• September 26, 2022

Your State Pension Hates You

State laws mandate that pension fiduciaries have a duty of loyalty to manage retirement plan assets for the exclusive benefit of beneficiaries, i.e., state workers and retirees. Yet all-too-often public pension …

The Commercial Real Estate Market: Crash, Train Wreck, Or Apocalypse?

Dire warnings about commercial real estate appear almost daily these days. While office markets are stressed due to increased working from home, some real estate professionals see an increasingly bifurcated market, …

Apple’s Tim Cook Launches New Initiative: ‘It’s About Values’

The Southbank in London is a cultural hotspot. The National Theatre sits alongside stunning arts cinemas from the British Film Institute (BFI Southbank). And then there’s the Southbank Centre. This includes …

The ACM, Association for Computing Machinery, founded in 1947, is celebrating its 75 year anniversary in 2022. From its first gatherings of professionals, it has grown to being the largest and most influential computer science organization in the world, with 4 million users of their services, and their well known ACM A.M. Turing Award, which is considered the Nobel of computing science. Yannis Ioannidis, in July, took office as the new ACM President. His remarkable vision, shapes ACM as the association begins its next 75 years, and it’s demonstrated in this first interview, which is unscripted and provided in full below.

This article is based upon insights from my daily pro bon0 work with more than 400,000 CEOs, investors, scientists, and notable experts.

INTERVIEW YANNIS IOANNIDIS ACM PRESIDENT

The video interview is found with the non-profit ACM (interviews by Stephen Ibaraki). AI is employed to generate the transcript which is then edited for brevity, clarity while staying with the cadence of the chat. AI has about an 80% accuracy so going to the full video interview is recommended for full precision. Time stamps are provided however with the caveat that they are approximate.

It’s good to look at Yannis’s complete background with this direct link to the interview page with extensive profile and video link.

Yannis’s leadership roles are extensive and briefly summarized:

Yannis Ioannidis, ACM president (July 2022-June 2024); professor National and Kapodistrian University of Athens, affiliated faculty (President, General Director 2011-2021) “Athena” Research and Innovation Center; coordinator and legal entity head OpenAIRE; software director European Human Brain Project; coordinator EOSC Future strategic project, implementing the core elements European Open Science Cloud; coordinator or a partner in tens of other European and national research and innovation projects; led or is currently leading the creation of new international organizations and spin-off companies; Greek delegate European Open Science Cloud (EOSC) Steering Board, Greek delegate European Strategy Forum on Research Infrastructures (ESFRI), ESFRI representative to the e-Infrastructures Reflection Group (e-IRG); serves on the Steering Committee of the IEEE International Conference on Data Engineering and the Strategic Advisory Board of the Destination Earth Initiative in Europe; closely involved in the activities of the United Nations Sustainable Development Solutions Network (UNSDSN), member of the strategic management board of the SDSN Greece regional hub as well as a vice-chair of the new thematic SDSN Global Climate Hub.

Stephen Ibaraki 00:00

Yannis, thank you for coming in. And congratulations as the president of ACM. ACM is the largest computing science organization in the world. This year is their 75th anniversary as well; it is definitely number one ranked. Together with being the largest in computing science and with so many different success factors associated with its members. You are in the succession of presidents of the organization. Again, congratulations.

Yannis Ioannidis 00:34

Thank you very much, Stephen. It’s a great honor to be elected and humbling also. I look forward to the next two years of trying to step on what my predecessors have built and move our organization in its fourth quarter century of life.

Stephen Ibaraki 00:57

Yannis you have just a remarkable history of success. And one of the questions I always ask people like yourself, who are history making; you are iconic, you’re a pioneer in so many different areas. And that question is, what are maybe two or three inflection points that really created this marvelous, wonderful researcher and human being, that is making so many contributions to the world?

