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Alexander and Team on What Leadership Means in Data Science · The Effective Data Scientist

• 0:07
  Speaker 1:
• 0:17
  Speaker 2: Welcome to the Effective Data Scientist Podcast!
• 0:20
  Speaker 2: This podcast is designed to help improve your skills, save focus manage successful projects and have fun at work.
• 0:28
  Speaker 2: Be part of our community.
• 0:30
  Speaker 2: –
• 0:30
  Speaker 1: this
• 0:31
  Speaker 2: is an independent podcast.
• 0:33
  Speaker 2: Hey,
• 0:43
  Speaker 0: hello everyone.
• 0:44
  Speaker 0: Welcome back to the Effective Data Scientist podcast.
• 0:48
  Speaker 0: I'm Aziza and today i am here with Alexander and Paolo And Today we are tackling The human element of the tech world.
• 0:57
  Speaker 0: We often talk about algorithms About statistics About technical topics But rarely about people who steer this ship.
• 1:06
  Speaker 0: What does leadership mean?
• 1:08
  Speaker 0: what we learn from leadership and how should leadership function so that would become effective statisticians, effective data scientists and human beings maybe.
• 1:19
  Speaker 0: That's our topic today And I welcome Alexander and Paolo.
• 1:24
  Speaker 0: Happy to have this conversation with you.
• 1:27
  Speaker 2: Hi Aziza It really a pleasure to have this conversation with you both today and it's really a privilege to have Alexander on this episode, to discuss his very relevant topic.
• 1:39
  Speaker 2: I ask Alexander.
• 1:41
  Speaker 1: thanks so much for inviting me to use this episode.
• 1:44
  Speaker 1: i'm very honored and i am very excited to talk about this topic because this has been very close to my heart or quite a long time.
• 1:53
  Speaker 1: And on the other podcast, The Effective Statistician there are already lots of episodes about this.
• 1:59
  Speaker 1: But let's talk what it means for data scientists!
• 2:03
  Speaker 2: I met online Alexander when i started listening to the podcast, The Effective Satisfaction and then i started to hear more about leadership principles in our day-to-day work.
• 2:16
  Speaker 2: And it was really interesting for me coming from an academic background at that time... ...I was working on public sector and academia And at that time these topics regarding soft skills, how to be effective and influence your organizations.
• 2:35
  Speaker 2: Projects were quite unusual.
• 2:37
  Speaker 2: I was mostly focused on the development of technical skills... ...and learned much later about improving my day-to-day work with this leadership principle.
• 2:51
  Speaker 2: Then i enrolled into a leadership program run by Alexander in the first wave, and it was really interesting.
• 3:00
  Speaker 2: And the program was so exciting at that time.
• 3:04
  Speaker 2: a few years ago I learned about leadership principles.
• 3:09
  Speaker 2: The thing is every statistician, every data scientist should learn a bit about these principles how to benefit from them for their work in organizations.
• 3:21
  Speaker 2: What do you think Alexander?
• 3:24
  Speaker 1: For me I stepped over this topic also rather early in my career.
• 3:30
  Speaker 1: First, I thought kind of leadership is just something for supervisors from managers who have direct reports and that was my understanding.
• 3:40
  Speaker 1: but then i was told so that everybody can lead said everybody can delegate said Everybody can drive things forward especially our community.
• 3:51
  Speaker 1: we work very often in cross-functional teams, we have people from all kinds of different parts of the business that are not directly associated with data science necessarily.
• 4:04
  Speaker 1: And here maybe you know it's only one where there is a data science background or may be one or few with this background and we often struggle then to let say work effectively.
• 4:20
  Speaker 1: And I think there's a couple of reasons for this.
• 4:22
  Speaker 1: The first is the misunderstanding that leadership is just for supervisors, it's everybody.
• 4:32
  Speaker 1: Leadership in the sense means you create followers so others follow your advice.
• 4:40
  Speaker 1: and here's the first topic we need to be part.
• 4:50
  Speaker 1: So we are not consultants that come from outside and then say, okay you should do XYZ.
• 4:59
  Speaker 1: But if you don't do I don't care yeah?
• 5:04
  Speaker 1: This is an owner's mindset instead of a renter's mindset.
• 5:09
  Speaker 1: so the owner mindset means that You're part of team your part of project.
• 5:15
  Speaker 1: The success in this project A renter is like, that's not your project.
• 5:23
  Speaker 1: You're just assigned to it and whether this project fails or not you don't care.
