The dragons of the unknown; part 9 – learning to live with the unknowable

Introduction

This is the ninth and final post in a series about problems that fascinate me, that I think are important and interesting. The series draws on important work from the fields of safety critical systems and from the study of complexity, specifically complex socio-technical systems. This was the theme of my keynote at EuroSTAR in The Hague (November 12th-15th 2018).

The first post was a reflection, based on personal experience, on the corporate preference for building bureaucracy rather than dealing with complex reality, “facing the dragons part 1 – corporate bureaucracies”. Part 2 was about the nature of complex systems. The third followed on from part 2, and talked about the impossibility of knowing exactly how complex socio-technical systems will behave with the result that it is impossible to specify them precisely, “I don’t know what’s going on”.

Part 4 “a brief history of accident models”, looked at accident models, i.e. the way that safety experts mentally frame accidents when they try to work out what caused them.

The fifth post, “accident investigations and treating people fairly”, looked at weaknesses in the way that we have traditionally investigated accidents and failures, assuming neat linearity with clear cause and effect. In particular, our use of root cause analysis, and willingness to blame people for accidents is hard to justify.

Part six “Safety II, a new way of looking at safety” looks at the response of the safety critical community to such problems and the necessary trade offs that a practical response requires. The result, Safety II, is intriguing and has important lessons for software testers.

The seventh post “Resilience requires people” is about the importance of system resilience and the vital role that people play in keeping systems going.

The eighth post “How we look at complex systems” is about the way we choose to look at complex systems, the mental models that we build to try and understand them, and the relevance of Devops.

This final post will try to draw all these strands together and present some thoughts about the future of testing as we are increasingly confronted with complex systems that are beyond our ability to comprehend.

Computing will become more complex

Even if we choose to focus on the simpler problems, rather than help users understand complexity, the reality is that computing is only going to get more complex. The problems that users of complex socio-technical systems have to grapple with will inevitably get more difficult and more intractable. The choice is whether we want to remain relevant, but uncomfortable, or go for comfortable bullshit that we feel we can handle. Remember Zadeh’s Law of Incompatibility (see part 7 – resilience requires people). “As complexity increases, precise statements lose their meaning, and meaningful statements lose precision”. Quantum computing, artificial intelligence and adaptive algorithms are just three of the areas of increasing importance whose inherent complexity will make it impossible for testers to offer opinions that are both precise and meaningful.

Quantum computing, in particular, is fascinating. By its very nature it is probabilistic, not deterministic. The idea that well designed and written programs should always produce the same output from the same data is relevant only to digital computers (and even then the maxim has to be heavily qualified in practice); it never holds true at any level for quantum computers. I wrote about this in “Quantum computing; a whole new field of bewilderment”.

The final quote from that article, “perplexity is the beginning of knowledge”, applies not only to quantum computing but also to artificial intelligence and the fiendish complexity of algorithms processing big data. One of the features of quantum computing is the way that changing a single qubit, the equivalent of digital bytes, will trigger changes in other qubits. This is entanglement, but the same word is now being used to describe the incomprehensible complexity of modern digital systems. Various writers have talked about this being the Age of Entanglement, eg Samuel Arbesman, in his book “Overcomplicated: Technology at the Limits of Comprehension)”, Emmet Connolly, in an article “Design in the Age of Entanglement” and Danny Hillis, in an article “The Enlightenment is Dead, Long Live the Entanglement”.

The purist in me disapproves of recycling a precise term from quantum science to describe loosely a phenomenon in digital computing. However, it does serve a useful role. It is a harsh and necessary reminder and warning that modern systems have developed beyond our ability to understand them. They are no more comprehensible than quantum systems, and as Richard Feynman is popularly, though possibly apocryphally, supposed to have said; “If you think you understand quantum physics, you don’t understand quantum physics.”

So the choice for testers will increasingly be to decide how we respond to Zadeh’s Law. Do we offer answers that are clear, accurate, precise and largely useless to the people who lose sleep at night worrying about risks? Or do we say “I don’t know for sure, and I can’t know, but this is what I’ve learned about the dangers lurking in the unknown, and what I’ve learned about how people will try to stay clear of these dangers, and how we can help them”?

If we go for the easy options and restrict our role to problems which allow definite answers then we will become irrelevant. We might survive as process drones, holders of a “bullshit job” that fits neatly into the corporate bureaucracy but offers little of value. That will be tempting in the short to medium term. Large organisations often value protocol and compliance more highly than they value technical expertise. That’s a tough problem to deal with. We have to confront that and communicate why that worldview isn’t just dated, it’s wrong. It’s not merely a matter of fashion.

If we’re not offering anything of real value then there are two possible dangers. We will be replaced by people prepared to do poor work cheaper; if you’re doing nothing useful then there is always someone who can undercut you. Or we will be increasingly replaced by automation because we have opted to stay rooted in the territory where machines can be more effective, or at least efficient.

