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The Connector.
The Connector Podcast - Unveiling AI Ethics with IBM's Insight and Navigating Digital Partnerships with Arrow
Get ready to navigate the complex tapestry of AI ethics and partnerships with the Connector podcast! I’m Koen Vanderhoydonk, and in this episode, I’m joined by IBM's Michel Van Der Poorten and Arrow's Francis Mukwayanzo to unravel how the tech titan IBM harnesses AI to amplify human ingenuity. Michel grants us exclusive access to IBM's conscientious approach to AI ethics. We don't stop there; join our discourse on the intricate dance of global AI applications and legislation, where you'll learn why the EU is at the forefront of this arena.
Continue to the conversation a link with us on LinkedIn
Michel: https://www.linkedin.com/in/michelvanderpoorten/
Francis: https://www.linkedin.com/in/fmukwaya/
Koen: https://www.linkedin.com/in/koenvanderhoydonk/
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Koen Vanderhoydonk
koen.vanderhoydonk@jointheconnector.com
#FinTech #RegTech #Scaleup #WealthTech
Welcome to the Connector podcast, an ongoing conversation connecting fintechs, banks and regulators worldwide. Join CEO and founder Cohen van der Hooydonk as you learn more about the latest available trends and solutions in the markets.
Speaker 2:Welcome to another podcast episode from the Connector, and today I have a special guest. It's a partnership and it's IBM and Arrow. So can I start with you, Michel IBM.
Speaker 3:Sure. So hi everybody. I'm Michel van der Poelten, I'm working at IBM and I'm in charge of recruiting new partners to our ecosystem and been involved with AI for the past 10 years.
Speaker 2:Oh, excellent. And on my right side, Francis from Arrow.
Speaker 4:Thank you for the opportunity Indeed. So my name is Francis. I am Francis Mukweyanso.
Speaker 2:I am part of Arrow ACS, who is IBM's value-add distributor, and I'm responsible for the business development activities helping our business partners grow and expand our businesses guys I hope you're as excited as I am today, because it's a real joy to have one of the forefront players in ai ibm around the table, and everyone probably knows about the blow, about jeopardy and about all these magical things that were done by IBM. But what I'm wondering is what is the future? Like Michel, Sure.
Speaker 3:So, koen, let me first take you back six years in our history, to 2018, when we had something which you didn't mention yet, which is Project D-Baiter. Project D-Baiter was actually a large language model avant la lettre, because we were able to play the game of debating and actually win against professional debaters and win on the information side. However, on the way the message was brought, the human debate was better. So for me, it really underpins already one of the fundamental principles we have. It is about augmenting humans, not replacing humans. The other thing which we think is crucial is that AI is there to help business, and that also means that what our clients are doing with our solutions the insights are theirs, the data is theirs. We don't want anything to do with their own stuff. It is their stuff and will remain their stuff. That's the way we view the use of AI.
Speaker 2:All right.
Speaker 4:So basically AI for business.
Speaker 2:I think, a very important element that you touch upon immediately, especially when you talk about human interactions. It's around the ethics of AI. So what's the view on ethics?
Speaker 3:So for us it's the basis of everything actually. So inside of ibm we have two ladies who are in charge of our ai ethics board. Those two ladies are francesca rossi and christina montgomery now. Francesca r Rossi was originally a professor in Italy, but she's one of the ladies who participated in the High Expert Council for the EU legislation, so she's been involved from day one on distilling this legislation and then brought those insights into IBM and we now have a board which reports directly into our corporate board on how do we handle AI ethically, and that has been brought into a complete methodology which is being deployed across the whole of IBM, also making sure that everybody at IBM is trained to understand what it actually means to have ethical AI. So it's really at the corner or at the center of our way to go to market to develop our products.
Speaker 2:And because, I mean, ibm has always been a global leader and still is today. So what I'm wondering? If you look at AI and the applications, do you actually see a difference in regions, in areas, in countries?
