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Book Review: The Checklist Manifesto

TL;DR: A useful read for the inquirer. Just as good as the summary for the practitioner.

I finally got to read The Checklist Manifesto by Atul Gawande. This is years after I read the CapitolReader summary of the book, which is one of many summaries of this book. I became excited with the idea presented in the book by just reading the summary. The main idea is that the simple mechanism of checklists can be used to improve performance, and safety, in many areas from surgery to construction. Checklists are a useful mechanism to guarantee that known wisdom is put to use when needed, even at times of stress and cognitive overflow. After all, the challenge is often not the know-how we don’t have but the vast amount of know-how we do have but fail to use when needed.

After reading the summary I became an advocate of checklists. I use them wherever I can. I even wrote my own software that generates different instances from master checklists for different uses, some as simple as travel packing and preparations.

The book by Atul Gawande is interesting and well-written. Slightly to my disappointment, however, reading the book does not add much on the pragmatic creation and use of checklists. It mostly covers the experiences and evidence of the uses of checklists in different areas, as well as research into their usefulness. It is an educating read on the study of the merits of checklists, but perhaps less of a guide for checklists practitioners.

Pausing AI development? As if we could...

When we hear of a new way in which artificial intelligence (AI) can risk humanity, or even just move someone’s cheese, the debate often changes to whether or not we should pause AI development until some impact analysis is carried out, or some regulation kicks in.

I do not think that pausing AI development is even a plausible option to be considered. History has shown that technology never stops. We have tried this in areas that are much riskier for humanity, and without much success. We should accept that Humanity is insufficiently consensus-driven, and the stakeholders in AI technologies have too many easy ways to bypass bans, and too many good reasons to do so. Yes, there is serious lobbying promoting this pausing option, but I would argue that most is for pausing productization, rather than development, and is, to a notable extent, led by players who are just late in the market and need some time to catch up.

Getting Things Done (GTD) and what I made of it

I finally got to read the book “Getting Things Done” by David Allen. I have read quite several books on time management and related topics, so I was almost surprised that it took me so long to get to this particular one, which is considered by many as a classic. I got to this book more or less by mistake. A while back I started using a command-line task management tool called TaskWarrior, another old Linux tool that has been known to anyone but myself for decades. This tool referred to the “Getting Things Done” methodology that was taught in the book, so I ended up reading the book as well, out of appreciation for some of the features that were inspired by this book.

I am not going to summarize this book now, nor the GTD methodology. There are dozens of write-ups about it by now. I am also not going to describe that TaskWarrior program, because this would not be the best use of your time or mine. Instead, I will discuss my most important findings: those relatively novel ideas of task management that I adopted from either the book or the software, or even just from my own experience with the two (even if not directly taught by any of these). So it’s not really a book review, but just my own takeaways that were either written in the book or were somehow inspired by the book, or by the software that I am using.

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Decentralized Finance that is too perfect for reality

Blockchains, DeFi, DAO, and Web 3.0 in general, all carry the message of decentralization, and particularly of decentralizing financial systems. Decentralization means, for the most part, eliminating the trusted authorities that are involved in various types of transactions. Those transactions could be agreements (to be facilitated by decentralized smart contracts) and the transfer of funds in general (to be facilitated by Bitcoins and alike). Centralization of financial services is considered evil, because the middlemen often have their own incentives, and even when they don’t, they often charge a lot for their essential role in the system. As we move into the decentralized era, we have smart contracts, which enforce themselves using machine code, without a trusted executor, and Bitcoins, which carry value and can be transferred between people without them having to trust any specific or state-owned service provider. Nice.

This post is neither for nor against decentralization. As I see it, nothing can be said against what is essentially an option. A decentralized system is considered as such because it does not require a centralized authority, not because it does not allow one to exist. If you find that you really miss a middleman, then you can always appoint one. If you want the state bank to manage your Bitcoins, then nothing would prevent that. You get an option, and having options is always good.

This post discusses how suitable the current decentralized financial systems are, considering the world they operate in. My take, as the title may disclose, is that while decentralized systems are an excellent idea and a worthy option, their current implementation suffers from shortcomings that we will just have to fix before they can become mainstream. There are many shortcomings, of course, and who am I to even enumerate them, so I will focus on one: the decentralized systems today assume too much perfection; it’s not that they don’t work well — it is that they don’t fail well.