If we fail to deal with complexity the danger is that mainstream testing will be restricted to “easy” jobs – the dull, boring jobs. When I moved into internal audit I learned to appreciate the significance of all the important systems being inter-related. It was where systems interfaced, and when people were involved that they got interesting. The finance systems with which I worked may have been almost entirely batch based, but they performed a valuable role for the people with whom we were constantly discussing the behaviour of these systems. Anything standalone was neither important nor particularly interesting. Anything that didn’t leave smart people scratching their heads and worrying was likely to be boring. Inter-connectedness and complexity will only increase and however difficult testing becomes it won’t be boring – so long as we are doing a useful job.

If we want to work with the important, interesting systems then we have to deal with complexity and the sort of problems the safety people have been wrestling with. There will always be a need for people to learn and inform others about complex systems. The American economist Tyler Cowen in his book “Average is Over” states the challenge clearly. We will need interpreters of complex systems.

“They will become clearing houses for and evaluators of the work of others… They will hone their skills of seeking out, absorbing and evaluating information… They will be translators of the truths coming out of our network of machines… At least for a while they will be the only people who will have a clear notion of what is going on.”

I’m not comfortable with the idea of truths coming out of machines, and we should resist the idea that we can ever be entirely clear about what is going on. But the need for experts who can interpret complex systems is clear. Society will look for them. Testers should aspire to be among those valuable specialists. conductorThe complexity of these systems will be beyond the ability of any one person to comprehend, but perhaps these interpreters, in addition to deploying their own skills, will be able to act like a conductor of an orchestra, to return to the analogy I used in part seven (Resilience requires people). Conductors are talented musicians in their own right, but they call on the expertise of different specialists, blending their contribution to produce something of value to the audience. Instead of a piece of music the interpreter tester would produce a story that sheds light on the system, guiding the people who need to know.

Testers in the future will have to be confident and assertive when they try to educate others about complexity, the inexplicable and the unknowable. Too often in corporate life a lack of certainty has been seen as a weakness. We have to stand our ground and insist on our right to be heard and taken seriously when we argue that certainty cannot be available if we want to talk about the risks and problems that matter. My training and background meant I couldn’t keep quiet when I saw problems, that were being ignored because no-one knew how to deal with them. As Better Software said about me, I’m never afraid to voice my opinion.better software says I am never afraid to voice my opinion

Never be afraid to speak out, to explain why your experience and expertise make your opinions valuable, however uncomfortable these may be for others. That’s what you’re paid for, not to provide comforting answers. The metaphor of facing the dragons of the unknown is extremely important. People will have to face these dragons. Testers have a responsibility to try and shed as much light as possible on those dragons lurking in the darkness beyond what we can see and understand easily. If we concentrate only on what we can know and say with certainty it means we walk away from offering valuable, heavily qualified advice about the risks, threats & opportunities that matter to people. Our job should entail trying to help and protect people. As Jerry Weinberg said in “Secrets of Consulting”;

“No matter what they tell you, it’s always a people problem.”

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Quantum computing; a whole new field of bewilderment

At primary school in London I was taught about different number bases, concentrating on binary arithmetic. This was part of an attempt in the 1960s to bring mathematics up to date. The introduction of binary to the curriculum was prompted by the realisation that computers would become hugely more significant. It was fascinating to realise that there was nothing inevitable or sacrosanct about using base 10 and I enjoyed it all.

When I started working in IT I quickly picked up the technical side. I understood binary and with a bit of work, keeping a clear head, everything made sense. It was mostly based on Boolean logic. Everything was true or false, on or off, pass or fail, 1 or 0.

Now this simple state of affairs applied only to the technology. When you started to deal with humans, with organisations, with messy social reality it was important to step back from a simple binary worldview. You can’t develop worthwhile applications, or test them, if you assume that the job simply requires stepping through a process that is akin to a computer program, with every decision being a straightforward binary, yes/no, pass/fail. I’ve talked about that at length elsewhere, eg here “binary opinions – yes or no?“.

Recently I’ve been reading about quantum computing. I’d vaguely known about the subject before. I knew it was a radically different approach to computing, but I hadn’t thought through just how radical the differences are, or the implications for testing. It’s not just testing of course. When a completely new form of computing comes on the scene, one that leaves all our expectations, assumptions and beliefs in tatters, there will be huge ramifications throughout IT. Traditional computers won’t vanish; there will still be plenty of jobs working with them. People will continue to specialise in specific areas of computing. The problem for testers will be that quantum computers are going to be used for new applications, to do things that were previously impossible, and traditional testing techniques won’t necessarily be readily transferable.

What’s so different about quantum computing?

I’m not going to try and provide an introduction to quantum computers. If you think you understand them and you haven’t done some serious study of quantum physics then you’re kidding yourself. And as Richard Feynman said;

“If you think you understand quantum physics, you don’t understand quantum physics.”

