Panel What Do We Still Need to Learn?

Speaker 1 [00:02]

Oh, welcome to the next session, panel. What should we learn in the future? So this is also part of our initiatives, get outside and other perspectives together. And also, like, there was always a quick question, AI agents, coding, learning. and so actually paula paula is unfortunately sick so if you watch the stream get well soon so there was a workshop a lot of discussions at the conference and now this panel is about wrapping up and also bringing in sebastian from mercer to bring like the non-python developer bubble perspective here from the the other world like yeah because this community as you know was always about cross-pollination, getting different perspectives in. So I'm really looking forward on what was the outcome of the workshop and would like hand over to Sylvia to moderate the discussion. Please give them a warm welcome.

Speaker 2 [01:12]

Thank you So, thank you Alexander and I think this panel is one of the most decisive ones because we discuss one of the most fundamental questions, which is What do we still need to learn? Do we do we need to learn anything anymore or does AI? agents do the age AI agents take over And we would like to discuss the next 30 to 40 minutes together with you as well. Because there we have a seat and a microphone and we will give you some impulses from different perspectives. And then we would like to invite you to tell us your opinion and your opportunities in terms of learning. And in this panel, we would like to discuss the different learning aspects, how does AI reshape organizations, if it is already in state of the art or if the organizations are at the beginning. and also we would like to look at the skill sets. Is the skill set we have right now, is it enough or do we need other skills? And this is, I think, the most decisive point and we would like to take the discussion out of the ivory tower, beyond the ivory tower and then go into the realities. And let me just shortly introduce my two panelists. First of all, Dr. Christian Rother. I think you all know him. He is one of the organizers of the Python PyCon Festival. And he's a data analyst and also is talking about machine learning from his experience, background. and he's a software engineer and he wrote several books he told me yesterday so he will take over the perspective from the developer part and I made a workshop with him yesterday and we were talking about the learning challenges in the workshop yesterday and we would like to integrate this into the panel as well Yes, and the other panelist is Sebastian Unterreitmeier, so he is senior principal at the strategy consultancy Mercer and he is also part of the global center of excellence, is that right? And he is experienced more than 20 years in advisory of strategic people topics, so we meet him right in his core competency with our topic and i would like to open the discussion with a broader question i would say for um sebastian so um can you tell us maybe uh how mature is the ai adoption in certain industries can you give us an insight on that so i think

Speaker 3 [04:38]

So I think it's a very, very broad landscape we see. There we see still companies where they use just, you know, they deploy co-pilot and then people can use it or not. Nobody cares. Nobody's tracking the performance or something. That's the one side. The other side, we see that, especially in the software industry, companies actively working in creating a human AI workforce with the hope to employ the least possible amount of humans and the largest possible amount of agents. And that's, I would say, the broad perspective we see. Everybody's struggling with measuring the outcome of AI and the revenue gain. So it was promised that we will be 20% more proficient and productive, but the CEO is saying, okay, where's my 20% revenue rate or where's 20% cost reduction? So that's still a topic where we need to see how long companies will be investing and deploying AI when there's no measurable gain. I think there is, but it's not measured at the moment.

Speaker 2 [05:48]

So you just mentioned the cost cutting mechanism. So do you what what is your experience? What does this focus do with the people when they are just regarded as they are part of the Output oriented world they are part of the cost cutting mechanisms is what is your experience? What do their the clients say?

Speaker 3 [06:11]

I mean, it's that very bad practice of the CEO and the COO to optimize for the next quarter or this quarter results, right? This quarter results or they're gone or maybe the next quarter.

Speaker 2 [06:25]

in

Speaker 3 [06:25]

In this economy at the moment, it's attractive to say, okay, let's reduce our cost. How can we reduce our cost? How can we use AI and let go of people? A lot of companies are starting restructuring right now, and the question is then, what kind of capabilities do I need to be proficient in the future, and what workforce do I need to do that? And some companies start skill-based restructuring, structuring, which means that they are not just cutting out of the org chart a few people here, a few people there, but think about what kind of capabilities do we need, actually what kind of skills, and who's got these skills, in the hope that we can keep those people and lay off other people.

Speaker 2 [07:09]

And maybe a question also for Christian, do you see that there are some AI native firms, so to speak, and they outperform the more traditional and more established companies? Do you see this in your freelance?

