Eight to Late

Sensemaking and Analytics for Organizations

The pathologies of information – a tale of two systems

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Prologue

California, Jan 2000

“We tend to see the world in terms of entities rather than relationships,” said the professor, “and in doing so, we make a grave error.”

He paused, as though expecting disagreement.

“But relationships are between entities, without entities there can be no relationships,” she countered.

“And that is precisely upside down,” replied the professor. “It is the relationships that define entities and thus dictate how the entire system evolves.   “In evolution it is the relationship between species and environment that is primary, not the species or environment in isolation.”

“But what defines the relationship?” she asked.

“The information exchanged by the entities,” replied the prof. “As Gregory Bateson told us over a quarter century ago, information is a difference which makes a difference; a signal that provokes a response from another entity.   The stream of information between entities defines the relationships between them. It is the entire network of these relationships that determines the overall behaviour of a system, be it a person or a planet. If information turns pathological in some way, the system will show signs of sickness.”

“I’m not sure I understand…”

“You will in time,” he said cryptically.

Sydney, Sep 2020

It started with a general sense of malaise:  tiredness, occasional cramps, and a few other symptoms, each innocuous individually, but when taken together suggested that a visit to the doctor would be in order.

“I don’t think there’s anything to worry about,” said the doctor, after a brief examination, “but let’s do a few tests and a scan just to make sure.”

A few days later, a call from the doctor’s office. “The doctor would like to see you today,” said the receptionist, “can you come in at 3 pm?”  There was a hint of urgency in her voice.

The doctor got to the point immediately. “I’m sorry, I don’t have good news. There is a mass in your abdomen and the blood tests indicate that it might be malignant. There is also a hint that the disease may have spread to adjacent organs. You must see a surgeon urgently.   I’ve already arranged for you to see one tomorrow.”

Wuhan, Nov 2019

Rumours of a severe “pneumonia of unknown origin” started to circulate in the city in late November.  In a few weeks there were a couple of dozen hospitalized cases, some of them in intensive care.

Despite official assertions that things were “under control”, the proverbial person on the street could sense they were not.

Doctors on the frontline knew this was no ordinary flu, but the authorities held off on making an announcement, ostensibly to avoid panic.

Sydney, Oct 2020

“The operation went well,” said the surgeon, “I removed the primary tumour and a few secondaries that weren’t clearly visible on the scan.”

That was good news, but it also sounded like there was a caveat…

“Given the presence of secondary tumours, there is a high likelihood there are microscopic cancer cells in and around the abdominal cavity,” he continued, “I have taken some biopsies and sent them for microscopic examination.”

“Does that mean the cancer has spread?” she asked.

“It is possible,” he replied, “but let’s wait for the results before jumping to conclusions.”

Wuhan, Dec 2019

As the infection count mounted, it became increasingly obvious, even to the authorities, that this was more than an ordinary flu.  Moreover, as it always does, information (and the sickness) had started to find its way out of Wuhan to the hinterland and beyond.

On the last day of 2019, the Chinese authorities informed the World Health Organisation (WHO) about a pneumonia-like flu.

Controls on movements were duly imposed.

Sydney, Nov 2020

The test results confirmed the disease had spread.  The surgeon explained that chemotherapy was the likely next step and referred her to a medical oncologist for further treatment.

The oncologist confirmed the diagnosis and started her on a series of chemotherapy sessions to tackle the microscopic malignancies that had spread to areas distant from the original site.

WHO Head Office, Jan 2020

Following the notification from the Chinese authorities, WHO issued a disease outbreak announcement on 5th January.  The announcement advised travellers to be watchful for symptoms of respiratory distress but did not recommend any restrictions on travel.

Barely a week later, a case was confirmed in Thailand. It was a visitor from Wuhan.

Three weeks on from the Thailand case, there were over 7500 cases worldwide.  Although the vast majority were in China, there were over 80 cases confirmed in 18 other countries.

The virus had bolted.

Sydney, Nov 2020

As her treatment progressed, she often wondered if there was anything she could have done differently.

There wasn’t. The story, though not entirely foretold, had been cast in probabilities that could be traced back to an information pathology that occurred generations ago.