Yannis Ioannidis 01:21

Well, I think, as with everyone, everything starts from the family and my parents have been my first teachers of ethics, of principles, and even of ways of thinking. So, I mean, you cannot talk about it as a reflection point; it’s a lifetime of influence until their passing, and everything started there. And then I can point to, essentially, the main thing being the teachers I had in high school and at the university and graduate school. Every one of the foundational beliefs I have, or eventual behaviors, can be traced back to some teacher who gave me directly or indirectly a message. In high school I was very good in physics, mathematics, and so on. I was just okay in languages and things. At some point, I had a teacher who came and he had a degree in math and a degree in theology and a degree in literature. And, of course, you can imagine the kinds of ways of thinking he opened for me. Most of my research has been multidisciplinary and I can trace it back to the way he inspired us, the mathematically oriented students, to go and see a play of some deep script, and so on and so forth. And then my graduate advisor Gene (Eugene) Wong at Berkeley; he is an amazing personality and he really influenced me. And one of the things that he told me was, well, he told me two things that have stuck. One, he said, put your own standards, don’t live by others’ standards; you put your standards and live up to them. And of course, put them high. And, thinking this way on how to design my career and my agenda, my research agenda and others, my life agendas, in some sense, has been really influenced by Gene and I really thank him for that. And the other thing that he said was that innovation is more important than scholarship. Read what others have done, but don’t overdo it. Just think freely. And even if you do something that someone else has done, okay, this is not a problem, not a big problem. But think freely! And I’ve been trying to do that, as well. Of course, my children and my wife have been great teachers as well, in giving me challenges every day, and I’ve been blessed with a great family. So, I would say that these are the important things that have made me who I am professionally. And of course, all my colleagues, at different times, always pointing me in a way, in a direction that is outside my comfort zone. And I’m always hesitant to take the step outside. But with one push or two, I end up taking it. And I may be a little bit lost for a little bit. But I never regret it; it’s always an amazing path. But one has to step outside his or her comfort zone. And by now I do it even without the help of others. When I see something that I feel too comfortable with, I don’t abandon it, but I try to also go somewhere else. And that’s, I think, a lesson for everyone.

Stephen Ibaraki 05:53

I’m just reflecting on all of the great aspects of the journey; I can see the humanity part of it as just being a common theme. The second major theme is this aspect of being at the boundary. Don’t be afraid at looking at the boundary layers, the outlier aspects, because that’s where a lot of innovation occurs. You have to maintain yourself in that space. I understand because I’m an investor. I invest at the boundary layer. And then you’re at the beginning; you start this foundational aspect your parents provided. There’s your ethical groundwork, and so on. You have these marvelous teachers; teaching you, to again, think in diverse ways. Usually when you think in diverse ways, that includes inclusion, which means you’re thinking of the other and other people’s points of view. All of those things resonate with me. I really understand and respect all of these aspects of your life. I can see the interdisciplinary, multidisciplinary, sort of intersections of the different sort of work that you’ve done; I can see how it came from all of these aspects in your prior life. Okay, let’s get to what you’re doing currently. Can you talk about some of your research interests now, and why?