Speaker 4 [07:31]

I see an entire spectrum. So I see companies who are just starting to adapt who are waiting because they Observe that AI is a very new and very volatile technology where the the current buzzwords They change every couple of months at the moment I see Organizations that are more organized a more More open to experiment but some of those are struggling to keep things consistently in product production. I think that has to do a bit with error compounding. I do not see, I cannot think of a single example where an AI-centric organization has like massively outperformed a traditional one because I believe there's a firm portion of engineering that does not go away.

Speaker 2 [08:26]

And maybe you just mentioned this, I think, in one of your answers. Do you think that we are misunderstanding AI in terms of adoption when the company is treated just as a technical issue? So do we concentrate too much on our IT departments and they will deploy it? So is it too much we do the things we know already and too much risk averse?

Speaker 3 [09:04]

Well, I mean, a lot of companies see AI as a tool. And when I buy a new hammer, the whole world becomes a nail, right? You said hammer on everything, on my nails and screws and whatever. And that works to some extent. It might solve some problems, but I think we need to really fundamentally rethink the work and rethink what tasks in a certain job profile can be taken over by AI and what are other tasks where it really is valuable to have a human there and human knowledge and critical thinking and a sense of security and a common sense even.

Speaker 2 [09:41]

But are the company really in this state already that they break down their jobs to tasks and that they see, okay, this is a kind of standardized task and maybe an agent can do it. So do they dare to do this? Are they in this situation already or is it just a plan?

Speaker 3 [10:05]

No, it's it's I mean we I'm doing this in project worldwide for for 10 years and we called it Skills-based workforce planning and in the beginning and now it's more like future skills or something So it's it's about and the initial idea was also to say how can I get more value adding work? Or how can the job focus on the on on what is creating value for the company? And then you go to an automotive company and you see that their top R&D engineers are spending 20% of their time just I'm just putting data into systems, something that you could do with RPA or where you could, you know, you can bounce that to an assistant role or to junior role. So that was the beginning of that. And now with AI, it gains more traction and more companies do that. And I think it's still the role of HR to do it, but HR struggles a little bit with going into this business discussions and also maybe taking on the tension that is in the room when doing that.

Speaker 2 [10:56]

So do you also have in your projects the the question of what how will the role of the developer Change is it do you have also experiences with developer data scientists? Yeah, all kinds of developer because our audience consists of a lot of developers

Speaker 3 [11:16]

of developers. Yeah, I'm currently doing that for a company, Global Software Development, and they will go into an agentic workforce mainly, let's say, and that's the big question. What's the role of a junior developer and how can we develop junior people to be seniors? Because if we just focus on seniors with agentic AI, then in 10 years we will have a big demographic problem, right? So how do we train junior people when we are robbing them of the experience of going to that valley of pain writing boilerplate code and stuff like that, right? And that's a question, yeah, absolutely.

Speaker 4 [11:51]

I don't think this is a new problem, but like in many other examples, the AI acts as an amplifier here.

Speaker 2 [12:03]

So, who is responsible for, you just mentioned the AI department, and I've seen in your, there is a global study from Mercer, and it's called Global Talent Trends, and I remember there was one insight which was, I think, very central, the strategic gap, you called it, that you have the perception gap between the C-suite and HR, and what is this gap? Can you tell us a little bit about the mutual expectations on both sides? You just mentioned that HR is not at the business table.

Speaker 3 [12:46]

Yeah, so HR in a lot of companies is focused on the people topics they would say, but they're not talking to the business. So I would say they ignore their customer. So they should develop methods and standards and best practice, not only to help the individual, but also the organization. And that means that they need to come closer to the business, that they need to be part of that strategic discussions, that they need to understand how the company makes money and what kind of capabilities we need and how that translates into the roles we need and then also ultimately in the skills and what HR can do. And a lot of HR people are shy at the discussion because it's not always a good or an easy discussion. And we see that the majority of strategies, the company strategies I get from clients that were developed by the strategy consultants, but none of them is a translation between what we want to do in the strategy and what does that mean for our workforce. We will automate 90% of our customer service. Okay, so we let go of all of your customer people. No, but that's what you're saying. And we are often bridging that gap and making that translation. That should be the role of HR, but it's not a comfortable one. But, yeah, who else should do it, right?

