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Let’s try to guess what the near future of the VR/AR industry might look like if the key players of this market continue to develop in the way they are doing now. Everything is simple: it is a device, a helmet, or glasses weighing 300- 600 grams (sometimes more), with elements made of glass, plastic, or aluminum, and operation time of up to several hours. Undoubtedly, it looks great. Almost like in the science fiction novel “Ready Player One” by Ernest Klein. It seems that you can hardly enter the actual parallel digital reality with such a gadget in everyday life. Surely, it will be a disaster for your neck… I do believe the core problem is hidden in the philosophy of technology itself. I keep asking myself, why are we still trying to put a huge box capable of doing some calculations directly on top of our heads? Why do we do this instead of solving the problem in a more sophisticated way, with a device that is dozens (or even hundreds) of times lighter, smaller, and, more importantly, can be mass-produced? I do believe that the future lies in XR technology and spatial computing. Their potential is so huge and promising that an XR gadget can easily become a versatile device for any kind of purpose. Let me explain what I mean by this. In my ideal world, such a gadget would be used not only to display some entertainment content but also to address healthcare issues and communication and, perhaps, for us all to evolve into something more as a biological species. Still, let’s not jump ahead of ourselves. Now seems like a good time to give you some more detailed explanations of what VR, AR, and XR are. VR or Virtual Reality — is a virtual reality where a user only sees a digital environment. One can view this environment by using a special gadget. AR or Augmented Reality— is an augmented real world. The user has some kind of gadget through which he can observe the surrounding real environment. But, at the same time, he can see the added digital objects around him. Finally, XR or Extended Reality is the common definition of a whole set of virtual technologies. XR covers a wide range of hardware and software solutions, including sensor interfaces, apps, and their infrastructure. The point is that XR can be used widely, from gaming to completing business tasks in healthcare, architecture, education, and so on. The applications are essentially limited only by your imagination. It seems that the current VR industry is an absolute dead end. That is because the main focus is on VR/AR technology, which, by definition, has limited functionality. But, to prove this, we’ll have to go back deep in time, about a century or so! So, within this manifesto, we’ll try to answer the question of what the future holds for us. I’m Roman Axelrod, the founder of XPANCEO — let’s figure it out together! The History of VR Do you want to know what I find the funniest? The idea of an augmented reality device was conceived back in 1935. At that time, the novel “Pygmalion’s Glasses” by American science fiction writer Stanley Weinbaum was published. According to the novel’s plot, one professor invented spectacles that let you create an optical, auditory, gustatory, kinesthetic, and olfactory illusion of reality. Note that Pygmalion’s Spectacles actually had all the features that modern devices promise us. They even look like the standard AR glasses. Remember these — Pygmalion’s Spectacles. We’ll need them later on. From the early 50’s and right up to the early 90’s, while the technology was being mastered, a great number of unordinary VR gadgets were developed. And they were all supposed to function like Pygmalion. Initially, such gadgets occupied half the space of a room. For example, the Sensorama “film booth”, which was designed and developed by cinematographer Morton Heilitt in 1956. Inside it, there were film projectors displaying images and speakers playing stereo sound. There was even a vibrating armchair and a device to simulate odors! By 1968, the American scientist Ivan Sutherland introduced the very first computerized VR- helmet called the Sword of Damocles to the public. The device, which looked a bit like a medieval torture tool, could smoothly produce simple 3D models of various geometric shapes. It could also change the position of the head in the environment to change the image perspective. “The Sword of Damocles” At a glance, these prototypes look absolutely bizarre. You are supposed to put this incomprehensible box on your head and make yourself feel uncomfortable just to watch some content. Everybody understood that the world needed VR, but the way it was realized seemed odd. However, these were the computer games that boosted the industry's development the most. By the way, they did it twice while VR technology was still in existence. Early 90's Since the early 90s, all kinds of VR helmets, hand-tracking gloves, and other nice stuff for immersing yourself in the digital world started to take over the mass market. Nintendo, with its Virtual BoyLink, was one of the key pioneers in this field. Forte VFX1 helmet with MS-DOS on-board lets you play the shooters of that time in VR.    No doubt, DOOM looked impressive in such a headset. In total, dozens of devices were introduced to the market. However, by 2000, the VR boom began its downturn. For sure, each device of that period was a true engineering masterpiece and a miracle. Now, it’s hardly believable that all these gadgets were created 20 or even 30 years ago! Still, the following drawbacks emerged: Exorbitant cost
Awkward and unfriendly ergonomics
Short operation time
No content
Lack of comfort for daily use (weight does make a difference!) Does that ring any bells? Exactly! All modern VR gadgets have the same drawbacks. Come on, in the whole time the industry has existed, has no one figured out how to deal with it, or made any conclusions? It’s absolutely clear that if a technology does not evolve throughout a significant period of time, it’s a dead end, isn’t it? VR Today Anyway, the VR industry has successfully plunged into the abyss of oblivion for decades until it resurrected again, primarily because people do love VR. You probably know what I’m talking about. This is Oculus Rift — the resurrection of VR. It’s the young guy known to us as Palmer Lucky, who literally turned into a techno occultist and pulled the entire industry out of the grave. Palmer has been crazy about VR since his teen years. His holy grail was to create the VR helmet of his dreams. After creating a prototype, he launched his project on Kickstarter in 2012, and it was a huge success. And a true renaissance broke out! 600 days after the project’s launch, Facebook acquired Oculus Rift. At the same time,** Valve** started to develop its own helmet, and even** Microsoft** announced its VR developments. And Apple’s Vision Pro helmet became the pinnacle of the trend. So, Vision Pro had two in-built 4K 100Hz Micro-OLED displays on board. The viewing angle — 110 degrees. To interact with the outside world and track the user’s positions, engineers equipped it with 12 cameras. It sounds great, but don’t forget that it weighs 600 grams. The external battery life varies from two to four hours. And the base version will cost you 3500 USD. All in all, it is really well made, and it costs a whole lot of money. And the rocks we’re chipping away at are still the same as decades ago: Uncomfortable