Yannis Ioannidis 07:23

The why may be hard to explain. As I said, something interesting comes up and then the right environment, and then that’s where things go. I have to say that I have been blessed with quite a bit of funding, and with amazing people around me in my team; my team is quite large and very diverse and multidisciplinary. So, there are four or five directions that I’m working on. Most of my work has been on data. I mean, I’m a data guy, databases, data management, and so on. And, not always, but often working on the multidisciplinary aspects, I mean, being inspired by data problems that others have, and then abstracting them to my own fields, doing some work, and then hopefully returning back in a way that is applicable and useful to the ones who have the problem. Currently, let me say, one major activity that I’m involved in, in Europe, is a very big project called Human Brain Project, which is a 10-year $1 billion roughly funding to understand the brain and try to simulate it; come up with a digital twin of the brain, so to speak. Now, obviously, you cannot really do it in 10 years and with just 1 billion but a lot of progress has happened. And my role there is, in addition to offering technological architectures for the whole thing and coordinating the technological development of the infrastructure for this, a particular role is what do you do with data in hospitals, clinical data, neural / neurological data, in order to try to identify issues with neurodegenerative diseases. Neurodegenerative diseases are rare diseases. So, within a hospital, you have few patients and few data points. So, you cannot draw statistically significant results. You need to come up with data from many hospitals in many countries in order to reach a volume of data where some trends and some correlations and causalities could possibly be identified. So, you need to federate hospitals. But then these are clinical data. The data is private to the patients, and also covered with a bunch of laws and regulations local to the hospital or to the country, and so on and so forth. Some data cannot live in hospitals and some data cannot leave the country. How do you apply machine learning and other analytics in a way that is privacy preserving, and regulation and law abiding from a federation of hospital data? This is a fascinating problem. There’s a bunch of technologies that can be employed here and applied. But there is no final answer. And there’s lots of research, bringing differential privacy and secure multi party computations and other techniques that already exist, but in that particular environment, it is still a challenge to serve the particular needs, and also do all this efficiently and bring in technological descriptions of the regulations. For example, in Europe, we have GDPR, the General Data Protection Regulation. How do we encode this into your data processing, into your data, your privacy preserving algorithms, in order to do it in an efficient way, and in a way that then everyone else will trust, the hospitals will trust, the patients will trust, in order to bring in this wealth of data to the service of research? So that’s one major area that I’m working on. And let me mention a second one, completely different. And that is data related. But it’s also more, I shouldn’t say computer human interaction, but anyway, more on the user side. And I’ll give you one motivation for it. When you go to a museum, and you visit a museum (so we will go to humanities, to a certain extent), you stand in front of an exhibit. And then you read a little story in a card next to it, or someone tells you a story, or you have the audio guide. And then you go to the next exhibit, and you read another card, and so on and so forth. So, your visit is exhibit centric, you visit exhibits, and little stories pop up, guided by the exhibits. So, your visit is exhibits centric. If we reverse this (we have reversed this, and we’ve been working on what I’ll say roughly 10 years), make it story centric, you have a story, which is the main aspect, the main guiding force of your visit. And as part of the story, the exhibits pop up, connected by a common thread that the story gives you. And of course, since you have this ability, the story may not be just a narration, I mean, you have your mobile phone or your tablet with you. It’s not just a linear narration, it may have loops and may have branches that are taken based on your choices or quizzes, or so that the visit is personalized based on your interests or the way the system sees your behavior and, on the fly, understands your mood. So, the same story can be given to you in many ways. And it can be as I said, it can have virtual reality, augmented reality, etc. And the key thing is that it has a thread, a common thread, so that the exhibits are not isolated from each other. They are part of a story. And this has an amazing effect on your appreciation of what the museum is showing you. On top of the historical truth or the artistic truth you can add fiction, while respecting, of course, the history and the art. And the effect of people appreciating what they have, remembering what they saw, liking museums, is amazing, with lots of evaluations we’ve done with little children, with adults, with groups playing social games while at the museum. And of course, this can be expanded beyond museums, can go into archaeological sites, other points of interest, city tours, and so on and so forth. This has tremendous research challenges in terms of human machine interaction, call it in general, it has challenges in terms of personalization and recommendation on what to do next, or which branch of the story to follow, profiling people on the fly, data mining to see how people behave in this site versus the other and a wealth of other information. So, this is another line of research that a part of my team is working on with, which is very different from the other one, but equally exciting. And I won’t go into the details of others, but let me mention also, data analytics on issues that are related to climate and climate data. And in general, the SDGs, that “AI for Good” is trying to promote and bring technology and AI to address them. And open science. Open science is a major element of my effort with little research in that, but developing OpenAIRE, which is the main infrastructure in Europe, for supporting the open access and open science policies, with all research outputs, publicly funded research outputs, publications, but also datasets, software, and so on and so forth. So, these are two other lines of work that parts of my team are working on. And in all these, individual very technical problems pop up. How do you change SQL, the SQL language, so that you can embed in it, in a natural way, Python code that does the analytics? And how do you take advantage of the hardware and the cache coherency protocols in order to do this faster, in graph joining? Or in how do you combine that with random Python code. So, a whole bunch of technical work, purely technical, pure computer science, pure informatics work, but within this context of exciting applications in many other fields. So I feel lucky, blessed with the amazing team that I have, with colleagues that are working with me both at the University of Athens and the Athena Research Center (I’m affiliated with both), and also others around Europe, mostly, and the rest of the world. So, this is roughly where I am.