Speaker 2 [14:00]

Yeah, I think that they missed for years that they have this translation between the c-suite and also between IT and HR which is also I think a big topic for years that they should work closer together Christian what is your experience? What what can be an idea for them to work closer together because AI is a chance It's a threat, but it's also a chance. I think for for both departments

Speaker 4 [14:28]

for for HR and and IT and

Speaker 2 [14:30]

And IT. Yeah.

Speaker 4 [14:32]

The threat that I see at the moment is a bit pointing into the other direction because I hear a lot that, at least in the bigger companies, that they receive a lot of CVs from applicants that have been generated by AI and then they get evaluated by an AI. I think I may be wrong because I'm not working in any of these organizations, but that sounds to me like there's more distance being put between the people, not less. Thank you.

Speaker 2 [15:03]

Okay, so that means, Sebastian, a question to you, so what is your experience, how can an alignment, is there a chance to align between IT and HR, or do you think that they are in their both own worlds, and they have so many different tasks on the table? because I just remember the the digitization so they had to they they appointed and announced and CDO and then they said okay now we have the CDO and he can do everything do you think it's the same with the AI implementation and adoption

Speaker 3 [15:47]

I mean, talking helps. It would help if they would even talk to each other, right? So if there would be a real urge to understand each other and to understand the different perspectives and to understand the technical capabilities, but also the ways how this is changing work. So when we're looking or helping companies with AI adoption, and I'm responsible at Mercer for that topic as well, within our company, the problem is not the junior level. They know AI, they use it, They have good experience with it because they now can close the knowledge gap faster. They cannot evaluate all of the output because they are missing the experience and the years. But they have more access to knowledge now. The problem is people like me are doing this for 20 years. I could say, I know everything about it. Why should I disrupt my own practice? We do the project the way we did it for 10 years. It's good enough for the client. right and this is the thinking that you need to need to reshape and that goes for all of the all of the functions and in the company that you think about how can you do work differently how can you yeah basically disrupt your own your own practice

Speaker 2 [17:03]

What would you say, there is also a big task, I think, for the leadership inside the companies. And I made, personally, I made the experience that the leaders just, they hesitate and they do almost nothing and they just see the ball rolling. So what do you think is their role in terms also of trust building and in terms of transparency, I would say?

Speaker 3 [17:34]

I think that we have a fundamental wrong understanding in a lot of companies about leadership. So I have direct reports. My direct reports are not working for me. I'm working for them. It's my role to move them forward, to give them opportunities in terms of projects and to see them grow in whatever direction they want, even if it's outside of Mercer, I'm fine, totally fine, and to enable that and to even the path for them. And as part of that, I need to bring them aboard on this AI journey and make it mandatory for them to use it. And I think a good way what companies are currently starting to do is to basically make AI usage part of the performance management. So really force, if you will, managers to make moves in that AI adoption direction and also disrupt the practices within the company before the market will do.

Speaker 2 [18:34]

Yeah, that's a good point because you are talking about enablement and I also see that there is less enablement than it should be. There is more pressure on each employee, but I think enablement also means that you maybe integrate your performance goals also with the development of people to do this together, not just do the one thing or the other thing. And I think there is still a lot of work to do. So Christian, what is your experience there?

Speaker 4 [19:07]

On the development of staff.

Speaker 2 [19:10]

Yeah, also in terms of the leadership, so the behavior of the leadership in this situation when it comes to reshaping the organization. Are you still in these projects as well?

Speaker 4 [19:25]

It's it's small company projects, but but yes So the the difficult the difficult task is to come up with a long-term plan at the moment So that because you need to make a decision What is it that you want to do what what you want to try or what you want to get done? and and making that decision right now is Is hard because the tools next year might already Have have shifted to a new spot. Yeah, so because we are we are still from an engineering point of view we are still in the process of understanding what we can do with this ai thing yeah i don't think we have fully understood that yet yeah so that is that is hard that creates uh that that creates uncertainty for for everybody involved i guess

Speaker 2 [20:14]

Exactly. So let's maybe switch to the topic we had yesterday already in the workshop, and I'm not really sure who was joining the workshop, but it was really interesting to see that a lot of people were thinking about the topic, what can I learn in the future?

Speaker 4 [20:15]

Exactly.