Large


Weighty


No content


Short operation time So, the industry giants joined the race. But, to be honest, all the engineers achieved either in Vision Pro or in Meta Quest was just upgrading the hardware and fitting it into a form factor from the 90s. Personally, I call it the Curse of Pygmalion. Almost a hundred years ago, Stanley Weinbaum set the standard that today’s engineers are trying to reproduce. If we take a look at the PC market, the development of VR started exactly in the same way. In the beginning, there was a huge machine that occupied an entire room. Then, while the technology developed and matured, its dimensions decreased. As a result, now we have smartphones. However, if we are talking about VR gadgets, their development stopped somewhere in the early 90s. Sounds like a dead end, doesn’t it? Let’s say Apple upgrades its helmet and equips it with, for example, an M10 chipset and the most advanced cameras of that time. The gadget would work ten times faster and display incredible image quality, but it would still be a helmet with, most likely, a limited field of view, and you would still have to wear it on your head. It seems like we humans have already gone down the wrong path of VR gadget development. We try to fit very complex components like screens, cameras, or batteries into a small piece of electronics. Instead, we have to figure out how to avoid doing so. But before we get down to this issue, we really do have to speculate a little about another important thing — AR glasses! Most importantly, we’ll finally find out what kind of device is to become the key XR gadget. So, stay tuned! To Be Continued… Let’s try to guess what the near future of the VR/AR industry might look like if the key players of this market continue to develop in the way they are doing now. Everything is simple: it is a device, a helmet, or glasses weighing 300- 600 grams (sometimes more), with elements made of glass, plastic, or aluminum, and operation time of up to several hours. Undoubtedly, it looks great. Almost like in the science fiction novel “Ready Player One” by Ernest Klein. It seems that you can hardly enter the actual parallel digital reality with such a gadget in everyday life. Surely, it will be a disaster for your neck… I do believe the core problem is hidden in the philosophy of technology itself. I keep asking myself, why are we still trying to put a huge box capable of doing some calculations directly on top of our heads? Why do we do this instead of solving the problem in a more sophisticated way, with a device that is dozens (or even hundreds) of times lighter, smaller, and, more importantly, can be mass-produced? I do believe that the future lies in XR technology and spatial computing . Their potential is so huge and promising that an XR gadget can easily become a versatile device for any kind of purpose. I do believe that the future lies in XR technology and spatial computing Let me explain what I mean by this. In my ideal world, such a gadget would be used not only to display some entertainment content but also to address healthcare issues and communication and, perhaps, for us all to evolve into something more as a biological species. Still, let’s not jump ahead of ourselves. Now seems like a good time to give you some more detailed explanations of what VR, AR, and XR are. VR or Virtual Reality — is a virtual reality where a user only sees a digital environment. One can view this environment by using a special gadget. VR or Virtual Reality AR or Augmented Reality — is an augmented real world. The user has some kind of gadget through which he can observe the surrounding real environment. But, at the same time, he can see the added digital objects around him. AR or Augmented Reality Finally, XR or Extended Reality is the common definition of a whole set of virtual technologies. XR covers a wide range of hardware and software solutions, including sensor interfaces, apps, and their infrastructure. The point is that XR can be used widely, from gaming to completing business tasks in healthcare, architecture, education, and so on. The applications are essentially limited only by your imagination. XR or Extended Reality It seems that the current VR industry is an absolute dead end. That is because the main focus is on VR/AR technology, which, by definition, has limited functionality. But, to prove this, we’ll have to go back deep in time, about a century or so! So, within this manifesto, we’ll try to answer the question of what the future holds for us. I’m Roman Axelrod, the founder of XPANCEO — let’s figure it out together! I’m Roman Axelrod, the founder of XPANCEO The History of VR Do you want to know what I find the funniest? The idea of an augmented reality device was conceived back in 1935. At that time, the novel “Pygmalion’s Glasses” by American science fiction writer Stanley Weinbaum was published . According to the novel’s plot, one professor invented spectacles that let you create an optical, auditory, gustatory, kinesthetic, and olfactory illusion of reality. “Pygmalion’s Glasses” was published Note that Pygmalion’s Spectacles actually had all the features that modern devices promise us. They even look like the standard AR glasses. Remember these — Pygmalion’s Spectacles. We’ll need them later on. From the early 50’s and right up to the early 90’s, while the technology was being mastered, a great number of unordinary VR gadgets were developed. And they were all supposed to function like Pygmalion. Initially, such gadgets occupied half the space of a room. For example, the Sensorama “film booth”, which was designed and developed by cinematographer Morton Heilitt in 1956. Inside it, there were film projectors displaying images and speakers playing stereo sound. There was even a vibrating armchair and a device to simulate odors! Sensorama Sensorama By 1968, the American scientist