Speaker 3:So for sure, the EU is ahead of the pack as far as regulations go. We, as everybody knows, here we have now, I think, for two weeks, the regulation has been passed. Now, of course, it needs to be translated in local legislation, but the regulation as such has been passed, so that's excellent. We see some upcoming regulation in the States. There's the Presidential Act on AI. There are a number of organizations being built around ethical AI, so I think it's completely different in the landscape, but you see that it's picking up uh interest and importance all across the globe. So what we're trying to do from an ibm perspective is because we're working with global clients as well is to help them understand what are the regulations in the different regions and make sure that we help them conform to the local legislations to make sure that they don't get into trouble.
Speaker 2:And would you see from a Watson application point of view that there are also different applications in different regions of the world?
Speaker 3:So, for Watson is our older name, we now have Watson X. Why did we add? What's an x to it? The x indicates that we're now also able to handle next to traditional ai, machine learning and so on, we can also handle generative ai. Um. Are the differences in what we see across the world? The world um? Not that much, I would say today. For us, the three main use cases are customer interactions. Secondly, it's all about internal optimization. And third is everything to do with coding helping developers code in a more efficient way. Those are are three big domains, and those three big domains help us distill offerings which work across the globe actually. So that's what I see. I don't see that many differences from a use case perspective.
Speaker 2:I have to admit that moment. Well, I think you're the ultimate person to ask, because you're responsible for partnerships. A lot of what we see today is around collaboration. How would you marriage, partnership, collaboration and an AI?
Speaker 3:Yeah, so actually, ibm has made a huge change over the past two years and for us, the first route to market is actually our ecosystem partnerships and, by the way, arrow is, in that domain, crucial for us because they are the interface towards the end partners and those end partners have their end clients. So for us, this is the first route to market. Secondly, what we see is that a lot of those new partners are working on AI technology, but they're using full open source stacks, which is great. But what they sometimes lack is the possibility to bring it to an enterprise level, and that's where we can combine our technologies with the open source knowledge together, often with their own intellectual property, which we can enhance with bringing our technology into their solutions, so that they can focus on what sets them apart from the competition, and we can help them strengthen their offering in different domains. From a platform level, from a cybersecurity level. Those are different topics we can also address together with these startups, which typically don't have that expertise in those domains.
Speaker 4:But I guess also in addition, like from a regulation-related aspect.
Speaker 3:Of course. So we also help those VPs make sure that their solutions comply to the regulation, because they are ultimately selling this solution to their clients. They need to make sure that what they're offering meets the requirements of the regulation in the country where the client is operating.
Speaker 2:And do you have some examples that you can share with us where collaboration in AI was established?
Speaker 3:So we have a partner and, by the way, we've been working together with Arrow on that partner and that partner has developed a minimal, viable product on helping their clients understand the regulation on AI and what they have to do to be able to afterwards translate it into a real solution. So they they have ingested all regulation on AI. The DPO, so the data privacy officer or the chief data officer, can ask questions to the system. The system will ask clarifying questions. The DPO or CDO can then give those additional information, gets back the correct information on the regulation, can even look at the source of that information and then tell to the business who wants to do certain project okay, this is in line with regulation or not. And what we're also looking there, together with Arrow, is to be able to involve the AI lab of Arrow. Maybe, francis, you can give some more details on that side.
Speaker 4:Yeah, sure. So first of all, just to kind of clarify the role of our AI lab on a nutshell and to put it simple, no-transcript. So the AI lab is there to help our business partners go through testing projects, trainings, deployments aspect, but also to be able to use it as a sandbox for them to really train themselves.
Speaker 2:Very important.
Speaker 4:So I think it's a very strong initiative that's really adding a differentiating value for our business partners. So in that perspective, we are indeed working very closely with the IBM client engineering team to really make sure that we have a total package helping our business partners with their go-to-market initiatives.
Speaker 2:Well, thank you for sharing that. I cannot help it because when talking to somebody from IBM, I think what comes to me is that you guys are so much involved in a lot of the big organizations worldwide. So today we talk AI, but I could also have like a call on cloud and cybersecurity, but let's maybe put them in the mix. So how do you see AI is actually helping on those more traditional elements in business?
Speaker 3:Sure. So what we see is that AI, whether that's traditional AI, so machine learning, or generative AI will be a great help in increasing the cybersecurity. Now we should not kid ourselves the bad actors will also have access to this kind of technology. So it will be, of course, as always, it will be a race to make sure that we stay ahead of what the bad actors can do.