Speaker 2 [20:36]

and I think they were very hopeful that there is still a lot to do for them in terms of the skill set in the future. But if AI can code, write and process, so what should human learning be in the future? So maybe we can open up the discussion a little bit more on the skill level. Yesterday we had this topic of where is my critic? Is creativity the thing I really would like to do in the future? And am I afraid of losing creativity when it comes to AI as an assistant? So what is your opinion about it?

Speaker 4 [21:22]

So my understanding of creativity is that it needs a fundamental skill base. Yeah, like if you want to play music, you need to rehearse the musical scale first. This is why I use Python libraries to make pictures. And I make my students make pictures with Python. And I think these fundamentals, they don't go away. I have a top 10 list of IT skills that I transmit to my students from time to time. Python, by the way, is not on the list. So there is stuff like the bash command line version control with Git. There is Docker. There is fundamentals of algorithms and a couple of more. SQL and RegEx, they are candidates for getting dropped off the list because AI has made that part quite easy. But I believe the other part is still quite essential to know what's going on when you are working close to engineering or in engineering.

Speaker 2 [22:30]

Sebastian, you told me before the panel that you have a different opinion on creativity.

Speaker 3 [22:36]

creativity. I have two very conflicting words in my mind. First of all, I come from a creative background doing photography a lot of years also professionally making electronic music as a hobby so I'm very, very concerned when it comes to AI going in that direction and being better than me of course. So that's the one thing. The other thing is the business perspective and if you go to a boardroom and tell them about creativity they will say, how does your creativity make me money? And I think there's a fundamental misunderstanding about creativity in the business context. Nobody wants people to be creative. They want people to repeat successful patterns. I hired the art director from Adidas at Puma because he was very successful at Adidas and I hope that he can transfer that pattern to my company. Nobody wants Taylor Swift to be creative and start Mongolian goat throat singing, right? And she should please repeat the songs she has, of course in a variety, in different topics about love. And that's what we love her for, but it's about repeating patterns, it's not inherently about creativity, unless that leads to breakthroughs, of course, and to new products or something. For that it's very helpful, yeah.

Speaker 4 [23:54]

Okay, but the question is how do we understand creativity, not how we make money, right?

Speaker 2 [23:59]

That is the following question right now. So you have a different interpretation of creativity than Sebastian.

Speaker 3 [24:10]

I don't know, I think it's, I mean, the thing is, I think we come to the baseline that the work of people are evaluated based on what they contribute to the company. I had a CEO a few weeks ago and he said to me, every hiring decision is a one million dollar decision. I was like, why is that? Because the average salary rate all in is 100,000 euro and people stay for 10 years. The one million dollar decision, if I hire someone, I want to know what I get out of that person. And you can despite that from a moral and ethic point of view, but that's how capitalism unfortunately works

Speaker 2 [24:48]

Yeah, creativity was a big topic yesterday and we also talked about the The skill critical thinking which is also I think everybody has has a different thing in mind when it comes to critical thinking what is it and It's also I think context-based in in terms of in which business context you are But I think this is also something we have a common sense about that we need our critical thinking when really AI penetrates our jobs too much so so what is it for you critical thinking we were talking about that yesterday already

Speaker 4 [25:30]

Yeah, I'd like to rephrase one point where the discussion made me think of. There is a field in philosophy that is called epistemology, that is the science of knowing things. I don't think that is part of most computer science curricula. I came across that more or less by accident or because I had a mentor who gave me a book about it. And it's thinking about systematically whether we can trust something that some results show us. And it's become more relevant today than it was before because if we have a machine that is basically producing words and we know that maybe one in 10,000 words is wrong and we have it produce one million words in a row or a billion or whatever, But it becomes a math exercise to find out How probable it is that the total result is correct. Yeah, and what does it mean if these these small arrows? arrows if they accumulate is that something that we can deal with or Does itself correct or? Does the error mess up everything over time? I don't know. Yeah, we don't that that is for us to find out

Speaker 2 [26:58]

But I'm wondering if this kind of critical thinking is interested for a leader or somebody who has a team and he said, okay, let's just substitute some skills through AI. And so how do you bring this critical thinking to the attention of the leaders that they see, okay, we need this guy and we need exactly his skill?