• 5:29
  Speaker 1: they can take your advice but Don't Take Your Advice...you DON'T CARE!
• 5:33
  Speaker 1: That is a huge difference.
• 5:35
  Speaker 1: And now if you go into the owner mindset then its really about the overall project making sure It Is Successful One of The First Things Of Course To Understand What does success actually mean?
• 5:52
  Speaker 1: I think a lot of people don't understand that, or at least within the team have very different understanding.
• 6:02
  Speaker 1: And so as leader you need to first understand where do we want get it from and what does success look like across the team.
• 6:14
  Speaker 1: Does meeting certain quality targets mean being on time?
• 6:19
  Speaker 1: Does it mean being on budget?
• 6:21
  Speaker 1: What does that mean?
• 6:23
  Speaker 1: and if you talk to different parts of the team, You may get very very different understandings.
• 6:29
  Speaker 1: And so first leadership is a very much mindset topic.
• 6:35
  Speaker 1: If you want be come successful in few wanna be impactful make your own.
• 6:43
  Speaker 1: Actually many us are potentially outside work already leaders.
• 6:49
  Speaker 1: Maybe you are involved in a sports club and you train your team, maybe kids' teams or whatever.
• 6:58
  Speaker 1: You're a leader!
• 6:59
  Speaker 1: Maybe you're involved with some kind of church activities and organize something there...you're the leader.
• 7:07
  Speaker 1: Or maybe you organized something within your bigger family..you're our leader.
• 7:12
  Speaker 1: Again & again & again.
• 7:14
  Speaker 1: these So-called soft skills, although I don't like this term with more say human skills help so much.
• 7:22
  Speaker 1: Now it's important to understand these skills and that is the last thing that i want to talk about.
• 7:29
  Speaker 1: Would you be a good data scientist if you haven't invested in technical skills?
• 7:36
  Speaker 1: Probably not.
• 7:37
  Speaker 1: Nobody becomes a data scientist without developing coding skills and statistics skills, and understanding the business.
• 7:44
  Speaker 1: Why do people think that they can become great leaders without investing in these leadership skills?
• 7:51
  Speaker 1: I think this is one of the most commonly misconceptions.
• 7:56
  Speaker 1: it includes management.
• 7:57
  Speaker 1: The vast majority of managers have never ever gotten any kind of formal training.
• 8:03
  Speaker 1: Just because you have a title of whatsoever doesn't mean your leader.
• 8:08
  Speaker 1: So this is my kind of little bit starting point here?
• 8:12
  Speaker 2: Yeah, I think it's very important to recognize that leadership skills are not important for the top management.
• 8:20
  Speaker 2: They're also important for people working in the team or project.
• 8:26
  Speaker 2: You can start your career and then invest in leadership skills.
• 8:32
  Speaker 2: There are so many opportunities to influence the project, to influence your team.
• 8:38
  Speaker 2: I really like the sentence make it your own.
• 8:42
  Speaker 2: I mean i think ownership is probably one of the core principles that I like most.
• 8:49
  Speaker 2: you have to care about uh your project.
• 8:52
  Speaker 2: You have to cared about your team.
• 8:53
  Speaker 2: no matter the position Your feeling in the theme there is always something important.
• 9:02
  Speaker 2: It doesn't need to be something extraordinary or exceptional.
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  Speaker 2: To also a simple advisor, keeping track of the lessons you learned during your project and it can be important for follow-up or other projects.
• 9:18
  Speaker 2: so there are many opportunities that inner team members can pick up as an example.
• 9:25
  Speaker 2: low-winging through its right.
• 9:26
  Speaker 2: I think you explained very well why it's important to invest in these skills, what can you do for example as people or with the management of top management to start progressing on this human skill?
• 9:43
  Speaker 1: I think there are a couple different things that you could do.
• 9:46
  Speaker 1: First i would check whats available within your organization.
• 9:49
  Speaker 1: Are there any resources you can tap into inside your organization?
• 9:54
  Speaker 1: A lot of bigger organizations already have some kind of courses, materials that you can have access to.
• 10:04
  Speaker 1: Have a chat with your supervisor whether he knows about things.
• 10:08
  Speaker 1: HR is usually also good area here for getting help and support knowing what's available.
• 10:14
  Speaker 1: Second is get a mentor.
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  Speaker 1: Find someone who think it very good in terms of human skills.
• 10:24
  Speaker 1: Ask him whether you can have from time to time discussion.