Speaker 3:At the same time, we also know and unfortunately we have had very recent examples here in belgium as well, on bad actors able to get in to organizations. So there we're also working on and even have developed solutions which are there to protect against ransomware. Or, if the ransomware has been unfortunately deployed and the data is blocked, we are able to get back to operational state as quickly as possible because we can assure that the data is indeed safe. And we now have even introduced at the level of memory chips that we can detect at the level of a memory chip whether there is a virus being added or a trojan. So we really have, at even at that level now, the capability of detecting that kind of behavior, amazing, amazing.
Speaker 2:So I guess we almost do our last question, and the last question is usually about what does the future look like? So I'm wondering um, where does all this innovation lead to, and how does that look like for IBM, but also for Arrow?
Speaker 3:Sure. So for us, one of the things we see and you probably have heard about that, Koen there are a lot of large language models which are being added all the time. You probably also heard that they consume a lot of energy. So one of the things we're looking at is making sure that, with lean and mean large language models, we're able to address the requirements of the market, of our clients. But that's only one aspect. The second thing we've been working on that's together with our colleagues in research is on making sure that the way to develop new large language models can be done in open source via community approach and you will hear a lot more about that later this month, so I can really have a teaser there. And together, of course, with Arrow, we will certainly be using more and more their AI lab, because they have functionality and possibilities there which we currently don't have, even on our cloud. So that's great to be able to have that kind of collaboration.
Speaker 2:So one plus one makes 11, Francis.
Speaker 4:Yeah, definitely. And to add up on top of that, I think, um, from from, from our perspective, you know like we represent a multitude of different vendors. So, um, in the era where ai is such a big topic, a big, important topic, um, we find it as part of our responsibility as well to make sure that any technology or solution we're providing to our partners, to the market, actually not only ethical but also secure. So I think one of the strengths that, when you ask a question like looking ahead or whatsoever in regards to IBM technology, is it's a technology that's always, you know, like looking ahead in different aspects, including security, including, you know, regulations, but also market dynamics.
Speaker 2:I think the market calls that AI for good, and that's probably a very good closure for this conversation because it opens up a lot of interest for more conversations. So maybe, francis, I heard that something nice is to be announced.
Speaker 4:Yeah, well, there are many things to be announced, many nice things to be announced, to be more precise, but in this particular case, yes, we have, as a distributor, we have several initiatives that we undertake to make sure that, okay, that the market awareness is there, but also inspiring the markets on the right approaches, the right technologies, et cetera. So, in that spirit, we are organizing a roundtable, this time in Luxembourg and for our business partners, whereby we want to provide them with practical insights on, okay, what is AI for good and what does that mean and how do you go about it? You know, like, where do you start? Where?
Speaker 1:does it end?
Speaker 4:Does it even end somewhere. So this is on the 25th of June, so, if you're interested, I think this is a right call to action, like come and join the conversations.
Speaker 2:Yeah, then let me make it even more concrete. How do they catch you? How did I catch you? How did I contact you?
Speaker 4:It's very simple. So my name is Francis Mukweanzer. I am actually the business developer manager looking after IBM within Arrow, so please call Arrow or email me. I'm to be found on LinkedIn, so it's a very unique name and very, quite easy to find Mucuayanzo.
Speaker 2:I will make sure I put it in the comments, because I have a difficult name too. What about you, Michel? Where can people find you?
Speaker 3:For sure, I'm also on LinkedIn. You can also find me on Twitter, sorry, on X, as it's called now. So my handle there is MichelVdp, but just reach out to me, and my name is also quite difficult to spell, so, kun, if you could put it in the comments I'll definitely do so, and I thought I was the only one with a difficult name, but join the club gentlemen, thank you so much for having you both in this podcast.
Speaker 2:This was amazing. Thank you also for the audience of tuning in and more of this insights from the industry to be followed in this podcast channel. Thank you very much.
Speaker 1:Thank you thanks for listening to another episode of the connector podcast. To connect and keep up to date with all the latest, head over to wwwjointhekonnectorcom or hit subscribe via your podcast streaming platform.