I’ve picked up this book to continue my reading into our ability to reason and understand the reality around us. I’ve described this journey in my previous posts, e.g. https://metrics.blogg.gu.se/?p=438
This book goes beyond the trust and explores how we can be wrong and how, sometimes, we should actually be wrong. It describes different models of being wrong and also whether it is good to be right or not.
What I find interesting is the systematic overview of the sources of errors and how we deal with it.
I recommend to take a look at the book as a bedtime reading to learn about our view on being wrong. It describes interesting situations and analyzes them from different perspectives.
As part of my weekend reading I took on a book about cultures. Not a typical reading of mine, but I though I would give it a try. This book is about differences in cultures from the perspective of rules, laws, principles. It is a common knowledge that some societies are very relaxed (e.g. Scandinavia) whereas some are very strict (e.g. Singapore). Commonly, we also know that the loose societies are more creative, whereas the more disciplined ones are very, well, disciplined.
This book also makes a point that it’s not as simple as that. This is not a linear relationship and there is some golden middle. Just being a loose society does not guarantee innovativeness and just being strict does not guarantee discipline. People need a “lagom” (here is a good Swedish word, meaning just right, in the middle, just enough, not too much and not too little) set of rules and looseness in the society.
When I read the book I thought about well-functioning organisations. In the companies and teams that I visit (or used to, before the pandemic), I often saw teams that were working together well with some degree of looseness, but not completely without the rules. They tend to perform well and function well when all team members understand the goals and rules of the game. I’ve also seen teams that are not able to function at all. They do not respect each other, have no respect for rules and provide no support for each other. They are “too loose” and therefore they are groups, but not really teams. At the same time I saw teams where the narcissistic boss controls everything and everything needs to go through the boss. They do not produce much, trust me.
However, there is also one more aspect – it’s where you come from. I, for that matter, cannot work in a self-organising team. I just don’t know how to find my place. One of my friends told me once – “Either you lead, or you follow or you get the hell out of the way”. Well, I’m more for that kind of the rule. Following is nice and I like it, but self-organising is so-so.
I’m actually part of a self-organised team in one of my assignments. I don’t know what to do there, I rely on a friend from the team to tell me when is my turn to speak and if I should say something or not. He also tells me when it’s a good time to do things and when it’s just a discussion. I’m not providing the name of the friend, but I’m super happy that I have him!
To sum up, I really recommend to read this book as it provides a bit wider perspective on rules in societies than the most common books from the organisational theories. It is about a normal person like me trying to find a place in life (well, by now I would actually think that this is easier, but maybe I’m just wiser to realise certain things).
Thanks for listening and tun in for the next blog post.
A while back I read an article in ZDNet about Linus Torvalds, the creator of Linux, and his daily work. He was (at the time of reading, which is ca. 2 years back) still working on the code. However, he was mostly working on the design of the system, reviewing patches and supporting younger designers. I’ve also read a number of articles which claimed the importance of code reviews as a way of teaching younger designers about the product and the code base.
In this paper, I’ve found that the support for younger designers is what the elite developers do a lot of. It seems that the communication, organisation and support are the activities that the elite developers find important. It’s aligned with what we do at the universities as well. The most elite professors work with students, show them how to program and how to structure their code. Seems like this is a very good way of continuing your career – help other be better.
I guess it’s time to change my wallpaper from “coding” to “teaching”….
Abstract: Open source developers, particularly the elite developers who own the administrative privileges for a project, maintain a diverse portfolio of contributing activities. They not only commit source code but also exert significant efforts on other communicative, organizational, and supportive activities. However, almost all prior research focuses on specific activities and fails to analyze elite developers’ activities in a comprehensive way. To bridge this gap, we conduct an empirical study with fine-grained event data from 20 large open source projects hosted on GITHUB. We investigate elite developers’ contributing activities and their impacts on project outcomes. Our analyses reveal three key findings: (1) elite developers participate in a variety of activities, of which technical contributions (e.g., coding) only account for a small proportion; (2) as the project grows, elite developers tend to put more effort into supportive and communicative activities and less effort into coding; and (3) elite developers’ efforts in nontechnical activities are negatively correlated with the project’s outcomes in terms of productivity and quality in general, except for a positive correlation with the bug fix rate (a quality indicator). These results provide an integrated view of elite developers’ activities and can inform an individual’s decision making about effort allocation, which could lead to improved project outcomes. The results also provide implications for supporting these elite developers.