Speaker 4 [27:28]

I think that becomes a risk in the terms of leadership that has to do with risk assessment. If I use an AI model, there is a residual chance that the AI will mess up hopelessly. And at the moment, that risk is, I believe, a bit higher than when a human does the job for quite a lot of cases. I'm not talking about translating a piece of text. They are quite reliably doing that. I'm not talking about transcribing voice, I'm not translating about translating Python to Java but about, I don't know, writing requirements for a programming project, for instance, that I would not dare to give away.

Speaker 3 [28:12]

Yes, absolutely. I would agree it's it's it's more it so and I think it's a very very good idea also to Assess and which parts of the company for which jobs you can use a is at Mercer. We do a lot of Pension investment and things like that and we are very careful if you're using I for that and for which purpose In consulting if you you know If you have ten interviews and you need a transcript of the interviews and then you need to summarize that if there's a mistake in it It's not nice, but it's it's not you know, something go up another day but if he screw up some investments that would be bad so I think it's very and then and there the board is listening you know when you're talking about risk and risk mitigation so I think that critical thinking is extremely important and it's also something and I like the philosophy thing you mentioned I need to learn that word my wife my wife is epistemology epistemology my wife is philosopher I can impress her today so no the thing is I think it's also critical for juniors to learn that and not only have a python or coding experience but also have or build up domain knowledge build up expertise in pharma in in finance whatever whatever your your your area is and bring that together so not only focus on coding also focus on how can you can you help them the company make money how do you understand these business drivers and how to mitigate risk and I think also from I think AI is you know it's trickling in everyday life in a way that we couldn't imagine probably a lot of people here use AI also for to deal with or have a companion for mental topics or to you know shape certain ideas in their head and something like that where it's not only about translating so how do we make sure that this is purposefully treated and the data safely stored, the data not used for whatever purpose that is malicious.

Speaker 4 [30:09]

I'd like to give a positive example, because so far I've been a little bit cautious, that might go well with managers. If I have some work of a junior developer or a mid-level developer that is automatically reviewed by an AI or a senior developer as well, then we have a rather cheap mechanism to improve the quality of code that otherwise would require a senior person to spend a considerable amount of time. And if we have an extra guardrail before that, that makes some of the issues go away that might make companies more productive or make programmers more productive.

Speaker 2 [30:58]

Yeah, but this is also a good point to talk about more on the side of the social skills we need, or maybe we now define as really valuable, because you just mentioned the problem-solving side. What do you think in terms of maybe social skills like more empathy, development of more empathy, trust? Does this have more attention right now or what is your opinion about that?

Speaker 4 [31:34]

So, I'm observing that there's a lot of people around me who notice that having a healthy environment in their communication is more and more important and they are prioritizing that for themselves. I think that has a little bit to do with the pandemic that we had five years ago. That in in a sense I feel that that many of us still recovering for that I I sometimes feel I do yeah that And Taking taking care of your own mental well-being is part of the job of an engineer and maybe that That did not have such a high priority Priority ten years ago as what I observe today

Speaker 2 [32:33]

today.

Speaker 4 [32:34]

At least people are more open to talk about it. And I appreciate that people talk about it at this conference here.

Speaker 2 [32:44]

Yeah, Sebastian, what is your experience on the meaning or the stronger meaning of the social skills? Does it raise in times of AI or what do you think about it? Like I just said, empathy. I hear a lot of empathy words when it comes to leadership, for example. Trust also when it comes to AI. So are these also the words in your business context?

Speaker 3 [33:14]

Yes, and I mean, it's from a career perspective, and I think that is valid for forever, basically, is how do you connect in the company and what are you known for? Are you the person known for writing code or are you the person known for understanding the business, taking on the requirements, having exchange with them? Even if you're just writing the code on a junior level, do you seek that exchange with the business side, with the stakeholders? do we try to understand that that's important because then you will be known for that and you're not the person that is writing the code where nobody knows what you actually do or can even appreciate what you're actually doing, right?

Speaker 4 [33:59]

I I am I have made the the observation that that several people in engineering they struggle with naming specifically what communication skills they they have and What skills are out there and this is why I'll when I read people's CVs What I what I like a lot is when they put like their their personal interests there so If somebody is let's say they are Coaching a sports team or participating in a sports team that is communication if they engage in some sort of non-profit That's a different kind of communication. And if they I don't know if they if they run a bar for some time that's That's definitely useful communication skill as well

Speaker 2 [34:54]

So before we come to our fishbowl approach, I would like to put one question to both of you. We didn't talk about the change of learning, so the manner of learning. What do you think, how does AI reshape the manner of learning we had from the past? Is it just like several formats of learning? Is it learning on the job? What are your experiences?