Stephen Ibaraki 18:20

There’s a lot to unpack here. This could be three separate interviews. I’m going to ask a few more follow up questions, because and what the audience doesn’t realize is that when I do these interviews, they’re unscripted. We have a dialogue. And then I will drill further. One part of the work that you’re talking about is this Human Brain Project. You’re working on the data aspects, with the clinical data, and then ensuring, how do you protect it? How do you use it within the regulatory frameworks? But within this brain virtualization, what is the intersection of 85 billion brain cells, there’s probably 125 trillion synapses. And then to map that within this Brain Project, and then all the associated data that’s connected to that. You have this confluence of things like exascale supercomputing, for example, El Capitan in the US. I did an interview and Forbes article with Jack Dongara, and he talked about some of these super computers, their modeling capability, and enormous computational capability. You’re also seeing quantum computing becoming a possibility. Right? And in fact, Jack talked about it. Also, I interviewed, Travis Humble (heads up quantum computing), at Oak Ridge National Laboratories, and he’s doing hybrid computing. This is supercomputing married to quantum computing and more. You can look at nature-bound problems, and they fit well into quantum computing; just the way quantum computing services are designed. What do you think about this intersection and on the hardware side and the implications; the massive data required in terms of the whole brain structure. There are new computational frameworks, and the interleaving of data within all of that? This is a little bit futuristic, but I just want to get some your thoughts.

Yannis Ioannidis 20:41

On the clinical side that we’re working on, the data is not that big. The data becomes really big when you go into the cellular, sub-cellular, molecular, and neural level, and then you get the numbers that you talk about, which medicine is not as advanced to be able to go to in order to deal with diseases. But when it comes to research, when you want to study the research, colleagues in the Human Brain Project, who are neuroscientists of various levels, it’s amazing what they’re doing by atlasing the brain or having actually the virtual brain, in TVB. The Virtual Brain is a tool where you can, to the extent that they have been able to, simulate the brain, and hopefully now there are attempts to use the simulations in brain surgeries. And in order to simulate though, you need HPC, you need high performance computing, exascale, I don’t know if we will go to zetascale that you talked with Jack about. But for the time being exascale would be enough. It’s … the sky’s the limit. And quantum computing, we don’t quite understand yet its capabilities. When will quantum phenomena get into the way of fast computing? But I’m really excited by the prospects of us being able to solve issues of brain simulations, and, others, and combining them with quantum and high performance exascale. High performance is at the boundaries that we’re talking about, and you never know what great things will come out of it. It’s already very challenging. But still, we don’t have a good understanding of the brain; we have a much better understanding than what we had 10 years ago, and not just by the Human Brain Project. There are brain projects in the US, of course, in Japan and in China, and in other parts of the world, Canada. And it’s a global, if you want, effort to understand this, let’s say, last frontier of understanding within our body; not that we know exactly what is happening in many other parts, but this is definitely … we are the furthest away of getting some understanding of the brain. And it’s all about data. Of course, it’s music to my ears, since I’m a data guy, that the more data you’re able to capture, the finer your simulations are in terms of the brain geometry and structure and the relationship of structure with function, which neuroscientists are really working on. The more data you have and the more complex the relationship, the higher the computational power you need; you cannot do with regular machines or regular clusters what is necessary in order to simulate; with a goal being, the digital twin of the brain! And the digital twin of the brain, singular, is already simplifying, because it’s not one digital twin. Everyone’s brain must have a digital twin because there are differences between my brain and your brain and so on. So, how to do that? We’ll have to be advancing both our hardware, our high-performance hardware, and our data manipulation techniques, and our computational skills and algorithmic skills for many decades in order to achieve that. So, there’s job security for all of us in informatics and computer science. And since I mentioned digital twin, in Europe, there is a recent initiative called Destination Earth. And the goal is to have the digital twin of the earth. Although the concept of digital twins started from industry, to have a digital form of a machine, a ship, etc., now, you see, this concept is transferred to much more, to different realms. So, the digital twin of the Earth, I mean, you cannot imagine, especially if you think about the brains living in bodies on Earth, but even if we ignore the animal kingdom, including humans, just the Earth, the atmosphere, the environment, it’s a huge issue to come up with its digital twin, you cannot do it without very strong HPC. And the world I hope will be united, and not divided in these efforts about the brain, the earth and so on. I hope we can find more things to unite us than things that have been dividing us. And science and the challenges that we face is a good motivation.

