Archive for the ‘Decision Making’ Category
Complex decision making as an infinite game
A decision is the act of choosing between two or more options.
There are two kinds of decisions, computable and non-computable [1]. In the former, options are well-defined and finite in number, and there are unambiguous facts (data) available based on which options can be rated. In the latter, options are neither clear nor enumerable and facts, if available at all, are ambiguous.
Computable decisions are simple, non-computable decisions are complex. We’ll refer to the two decision types by these names in the remainder of this article.
An example of a simple decision is buying a product (TV, car or whatever) based on well-defined criteria (price, features etc.). An example of a complex decision is formulating a business strategy.
It should be clear that simple decisions involve smaller temporal and monetary stakes – i.e. the cost of getting things wrong is limited and the effects of a bad decision wear off in (a relatively short) time. Neither is true for complex decisions: the cost of a poor choice can be significant, and its negative effects tend to persist over time.
A key feature of complex decisions is that they (usually) affect multiple parties. That is, they are socially complex. This has implications regarding how such decisions should be approached. More on this later.
Conventional decision theory is based on the notion of maximizing benefit or utility. For simple decisions it is assumed that utility of each option can be computed; for complex decisions it is assumed they can be estimated, or at least ranked. The latter assumption is questionable because each party affected by a complex decision will have its own notion of utility, at least at the outset. Moreover, since neither options nor facts are unambiguous at the start, it makes little sense to attempt to estimate utility upfront.
The above being the case, it is clear that complex decisions cannot be made on the basis of maximizing utility alone. Something else is needed.
–x–
James Carse’s classic book, Finite and Infinite Games, begins with the following lines:
There are at least two kinds of games. One could be called finite, the other infinite. A finite game is played for the purpose of winning, an infinite for the purpose of continuing the play.
A finite game ends when a player or team wins. However, “just as it is essential for a finite game to have a definitive ending, it must also have a precise beginning. Therefore, we can speak of finite games as having temporal boundaries.”
The parallel between simple decisions and finite games should be evident. Although less obvious, it is useful to think of a complex decision as an infinite game.
When making a complex decision – such as a business strategy – decision-makers will often focus on maximising potential benefits (aka utility). However, as often as not, the outcome of the decision will fall far short of the expected benefits and may, in some cases, even lead to ruin. This being so, it is perhaps more fruitful to focus on staying in the game (keep playing) rather than winning (maximising utility).
The aim of a complex decision should be to stay in the game rather than win.
How does one ensure that one stays in the game? Heinz von Foerster’s ethical imperative offers an answer”
Always act to increase your choices.
That is, one should decide in such a way that increases one’s options in the future thereby increasing chances of staying in the game. One can frame this discussion in terms of adaptability: the greater the number of options the greater the ability to adapt to unexpected changes in the environment.
How can one “act to increase one’s choices”?
One way to do this is to leverage social complexity: get different parties to articulate their preferred options. Some of these options are likely to contradict each other. Nevertheless, there are ways to handle such a diversity of potentially contradictory views in an inclusive manner (for an example, see this paper; for more, check out this book). Such an approach also ensures that the problem and solution spaces are explored more exhaustively than if only a limited number of viewpoints are considered.
The point is this: there are always more options available than apparent. Indeed, the number of unexplored options at any stage is potentially infinite. The job of the infinite player (decision-maker) is to act so as surface them gradually, and thus stay in the game.
–x–
Traditionally, decision-making is seen as a logical undertaking based on facts or data. In contrast, when viewed as an infinite game, complex decision-making becomes a matter of ethics rather than logic.
Why ethics?
The answer lies in von Foerster’s dictum to increase one’s choices. By doing so, one increases the chances that fewer stakeholders’ interests are overlooked in the decision-making process.
As Wittgenstein famously said, “It is clear ethics cannot be articulated.” All those tedious classes and books on business ethics miss the point entirely. Ethical matters are necessarily oblique: the decision-maker who decides in a way that increases (future) choices, will be acting ethically without drawing attention to it, or even being consciously aware of it.
–x–
Any honest discussion of complex decision-making in organisations must address the issue of power.
Carse asserts that players (i.e. decision-makers in the context of this article) become powerful by acquiring titles (e.g. CEO, Manager etc.). However, such titles can only be acquired by winning a finite game– i.e. by being successful in competitions for roles. Power therefore relates to finite rather than infinite games.
As he notes in his book:
Power is a concept that belongs only in finite play. To speak meaningfully of a person’s power is to speak of what that person has already achieved, the titles they have already won.