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Book review: "Decisive"

I recently read the book Decisive by Chip Heath and Dan Heath. This is one of the better growth books I’ve read lately, because it nicely combines scientific truths with actionable guidelines. Most growth books are either purely motivational, repeating shallow inspirational mantras with small tweaks, or they present solid logic that explains how things could be better, just without much hints on how one can put this logic into practical use. This book, on the other hand, explains well-substantiated pitfalls in our decision-making logic and also offers simple mental hacks to help us overcome those pitfalls. I also liked that each chapter concludes with a single-page summary that makes it easy to recap what was taught and the conclusions of each chapter. I find this immensely useful because I’m the type of person who reads very little each day, and not every day, so reading a single chapter can sometimes take me weeks.

The rest of this post lists my key takeaways from this book.

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Recommended: A Corporate Anthropologist’s Guide to Product Security

I recently read a good essay by Alex Gantman titled: A Corporate Anthropologist’s Guide to Product Security. It’s a year old, but I did not notice it before, and in any event, its contents are not time-sensitive at all. If you’re responsible for deploying SDLC in any real production environment, then you are likely to find much truth in this essay.

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Getting security requirements implemented

Every company that has both development teams and security teams also enjoys a healthy amount of tension between them. Specifics of the emotions involved may vary, but quite often security guys see developers as: not caring enough about security, focusing on short-term gains in features rather than on long-term robustness, and all-in-all, despite best intentions, still not “seeing the light”. Developers, in turn, often see their security-practicing friends as people with overly intense focus on security, which blinds them to all other needs of the product. They sometimes see those security preachers as people who maintain an overly simplistic view of the product design, and particularly of the cost and side-effects of the many changes they request for the sacred sake of security.

People of both camps are to a certain extent right, and to a certain extent exaggerating and not giving the other side enough credit. And yet, it doesn’t even matter where the truth lies, nor if there is truth at all. What matters is that there are two groups that are both essential for product success, and which should work towards a common goal: a product that has many appealing properties, including security.

The rest of this post presents tips for proper collaboration between security and development teams, specifically where it comes to setting and implementing security requirements. Due to my default affiliation with the security camp, the actions I prescribe are targeted primarily at the security people, but I hope that both developers and security practitioners can benefit from the high level perspective that I try to convey in the following five tips.

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Patents invented by Machine Learning

A few months ago I read an interesting post, which I felt compelled to write about. The post titled “Australian Court determines that an Artificial Intelligence system can be an inventor for the purposes of patent law” tells exactly what its title denotes. The case in question comes from the drugs industry, which has always been an avid user of the patent system, but one can easily see how the verdict can be applied to many (if not all) patent areas as well.

The article reads:

“In Australia, a first instance decision by Justice Beach of the Federal Court has provided some guidance: pursuant to Thaler v Commissioner of Patents (2021) FCA 879, an AI system can be the named inventor for an Australian patent application, with a person or corporation listed as the applicant for that patent, or a grantee of the patent.” [...] Worldwide, this is the first court decision determining that an AI system can be an inventor for the purposes of patent law.” [...] “The UK Intellectual Property Office (UKIPO), European Patent Office (EPO), and US Patent and Trademark Office (USPTO) each determined that an inventor must be a natural person.”

An appeal process is still ongoing, but this judgment still serves as an important milestone in the anticipated future of artificial intelligence, which bears enough resemblance to traditional human intelligence to demand similar treatment, first as art, and now also as the subject of patents.

I must admit that when I first read this article it seemed to me as a joke, and even a funny one at that. However, as I kept thinking about it, it made more and more sense. The purpose of this post is to take you through my thought process.

Just note that I am not a lawyer, not a patent attorney, and only express an opinion as someone who’s nowhere close to being authoritative on the subject.

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An interview on security challenges of organizations deploying IoT

On July 12th, I was interviewed on Security challenges of organizations deploying IoT. The recorded (and transcribed) video interview can be found here. For those who prefer a written abstract, here is the outline of what I said in reply to a short set of questions about the security challenges with IoT deployment, and the approach followed at Pelion to overcome them.

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