Ivan Sutherland introduced the very first computerized VR- helmet called the Sword of Damocles to the public. Sword of Damocles Sword of Damocles The device, which looked a bit like a medieval torture tool, could smoothly produce simple 3D models of various geometric shapes. It could also change the position of the head in the environment to change the image perspective. “The Sword of Damocles” “The Sword of Damocles” At a glance, these prototypes look absolutely bizarre. You are supposed to put this incomprehensible box on your head and make yourself feel uncomfortable just to watch some content. Everybody understood that the world needed VR, but the way it was realized seemed odd. However, these were the computer games that boosted the industry's development the most. By the way, they did it twice while VR technology was still in existence. Early 90's Since the early 90s, all kinds of VR helmets, hand-tracking gloves, and other nice stuff for immersing yourself in the digital world started to take over the mass market. Nintendo, with its Virtual Boy Link , was one of the key pioneers in this field. Virtual Boy Link Forte VFX1 helmet with MS-DOS on-board lets you play the shooters of that time in VR. No doubt, DOOM looked impressive in such a headset. Forte VFX1 No doubt, DOOM looked impressive in such a headset. In total, dozens of devices were introduced to the market. However, by 2000, the VR boom began its downturn. For sure, each device of that period was a true engineering masterpiece and a miracle. Now, it’s hardly believable that all these gadgets were created 20 or even 30 years ago! Still, the following drawbacks emerged: Still, the following drawbacks emerged: emerged: Exorbitant cost Awkward and unfriendly ergonomics Short operation time No content Lack of comfort for daily use (weight does make a difference!) Exorbitant cost Exorbitant cost Awkward and unfriendly ergonomics Awkward and unfriendly ergonomics Short operation time Short operation time No conten t No conten Lack of comfort for daily use (weight does make a difference!) Lack of comfort for daily use (weight does make a difference!) Does that ring any bells? Exactly! All modern VR gadgets have the same drawbacks. Come on, in the whole time the industry has existed, has no one figured out how to deal with it, or made any conclusions? All modern VR gadgets have the same drawbacks. It’s absolutely clear that if a technology does not evolve throughout a significant period of time, it’s a dead end, isn’t it? VR Today Anyway, the VR industry has successfully plunged into the abyss of oblivion for decades until it resurrected again, primarily because people do love VR. You probably know what I’m talking about. This is Oculus Rift — the resurrection of VR. It’s the young guy known to us as Palmer Lucky, who literally turned into a techno occultist and pulled the entire industry out of the grave. Palmer has been crazy about VR since his teen years. His holy grail was to create the VR helmet of his dreams. After creating a prototype, he launched his project on Kickstarter in 2012, and it was a huge success. Oculus Rift And a true renaissance broke out! 600 days after the project’s launch, Facebook acquired Oculus Rift. At the same time,** Valve** started to develop its own helmet, and even** Microsoft** announced its VR developments. And Apple’s Vision Pro helmet became the pinnacle of the trend. acquired started announced Apple’s Vision Pro became the pinnacle So, Vision Pro had two in-built 4K 100Hz Micro-OLED displays on board. The viewing angle — 110 degrees. To interact with the outside world and track the user’s positions, engineers equipped it with 12 cameras. It sounds great, but don’t forget that it weighs 600 grams. The external battery life varies from two to four hours. And the base version will cost you 3500 USD. All in all, it is really well made, and it costs a whole lot of money. And the rocks we’re chipping away at are still the same as decades ago: Uncomfortable Large Weighty No content Short operation time Uncomfortable Uncomfortable Uncomfortable Large Large Large Weighty Weighty Weighty No content No content No content Short operation time Short operation time Short operation time So, the industry giants joined the race. But, to be honest, all the engineers achieved either in Vision Pro or in Meta Quest was just upgrading the hardware and fitting it into a form factor from the 90s. Personally, I call it the Curse of Pygmalion. Almost a hundred years ago, Stanley Weinbaum set the standard that today’s engineers are trying to reproduce. Personally, I call it the Curse of Pygmalion. If we take a look at the PC market, the development of VR started exactly in the same way. In the beginning, there was a huge machine that occupied an entire room. Then, while the technology developed and matured, its dimensions decreased. As a result, now we have smartphones. However, if we are talking about VR gadgets, their development stopped somewhere in the early 90s. Sounds like a dead end, doesn’t it? Let’s say Apple upgrades its helmet and equips it with, for example, an M10 chipset and the most advanced cameras of that time. The gadget would work ten times faster and display incredible image quality, but it would still be a helmet with, most likely, a limited field of view, and you would still have to wear it on your head. It seems like we humans have already gone down the wrong path of VR gadget development. We try to fit very complex components like screens, cameras, or batteries into a small piece of electronics. Instead, we have to figure out how to avoid doing so. But before we get down to this issue, we really do have to speculate a little about another important thing — AR glasses! Most importantly, we’ll finally find out what kind of device is to become the key XR gadget. So, stay tuned! To Be Continued… To Be Continued…