Be that as it may, one cannot overlook the reality that those in powerful positions can (and often do) subvert the decision-making process by obstructing open and honest discussion of contentious issues. Sometimes they do so by their mere presence in the room.
How does a complex decision-maker deal with the issue of power?
Carse offers the following answer:
How do infinite players contend with power? Since the outcome of infinite play is endlessly open, there is no way of looking back to make an assessment of the power or weakness of earlier play. Infinite players look forward, not to a victory but toward ongoing play. A finite player plays to be powerful; the infinite player plays with strength. Power is concerned (and a consequence of) what has happened, strength with what has yet to happen. Power will be always restricted to a relatively small number of people. Anyone can be strong.
What strength means is context-dependent, but the following may help clarify its relationship to power:
Late last year I attended an end-of-year event at the university I teach at. There I bumped into a student I had mentored some time ago. We got talking about his workplace (a large government agency).
At one point he asked, “We really need to radically change the way we think about and work with data, but I’m not a manager and have no authority to initiate changes that need to be made.”
“Why don’t you demonstrate what you are capable of? Since you are familiar your data, it should be easy enough to frame and tackle a small yet meaningful data science problem.” I replied.
“What if my manager doesn’t like my taking the initiative?”
“It is easier to beg forgiveness than seek permission.”
“He might feel threatened and make life difficult for me.”
“If management doesn’t like you’re doing, it’s their loss. What’s the worst that could happen? You could lose your job. With what you are learning at university you should have no trouble moving on to another role. Indeed, by doing so, you will diversify your experience and increase your future options.”
–x–
To summarise: when deciding on complex matters, act in a way that maximises possibility rather than utility. Such an approach is inherently ethical and enhances one’s chances of staying in the game.
Complex decision making is an infinite game.
[1] There are many other terms for this classification: tame and wicked (Horst Rittel), programmed and non-programmed (Herbert Simon), complicated and complex (David Snowden). Paul Culmsee and I have, perhaps confusingly, used the terms uncertain and ambiguous to refer to these in our books. There are minor contextual differences between how these different authors interpret these terms, but for the most part they are synonymous with computable/non-computable.
3 or 7, truth or trust
“It is clear that ethics cannot be articulated.” – Ludwig Wittgenstein
Over the last few years I’ve been teaching and refining a series of lecture-workshops on Decision Making Under Uncertainty. Audiences include data scientists and mid-level managers working in corporates and public service agencies. The course is based on the distinction between uncertainties in which the variables are known and can be quantified versus those in which the variables are not known upfront and/or are hard to quantify.
Before going any further, it is worth explaining the distinction via a couple of examples:
An example of the first type of uncertainty is project estimation. A project has an associated time and cost, and although we don’t know what their values are upfront, we can estimate them if we have the right data. The point to note is this: because such problems can be quantified, the human brain tends to deal with them in a logical manner.
In contrast, business strategy is an example of the second kind of uncertainty. Here we do not know what the key variables are upfront. Indeed we cannot, because different stakeholders will perceive different aspects of a strategy to be paramount depending on their interests – consider, for example, the perspective of a CFO versus that of a CMO. Because of these differences, one cannot make progress on such problems until agreement has been reached on what is important to the group as a whole. The point to note here is that since such problems involve contentious issues, our reactions to them tend to be emotional rather than logical.
The difference between the two types of uncertainty is best conveyed experientially, so I have a few in-class activities aimed at doing just that. One of them is an exercise I call “3 or 7“, in which I give students a sheet with the following printed on it:
Circle either the number 3 or 7 below depending on whether you want 3 marks or 7 marks added to your Assignment 2 final mark. Yes, this offer is for real, but there a catch: if more than 10% of the class select 7, no one gets anything.
Write your student ID on the paper so that Kailash can award you the marks. Needless to say, your choice will remain confidential, no one (but Kailash) will know what you have selected.
3 7
Prior to handing out the sheet, I tell them that they:
- should sit far enough apart so that they can’t see what their neighbours choose,
- are not allowed to communicate their choices to others until the entire class has turned their sheets.
Before reading any further you may want to think about what typically happens.
–x–
Many readers would have recognized this exercise as a version of the Prisoner’s Dilemma and, indeed, many students in my classes recognize this too. Even so, there are always enough of “win at the cost of others” types in the room who ensure that I don’t have to award any extra marks. I’ve run the exercise about 10 times, often with groups comprised of highly collaborative individuals who work well together. Despite that,15-20% of the class ends up opting for 7.
It never fails to surprise me that, even in relatively close-knit groups, there are invariably a number of individuals who, if given a chance to gain at the expense of their colleagues, will not hesitate to do so providing their anonymity is ensured.