If a primary school introduction to binary arithmetic allowed me to get to grips with traditional, digital computers, then the equivalent for quantum computers would be at least an undergraduate degree in physics. Here is a good overview.

I’m just going to run through three features of quantum computers that make my head spin, that have persuaded me that everything I knew about computers will be useless and I will be as well prepared as a peasant trying to get to grips with Excel after stumbling through a time portal from the Middle Ages.

First, instead of bits we have qubits. Bits can be 0 or 1. Once set to a value they don’t change until we perform some operation. The possible states of a qubit are excited or relaxed, which could be considered equivalent to 0 or 1. The fundamental difference is that they can be both at the same time, or rather a mixture of the two. This property is superposition. However, when the qubit is measured it will be frozen as one or the other.

The second weird feature of qubits is that different qubits influence each other. In traditional computing if we operate on a bit then no other bits will change. If they do it’s because the logic of the program controls these changes. In quantum computing that doesn’t apply. Changing a qubit will cause other qubits to change. Qubits are not independent of each other; they are all linked to each other. This is called entanglement.

The third weird thing about quantum computing is that algorithms are probabilistic, not deterministic. A classical digital computer will run through an algorithm and produce the right answer, or rather it will produce a predictable answer that is consistent with the algorithm’s logic. A quantum computer won’t always give the right answer straight away. It might have to send the same input through the same process many times and the results should converge on the right answer, probably.

I’m telling you this not because I think it will give you any sort of useful understanding of quantum computing. A spot of humility is in order. I pass on this information in the hope you realise you have as little idea as I do.

In summary, quantum computing is moving way beyond dear old familiar Boolean logic. Boolean algebra is still valid, but it is only relevant to one part of a wider reality and quantum computers will allow us to explore beyond the Boolean boundaries.

I have done my share of white box testing, delving into the guts of applications to understand what is going on. I know I will never be in a position to do that with quantum computers, even assuming that they are in widespread use before I retire. I doubt if there are many, if any testers, who will be better placed than I am.

What will quantum computers be used for?

If white box testing poses a tough challenge what about black box testing? As I said earlier, quantum computers will be used for problems that traditional computers can’t help with. One application will be the transformation of cryptography. Quantum computing will probably render existing cryptographing techniques obsolete. Other likely uses will be new ways to search and interrogate massive databases, and financial modelling that requires fiendishly intricate calculations on huge volumes of data. These are the applications that caught my eye, because of my background in financial services. A big problem for testers will be, how do you evaluate the output if the computer is doing something that can’t be replicated by other means? This isn’t a new problem, but quantum computers will massively increase the difficulty.

Blind computing guiding the blind?

I wrote about the problems I’d encountered working with big data a few years ago. Our approach could be summed up simply as;

  • build a deep understanding of the domain and the data, and the essential relationships or rules,
  • get the business or domain experts heavily involved and pick their brains,
  • ensure you influence the design so that it is testable, ideally so that the solution enables testing of separate segments which can be isolated so you can bring your acquired knowledge and understanding to bear.

The first two points will always be relevant regardless of the technology. The third one has been picked up by quantum computing scientists who have developed a technique called blind quantum computing.

The blind technique involves running a separate, simpler(!), quantum computer called a verifier alongside the server running the test application. The verifier feeds the server with small, discreet calculations to perform. It does this in a way so that only the verifier, and the testers, can know what the answer should be, and the server knows only what operations it should perform. This is the simplest explanation of blind quantum computing I’ve been able to find.

An obvious observation is that this is hardly black box testing as we have known it. Who programs and controls the verifier? It is a quantum computer, and I doubt if ISTQB accreditation will ever get you very far here.

Fields of bewilderment

I don’t have any answers here, and I strongly suspect easy answers will never be available to testers who work with quantum computers. That, perhaps, is the point to take away from my article. Writing this has felt less like trying to spread some understanding of an immensely difficult subject, and more like an account of a bewildered ramble through my freshly expanded fields of ignorance.

I can’t state with confidence that software testers will ever move into quantum computing. Perhaps the serious testing will be done by quantum computing scientists. That raises its own dangers. Will they have the right instincts, an appropriate sceptical and questioning approach? There is already talk of quantum computers permitting the development of perfect software. Apparently they will be able to work their way through every conceivable permutation of data to establish that the application was built to its specification. Of course there is a huge, familiar old question being begged there; how does anyone know the spec was right?
Opening of the poem 'Youth and Hope' from which the quote 'perplexity is the beginning of knowledge' comes

I worry that good testers may be frozen out of working with quantum computers, and that the skills and questions they do have, and that will remain relevant, will be lost. Whatever happens I am confident that testers imbued with the principles of Context-Driven Testing will be better prepared than those who know only what they learned to pass ISTQB exams, or who are accustomed to following prescriptive standards. Whatever the future holds for us it will be interesting! After all, perplexity is the beginning of knowledge.