The Curse of Pygmalion: VR and AR Is at a Dead End

পিগম্যালিয়নের অভিশাপ: ভিআর এবং এআর শেষের দিকে

Der Fluch von Pygmalion: VR und AR stecken in einer Sackgasse

La maldición de Pigmalión: la realidad virtual y la realidad aumentada están en un callejón sin salida

La malédiction de Pygmalion : la réalité virtuelle et la réalité augmentée sont dans une impasse

पिग्मेलियन का अभिशाप: वीआर और एआर एक मृत अंत पर है

ピグマリオンの呪い: VR と AR は行き詰まりに陥っている

피그말리온의 저주: VR과 AR은 막다른 골목에 있습니다

A maldição de Pigmalião: VR e AR estão em um beco sem saída

Проклятие Пигмалиона: VR и AR зашли в тупик

Pygmalion'un Laneti: VR ve AR Çıkmaz Sokakta

Lời nguyền của Pygmalion: VR và AR đang đi vào ngõ cụt

皮格马利翁的诅咒：VR和AR已走进死胡同

Our lives and careers are journeys, so we should expect that we’ll be learning for the duration we’re on this planet. As long as we’re moving forward in life, we have experiences to learn from. When I reflect on my career, there are a lot of lessons that I wish I could have taught myself early on. While I can’t talk to my younger self, I can share these with you! 1 – Keep Building Keep building things. It doesn’t matter if they’re not million-dollar product ideas. Build things to learn about how they work. The goal when we’re building things, especially early in our software engineering journeys, is not to get-rich-quick. The goal is to practice and learn. There’s no shortcut to mastery except for understanding sooner that there’s no shortcut. We need to practice — so build software. 2 – Reinvent The Wheel We’re always told to not reinvent the wheel. There’s no point doing it if someone else has already done it. But this isn’t always good advice. Reinventing the wheel is one of the best ways to understand how something works and the complexity behind it. It might not be the best thing to chase in a production environment with paying customers, but it’s great for learning. If you’re ever curious about how things work or interested in the complexities of a system or technology — try building it yourself. You’re almost guaranteed to learn something about what you’re diving into. I’d be shocked if you didn’t! 3 – Learn In Public Document your journey so others can learn alongside you. This can help reinforce learning in so many ways because you need to find ways to explain the concepts that you think you’re now understanding. However, don’t masquerade as an expert. Be humble and acknowledge that you’re new and learning. Others will be more willing to help. Remember that everyone has different opinions. Some people are more loud but it doesn’t make them more correct. In fact, the louder people unwilling to listen to other perspectives are more often than not going to be less helpful. So don’t be discouraged. If people correct your mistakes, this is a great chance for you to take lessons learned and improve! 4 – We Build Software In Teams In the large majority of cases, software is built in teams. This means that you need to focus on communication skills, collaboration skills, and ALL of the other skills that aren’t just technical. When it comes to technical direction, you need to consider that it’s not just your choices. This is a good thing — because the different backgrounds, experiences, and perspectives will allow you to build better software as a group. 5 – Composition > Inheritance Inheritance gets pushed a LOT when teaching programming but if you gravitate towards using composition early then you’ll “shortcut” a few years of really crappy code. Seriously. I’m guilty of writing mountains of code with ridiculously long inheritance hierarchies. I can’t blame this entirely on WinForms and the Controls paradigm that was used… I should have taken some responsibility! I’d spend a good portion of my early career rewriting a lot of overly complex inheritance code because it became too complex. 6 – Don’t Fear Learning Don’t be afraid to learn new things. Building expertise can feel great, but don’t let it make you feel so safe that new things feel scary. You’re going to suck at new things but it’s very temporary. You’ll prove to yourself repeatedly that you eventually get working knowledge and feel very comfortable. In my career, my best growth opportunities were when I was forced into something new and uncomfortable. Every time I came out on top. Discomfort led to incredible learning experiences. 7 – Own Your Career Development Nobody is as interested in your career progression as you are. Great managers will indeed help encourage you and give you opportunities to move things along. But we can’t just sit back and wait for this. We won’t always have amazing managers. The sooner you realize that being passive is not a good strategy for progression, the sooner you can take action. 8 – Remember To Have Fun You’re in this for the long haul, spending many hours of your life building software. You better enjoy it. Not every day is going to be easy. Not every day will be interesting. Not every day will exciting. But overall, you need to find ways to enjoy what you’re doing. It will help you learn. It will help you be engaged. It will help you be motivated to push through interesting challenges. Software engineering is very mentally demanding and it’s often hard to find a good work-life balance… So keep this one in mind throughout your career. If you enjoy this kind of content, I write about related topics often in my weekly newsletter. You can subscribe to it for free: https://weekly.devleader.ca Our lives and careers are journeys, so we should expect that we’ll be learning for the duration we’re on this planet. As long as we’re moving forward in life, we have experiences to learn from. When I reflect on my career, there are a lot of lessons that I wish I could have taught myself early on. While I can’t talk to my younger self, I can share these with you! 1 – Keep Building Keep building things. It doesn’t matter if they’re not million-dollar product ideas. Build things to learn about how they work. The goal when we’re building things, especially early in our software engineering journeys, is not to get-rich-quick. The goal is to practice and learn. There’s no shortcut to mastery except for understanding sooner that there’s no shortcut. We need to practice — so build software. software engineering 2 – Reinvent The Wheel We’re always told to not reinvent the wheel. There’s no point doing it if someone else has already done it. But this isn’t always good advice. Reinventing the wheel is one of the best ways to understand how something works and the complexity behind it. It might not be the best thing to chase in a production environment with paying customers, but it’s great for learning. understand how something works and the complexity If you’re ever curious about how things work or interested in the complexities of a system or technology — try building it yourself. You’re almost guaranteed to learn something about what you’re diving into. I’d be shocked if you didn’t! 3 – Learn In Public Document your journey so others can learn alongside you. This can help reinforce learning in so many ways because you need to find ways to explain the concepts that you think you’re now understanding. However, don’t masquerade as an expert. Be humble and acknowledge that you’re new and learning. Others will be more willing to help. Remember that everyone has different opinions. Some people are more loud but it doesn’t make them more correct. In fact, the louder people unwilling to listen to other perspectives are more often than not going to be less helpful. So don’t be discouraged. If people correct your mistakes, this is a great chance for you to take lessons learned and improve! 4 – We Build Software In Teams In the large majority of cases, software is built in teams. This means that you need to focus on communication skills, collaboration skills, and ALL of the other skills that aren’t just technical. When it comes to technical direction, you need to consider that it’s not just your choices. This is a good thing — because the different backgrounds, experiences, and perspectives will allow you to build better software as a group. 5 – Composition > Inheritance Inheritance gets pushed a LOT when teaching programming but if you gravitate towards using composition early then you’ll “shortcut” a few years of really crappy code. Seriously. I’m guilty of writing mountains of code with ridiculously long inheritance hierarchies. I can’t blame this entirely on WinForms and the Controls paradigm that was used… I should have taken some responsibility! I’d spend a good portion of my early career rewriting a lot of overly complex inheritance code because it became too complex. 6 – Don’t Fear Learning Don’t be afraid to learn new things. Building expertise can feel great, but don’t let it make you feel so safe that new things feel scary. You’re going to suck at new things but it’s very temporary. You’ll prove to yourself repeatedly that you eventually get working knowledge and feel very comfortable. In my career, my best growth opportunities were when I was forced into something new and uncomfortable. Every time I came out on top. Discomfort led to incredible learning experiences. 7 – Own Your Career Development Nobody is as interested in your career progression as you are. Great managers will indeed help encourage you and give you opportunities to move things along. But we can’t just sit back and wait for this. We won’t always have amazing managers. The sooner you realize that being passive is not a good strategy for progression, the sooner you can take action. 8 – Remember To Have Fun You’re in this for the long haul, spending many hours of your life building software. You better enjoy it. Not every day is going to be easy. Not every day will be interesting. Not every day will exciting. But overall, you need to find ways to enjoy what you’re doing. It will help you learn. It will help you be engaged. It will help you be motivated to push through interesting challenges. Software engineering is very mentally demanding and it’s often hard to find a good work-life balance… So keep this one in mind throughout your career. If you enjoy this kind of content, I write about related topics often in my weekly newsletter. You can subscribe to it for free: https://weekly.devleader.ca If you enjoy this kind of content, I write about related topics often in my weekly newsletter. You can subscribe to it for free: https://weekly.devleader.ca https://weekly.devleader.ca