Speaker 4 [35:32]

So, I mean, I'm doing lots of teaching and training. I would say in a positive sense, it makes more time for me to answer the interesting and difficult questions and less questions of the type, hey, where the answer is, hey, you forgot a closing bracket here. That is something that I like because that makes people get things done faster. On the other hand, I've also had to have people fail university courses because the reports that they sent in were completely AI-generated and referenced articles that didn't exist. So I assume that's part of a learning curve. But in general, yeah, it's a useful tool. You can look up things, you can get explanations, but it does not replace a teacher because the job of a teacher, trainer, coach is to show a path and gain interest, make interest and inspire and maybe highlight a few stepping stones and AI is quite bad at all of that.

Speaker 3 [36:52]

I think that the development community also have a very good habit of helping each other and learning each other. I was coding in the 90s and early 2000s, so we had Usenet and then there were the forums and then YouTube started sometime and then you just, if you wanted to know something, you could look that up or you could ask in a forum and people would help you. And this is a kind of a habit that we don't see in many other functions within a company. You don't have that in marketing, you don't have that in finance or to a less way lesser degree right in general um learning is is blending with work so that's the general trend at the moment so to say how can we have like also maybe an agent that sees what i'm doing on my laptop if you want to do that and comes up with training ideas and comes up with short videos or whatever to to help me do the work better so it's basically microsoft clippy on steroids and we don't want that but that's the general idea at the moment so don't send people to expensive trainings unless it is really helpful and purposeful. Yeah.

Speaker 2 [37:59]

And I think we also have to regard that the competitive advantage at the end shouldn't be the tool, it should be the talent. So therefore I think the learning, the manner of the learning is integrated in what we do every day. So where we look, where are our sources, what is our community? I think this is the foundation of the knowledge in the future. So this is just my opinion.

Speaker 3 [38:29]

My opinion. And I think it's also a question about USP. So when I look in my profession in consulting, when every consultancy is using the same three or two AIs, what's the USP? Yeah, exactly. What can I add there? I can draw on the past, on the projects, whatever, but is that enough? Yeah. That's something we need to ask a thing for a lot of domains.

Speaker 2 [38:54]

Exactly. So I would like to open up the fishbowl session for somebody from the audience. So who has a question or a topic which he would like or she would like to share with us? So we are really happy to have you here on the stage.

Speaker 1 [39:14]

so hello yes microphone yes so yeah we have a few questions from the audience i'm going to read them and of course you can still upload and ask questions we are talk python talks talks python sorry i'm confusing it for the podcast so straightforward what are the 10 key skills currently on the list Thanks for watching.

Speaker 4 [39:40]

I maybe can come up with seven. So it's Bash, Git, Docker, SQL, RegEx, algorithms, data modeling. Ah, that's seven. Ask me for the other three in the break. I may need to look them up. Thank you.

Speaker 3 [39:57]

So I followed the first rule of consulting let the client do the work and so I asked on LinkedIn My peers and that's the first time I get any value out of that platform. So Some things they come up. They're fun. Very interesting So it is that analytic thinking it is also resilience to be to be able to constantly shift and pivot and also accept that your profession is changing agility creative thinking curiosity Comes to mind and also the ability to build your own path to steer your your your own career And what I what I added from my I would like to add from my side is this, you know Going into this system thinking that system designers architectural Areas understanding the domain bringing it together with the technical expertise to create value for the company

Speaker 1 [40:46]

This one is, I love this question.

Speaker 3 [40:52]

Paula here.

Speaker 1 [40:54]

Thanks for the well-wishers, Alex, watching the stream. So actually, Paula, who was...

Speaker 2 [40:59]

Okay.

Speaker 1 [40:59]

Oh, okay. Part of the team before she got there. So Paula's question, question for all. What is the most valuable skill that the complete workforce should acquire now if they don't have it?