• 10:28
  Speaker 1: supporters set up a first meeting and say, I would like to learn about leadership.
• 10:34
  Speaker 1: Does that mean what do you do with these kind of different topics?
• 10:38
  Speaker 1: And then you can talk about different case studies and learn that.
• 10:45
  Speaker 1: Another thing is external resources.
• 10:49
  Speaker 1: there are podcasts books you can read, like I've also written a book How to be an Effective Statistical and that's for Data Scientist, Statistical & Other Quantitative Scientists.
• 11:05
  Speaker 1: And it is not written in the abstract way.
• 11:08
  Speaker 1: It´s written more like a novel with lots of different experiences That play as the main protagonist Of the book goes through and then needs to manage.
• 11:22
  Speaker 1: Unfortunately Kler has a very, very good mentor and he helps her to get through all these different struggles.
• 11:30
  Speaker 1: And every chapter ends with some key takeaways but also some actions that you can do.
• 11:38
  Speaker 1: You can find the book if you search for my name Alexander Schacht on Amazon.
• 11:45
  Speaker 1: It's just a few bucks so it is really cheap.
• 11:49
  Speaker 1: And I'll also start this year with Q&A sessions around the book, which will be for free.
• 12:00
  Speaker 1: So if you follow this podcast, you'll probably learn more about it and can also follow on LinkedIn at this bell icon in my LinkedIn profile of your click-sets to make sure that you don't miss anything.
• 12:16
  Speaker 1: algorithm is pretty selective with what I post.
• 12:18
  Speaker 1: And the last thing, if you want to invest more and are really serious about it contact me on LinkedIn.
• 12:26
  Speaker 1: You can probably enroll into my leadership program.
• 12:31
  Speaker 0: Thank you Alexander!
• 12:32
  Speaker 0: You mentioned a lot of sources for becoming good leader... ...and i think made use almost every source that you mentioned And I really feel privileged to have access to these sources.
• 12:45
  Speaker 0: Do you also mention the mentorship?
• 12:47
  Speaker 0: I think mentorship is a great way to connect with leaders who inspire and want to learn from them, it's very good!
• 12:56
  Speaker 0: Thank-you for being my mentor as well... ...I count on you as one of my mentors and learned a lot about your podcast effective statistician.
• 13:06
  Speaker 0: Also in this book that was written by me As I mentioned, I also wrote a review for this book mentioning that there are lots of technical resources.
• 13:17
  Speaker 0: My bookshelf is full of statistics and mathematics in all the data science books.
• 13:23
  Speaker 0: but how to use that knowledge effective and make an impact?
• 13:28
  Speaker 0: That was something missing on my shelf!
• 13:30
  Speaker 0: And i'm super happy to have this book to help me fill these gaps.
• 13:35
  Speaker 0: How do I use this technical knowledge, really bring these knowledge into action and make an impact?
• 13:42
  Speaker 0: This was a very good source.
• 13:44
  Speaker 0: And i highly recommend it because this is based on real scenarios that we face in our daily life... ...and how to deal with certain situations where we face challenges.
• 13:58
  Speaker 0: appreciated thank you so much for writing the book.
• 14:03
  Speaker 0: Actually,
• 14:03
  Speaker 1: in this book the examples are more real than you would think.
• 14:09
  Speaker 0: So that makes even more sense to go through these examples and really learn from those?
• 14:14
  Speaker 0: And also I mentioned it's not being kind of a stranger in team matters like.
• 14:21
  Speaker 0: we all face this phase.
• 14:25
  Speaker 0: when start our career We come from university with statistics or data science background.
• 14:30
  Speaker 0: We are ready, we're good in learning and understanding the material – the technical part of statistics.
• 14:38
  Speaker 0: but really when you join companies it's very challenging to find ourselves.
• 14:45
  Speaker 0: I can speak about my story that i was feeling while joining industry as a statistician, I didn't know what to do.
• 14:53
  Speaker 0: And i think here the role of leaders is very important and you need some kind of supervisors that really guide you through... ...and show this world.
• 15:03
  Speaker 0: how do you apply that theoretical knowledge in industry.. ..to solve real problems?
• 15:09
  Speaker 0: First ,I think the roles of the supervisor are very important so they don't get lost or orientation support.
• 15:18
  Speaker 0: And then one side is technical skills that you have.
• 15:21
  Speaker 0: Another side, it's that you had a supervisor.