I Wish I Understood These 8 Things Earlier In My Career

Today, I am speaking with Reza Bashash, Tech Lead & Co-Creator at Coreum, and we will discuss the importance of a multidisciplinary approach to blockchain education. We will also talk about the wider effects of blockchain education, how important it is for businesses and universities to work together, and the challenges and strategies for integrating blockchain education into university curriculums. Can you explain the importance of a multidisciplinary approach in blockchain education and why Coreum has focused on this? Taking a multidisciplinary approach to blockchain education is crucial because it mirrors the ecosystem’s inherent complexity and diversity. Blockchain encapsulates a vast array of technological components in its operations, and it stretches into multiple sectors with its own learning curves and nuances. Think of it this way: Blockchain technology in the context of cybersecurity or voting requires different background knowledge than its use in tokenizing real-world assets or other use cases. At Coreum, we recognize this diversity as part of why blockchain technology is so revolutionary. By emphasizing a multi-faceted, multidisciplinary approach to workshops and other educational tools, we prepare students and anyone fascinated by blockchain technology to understand the breadth of what it can achieve. Likewise, it helps students prepare for the challenges that may pop up across blockchain technology sectors. How does the program specifically cater to students from non-technical backgrounds, such as business, marketing, and UX/UI design, to get them involved in the blockchain ecosystem? A successful project does not only rely on the underlying technology but the actual product and business around it—which means that our program has to resonate with students who are not in technical programs or have backgrounds in tech. However, just because students might not be explicitly involved in the technical aspects of blockchain technology doesn’t mean they don’t need to understand what happens behind the scenes. Our workshops ensure that the students have a solid understanding of the technical aspects of blockchain. They also highlight how it interacts with UI/UX and other critical business aspects. How does the program encourage collaboration between students of different specialties, and what benefits do you see from such interactions? Through our interdisciplinary workshops and partnership programs with universities, Coreum facilitates an environment where students across faculties and departments can collaborate on blockchain projects and collaborate according to their specialties. By taking a hands-on approach, these programs not only broaden the student’s understanding of the technology but also show how they can contribute by combining valuable skill sets. In the long run, it creates a space where students can interact with each other, which eventually leads to innovative solutions that are technically sound, market-ready, and user-friendly. With the inclusion of compliance in the program, how do you educate students about the legal and ethical considerations of blockchain technology? Coreum’s university partnerships and workshops focus on technical implementations and interactions. We strongly encourage students to educate themselves and conduct thorough research on project specifics from a legal and ethical standpoint. Beyond technology and finance, in what other sectors do you see blockchain education having a significant impact? As I mentioned in the first question, blockchain’s diversity is its strength—which means it has the power to impact nearly any sector through its technological framework. Coreum’s educational initiatives take every measure to emphasize the vast scope of blockchain’s potential to the students taking the program. We do this to ensure that students know the possibilities beyond the finance and tech horizons, which are impressive but greatly reduce the blockchain’s true capabilities. Blockchain education is especially critical now in sectors that its technology can immediately augment, and we hope to inspire students in these areas to understand its capabilities. That includes fields such as humanitarian work and philanthropy, healthcare, supply chain management, and even the education system itself. What role do partnerships between academia and the blockchain industry play in shaping the future of blockchain education? Academia is a nest for innovation. We constantly hear about some of the most innovative technological solutions of our time being sparked by students while they’re still in university. But if students aren’t aware of new technologies and how they can improve so many different sectors, they don’t know how to contribute to building something transformative. Coreum’s aim with its university partnerships is to continue dialogue and collaboration with the academic realm and exemplify how education can evolve through blockchain development. Students are builders of the future, so it makes sense to meet them at their level and educate them in a way that engages them with blockchain technology early on. Could you provide examples of how students from fields like marketing or design can apply their skills in blockchain projects through your program? Coreum’s workshops offer students practical opportunities to use their skills and industry knowledge in a highly collaborative environment. For students in marketing or design, these workshops engage them with blockchain projects, where they can develop branding strategies for startups or design user interfaces and experiences for blockchain applications. These experiences shape their practical abilities and highlight the indispensable role that diverse backgrounds and areas of expertise play in the blockchain ecosystem. What are the biggest challenges in bridging the knowledge gap between traditional education systems and the rapidly evolving blockchain industry? What can often happen in traditional education systems dealing with new technologies is that the technology itself moves faster than educators can catch up to it. When an educator completes a course or workshop, the technology they’re trying to inform and familiarize students with may have already evolved to something new. Our Coreum workshops tackle this issue head-on by continuously updating their curriculum and content. This ensures that educators and students have the most current information and tools to remain at the forefront of blockchain’s consistent innovations and advancements. How can blockchain education be effectively integrated into university curricula without disrupting traditional disciplines? Effectively integrating blockchain into existing university curricula and systems can happen without necessarily upending how students learn now or interfering with their other studies. Coreum advocates for universities and other higher education institutions to offer elective courses, interdisciplinary projects, and extracurricular workshops. Using this multifaceted strategy, students interested in blockchain can pursue education in the field alongside their major, enriching their educational and professional journey without disrupting traditional disciplines. Forcing students to learn about fields that they have no interest in is not conducive to a productive or impactful learning environment. Still, they should be encouraged to be inquisitive throughout their educational tenure. Looking ahead, how do you see the role of multidisciplinary education evolving in the blockchain ecosystem, and what plans does Coreum have to support this approach further? As blockchain technology becomes more integral to various industries and subsectors, we’re likely to witness a heightening demand for educational initiatives for it. That being said, retaining the multidisciplinary approach in any case is important. Coreum continues its commitment to offering workshops and expanding its partnerships with universities and other educational institutions. As we look ahead, we are working to continue fostering inclusive educational environments that encourage collaboration to prepare students for the future of blockchain technology.

