. So you should be getting involved in origin trials because you want to give the feedback to shape the APIs, and you're expecting them to iterate and change rapidly. So with that in mind, see how you can get involved. Hopefully it's relatively light process. You can head over to the origin trial site here, and it is going to show you all of the active trials.  You will need to fill out some information, unsurprisingly, about the origin that you want to register, along with some properties of where your token will reply and expected usage levels. Now, the token you'll get back is just a long string, which you then need to add to your site. This can either be in a meta tag in the page or an origin trial header in the response. Now, several of the privacy sandbox origin trials are a little bit different. So even if you've signed up for origin trials before, this bit may be new to you. This is also where the customer role is going to see some of these effects. So while I said many of these APIs are about providing those privacy-preserving approaches to cross-site use cases, which means that you are likely going to want that functionality in a cross-site context. However, you can't really get every single one of your customer sites to sign up, get a token, add it to their site, and so on. So third-party origin trials therefore allow implementers to enable the origin trial for their service when it is used in a cross-site context. That means for a conversion measurement, you'll see the little third-party checkbox. Check that. For third-party origin trials, we often do a little review before granting the token, so you may not receive it immediately. Once you do, though, and this is an important difference, your third-party script is going to be responsible for injecting the meta tag with your token on the first-party site. In other words, the site that is using your service. Do that, and you are good to go. OK, I told you it was real, so let's check it out. I am just going to show you slides, though, to talk you through it, but there is a link there, there. Yeah, there's a link there, and so you can feel free to follow along if you've got another browser window or a laptop. It is also linked from all the documentation, so you don't need to do it right now. You can jump in after the talk. So first up, a quick sidetrack into enabling flags. You don't need this for the origin trial, as the point is you can test on normal users, and you also need these particular flags, past Chrome 91, but I wanted to show you how we allow opt-in access to new APIs and behavior for developer testing. So this first flag here will allow you to specifically enable the API, and then we also have this second enable experimental web platform features flag, which we use as a wider bucket to get in progress features. Now, if you are following along, you probably shouldn't do this in the same browser you're using to watch the stream, because it will require restarting Chrome, and I don't want to lose you right now. OK, so the demo has three parts, and I tend to arrange them on my screen like this. It's a bit small to read. Don't worry about that. I just want to talk you through the process, and I'll zoom in on the important bits. We've got our example publisher site in green. If you open up DevTools, you'll see helpful instructions there from more to the demo together. There's also conversion internals in the top right. That's the internal Chrome page that shows you all the events the API is storing. And in red, we've got our demo ad tech server, where we'll be able to see the events coming in. So I see an ad for shoes here. I suspect some of us haven't had to wear them in a while, but I certainly feel like a bit of retail therapy is in order, so I'm going to go ahead and click that. That takes me to a product page where I can get ready to buy them. But before we do, I'm going to pop over to the internals page and click refresh. And that's going to show me the impression data from my click on the ad. So this is the on-device browser storage that I talked about before. You can see the extent of the data that's been collected. And if you remember the anchor tag I showed you earlier, it's those attributes that generated this. You can also always use DevTools in the demo to take a peek at the anchor tag before you click it. OK, so let's go ahead and get ourselves some new shoes. On our very lightweight confirmation page, you can see the pixel that we've got embedded from our ad tech provider. If you were to look in the network tab in DevTools, you'd also see that this is the request that goes to that dot well known URL via the redirect that I mentioned before. OK, over in internals, I also now have a pending report. You can see it's this report that is providing the link between the impression data collected earlier and the conversion data that our picks are added. So like I mentioned, sending of these is intentionally delayed to minimize tracking opportunities through timing, but the internal developer page allows us to trigger them all right away. So I'm going to go ahead and click that button, and there it is. The ad tech server receives the report with the impression and the conversion data. Now, I realize that sending two numbers from one screen to another is perhaps not the most exciting demo you've ever seen, but what's important here is the pattern. Instead of joining the identity across sites with a cookie, we've taken two cross-site events, stored them on the device, and then we've just sent the result to a third party. So that's the aspect to really take away from this. We start moving away from needing to join identity to link events, and instead create APIs that led the decision moved to your device, and it's just the result that gets sent on. OK, that's a little example of how we're looking to build our proposals that really do meet the use cases. And what I want to call out here is that the event conversion measurement API has already changed significantly. In fact, I think we may have changed the name for it as a result of the origin trial feedback. So we're really working in the open here to get something that is going to meet that balance of both capability and privacy. So if these use cases apply to your business and you can put developer time down to test them in real world scenarios, then origin trials are where we need you. We've walked through the conversion measurement one together, so I'm hoping you feel equipped to jump into some of the others. We'll continue to share details of those across our various developer channels. OK, that was quite dense, but that is if for me for now a lot to digest, but I will be back with you for Q&A soon. So let me know if there's anything that I need to clear up. And with that, I'll hand back over to Hanne. Thanks and see you later.


It's all about rhythm and timing, so. Can you put a percent on where you think you're at health-wise right now? I mean, I feel good enough to go, I feel like. And I'm only getting better, so. And what is the challenge like? Are we going to make it back this week? Best off? Yeah. Are you excited about that? And can you get to the full green tank I have ready for this? Yeah, of course. I think, yeah, they're leading the league in passing yards and touchdowns and all that stuff, so. I think, you know, every week a team has a certain identity and they're definitely known for throwing the ball, so. Appreciate it. How does it feel just to be back, being able to practice after this one? It feels great, you know. I was from the outside looking in, kind of like the kid eating his lunch alone, but now I'm with everyone, so. I'm excited. Do you have a chance this week, or is the process maybe going to be longer?  I just take it one day at a time, so. How eager and rare in that area? Yeah, very eager, but I also learn, like, you know, certain injuries you can fight through certain injuries you can't. I learned that the hard way, so I take it one day at a time. What were you doing to kind of get to this point where you can be at least designated for return? I mean, it's just constant rehab, constant body maintenance. Staying sharp mentally, so the transition from IR to, you know, where I'm at now is easy. And with that staying sharp mentally, you were still able to be involved in the DB meetings and all that? Yeah, 100%. And I was able to watch a lot more film than I'm used to, and a lot more than... I think some of the players, just because, you know, they're out practicing. I'm in here, I got nothing else to do other than get treatment, so.   What makes him so unique in that category?  How about their running backs? I mean, I'm not sure, you know, whenever we can, I would say. It's going to be tempo. We got to get out there and watch film and prepare the right way. I think we'll be all right. Nobody really talks about their running backs. How good are they? They're kind of an underrated group for them, you think? I think they have a pretty good set of backs. Seeing the rookie, he runs pretty hard. And then Clyde, he's been there. He runs, you know, as well. And they have one change of speed, power. I think they have a nice little group there. You guys obviously going with the same record. Do you allow yourself to think about the, you know, the swing aspect of this game in terms of seeding and all that stuff and playoff positions? It really doesn't. It's just another game for us.  We're going to prepare the same way we've been preparing these last few weeks.  You know, just the same routine.   But I just feel like as long as we're on the same page, you know, as a defense, I feel like we'll do a great job. You know, I feel like we have done a great job in the past, you know, mixing things up on them. So that's going to be key for us. I mean, I feel like that's the standard now for me, you know, so I have to be locked in at all times, you know, it's been times where I gave up a player to, but these games, you can't get those up, you know, because it's a big game, you know, as far as being in division, not division, but in the conference opponent. You know, these games count, you know, later down the road too. So it's just more of a reason, you know, to be locked in, you know, everything that I have to handle. Yeah. Right.