• 15:24
  Speaker 0: and then collaboration the communication skills come into role because we find ourselves in an interface of data science people... ...and right questions as much proposing to write methods overcome challenges solve problems industrial problem with our skills.
• 15:44
  Speaker 0: And I find in most of the cases, what happens if you just focus on our technical skills and try to... without understanding the process.
• 15:52
  Speaker 0: Without really finding ourselves in which world we are.
• 15:56
  Speaker 0: it's very difficult!
• 15:58
  Speaker 0: What i learned for myself is that understanding this process helps become a part of your team working with.
• 16:07
  Speaker 0: At the beginning, you find yourself as a stranger who doesn't know about the processes.
• 16:11
  Speaker 0: It's really difficult to find questions that we want to ask or understand problems but once you learn all of these processes and how it works in this world then you can propose better solutions because you already know where they are.
• 16:27
  Speaker 0: Do You think This is important?
• 16:29
  Speaker 1: Absolutely!
• 16:30
  Speaker 1: I was just thinking what you were talking about The first really really important leadership tool And that's listening.
• 16:38
  Speaker 1: So when I think about how are you started in the industry, it was just listening for where can i apply my tools and my techniques?
• 16:48
  Speaker 1: It wasn't listening to what actually is a problem.
• 16:54
  Speaker 1: What actually is the problems within business?
• 16:59
  Speaker 1: The most important leadership skill is listening, because that will give you insights into where the others are coming from.
• 17:14
  Speaker 1: What's a business wants or what the competition has doing?
• 17:18
  Speaker 1: All these kind of different things and through that You will get knowledge lots of leadership classes focus on for example presentation skills speeches and writing, all these kind of things.
• 17:33
  Speaker 1: And yes!
• 17:33
  Speaker 1: These are all important but more important is listening.
• 17:38
  Speaker 1: the better you're listening irrespective which level your are actually it becomes more important if you climb a ladder.
• 17:46
  Speaker 1: The Better You Will Make Decisions the better will be able to make connections building trust with the other team members, so that you trust them and even more important they trust you.
• 18:06
  Speaker 1: Because let's face it all these non-technical people don't have a clue what an ML algorithm is or what this biased or unbiased estimator of what its feature selection are those kind of different things.
• 18:23
  Speaker 1: And to be honest For them, what we do is a little bit like black magic or maybe white magic.
• 18:32
  Speaker 1: It's the right thing!
• 18:34
  Speaker 1: But why should they trust you?
• 18:37
  Speaker 1: And here if you listen to them he shows that you care.
• 18:41
  Speaker 1: and If you follow up and Do whatever you say and you say what you do He showed us that you have character.
• 18:49
  Speaker 1: when You can then solve their problems.
• 18:52
  Speaker 1: who show that you Have competence?
• 18:55
  Speaker 1: And these are the three important things.
• 18:57
  Speaker 1: Care, character and competence... ...and by the way first two are much more important in terms of trust than last one.
• 19:06
  Speaker 0: So the first was care, character & competence.
• 19:10
  Speaker 0: so you mean the first two ones?
• 19:12
  Speaker 0: Care & Character
• 19:14
  Speaker 1: are more important then competence.
• 19:16
  Speaker 1: In the end of course we need all three of them.
• 19:18
  Speaker 1: If you lack one of them it's this whole trust product equals to zero.
• 19:26
  Speaker 0: And what do you mean by character in this regard?
• 19:29
  Speaker 1: The character is very much about your values.
• 19:34
  Speaker 1: and how's your value also align with the values of others, whether you act in accordance to your values.
• 19:46
  Speaker 1: So for example ZG picks a truth integrity.
• 19:52
  Speaker 0: You're authentic
• 19:54
  Speaker 1: likes to work authentic so much, because people very often misunderstand that.
• 19:59
  Speaker 1: It's important said for example if you mess something up yeah your proactive about this.
• 20:07
  Speaker 1: Yeah?
• 20:07
  Speaker 1: That character!
• 20:10
  Speaker 1: If he say things like unrealistic that we will hit his one month deadline You speak about it early although maybe it's not nice to speak about that or uncomfortable.
• 20:27
  Speaker 1: In a sense you need to be courageous, so this has lot to do with character.
• 20:35
  Speaker 2: I think it is important to emphasize that caring characters can really support if they are competent person in the data science space The best satisfaction or the best scientist in terms of knowledge, tools and algorithms.
• 20:55
  Speaker 2: But if you lack current character You won't be able to influence the outcome Of your projects right?