Blockchain Beyond Coding: A Multidisciplinary Approach to Education

HackerNoon editorial team has launched to celebrate their achievements and share their struggles. We need more women in technology, and by sharing stories, we can encourage many girls to follow their dreams. ! this interview series with women in tech Share your story today Tell us about yourself! My name is Kamala Manju Kesavan, and I’m deeply passionate about technology and innovation. At a young age, growing up in Madurai (Tamil Nadu, India), I grew fascinated by computers and how they work, and this curiosity led me to pursue a career in computer science. I've always been driven by a desire to learn and explore new ideas, due to which I have taken on various challenges and opportunities in the tech industry. I am a transformational technical leader boasting over 20 years of experience in the realm of enterprise software implementation. My expertise encompasses technology solution strategy, software development, QE, test automation, and DevOps. My unique strength is my ability to bridge the gap between business strategy and technology, whilst fostering a culture of innovation and continuous improvement. I have a proven track record of leading global technology teams in digital transformation. Currently working as Director of Software Engineering at VISA , I hold a Master of Science in Cloud Computing Architecture from the University of Maryland, and a Master of Computer Science from Madurai Kamaraj University, India. Why did you choose this field in the first place? I opted to pursue computer science because it promised me autonomy and freedom. Since I am an Indian woman, the familial expectation was for me to become a teacher or homemaker, but I desired a path that would give me greater independence. Choosing computer science allowed me to chart my own course in life. However, financing my education proved challenging as my family couldn't cover the expenses, and we didn't qualify for student loans. Consequently, I balanced full-time work as an elementary school teacher after completing my Bachelor of Physics degree to finance my computer science degree and pursue my aspirations. What tech are you most excited/passionate about right now and why? I believe that the future of the tech world will revolve around how to best train, update, and store AI models. AI thrives on data for updating and training, and since cloud computing is cost-effective and scalable, it will become very important for the development of this field. Cloud computing will have a crucial role in terms of democratizing access to AI model training. With cloud-based infrastructure, aspiring AI experts can leverage powerful computing resources without having to make a lot of upfront investment in hardware. This accessibility will lower the barrier to entry for AI experimentation and development and open doors for innovation and collaboration across diverse communities. I'm particularly excited about cloud computing because it means a wider range of individuals, including those from underprivileged backgrounds or resource-constrained regions, can participate in AI research and development. By making it easier and cheaper to access computing resources, cloud platforms welcome more diverse voices to the field of AI, ultimately driving innovation and advancing the state of the art. Also, cloud computing offers flexibility and scalability. This will allow users to scale up or down their computing resources based on the demands of their AI projects. This dynamic scalability means that AI professionals have the computational power they need without being limited by the same kinds of hardware constraints. Overall, the accessibility and scalability afforded by cloud computing have the potential to accelerate AI research and development, democratize innovation, and foster more collaboration. As cloud technologies continue to evolve, I look forward to witnessing the transformative impact they will have on AI model training. What tech are you most worried about right now and why? ‘The popularity of short-form video content platforms, which emphasize quick, easily consumable material, can significantly impact the younger generation. These platforms thrive on lowering attention spans and maximizing user engagement, particularly among younger audiences. This brings up concerns related to their influence on cognitive development and creative expression. The trend towards shorter content formats, as seen on platforms like TikTok and YouTube Shorts, risks distorting the way we perceive creativity and content creation. Since there is an emphasis on instant gratification rather than thoughtful, well-crafted work, there's a good chance that we may find it harder to appreciate deeper, more meaningful content creation processes. Also, the rapid consumption of bite-sized content may lead to information overload and a shallow understanding of complex topics among young viewers. Without deeper exploration and analysis, there's a risk of missing out on valuable learning opportunities and critical insights that are needed for intellectual growth and development. It is definitely true that short-form video content offers entertainment and engagement, but it's essential to strike a balance. Encouraging young audiences to engage with more substantive material along with short-form content can greatly improve cognitive development, creativity, and digital literacy. This will ensure a more holistic approach to media consumption and learning. What are your hobbies and interests outside of tech? I love cooking and baking! This used to be my main hobby, but over the past two years, I've been dedicated to learning the violin. This year, I’ve also been delving into the intricacies of mandala art. Engaging in these hobbies has given me valuable perspectives that I can apply beyond the areas of art and music. These crafts have taught me discipline, patience, and attention to detail, which have directly contributed to my approach toward technology-based decision-making. Just as in music and art, in technology, making informed decisions needs one to be precise, creative, and willing to continuously learn and adapt. These experiences have sharpened my problem-solving skills and fostered a more holistic perspective. This has helped me approach complex technical challenges with more creativity and resilience. Let's talk about breaking the glass ceiling. What were the biggest challenges you faced as a woman in tech, and how did you deal with them? It was disheartening to see the expectation that I would reduce my level of work and ambition after giving birth or starting a family. It felt like my professional aspirations were being undermined solely because of my family responsibilities. However, I refused to let this stereotype dictate my path in life. Instead, I remained determined to pursue my career goals while also fulfilling my role as a mother. By challenging this expectation, I want to create a more inclusive and equitable environment where individuals are valued for their contributions regardless of their family status! Any questionable misogynistic story/situation you faced/handled, and you want to share with the HackerNoon Fam? In a casual dinner meeting many years ago, I encountered a misogynistic incident that left me feeling disrespected and frustrated. A male colleague made a derogatory remark implying that my professional achievements were solely due to my gender rather than my capabilities and hard work. Initially taken aback, I chose to address the situation calmly yet assertively. I confronted my colleague about his inappropriate comment, showing him that such remarks have no place in professional settings and undermine the contributions of women in the workplace. Despite the discomfort of the situation, I stood my ground and made it clear that I would not tolerate such behavior. While challenging, this experience reinforced the importance of speaking up against sexism and advocating for gender equality in all aspects of life. By addressing misogyny head-on and promoting mutual respect and inclusivity, we can strive to create a more equitable and supportive environment for everyone, regardless of gender. The lesson learned is that instances of misogyny can occur not only in formal work meetings but also in casual settings. Despite the pretense of normalcy, women need to remain vigilant in any discussion where they may be subjected to belittling or disrespectful behavior. This highlights the importance of women advocating for themselves and being prepared to address and challenge such incidents because this is the only way to promote a culture of respect and equality in all interactions. What was the biggest setback/failure that you faced, and how did you manage it? Since I was on a dependent visa, I faced many hurdles, which became harder when relocating to a new country for work. However, I now realize that I tackled these obstacles head-on with a lot of resilience and determination. I leaned on the support of my employer and colleagues, who offered invaluable assistance and understanding throughout this journey. Moreover, I constantly held on to a positive outlook, drawing lessons from my past experiences to navigate the situation more effectively. Through perseverance and adaptability, I successfully overcame these challenges. I believe that they have helped me emerge stronger and more focused in my professional journey. What's your biggest achievement that you're really proud of? In the early 2000s, funding my education independently was uncommon in my hometown in India. Despite this, I took the initiative to finance my entire degree myself. Through hard work and determination, I not only covered tuition fees but also managed living expenses. Any financial assistance from my family was repaid, reflecting my strong sense of financial responsibility. This accomplishment showcases my dedication and perseverance and shows my ability to overcome challenges. This led to many moments of immense pride, especially since my father was initially doubtful about me pursuing my higher education in faraway places. His eventual praise during his final days validated my decision and reminded me of the importance of my hard work in achieving my goals. In your opinion, why do we see this huge gender gap in the tech industry, and how can we reduce it? The gender gap in the tech industry is influenced by societal stereotypes, lack of representation, and workplace biases. To address this gap, it's vital to promote the visibility and representation of women in tech as role models. By showcasing diverse female leaders in the field, we can inspire the next generation to pursue tech careers. However, it's essential to educate everyone, not just women, about the importance of gender diversity in tech. Also, creating inclusive workplaces, advocating for STEM education for girls, and dismantling systemic barriers are crucial steps to bridging the gap. Overall, increasing the visibility of female role models and promoting gender diversity initiatives can help create a more inclusive and equitable tech industry. Who is your tech idol? Why? My tech idol is Alan Turing, whose brilliance and pioneering work in computing continue to inspire me. Despite facing adversity and not receiving the recognition he deserved in his time, Turing's perseverance and innovative spirit laid the foundation for modern computing as we know it. Do you have any advice for aspiring girls who want to join the field? While the tech industry presents its own set of challenges for girls, it's important to approach these challenges with resilience and determination. Your gender should never be a barrier to your success or limit your potential. Embrace every challenge as an opportunity to learn and grow stronger. Keep up-skilling and re-skilling to stay ahead of the curve, and remember to stay focused on your goals. Believe in yourself, amplify your voice, and recognize the value of your contributions. With perseverance and resilience, you have the power to conquer any obstacle and excel in the dynamic world of technology.