–x–
Conventional management thinking deems that any organisational activity involving several people has to be closely supervised. Underlying this view is the assumption that individuals involved in the activity will, if left unsupervised, make decisions based on self-interest rather than the common good (as happens in the prisoner’s dilemma game). This assumption finds justification in rational choice theory, which predicts that individuals will act in ways that maximise their personal benefit without any regard to the common good. This view is exemplified in 3 or 7 and, at a societal level, in the so-called Tragedy of the Commons, where individuals who have access to a common resource over-exploit it, thus depleting the resource entirely.
Fortunately, such a scenario need not come to pass: the work of Elinor Ostrom, one of the 2009 Nobel prize winners for Economics, shows that, given the right conditions, groups can work towards the common good even if it means forgoing personal gains.
Classical economics assumes that individuals’ actions are driven by rational self-interest – i.e. the well-known “what’s in it for me” factor. Clearly, the group will achieve much better results as a whole if it were to exploit the resource in a cooperative way. There are several real-world examples where such cooperative behaviour has been successful in achieving outcomes for the common good (this paper touches on some). However, according to classical economic theory, such cooperative behaviour is simply not possible.
So the question is: what’s wrong with rational choice theory? A couple of things, at least:
Firstly, implicit in rational choice theory is the assumption that individuals can figure out the best choice in any given situation. This is obviously incorrect. As Ostrom has stated in one of her papers:
Because individuals are boundedly rational, they do not calculate a complete set of strategies for every situation they face. Few situations in life generate information about all potential actions that one can take, all outcomes that can be obtained, and all strategies that others can take.
Instead, they use heuristics (experienced-based methods), norms (value-based techniques) and rules (mutually agreed regulations) to arrive at “good enough” decisions. Note that Ostrom makes a distinction between norms and rules, the former being implicit (unstated) rules, which are determined by the cultural attitudes and values)
Secondly, rational choice theory assumes that humans behave as self-centred, short-term maximisers. Such theories work in competitive situations such as the stock-market but not in situations in which collective action is called for, such as the prisoners dilemma.
Ostrom’s work essentially addresses the limitations of rational choice theory by outlining how individuals can work together to overcome self-interest.
–x–
In a paper entitled, A Behavioral Approach to the Rational Choice Theory of Collective Action, published in 1998, Ostrom states that:
…much of our current public policy analysis is based on an assumption that rational individuals are helplessly trapped in social dilemmas from which they cannot extract themselves without inducement or sanctions applied from the outside. Many policies based on this assumption have been subject to major failure and have exacerbated the very problems they were intended to ameliorate. Policies based on the assumptions that individuals can learn how to devise well-tailored rules and cooperate conditionally when they participate in the design of institutions affecting them are more successful in the field…[Note: see this book by Baland and Platteau, for example]
Since rational choice theory aims to maximise individual gain, it does not work in situations that demand collective action – and Ostrom presents some very general evidence to back this claim. More interesting than the refutation of rational choice theory, though, is Ostrom’s discussion of the ways in which individuals “trapped” in social dilemmas end up making the right choices. In particular she singles out two empirically grounded ways in which individuals work towards outcomes that are much better than those offered by rational choice theory. These are:
Communication: In the rational view, communication makes no difference to the outcome. That is, even if individuals make promises and commitments to each other (through communication), they will invariably break these for the sake of personal gain …or so the theory goes. In real life, however, it has been found that opportunities for communication significantly raise the cooperation rate in collective efforts (see this paper abstract or this one, for example). Moreover, research shows that face-to-face is far superior to any other form of communication, and that the main benefit achieved through communication is exchanging mutual commitment (“I promise to do this if you’ll promise to do that”) and increasing trust between individuals. It is interesting that the main role of communication is to enhance or reinforce the relationship between individuals rather than to transfer information. This is in line with the interactional theory of communication.
Innovative Governance: Communication by itself may not be enough; there must be consequences for those who break promises and commitments. Accordingly, cooperation can be encouraged by implementing mutually accepted rules for individual conduct, and imposing sanctions on those who violate them. This effectively amounts to designing and implementing novel governance structures for the activity. Note that this must be done by the group; rules thrust upon the group by an external authority are unlikely to work.
Of course, these factors do not come into play in artificially constrained and time-bound scenarios like 3 or 7. In such situations, there is no opportunity or time to communicate or set up governance structures. What is clear, even from the simple 3 or 7 exercise, is that these are required even for groups that appear to be close-knit.