Life is sustained by metabolic processes:  complex chemical reactions that occur at the level of individual cells. An example of a metabolic process is the breakdown of complex food molecules (such as carbohydrates) into simple sugars that the body can use to power various activities (such as your daily swim or run). At the most basic level, metabolic processes are governed by genes, segments of deoxyribonucleic acid (DNA) that serve as templates for proteins which form the raw materials for metabolic processes. Transmitted from parents to children, these biological blueprints are our original inheritance: they carry biologically significant information across generations.

From time to time, genes undergo mutations, unexpected changes in their composition.  These can range from errors in copying (transcription errors) to those caused by external factors such as exposure to radiation or harmful chemicals. Many mutations have no adverse effect because genes with minor differences in chemical composition often end up coding for the same protein (and thus have the same function as the originals). Such mutations do not change the information content of the genes.

 Sometimes, though, a mutation can change the information content (and hence the function) of a gene.  Some of these information errors will be caught and fixed up by corrective mechanisms that function like spellcheckers – i.e. they read the “words” encoded in the gene and compare them to a dictionary, fixing up minor information errors as they go along. Occasionally, however, an error will not be caught by these spellcheckers.  Some of these errors can end up being manifested as abnormal metabolic processes. One such abnormal process is uncontrolled cell division – aka cancer.

A family of well-studied mutations are associated with the BRCA1 and BRCA2 genes which relate to a person’s chance of developing BReast CAncer.  These are tumour suppressor genes – i.e.  they help fix DNA errors that can lead to uncontrolled growth of breast and ovarian tumours.   It is therefore not surprising that certain mutations in these genes can lead to an increased lifetime risk of developing these cancers. Moreover, the loss of tumour suppression mechanisms in affected individuals implies that secondary cancer cells that migrate to other organs have a greater chance of proliferating unchecked.

Sydney, Apr 2020

A friend and I were talking about the virus over Zoom. “There’s the disease, which is a problem,” I said at one point, “and then there’s all the misinformation about it.” This was around the time #toiletpaperapocalypse and other collective insanities were doing the rounds.

“Yes,” he replied, “and it is hard to tell which of the two is a bigger problem: the former requires physical proximity for transmission, the latter can go viral the world over in a matter of minutes. Technology seems far more effective at amplifying stupidity over intelligence.”

Whatever else it may be remembered for, 2020 will undoubtedly go down in our collective memory as the time of COVID. Now, a year on from the first reports of a “pneumonia of unknown origin” from Wuhan, the origins of the disease remain unclear.    The lack of knowledge spawned several conspiracy theories, which seem to gain significantly more traction than reasoned arguments based on facts and evidence.

Why is this so? 

Peddlers of quack cures and those who downplay the dangers of the disease tend frame their messages as certainties; on the other hand, when scientists talk about their findings, they speak in tentative terms, emphasising the uncertainties.  It is the nature of science that findings are provisional and subject to revision. Unfortunately, in times of trouble, however, humans tend to prefer simplistic narratives that reinforce their beliefs over provisional facts based on evidence and reasoning. The latter are difficult for people to accept because they a) are complex and hard to understand, b) lack a compelling narrative, and c) may point to uncomfortable truths.

It is an irony of the human condition that when they matter most, facts and evidence tend to be trumped by beliefs.  This is not new; it has always been so. What is different now is the ease with which information can spread, aided by social media. Moreover, since these new technologies lack the ability to distinguish fact from fiction, information pathologies propagate at rates that were simply not possible before. The term information metastasis is an appropriate description of this process. It is indeed akin to a cancer.

Epilogue

Sydney, Dec 2020

The medications that coursed through her bloodstream were designed to stop cancer cells from multiplying.  Although the chemicals preferentially affected cancer cells, healthy ones were not entirely unaffected. Consequently, as the treatment progressed, she suffered a number of side effects, both physical and mental.

She saw the connection between her condition and the drama that was unfolding in the wider world. In particular, she understood that response to change provokes further change in a continuing dialogue of stimulus and response. Change, as the cliché goes, is the only constant, but differences between the purposes of the actors in the drama meant there would be no tidy resolution, only ongoing mutual adaptation.

In time she learned to read and respond to the signals from her body, resting when she sensed a wave of fatigue coming or talking to friends when a cloud of depression threatened. In doing so, imperceptibly yet inexorably, her relationship to the world around  her changed. It was neither better nor worse, it was simply different. She knew it had to be so.