Kamala Manju Kesavan - Director of Software Engineering at VISA

Authors: (1) Savvas Petridis, Google Research, New York, New York, USA; (2) Ben Wedin, Google Research, Cambridge, Massachusetts, USA; (3) James Wexler, Google Research, Cambridge, Massachusetts, USA; (4) Aaron Donsbach, Google Research, Seattle, Washington, USA; (5) Mahima Pushkarna, Google Research, Cambridge, Massachusetts, USA; (6) Nitesh Goyal, Google Research, New York, New York, USA; (7) Carrie J. Cai, Google Research, Mountain View, California, USA; (8) Michael Terry, Google Research, Cambridge, Massachusetts, USA. Table Of Links Abstract & Introduction Related Work Formative Study Constitution Maker Implementation User Study Findings Discussion Conclusion and References 7 FINDINGS Quantitative Findings. From the exit interviews, 12 of 14 participants preferred ConstitutionMaker to the baseline version. The results from the questionnaire are summarized in Figure 4. We found that ConstitutionMaker was perceived to be more helpful for writing rules that effectively guided the bot (Z = 8, p = .007), scoring on average 5.79 (𝜎 = 1.01) whereas the baseline scored 4.0 (1.51). When participants rewound parts of the conversation, they thought the ConstitutionMaker principles were followed by the bot better. Next, participants felt it was significantly easier (Z = 10.5, p = .006) to convert their feedback into principles with ConstitutionMaker (𝜇 = 5.86, 𝜎 = 0.91) than with the baseline (𝜇 = 3.93, 𝜎 = 1.39). The automatic conversion of kudos and critiques into principles eased the process of converting intuitive feedback into clear criteria for the bot to follow. Participants perceived that they were significantly more efficient (Z = 5, p = .004) writing rules with ConstitutionMaker (𝜇 = 5.86, 𝜎 = 1.51) than with the baseline (𝜇 = 3.64, 𝜎 = 1.34). Finally, participants also felt that writing principles with ConstitutionMaker (𝜇 = 3.0, 𝜎 = 1.41) required significantly less mental demand (Z = 1.5, p = .002) than with the baseline (𝜇 = 5.21, 𝜎 =1.78). There was no statistically significant difference for diversity (Z = 19, p = .06); participants felt that they exercised their creativity and wrote relatively diverse principles in the baseline. Next, regarding the feature usage metrics, participants wrote significantly more principles (t(13)=4.73, p < .001) with ConstitutionMaker than with the baseline; participants wrote on average 6.78 (𝜎 = 2.11) principles per chatbot with ConstitutionMaker and 4.42 (𝜎 = 1.24) principles with the baseline. Of the 95 principles written in the ConstitutionMaker condition, 40 (42.1%) came from kudos, where 37 were selected from the generate rationales and 3 were written; 28 (29.5%) came from critique, where 8 were selected and 20 were written; 13 (13.6%) came from the rewrite features; 14 (14.7%) were manually written. Participants found rewriting a bit cumbersome and preferred the less intensive workflow of describing what they liked or did not like to generate principles. In the following sections, we provide further context to these findings. 7.1 Participants’ Workflows for Writing Principles The two conditions led to quite different workflows for writing principles. In the ConstitutionMaker condition, participants commonly scanned the three candidate outputs from the chatbot, identified the output they liked the most, and then gave kudos to that output if they thought it had a quality that was not currently reflected in their principles. For example, while P1 was working on FoodBot, he was asking for easy-to-make vegetarian dishes, and in one of the bot’s candidate outputs, each suggested dish had a short description and explanation on why it was easy. He appreciated this, skimmed the kudos, and then selected one that conveyed this positive feature of the bot’s output. However, if participants disliked all of the responses, they would then switch to critiquing one of the outputs. Accordingly, this kudos-first workflow helps to explain how most of the principles participants wrote came from that principle elicitation feature. Meanwhile, in the baseline condition, participants generally wrote principles when the bot deviated quite a bit (in a negative way) from what they expected. P8 explained, “Here it feels like what I more naturally do is write corrective rules, to guardrail anything that goes weird...If it’s already doing the right thing it doesn’t need a rule from me. I wouldn’t feel the need to write those.” In the baseline condition, participants only see one candidate output from the chatbot, and this might deemphasize the stochastic nature of the chatbot’s outputs. As a result, when participants are okay with a response, they could feel that they do not need to write a principle to encourage that kind of response further. Overall, with the baseline, participants predominantly wrote principles to steer the LLM from less optimal behavior, while with ConstitutionMaker, participants mostly used kudos the most to encourage behavior they liked. 7.2 ConstitutionMaker Supported Users’ Thought Processes In the following section, we discuss how ConstitutionMaker supported participants’ thought process from (1) forming an intuition on ways the chatbot could be improved, (2) expressing this intuition as feedback, and (3) converting this feedback into a specific and clear principle. As P5 was using the baseline after using ConstitutionMaker, she explained how she wished she could see multiple outputs again: “Sometimes, I don’t know what I’m missing [in the baseline]. I’m thinking of the Denali hiking example [which occurred when she wrote principles for VacationBot with ConstitutionMaker]. Two of the responses didn’t mention that Denali was good for young children. But one did, and I was able to pull that out as a positive principle.” While she was writing principles for VacationBot with ConstitutionMaker, P5 started off the conversation saying she was looking for suggestions for her family, which included two young children. As the conversation progressed and a general location was established, P5 then asked for hiking recommendations, for which the bot gave some, but only one of its responses highlighted that the hikes it was recommending were good for young children. P5 gave kudos to that response and created the following principle: “Consider information previously inputted by the user when providing recommendations.” Ultimately, it can be hard to form opinions on responses without getting exposed to alternatives, so by providing multiple chatbot outputs, ConstitutionMaker supported participants in forming an intuition on how the model might be steered. 7.2.1 Multiple chatbot outputs helped participants form an intuition on how the model could be steered. . Upon seeing a candidate response from the chatbot, participants could intuitively tell if they liked or disliked it, but struggled to articulate their thoughts. The automatically generated kudos and critiques helped participants recognize and formulate this feedback. For example, while working on FoodBot with ConstitutionMaker, P9 asked the bot to identify the pizzeria with the best thin crust from a list of restaurants provided in a prior turn. The bot responded with, “Pizzaiolo has the best thin crust pies.” P9 knew he did not like the response, so he went to critique it and selected the following generated option: “This response is bad because it does not provide any information about the other pizza places that the user asked about.” The following principle was generated: “If the user asks about a specific attribute of a list of items, provide information about all of the items in the list that have that attribute,” which then produced a set of revised responses that compared the qualities of each pizzeria’s crusts. Reflecting on this process, P9 stated, “I didn’t like that last answer [from FoodBot], but I didn’t have a concrete reason why yet...I didn’t really know how to put it into words yet...but reading the suggestions gave me at least one of many potential reasons on why I didn’t like the response.” Thus, ConstitutionMaker helped participants transition from fast thinking [15], that is, their intuitive and unconscious responses to the bot’s outputs, to slow thinking, a more deliberate, conscious formulation of their feedback. 