Advertisement

Stephen Ibaraki 26:43

I’m just going to interject with just some additional thoughts. And then I’m going to unpack your other part, which is this narrative in museums rather than exhibits, and the open access portion. Then we’ll get to the ACM and your role there. But what you indicated is just so interesting. You talked about the digital twin of the earth, and so I just want to leave this thought; look at octopus and they have a distributed neural system. It’s not like ours. And yet there’s some kind of cognitive capability, you have these plants and they can solve problems, their root systems can solve problems. So, there’s some kind of computational framework embedded within plants and you have entire forest species communicating in some sense. Something’s going on, or you’re seeing even at the biological, small microbe level as well. It may be it’s not just capturing what’s in humans, it’s encompassing all of that computational whatever is happening within nature’s system. Add in analog computing to this confluence of digital to quantum computing to analog, and analog provides maybe some new capabilities. So I just want to leave the audience with these thoughts. I want to mine what you mentioned earlier. It’s quite profound, not thinking of a museum as a series of exhibits, but a story in which the exhibits will come in as a supporting actor to that narrative. That’s just a marvelous thought. I can see the complexity in trying to undertake that. But that marries very well with this idea of a metaverse and not Meta’s metaverse, but it’s something much more fun, much bigger, right? It ties into this idea of digital replicas of everything. It can also tie into education. Education right now is: I take a physics class, I take a biology class, I take an AI machine learning class, but they’re kind of disconnected. What if we took the same concept of a narrative, which the supporting actors that come in on the underlying story? What are your thoughts about that? You touched somewhat on that, expanding it to archaeological sites, and so on? Have you started thinking in that way? Like, for example, in education, so changing that paradigm of education?

Yannis Ioannidis 29:22

Absolutely. Let me take the easy example; the chief example, so to speak, history. How do you learn history? And even if you forget about being in the museum environment, and you are just at home or in school or elsewhere. When we learn history, it’s a series of events, with dates, and names and numbers that overwhelm the essence of history. Students usually don’t get emotionally attached to what they read. And that emotional attachment, this emotional engagement is what you want to capture in every knowledge or information transfer from somewhere to you or to someone else. In the museum, it is the statues or the art pieces. In history, it’s the event. In order for whatever transfer of knowledge or information to happen, you need the one who is the receiver to be emotionally engaged, emotionally attached to what is happening. And cognitive science has shown that giving this knowledge and this information through a story is a very effective way; much more effective than listing or outlining, or just in a prose, exposing whatever that data, whatever that information or knowledge is. And therefore imagine, instead of describing a battle as “it was this many from this side, that many from the other side, and so on”, you listen (possibly you have a visual also, but even if you just listen) and you are part of it; you’re given what happened to that battle with you as one of the soldiers, or with you present, having a role and some of these soldiers being identifiable roles. You see the interactions through the story, which may have some fiction. As long as the fiction respects the story, and all the historical events that are brought out in the story are accurate and valuable, then it’s very likely that the receiver gets engaged. All this is going into their memory. And they get excited about the knowledge of this and they want to learn more. So, I think these story-based and interactive (I want to put the interaction in because technology allows us for these stories to be interactive) story experiences, virtual, or even web-based, or in situ, or something hybrid, and so on, I think they can change a lot the way we teach children or we learn most subjects. Maybe some subjects, it’s very hard. I don’t know how to do higher order mathematics through a story. Maybe some creative person can do that. But this general approach we’ve tried it, we have experimented a little bit in a couple of educational environments with this and the impact on kids is extremely promising. We’re planning to continue that. It’s also that these experiences don’t have to be for an isolated individual. You can be experiencing a story with your grandchild, or with your friends, or in a small group. And you each have separate roles in this narration in the museum or in a virtual environment where a battle is happening. Or just to mention a sensitive issue for Greeks. You know, we have the Parthenon, and many pieces of the freeze of the Parthenon and other parts of it are not in Parthenon, they are in the British Museum. There is a big issue of the British Museum returning these pieces to Greece so that they can be placed where they were in the Parthenon. Currently, we haven’t done that, but you can imagine being in the Parthenon and through the story and virtual reality or augmented reality, to be seeing the pictures from the British Museum pieces superimposed on the actual place. And if you’re part of it, and the story brings you to those times, you can imagine the impact and the emotional connection that you get with that richness of knowledge or art, depending on the kind of environment. Going back to your educational question, most subjects, I think, will have a much better impact, educational impact, if they are taught through stories. And not just through listing of facts and numbers and names and events. I’m a data guy, but a series of data is not the best way to educate; a story with the data naturally coming in, is cognitively a much more effective, more fun way of conveying a message and knowledge.

Stephen Ibaraki 35:54

I’m just going to do a little bit of brainstorming just to end this segment. And then we’ll get into the ACM. And because we’re running out of time, I just find this so captivating…

Yannis Ioannidis 36:06

And a few things about open science you mentioned, so I think it’s good to just give a vignette about open, openness. Yes, please go ahead.