Ostrom also identifies three core relationships that promote cooperation. These are:
Reciprocity: this refers to a family of strategies that are based on the expectation that people will respond to each other in kind – i.e. that they will do unto others as others do unto them. In group situations, reciprocity can be a very effective means to promote and sustain cooperative behaviour.
Reputation: This refers to the general view of others towards a person. As such, reputation is a part of how others perceive a person, so it forms a part of the identity of the person in question. In situations demanding collective action, people might make judgements on a person’s reliability and trustworthiness based on his or her reputation.’
Trust: Trust refers to expectations regarding others’ responses in situations where one has to act before others. And if you think about it, everything else in Ostrom’s framework is ultimately aimed at engendering or – if that doesn’t work – enforcing trust.
–x—
In an article on ethics and second-order cybernetics, Heinz von Foerster tells the following story:
I have a dear friend who grew up in Marrakech. The house of his family stood on the street that divide the Jewish and the Arabic quarter. As a boy he played with all the others, listened to what they thought and said, and learned of their fundamentally different views. When I asked him once, “Who was right?” he said, “They are both right.”
“But this cannot be,” I argued from an Aristotelian platform, “Only one of them can have the truth!”
“The problem is not truth,” he answered, “The problem is trust.”
For me, that last line summarises the lesson implicit in the admittedly artificial scenario of 3 or 7. In our search for facts and decision-making frameworks we forget the simple truth that in many real-life dilemmas they matter less than we think. Facts and frameworks cannot help us decide on ambiguous matters in which the outcome depends on what other people do. In such cases the problem is not truth; the problem is trust. From your own experience it should be evident it is impossible convince others of your trustworthiness by assertion, the only way to do so is by behaving in a trustworthy way. That is, by behaving ethically rather than talking about it, a point that is squarely missed by so-called business ethics classes.
Yes, it is clear that ethics cannot be articulated.
Notes:
- Portions of this article are lightly edited sections from a 2009 article that I wrote on Ostrom’s work and its relevance to project management.
- Finally, an unrelated but important matter for which I seek your support for a common good: I’m taking on the 7 Bridges Walk to help those affected by cancer. Please donate via my 7 Bridges fundraising page if you can . Every dollar counts; all funds raised will help Cancer Council work towards the vision of a cancer free future.
Peirce, Holmes and a gold chain – an essay on abductive reasoning
“It has long been an axiom of mine that the little things are infinitely the most important.” – Sir Arthur Conan Doyle (A Case of Identity)
The scientific method is a systematic approach to acquiring and establishing knowledge about how the world works. A scientific investigation typically starts with the formulation of a hypothesis – an educated, evidence-based guess about the mechanism behind the phenomenon being studied – and proceeds by testing how well the hypothesis holds up against experiments designed to disconfirm it.
Although many philosophers have waxed eloquent about the scientific method, very few of them have talked about the process of hypothesis generation. Indeed, most scientists will recognise a good hypothesis when they stumble upon one, but they usually will not be able to say how they came upon it. Hypothesis generation is essentially a creative act that requires a deep familiarity with the phenomenon in question and a spark of intuition. The latter is absolutely essential, a point captured eloquently in the following lines attributed to Einstein:
“…[Man] makes this cosmos and its construction the pivot of his emotional life in order to find in this way the peace and serenity which he cannot find in the narrow whirlpool of personal experience. The supreme task is to arrive at those universal elementary laws from which the cosmos can be built up by pure deduction. There is no logical path to these laws; only intuition, resting on sympathetic understanding of experience can reach them…” – quoted from Zen and The Art of Motorcycle Maintenance by Robert Pirsig.
The American philosopher, Charles Peirce, recognised that hypothesis generation involves a special kind of reasoning, one that enables the investigator to zero in on a small set of relevant facts out of an infinity of possibilities.
Charles Sanders Peirce
As Peirce wrote in one of his papers:
“A given object presents an extraordinary combination of characters of which we should like to have an explanation. That there is any explanation of them is a pure assumption; and if there be, it is [a single] fact which explains them; while there are, perhaps, a million other possible ways of explaining them, if they were not all, unfortunately, false.
A man is found in the streets of New York stabbed in the back. The chief of police might open a directory and put his finger on any name and guess that that is the name of the murderer. How much would such a guess be worth? But the number of names in the directory does not approach the multitude of possible laws of attraction which could have accounted for Kepler’s law of planetary motion and, in advance of verification by predications of perturbations etc., would have accounted for them to perfection. Newton, you will say, assumed that the law would be a simple one. But what was that but piling guess on guess? Surely vastly more phenomena in nature are complex than simple…” – quoted from this paper by Thomas Sebeok.