7.2.2 Automatically providing kudos and critique rationales helped participants formulate their intuitive feedback Sometimes the generated kudos and critique rationales did not capture participants’ particular feedback on the chatbot, and so they would then write their own. Their feedback was often under-specified, and ConstitutionMaker helped convert this feedback into a clear and specific principle. For example, P4 was writing principles for VacationBot using ConstitutionMaker. During the conversation, they had told VacationBot that they were planning a week long vacation to Japan, to which the bot immediately responded with a comprehensive 7-day itinerary. P4 then wrote in their own critique: “This response is bad because it does not take into account the user’s interests.” The resulting principle was, “When the user mentions a location, ask them questions about what they are interested in before providing an itinerary.” This principle was aligned with what P4 had in mind, and reflecting on her experience using ConstitutionMaker, she stated, Finally, even when the resulting principle was not exactly what they had in mind, participants appreciated the useful starting point it provided. Along these lines, P11 explained, Overall, ConstitutionMaker helped participants specify their feedback into clear principles. 7.2.3 Generating principles from feedback helped users write clear, specific principles. “When I would critique or kudos, it would give examples of principles that were putting it into words a little bit better than I could about like what exactly I was trying to narrow down to here.” “It was easier to say yes-and with Tool A [ConstitutionMaker]. Where it [the generated principle] wasn’t all the way there, but I think it’s 50% of the way there, and I can get it to where I want to go.” 7.3 Participants’ Workflows Introduced Challenges with Writing Principles Participants struggled to find the right level of granularity for their principles, and the two conditions led to different problems in this regard. Both workflows had participants switch roles from end-user, where participants experimented with different user journeys, to bot designer, where they evaluated the bot’s responses to write principles. The more conversation-forward interface of the baseline blurred the distinction between these two roles. P3 explained that without the multiple bot outputs and principle elicitation features, And by leaning further into this user role, participants wrote principles that were more conversational, but under-specified. For example, while writing principles for FoodBot with the baseline, P11 wrote the principle “Be cognizant of the user’s dietary preferences.” What P11 really had in mind was a principle that specified that the bot should ask the user for their preferences and allergies prior to generating a meal plan. These underspecified principles often did not impact the bot’s responses and would frustrate participants while they used the baseline. “you can simulate yourself as the user a lot better in this mode [the baseline].” Meanwhile, while using ConstitutionMaker, the opposite problem occurred, where users’ workflows led to principles that were over-specified. For example, while working on VacationBot, P7 asked the model to help him narrow down a few vacation options, and the model proceeded to ask them questions (without any principle written specifying so). Appreciating that the model was gathering context, they selected a kudos that praised the model for asking about the user’s budget constraints prior to recommending a vacation destination. The resulting principle was, “Ask the user their budget before providing vacation options.” However, once this principle came into effect, the model’s behavior then anchored specifically to only asking for budget prior to making a recommendation. And so, this workflow of providing feedback at every conversational step, instead of for entire conversations, led to a principle that was too specific and impacted the bot’s performance negatively. While users generally appreciated ConstitutionMaker’s ability to form specific principles from their feedback, there were rare instances where the principles were too specific. Finally, in both conditions, by switching back and forth between the end-user to bot designer roles, participants would sometimes write principles that conflicted with each other. For example, while P2 was working on VacationBot with the baseline, they asked the bot for dog-friendly hotel recommendations in the Bay Area, and VacationBot responded with three recommendations. P2 wanted more recommendations and wrote a principle to “Provide >= 10 recommendations.” Later on in the conversation, P2 now had a list of dog-friendly restaurants, with their requisite costs, and he asked VacationBot which it recommends, to which it responded by listing positive attributes of all the hotel options. P2, who now wanted a decisive, single response wrote the following principle: “If I ask for a recommendation, give *1* recommendation only.” VacationBot, now with two conflicting principles on the number of recommendations to provide, alternated between the two. Ultimately, by providing feedback on individual conversational turns, participants ended up with conflicting principles. P8 imagined a different workflow, where he would experiment with full user journeys and then write principles: In summary, one’s workflow as they probe and test the model impacts the types of principles they produce and the challenges they face. “I think it might help me to actually go through the [whole] user flow and then analyze it as a piece instead of switching...it would allow me to inhabit one mindset [either bot designer or user] for a period of time and then switch mindsets.” 7.4 The Limits of Principles Some participants questioned if writing natural language principles was the optimal way to steer all aspects of a bot’s behavior. While writing a principle to shorten the length of the chatbot’s responses, P13 reflected, They imagined that aspects like the form of the model’s responses would be better customized with UI elements like sliders to adjust the length of the bot’s responses, or exemplifying the structure of the bot’s response (e.g., an indented, numbered list for recommendations) for the model to follow, instead of describing these requests in natural language. In a similar vein, P14 noticed that her principles pertained to different parts of the conversation, and as a list, they seemed hard to relate to each other. She wanted to structure and provide feedback on higher-level “conversational arcs,” visually illustrating the flow and “forks in the road” of the conversation (e.g., “If the user does X, do Y. Otherwise, do Z”). Principles are computational in a sense, and they dictate the ways the conversation can unfold; there might be better ways to let users author this flow, other than with individual principles. “It feels a little weird to use natural language to generate the principles...it doesn’t feel efficient, and I’m not sure how it’s going to interpret it.” This paper is under CC 4.0 license. available on arxiv

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