Stephen Ibaraki 36:14

I just want to get the audience to think of the confluence of your work with Pattie Maes of the Fluid Interfaces research group at MIT Media Lab; she’s been looking at these problems for 35 years. I just wrote a Forbes article on her work and this (futuristic) aspect of learning and so on in human machine interaction and what it means and the emotional aspect combined with, I will call it (for the future), DALL-E 4, not DALL-E 2 (currently in test mode release), to where you can have photorealistic images from large models (using natural language descriptions), but the next iterations where you can get photorealistic movies being created in real time, combined with LaMDA, which is this language model (got a little bit controversial in the news), but really, it’s a language dialogue assistant. So it makes it realistic, and maybe GPT-5 (current version is GPT-3) or some kind of version of that. And UNITY, which is this engine for creating environments (for the metaverse, virtual environments, gaming, movies, animations), and also the Unreal Engine (Epic Games). By combining all of those, you can create exactly what you’re talking about. I just want to move on now to your open access. So, let’s spend a few minutes on that. And then we got to get into the ACM because you are the new president.

Yannis Ioannidis 37:32

Absolutely. What can I say; open access is a little bit about …; Open science in general, and open access is part of open science, is a different paradigm of doing science, whose principles are openness, accountability, democratization. It’s a fair way to do science, especially when we’re talking about publicly funded research and its results. It has been proven, besides the philosophical reasons that they make open science work, that it also has an impact on how quickly innovation can happen. By having the results in the open, not closed, you give back to the society what society paid for you. And quickly others can build on top of your results and progress in ways that you had not thought of, or in many ways that you don’t have the time to work on. Then, of course, you can pick up from the openness of their results, to continue your work. It is as if we are all collaborating with one goal and there is no competition. In fact, open science doesn’t only talk about the end results to be open. But in principle, even during your research, to be opening up aspects of what you do, to explain how you are doing the work. Not only how you did the work, but also how you’re doing the work now. It is as if an artist doesn’t just show the final statue that they created, but also open up for others to see sketches of the statue. One of the arguments against this is: but how am I going to get credit, because someone else will steal it. Well, first of all, steal as much as you can, in the correct way, always giving credit. And stealing means you becoming known by someone who stole from you, as long as it’s done in the appropriate way, you get credit for what this is. Then science can progress faster. And more people who don’t have the privilege of being in high-end institutions or in more developed environments, will have now an opportunity. Although they have the capability of advancing science, when it’s not open, they have a harder time. What democratizes the whole thing, with particular rules of conduct and rules of engagement, of course, that have fairness, morality, due credit, and so on, is accountability. This is what openness gives us in science: accountability, which means reproducibility and repeatability. In science this is very important, because so far, many research studies and many research results have been proven wrong; for one reason or another, the original results could not stand the test of time, or the test of others to repeat it. Openness helps dramatically in this direction and makes us scientists to be more responsible. So, very quickly, there are a couple of styles for openness; thank God, policymakers have realized this and established mandates pretty much around the world, for all publicly funded results to be open, for open access. There are efforts to evaluate the researchers and the scientists in different ways than in the past, so that open science pays off, for the scientists, for the researcher, himself or herself. So. it’s the whole environment of how to do research that is changing with openness. I think we are at a transition point now. In 10 or 20 years, I think we’ll see a very different research environment, which I think will be much more exciting and fun than it is now. Because research and science is always exciting.

Stephen Ibaraki 42:39

This triggers a lot of ideas. In my mind, I’m thinking of a million years of social innovation evolution. And it really always comes down to sharing a common language and having a large enough community. So if you look at different sorts of pre human clusters, and why evolution and innovation then progress or communities where there’s so many different dialects of languages, and yet innovation doesn’t progress. It’s always about sharing, having a large enough community, and having that open communication of that sharing, and which is what you’re talking about. In fact, now we have the world’s largest community of sharing with open access and open sharing. But it just fascinating because I’m just thinking over the last many 1000s and 1000s of years. Okay, we’ve got about 10 minutes left, we want to talk about the ACM. For the audience, they may not be familiar with the Association for Computing Machinery. Can you tell us a little bit about the history but also what are the main sort of prime factors of why people should be engaged with the ACM and then your vision for where you want to take it as president?