• 21:02
  Speaker 2: I think this is a key point.
• 21:05
  Speaker 1: Yeah And that's as he other parts the influencing dimension.
• 21:10
  Speaker 1: Depending on where you're coming from influence may have positive for negative connotation.
• 21:15
  Speaker 1: In the end it's more about persuading people of doing the right thing, and finding a common solution that is workable.
• 21:25
  Speaker 1: And you can move forward with it.
• 21:27
  Speaker 1: in our leadership program we sometimes just talk about this getting your ideas into action.
• 21:34
  Speaker 1: That's another part leadership because at the end You can have some best ideas In terms how to improve This project or do this feature.
• 21:43
  Speaker 1: We could start that initiative.
• 21:46
  Speaker 1: If you don't get people on your side, it doesn't matter.
• 21:51
  Speaker 0: Thank You Alexander!
• 21:52
  Speaker 0: I want to come back to the care because we talked about a character and now i want to bring an example of that care.
• 21:59
  Speaker 0: maybe if this is right way for us think about it.
• 22:03
  Speaker 0: so as statistician data scientist professional We got questions like can you please analyze these data?
• 22:11
  Speaker 0: They give me their data And then they say yes This my job But if I really put the care, i would ask like why do you want me to analyze this data?
• 22:22
  Speaker 0: So Why is it important?
• 22:23
  Speaker 0: which kind of strategic decision Do You Want To Make based on this analysis or The Output.
• 22:31
  Speaker 0: What does It Means in Terms Of Cost?
• 22:34
  Speaker 0: Because This Is Very Important Most of the time for many years off my career, this part that find.
• 22:42
  Speaker 0: This is super important to really develop these care in terms of what does it mean?
• 22:47
  Speaker 0: For the business and really feel responsible for their results That you're delivering And really like when You know about how much impact will this decision or Will this result bring To the organization?
• 23:00
  Speaker 0: because When we get The data and we analyze the data We don't do It just for fun.
• 23:06
  Speaker 0: We are making a big impact.
• 23:08
  Speaker 0: How?
• 23:08
  Speaker 0: Because based on that, the strategic decisions will be made.
• 23:12
  Speaker 0: Decisions would be made based on this analysis and thats why I think when we're doing something... ...we should understand.
• 23:20
  Speaker 0: Why is it important to put our care there?
• 23:24
  Speaker 0: When you understand then we care.
• 23:26
  Speaker 0: And if we don't understand It's really difficult for us to deliver The ways or the methods of strategies we propose.
• 23:35
  Speaker 0: as a statistician, so data scientists may be not their best because We are missing.
• 23:41
  Speaker 0: We don't understand what is hidden behind?
• 23:43
  Speaker 0: What does that business goal objective is hitting behind?
• 23:47
  Speaker 0: So connecting this I think what defines the care in these terms?
• 23:51
  Speaker 0: did they describe it right way?
• 23:54
  Speaker 1: Yeah absolutely you need to take care Of what's he other person really wants to achieve and potentially the organization behind that as a person.
• 24:03
  Speaker 1: How precise do your results need to be?
• 24:07
  Speaker 1: Is it enough to have some kind of rule-of-sump outcome or you need really, really good estimation in which area as well?
• 24:17
  Speaker 1: I once had a student at my leadership program when we talked about this understanding business impact behind what you are doing he thought an excellent spreadsheet that he was providing to a colleague all the time on continuous basis.
• 24:36
  Speaker 1: He didn't know what this colleague was doing with his spreadsheet, so he went down to this colleague and said you do with it?
• 24:44
  Speaker 1: And then he described the workflow that he were doing with its spreadsheet.
• 24:57
  Speaker 1: This spreadsheet is probably the worst tool to make these decisions.
• 25:03
  Speaker 1: So he built a shiny app and told it to his co-worker, And he was really excited because that condensed one day task for half an hour Even better!
• 25:20
  Speaker 1: He wasn't only using this process but lots of other colleagues as well so they saved their overall business lots of time, and also improved the decision-making.
• 25:34
  Speaker 1: Just before this one actually pretty junior data scientist went to a colleague and asked what do you with it?
• 25:45
  Speaker 1: Why did he need that?
• 25:47
  Speaker 1: What was his
• 25:47
  Speaker 1: purpose?".
• 25:48
  Speaker 0: That's very good example!
• 25:52
  Speaker 1: He came back into the leadership program You know, super excited about his story and success.