I picked up this book to get some new perspective on research, work-life balance and, eventually, happiness. Not that I’m miserable, but I got intrigued by the recent developments in psychology and I wanted to take this as a bedtime reading. Midsummer reading, to be exact.
Well, the book is a great literature for that, no doubt about it. I like the style of the author and how he takes on examples. I also found that the book has two chapters about metrics and measurement. In chapter 2 and 3, the authors discusses our view on the science behind happiness and the fact that it’s very difficult (not impossible) to measure. There are ways to measure happiness, or estimate it.
What I like about the author’s approach is that he uses these measures to show temporal aspects of happiness – our estimations about how happy we will be, our happiness at the moment and finally our happiness after a while.
To sum up, the main point of the book is that happiness is what we create, not what we get.Just by changing the way we see things or how we compare things, can make us more happy.
Recently I’ve read a very interesting book about the disruption that happens in the banking sector. I’ve learnt that this is not the first book about the topic and I wanted to understand how things are actually working with AI and the banking sector.
We’ve published a paper a while back about the introduction to AI for bankers, but I wanted to know more about what has happened since then. The link to the paper is here: https://doi.org/10.2308/jeta-19-04-30-21
So, what’s new about this particular book? Or what’s new about the disruption?
The book talks a lot about the financial sector and how it evolved over the years. Bank 4.0 is a bank which is powered by AI and is able to reason about your economy at a higher abstraction level. Instead of asking “Siri, how much money do I have on my account?”, we can start asking questions like “Siri, can I affort buying the new Playstation 5?” and the assistant will answer that you can, but then you need to cut down on your vacation expenses and maybe replan the purchase of the new mobile phone (which is getting old).
A small disclaimer here: I use Siri as example, this has nothing to do with Apple services (at least nothing that I’m aware of).
Another interesting aspect of banking 4.0 is the fact that financial actors are more trustworthy than the banks. The young generation would rather interact with the actors like WeChat (https://metrics.blogg.gu.se/?p=407) than interact with the bank.
However, what I like best about the book is the fact that it problematizes the concepts related to disruption – for example how do you know that you are being disrupted? or when should a company start pivoting, or even whether pivoting or abandonment of the old model is possible in the company that is being disrupted.
Data veracity is a concept where we define the degree to which data corresponds to the true values. It comes from the metrological concept of “measurement trueness”, which is the degree to which the measurement quantifies the value correctly.
Well, that sounds very simple, but it is in fact quite complex. In our previous work, we scrutinized what it means to have veracious data in transport systems (https://ieeexplore.ieee.org/abstract/document/7535482). It turns out that “lying” is not the only option here.
In this book, the author looks into the way how things can be untrue. Sometimes deliberately by lying, sometimes by mistake. Sometimes, as we learn in the last chapter (with Brazilian aardvark), a mistake can actually end up being accepted as truth over time.
I recommend the book as it is written in a fantastic manner, providing examples from the real world (e.g. the alleged drone sightings over Gatwick in 2018). It even goes a bit further and discusses the need of replication of studies and that we should get more funding for making the scientific results more solid and robust.
Software Engineering is one of the newest engineering fields with a growing need from the society side. The field develops rapidly which poses challenges in developing sustainable software engineering education – allowing the alumni to be effective in their work over a long period of time (long-term impact of the education) and keeping the education attractive for the potential students and industry.
The objective of this presentation is to describe the experiences from using business intelligence methods to develop, profile and monitor software engineering education on the master level. In particular we address the following research questions:
Which data sources should be used in developing a profile of a master program?
How to combine, prioritize and communicate the analyses of the data from the different sources?
How to identify barriers and enables of attractive sustainable software engineering education?
The results are a set of experiences from using data from the national agencies in Sweden (e.g. the Swedish Council for Higher Education – UHR, the Swedish job agency – Arbetsförmedlingen, international master education portals – mastersportal.eu) as input in development and evaluation of a master program in Software Engineering at University of Gothenburg.
The conclusions show that using the available sources lead to creating sustainable programs and we recommend using the data sources to a larger extent in the national and international level.
The paper is an experimental validation of whether requirement diagrams speed up the understanding of requirement specifications or whether they increase/decrease comprehension. The results show that the comprehension is increased while there is no change in time.