Yannis Ioannidis 44:01

ACM, the Association for Computing Machinery was founded in 1947. So, as you said, we are celebrating the 75th anniversary of the organization. It was the first organization of computing professionals coming together to form a group, an organization, in order to, as the mission of ACM says, to advance the art, the science, the engineering, and the application of computing. And of course, 75 years ago, computing was very different from what it is now. But the principle stays the same and the goals stay the same. Currently, ACM is the largest organization of computing professionals with more than 110,000 members, that deal with many aspects of computing, from data that I mentioned, to computer interaction, programming languages, AI, health applications and so on, I won’t name them all. The goal is for all of us to interact, in conferences, in workshops, and meetings; publishing research results (ACM is a publisher), generating educational materials (you mentioned education) at all levels. The ACM IEEE curriculum for computer science for colleges and universities is a standard, worldwide standard, I would say, that all departments pretty much follow or adapt from it depending on their environment; but also curricula for K through 12 and other particular environments. There is effort for practitioners, who are not researchers, not educators, but people in industry, whether it’s big industry or smaller industry, how to be informed about technological advances, and so on. So, anyone that has anything to do with computing is someone who should be a member of ACM. In all the activities and services that ACM offers, there are about 4 million people who participate in them, from very little just attending a webinar, all the way to organizing conferences and being elected officers. So, 4 million people, which is still a small fraction of everyone that is a computing professional, around the world, 4 million people are taking advantage of ACM services, and in my mind, all of them should be members of ACM. To contribute and to give back and to volunteer their services, because the more you give …, the more you get. I started as a graduate student to be a student member of ACM, and then a professional member, and 17 years ago, I went to SIGMOD, which is my special interest group, offering my services there and in a whole bunch of other areas. Many others have done that. It’s an environment and association or organization that has and operates based on certain values. The main value is excellence. Everything that ACM does is trying to achieve excellence, from the quality of the conferences and the quality of the journals, and all the other material that it produces; excellence is in the DNA of ACM. And that’s what everyone who is a member of is trying to live up to. And the other one is ethics. Currently, we computing professionals have the future of the world in our hands, I’m exaggerating a little bit, but everything that we do in society, in industry, in other sciences, depends on computing. And our responsibility now is much larger than it was 20 years ago, where our influence on the world was much smaller, let alone 75 years ago when ACM was founded. So, in addition to our science, in addition to our research, in addition to the technologies that we produce, we have to be thinking of the implications that these technologies and research results will have on society, on humans, the environment and so on. And we cannot be continuing on our way without taking these things into account. ACM has developed a Code of Ethics, which every computing professional should abide by. It is, if you want, the contract that every ACM member is signing when joining and I think all of the 4 million people should be signing this contract, our Code of Ethics. It was developed the first time a couple of decades ago and as of two-three years ago, we have the new Code of Ethics, which really captures the modern aspects of computing and how we should behave. I think the excellence that we’ve always had and we always strive for, and our Code of Ethics, is something that truly characterizes the spirit behind everything that ACM does. It is a worldwide organization, it’s a global organization. It started from the US, but it has members in … I don’t remember quite the number, 190 / 180 countries around the world; it has a global footprint, and as a president, one of the things that I want to ensure is that it will grow much more in other parts of the world, where it is not as dense. It hasn’t penetrated as densely into the computing professional communities in these parts as it has in North America and Europe and in some other parts. The other thing that is related to the expansion is about what we started our discussion with, about multidisciplinarity, which is something that I really care about. Many other disciplines, many other sciences, as we said, cannot do without computation, you have computational biology and you have bioinformatics, you have computational chemistry and you have chem informatics and so on. So, we have a whole bunch of large communities of scientists and other professionals who are not computer scientists, who are not informaticians, they are something else, but they are drawn to computation, they get some of the computing skills. Of course, computing professionals also sometimes go to the other end and get some of the other discipline skills. So, these people in the middle, where as we say, most interesting things are happening, at the meeting places, at the borders, at the seams, it is extremely important for them to come join the family of ACM. So interdisciplinary, multidisciplinary, transdisciplinary, I mean, there are so many prefixes that exist and the differences in the concepts are nuances, but they are important. All these colleagues have a lot to offer to ACM and ACM has a lot to offer to them. So, in addition to the geographic global expansion, and also working on other diversity, equity and inclusion aspects that we need to be working on, expansion to the mixed disciplines, where computing is involved, is something that ACM should make an effort on. I look forward as President to help ACM grow because the richness that can be achieved in that way is incredible.