Peirce coined the term abduction (as opposed to induction or deduction) to refer to the creative act of hypothesis generation. In the present day, the term is used to the process of justifying hypotheses rather than generating them (see this article for more on the distinction). In the remainder of this piece I will use the term in its Peircean sense.
–x–
Contrary to what is commonly stated, Arthur Conan Doyle’s fictional detective employed abductive rather than deductive methods in his cases. Consider the following lines, taken from an early paragraph of Sherlock Holmes’ most celebrated exploit, The Adventure of the Speckled Band. We join Holmes in conversation with a lady who has come to him for assistance:
…You have come in by train this morning, I see.”
“You know me, then?”
“No, but I observe the second half of a return ticket in the palm of your left glove. You must have started early, and yet you had a good drive in a dog-cart, along heavy roads, before you reached the station.”
The lady gave a violent start and stared in bewilderment at my companion.
“There is no mystery, my dear madam,” said he, smiling. “The left arm of your jacket is spattered with mud in no less than seven places. The marks are perfectly fresh. There is no vehicle save a dog-cart which throws up mud in that way, and then only when you sit on the left-hand side of the driver.”
“Whatever your reasons may be, you are perfectly correct,” said she. “I started from home before six, reached Leatherhead at twenty past, and came in by the first train to Waterloo…
Notice what Holmes does: he forms hypotheses about what the lady did, based on a selective observation of facts. Nothing is said about why he picks those particular facts – the ticket stub and the freshness / location of mud spatters on the lady’s jacket. Indeed, as Holmes says in another story, “You know my method. It is founded upon the observation of trifles.”
Abductive reasoning is essentially about recognising which trifles are important.
–x–
I have a gold chain that my mum gave me many years ago. I’ve worn it for so long that now I barely notice it. The only time I’m consciously aware that I’m wearing the chain is when I finger it around my neck, a (nervous?) habit I have developed over time.
As you might imagine, I’m quite attached to my gold chain. So, when I discovered it was missing a few days ago, my first reaction was near panic, I felt like a part of me had gone missing.
Since I hardly ever take the chain off, I could not think of any plausible explanation for how I might have lost it. Indeed, the only time I have had to consistently take the chain off is when going in for an X-ray or, on occasion, through airport security.
Where could it have gone?
After mulling over it for a while, the only plausible explanation I could think of is that I had taken it off at airport security when returning from an overseas trip a week earlier, and had somehow forgotten to collect it on the other side. Realising that it would be near impossible to recover it, I told myself to get used to the idea that it was probably gone for good.
That Sunday, I went for a swim. After doing my laps, I went to the side of the pool for my customary shower. Now, anyone who has taken off a rash vest after a swim will know that it can be a struggle. I suspect this is because water trapped between skin and fabric forms a thin adhesive layer (a manifestation of surface tension perhaps?). Anyway, I wrestled the garment over my head and it eventually came free with a snap, generating a spray of droplets that gleamed in reflected light.
Later in the day, I was at the movies. For some reason, when coming out of the cinema, I remembered the rash vest and the flash of droplets. Hmm, I thought, “a gleam of gold….”
…A near forgotten memory: I vaguely recalled a flash of gold while taking of my rash vest in the pool shower some days ago. Was it after my previous swim or the week earlier, I couldn’t be sure. But I distinctly remembered it had bothered me enough to check the floor of the cubicle cursorily. Finding nothing, I had completely forgotten about it and moved on.
Could it have come off there?
As I thought about it some more, possibility turned to plausibility: I was convinced it was what had happened. Although unlikely I would find it there now, it was worth a try on the hope that someone had found the chain and turned it in as lost property.
I stopped over at the pool on my way back from the movies and asked at reception.
“A gold chain? Hmm, I think you may be in luck,” he said, “I was doing an inventory of lost property last week and came across a chain. I was wondering why no one had come in to claim something so valuable.”
“You’re kidding,” I said, incredulous. “You mean you have a gold chain?”
“Yeah, and I’m pretty sure it will still be there unless someone else has claimed it,” he replied. “I’ll have a look in the safe. Can you describe it for me?”
I described it down to the brief inscription on the clasp.
“Wait here,” he said, “I’ll be a sec”
It took longer than that but he soon emerged, chain in hand.
I could not believe my eyes; I had given up on ever recovering it. “Thanks, so much” I said fervently, “you won’t believe how much it means to me to have found this.”
“No worries mate,” he said, smiling broadly. “Happy to have helped.”
–x–
Endnote: in case you haven’t read it yet, I recommend you take ten minutes to read Sherlock Holmes’ finest adventure and abductive masterpiece, The Adventure of the Speckled Band.
Eight to Late 