Speaker 3 [41:22]

Let me look up my list. Maybe it's on there. Someone coined in likability and that it was more like a dystopian view. Some influencer said, okay, if you have very, very little people in the company, then people will look for likability. So who is likable? Because that's the person I would employ. Maybe something that what I'm looking for in recruiting at the moment. I look for people that are professionally lazy. So I want someone who is seeing, okay, I need to format that deck of 100 slides and not sitting there and doing that, but rather think about, do I really need to do that? Is there a way to reduce the slides? Is there a way to use something different? Can I use an AI for that? So basically, the ability to disrupt Your own profession and your own frameworks because sooner or later AI will do that or your competition with AI will do that

Speaker 2 [42:27]

That's interesting, professional laziness.

Speaker 3 [42:31]

Don't let my CEO hear that.

Speaker 4 [42:33]

So my my take for for Paula is personal integrity

Speaker 1 [42:43]

Next question. And I guess well wishes from everyone. I'm just guessing that now. As a student, does it still make sense to spend, invest years of time in doing bachelor, master's and software fields? Does education matter in this time?

Speaker 3 [43:06]

From a recruiting point of view, it's the entry bar. So how does recruiting work at our company? The recruiter checks all the baseline stuff, university degree, and everybody got an A grade anyway, so I don't need to look at that. I look more into the topics that you mentioned, right? What did they do? What kind of internships did they do? Did they engage in other stuff? Can I see this when we have conversations, conversation standards, this hunger to learn and the ability to shift. And I think for a junior, it will be crucial to show results of your work. So show me the app that you have coded and that has real users, even if it's only of you. Show me how you contributed to open source and worked with the code base from someone different, right? Because that's also a skill to learn. Show me how proficient you are with AI tools. That's something where you could prove, Because I think AI is, this is saying, I don't know from whom it is, AI is lowering the floor and heightening the ceiling. So it's easier to get into something, but it's more difficult to reach the top. And currently the baseline, a few years ago, the baseline was the junior level. And now the baseline is like a senior in their early years with experience. So that's some, you know, you need to get close to that doorstep so that you can get into the room.

Speaker 4 [44:31]

Like my take would be that if you finish a university degree and spend spend some years to finish a bachelor or a master Then that's that's a good indicator that you are that you are capable of getting things done. Yeah that even even if on the way, it's sometime sometimes boring and daunting and requires a bit of personal resilience and I'm not that much interested when I see a bachelor I'm a bit less interested in what exactly was the field of study because most of us are moving a bit away into some direction from what they originally learned anyway and I think we will move more around.

Speaker 3 [45:16]

Around in the future. Yeah, so so so certainly recruiting we also look for can you transfer what you have learned enough? Have done to to other to other parts and then to other topics because and not everybody can do that Even if they have studied and even have to have a doctor's degree

Speaker 2 [45:32]

Yeah, and maybe can add also stay flexible and adaptable, so not just stick too much to what you've done and what you've studied, so try to transfer your knowledge in practice as soon as possible.

Speaker 1 [45:49]

If candidates in HR both use AI, when will recruiting catch up to this reality and not ask for human-readable application materials?

Speaker 3 [46:04]

So a client of mine, and she said that publicly, so I can tell that story. She told that their recruiters got a phone call from someone who said, look, you just interviewed my roommate, and your recruiter had not realized that they were interviewing an avatar, an AI avatar, and we heard it from other clients as well. So HR is also deploying tools to analyze that. and try to exclude that it is AI. I still believe that there is value in meeting people personally and getting into an exchange and have, let's say, a broad set of methodologies how to assess someone. Recently, just three weeks ago, I had someone who showed me a presentation. They should do a presentation so that we can see how they are on stage, basically. And they showed me a presentation about a VCG study about AI from 2023 and I was like, okay Do you want to show me stone tablet on stone slabs or papyrus? It's all tech anyway, and he did it beautifully but he haven't understand that because the presentation was straight out of cloth and I Recognized that I told him is and he said yes, and that's okay But he was not able to explain more deeply what was on the slides He could read it and he had some shallow understanding, but he could not apply it. He had no No, no cases when you ask what does that mean in that case? What would you recommend just simple questions? And I think we need to adapt the HR Recruiting policies in a way that we can assess people from different perspectives

Speaker 4 [47:42]

I I don't have an answer on that because I I like to do personal interviews Obviously that approach doesn't scale very well So I usually when I when I get to sit on an interview then the list of candidates has been already filtered Yeah, so and

Speaker 1 [48:00]

Florian asks, given the AI transformation originates in the technical field, most of us are likely the early ones to be able to leverage it. What's the most efficient way to transfer this knowledge into non-technical businesses?