Stephen Ibaraki 53:31

You provide a really profound passionate picture and narrative of ACM and why they’re so important. They are number one in the world. They are THE computing science community in the world today. The largest digital library in the world today of research and practitioner material that practitioners can use. Great education programs, as you mentioned, and many conferences. 37 or 38 special interest groups which are focus areas of particular domains of computing science. For example, SIGGRAPH is the largest graphics organization in the world in its own right. Many of the journals are number one in the world in their own right. The Communications of the ACM is famous as a top ranked communication vehicle magazine and journal. You’re sitting on top of this; or in parallel with all of your colleagues in this organization / in the community. What would be the ideal case; when you finish your term? What would you like to see when you say: “Yes. I’ve achieved my vision”

Yannis Ioannidis 54:50

My vision is too large to be achieved in the two years of the presidency. So, I’m trying to think “high”, but also to have my feet on the ground. There are so many aspects I want us to be changing. Let me throw out a few things I want. And again, it’s about expansion, it is a vision that all 4 million people who are engaging with ACM, I would like them to be members of ACM. This has nothing to do with finances, or monetary issues. This is secondary, I mean, we have to study this. But the principle and the concept is that these 4 million people or more that will learn about this now, they should be members of ACM. If I can move the needle noticeably in this direction, that will be amazing, I’ll be very happy. Ιn the same vein, to have substantial presence in many other parts of the world, besides North America and in Europe. Increase North America, increase Europe, but also many other regions where we are far behind: Latin America, Africa, Southeast Asia, and many others. In doing so I want the spectrum of the profile of membership to become a lot more diverse, and a lot more inclusive. ACM is doing tremendous efforts in this direction. But still, with respect to women in computing, we have a lot more work to do and also on underrepresented minorities and in general, colleagues, professionals, that may be looking at ACM as something awesome and very high and unreachable and untouchable. I would like to establish mechanisms together with my colleagues and staff to make all of them feel welcome to ACM and be open to them and help them grow, and for ACM to grow with them by listening to what they bring that ACM may or may not be thinking about, because these people are not part of ACM. So, if in all directions, where ACM is not rich, we become richer in terms of profiles of members, whether it is a scientific profile or geographic profile or gender profile or any of these aspects, then I’ll be happy. Also, age profile; how do we attract the young generation? That is, this information deprivation that I had when I was young, because it was not as easy to get access to information, now with the web and the internet and openness and so on, this is not an issue for the younger generation, who was born with a mobile in their hand and a tablet in the other hand and glasses that show you something, a third thing. … So, attract to the values that ACM has, to attract the young generation! And our code of ethics and our values of excellence and other aspects around it are a key for the young generation; the young generation has pure eyes and wants us to move towards helping the world and making the world purer. I think the young generation will come help ACM to move in this direction, move towards AI for Good, move to interact with the UN and with the Sustainable Development Solutions Networks that are around the world to save us from the climate change and poverty, and to achieve all the 17 SDGs. So, if we can move the needle in a noticeable way towards diversifying, increasing our responsibility in doing that, and increasing our membership (again, I don’t care about the numbers; I care about the essence that is hidden behind increasing the numbers), then I will feel successful as a President.

Stephen Ibaraki 1:00:19

Yannis, you have your background and the fact that your upbringing and the mentors you have had and you continue to have and also your colleagues and the nature of your work is very much about all of those pieces.

Yannis Ioannidis 1:00:38

Also, students, I owe a lot to my students.

Stephen Ibaraki 1:00:42

You live the vision. So, you definitely are the role model for where you want to take ACM. Do you have any additional closing recommendations to the audience and then that’s the end of our dialogue here.

Yannis Ioannidis 1:01:04

Put your own standards to your life, to your professional and general life. Go after your dreams and connect to people that think differently from you. And have a joint trip with them in life and in work. And if you are related to computing, join ACM

Stephen Ibaraki 1:01:43

Thank you for coming in and sharing your insights, your history, your stories with us. And I really, really enjoyed our time together. I wish you much success in your journey and let’s do this again.

Yannis Ioannidis 1:01:58

Thank you very much. Thank you for having me. It was fun. Looking forward to the next opportunity. Thanks a lot, Stephen.

Advertisement

Leave a Reply

Your email address will not be published.