• 25:59
  Speaker 1: And just this one thing paid for the leadership program... ...for himself and all of other colleagues from that company!
• 26:08
  Speaker 1: It was a decent sized company though actually it's really big ones.
• 26:13
  Speaker 2: I would like to touch on another topic, which is important for me.
• 26:19
  Speaker 2: One book was really interesting when i joined the program called The Five Disfunctions of a team by Lencioni and in that we discussed at length this topic.
• 26:34
  Speaker 2: it's very important because now when you join new teams does apply to this team and I think it's really nice how you can diagnose these problems quite fast in some way.
• 26:51
  Speaker 2: In these principles, i think is very important to mention the lack of open discussions among the members so... ...in a way that is another way of telling about your theme or project.
• 27:07
  Speaker 2: we need to be open a form of proactivity.
• 27:13
  Speaker 2: I mean, we need to learn how to discuss in an open way because if everybody is silent maybe you can think that everything's going fine but this is rarely the case.
• 27:26
  Speaker 2: so i wanted to hear something about it.
• 27:29
  Speaker 2: Alexander?
• 27:30
  Speaker 1: This book is awesome to read!
• 27:31
  Speaker 1: It's novel with all kind different learnings and actually inspired me to write my book.
• 27:38
  Speaker 1: We talked already about a couple of these dysfunctions teams very often have.
• 27:42
  Speaker 1: And let's face it, teams are the smallest units where we usually produce anything.
• 27:48
  Speaker 1: Trust is the lowest level.
• 27:50
  Speaker 1: without trust within the team you don't get really any thing done.
• 27:54
  Speaker 1: The ability to conflict with other people because they can talk about problems and conflict I do not mean When people yell at each other, so yeah.
• 28:08
  Speaker 1: A most conflict is let's say done in a nice way that the avoidance of conflict not speaking about clash of priorities and things like that it's a problem holding each others accountable having common goals And then really making sure said its win for your overall team Not just even for individual teams.
• 28:30
  Speaker 1: These are all kind very important topics.
• 28:34
  Speaker 1: The book is really, really good.
• 28:36
  Speaker 1: I highly recommend it and there's so much in it that potentially we can have a couple of other episodes just about this book and about teamwork because team work can be a lot of fun!
• 28:49
  Speaker 1: And had some teams that were absolutely stellar and i loved them.
• 28:53
  Speaker 1: they are so effective but also worked on teams which was completely dysfunctional And it can have an impact on your mental health as well.
• 29:07
  Speaker 0: Thank you for sharing the insights, Pauli!
• 29:09
  Speaker 0: It was very interesting... The experience that you shared and Alexander thank-you for sharing your opinions about that.
• 29:15
  Speaker 0: As we wrap up what would be your message to the listeners?
• 29:20
  Speaker 0: so after this episode they know what to do?
• 29:23
  Speaker 1: I think we had a couple of action items.
• 29:25
  Speaker 1: So first is change your mindset.
• 29:28
  Speaker 1: if are not already kind of a team member, but the Team Consultant become a team Member.
• 29:35
  Speaker 1: Second is invest in your leadership skills.
• 29:39
  Speaker 1: keep going.
• 29:40
  Speaker 1: maybe it's just reading a book and applying it.
• 29:43
  Speaker 1: And if you want to go really fast contact me and I can get here enrolled into the Leadership Program or maybe run the Leadership program within your organizations.
• 29:55
  Speaker 1: that's easiest part.
• 29:56
  Speaker 1: then Organization Peaceful, it's the best part.
• 30:00
  Speaker 0: Paolo?
• 30:01
  Speaker 2: It was a great discussion and I encourage everybody to read The Book of Alexander and follow him for his initiatives on that topic too.
• 30:11
  Speaker 0: Great insights, Alexander.
• 30:12
  Speaker 0: Thank you for this discussion and Paolo thankyouforengagingdiscussion.
• 30:17
  Speaker 0: Hopefully our listeners will have takeaways from this episode And maybe to our listener as a reminder that the most complex system You'll ever work with it is not an neural network.
• 30:30
  Speaker 0: It's no any other technical skill.
• 30:33
  Speaker 0: Its'the person sitting at the desk nexttouand asking a question
• 30:38
  Speaker 2: Much more complicated
• 30:40
  Speaker 0: than we think.
• 30:42
  Speaker 0: Thank you to our listeners for joining us and listening, see ya next
• 30:48
  Speaker 2: time!