Speaker 3 [48:24]

I think one way is that it is already transferred by the use of standard software. So if you take marketing, if you take photography, music industry, that's all rather non-technical people, but they have AI in their Photoshop and in their whatever software they are using, and they even can't avoid it. Certain things that you have done by hand, you can now do in Photoshop with one click. So that's one way how that's trickling into the workforce. The other thing is that you need to educate people and that you need to... We also found out abstract examples or examples from a different domain, like, look, I can code a website in three minutes. That doesn't relate to them. They see it and they admire it and say, oh, that's interesting. But you need to be very close to their specific domain. You need to show use cases in finance, use cases in facility management, whatever the case is, and let them or work with them together to build that use cases. And then they will gain an understanding of what is possible and use it.

Speaker 4 [49:28]

My recommendation would be start with something that you're doing anyway, like one concrete example is when I create training materials, when I started as a freelancer, I spent some time doing hand-drawn images. That's a huge time sink. Now I can illustrate tutorials with AI images to make them look better. it's not mission critical if the image is not 100% correct I can live with that it's just flavor and the outcome is nice makes me more productive why not and find the one that works for you

Speaker 1 [50:12]

As a developer, I face more and more the growing expectations from clients that I should be able to produce more code, finish more tickets, etc., since now I have coding systems like GitHub Copilot, etc. Ignoring the ever-growing overhead for developers while hoping to sack the productivity gains doesn't sit right with me. What's your take on this? And what's your advice for devs in the C-suite? So C programming, yeah.

Speaker 4 [50:45]

this this is not a new phenomenon we've had that for uh for at least 50 years in engineering not with ai but some new tool comes managers expect us to be more productive and but we figure out no we can't yeah look look a bit what other people have written on the subject there's good books.

Speaker 3 [51:08]

And I think there is also a limit to productivity in that regard, especially for the expert or for the senior level, because what the seniors, and I can only say for my domain, but the output that I now need to check is much more rich and complicated and difficult because AI enriched it in a good way, which is beneficial for the client. but it's a lot more pressure for me to check that because I need to check more stuff and need to really make the connection back to the company strategy to make sure that AI hasn't hallucinated and things like that. So there's a limit to that. You can't do that eight hours a day. And you also need to do some dumb stuff like moving boxes around on a PowerPoint.

Speaker 1 [52:00]

We have many more questions, but I think it's time to wrap up with the last question. I'm just reading it. We are all adults here and talked a lot about education for adults in professional contexts. But being the parent of a two-year-old, what's your outlook on the future of our schools? The youth lives in an AI-filled world. Do we need to protect them? what will they learn or should learn it feels like the advent of the calculator in the math classes 10 times right now

Speaker 4 [52:40]

So my take, as a parent and as an educator, the math calculator hasn't made math go away. We still need to learn it, and we should. Yes, kids need to be protected from this avalanche of stuff. We are still in the process of figuring out how to do that best. And my personal take is, yeah, I think it's useful for kids to learn something about binary code.

Speaker 3 [53:16]

That's personal.

Speaker 4 [53:17]

personal opinion.

Speaker 2 [53:19]

Thank you.

Speaker 1 [53:21]

we had similar discussion yesterday and was basic experience and intuition was just like

Speaker 3 [53:28]

So my oldest son is 18. My youngest is 15 So they are really it's a really pressing question for them and the oldest one doesn't know what he wants to do So he's going into the world. She's going to Australia and say, okay do it and I think that's that's I mean We need to figure it out also how to talk society will develop and what what type of things to learn Coming back to my book because Anna the former colleague of my dear colleague Wrote me some of the skills She said live an active life build your own path learn how to create community and sense of belonging put life at the center and I like that doesn't make you money, but Maybe that's not the ultimate goal in life

Speaker 1 [54:07]

Thank you so much, Sebastian, Christian, Silvia, for this panel and all the work that preceded creating this panel and the output. Thank you for joining. Please give a warm applause to our panelists. Thank you.