–x–

Written by K

December 9, 2020 at 6:44 am

Collaborative reasoning in the age of Covid

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Ever since the start of the pandemic, there have been no end of opinions, presentations and reports on how we might navigate our way out of the crisis. Much of this takes a narrow, discipline-centric view, which is inadequate because the problem is multifaceted and thus defies traditional disciplinary boundaries. It is therefore of urgent importance to chart a course that considers all aspects of recovery, not just those relevant to specific interests.  A recent report produced by the Australian Group of Eight does just that.   The key points of the report are concisely described in an executive summary and snapshot, so I will cover just the main points in this article. My focus instead is on the platform used to create the report, as it offers an effective collaborative approach to tackling complex issues in a broad range of contexts.

To me the most amazing thing about the 192-page report is that it was produced by a taskforce comprised of over a hundred academics and researchers across diverse disciplines, collaborating over a three-week period. As stated in the exec summary:

To chart a Roadmap to Recovery we convened a group of over a hundred of the country’s leading epidemiologists, infectious disease consultants, public health specialists, healthcare professionals, mental health and well-being practitioners, indigenous scholars, communications and behaviour change experts, ethicists, philosophers, political scientists, economists and business scholars from the Group of Eight (Go8) universities. The group developed this Roadmap in less than three weeks, through remote meetings and a special collaborative reasoning platform, in the context of a rapidly changing pandemic.

Those who have done any collaborative work involving large groups will have stories to tell about how challenging it is to get a coherent result.  This taskforce achieved this in part by working on an online collaborative reasoning platform called SWARM, described in this paper.  This post is mainly about what SWARM is and how it works, but I will also describe how the Roadmap taskforce used the platform to come up with a comprehensive recovery plan and the key recommendations made therein. I’ll end with some thoughts on the use of SWARM in broader organizational and business contexts.

The SWARM platform

The platform was designed and implemented by a team led by Drs. Tim van Gelder and Richard de Rozario as part of a large Intelligence Advanced Research Projects Activity (IARPA) initiative. In essence,  SWARM is a cloud collaboration environment designed to enhance evidence-based reasoning in teams. It does this by supporting an approach called contending analyses, wherein team members produce and refine multiple distinct analyses of a problem, and then select the best one as their collective response.

On SWARM, team members create artefacts that represent their reasoning. Additionally, they can rate, comment on and contribute to artefacts created by others through the course of the challenge. This enables a “best response” to emerge through an iterative process of discussion, refinement and evaluation.

To understand how it works, it is necessary to briefly describe the various ways in which users can interact and contribute to solving the problem with each other in SWARM. The user interface of the SWARM platform consists of three panes (Figure 1).

Figure 1: SWARM user interface

 

The left pane contains the problem description and links to related documents. In the centre pane, users can post and update responses. A response may be a Resource (e.g. a link to an external article, a visualisation or an analysis) that contributes to understanding or solving the problem, or it may be a Report, which is a draft candidate for the team’s final output. Users can then comment on and rate others’ responses and comments. The most highly rated Report at the conclusion of the problem is submitted as the result of the group’s collaborative reasoning.

The right pane is a streaming chat window through which users can interact in real-time. To summarise, SWARM users can:

  1. converse with team members via the chat feed.
  2. post or update a Resource or a Report
  3. comment on a Resource or a Report, or
  4. rate a Resource, Report or Comment.

By design, SWARM does not prescribe (or proscribe) any particular analytical process. As van Gelder, de Rozario and Sinnott (2018, pp. 22-34) note, contending analyses:

…promotes engagement by providing the opportunity for any participant to contribute their own thinking (autonomy), to think in a manner matching their natural expertise (mastery or competence), and to earn the respect of others by drafting a well-regarded response (relatedness)’ – thus meeting each of the three psychological needs identified by self-determination theory.

The idea is that teams should be free to work in ways that suit them collectively, with individuals given the choice to contribute as and when they please. That said, SWARM, via its Lens Kit (https://lenskit.atlassian.net/wiki/spaces/LK/overview), offers participants a compendium of structured analytical techniques and other “logical lenses” that may be useful in analysing complex and uncertain scenarios in which the available information is scarce or  ambiguous.

The Roadmap to Recovery project

The Roadmap project involved over a hundred academics from the Group of Eight – a coalition of the oldest, largest and most research-intensive Australian universities. Over three weeks in April 2020, the team worked on developing scenarios for national recovery from the COVID crisis. Their recommendations are available in a comprehensive report.  The report is unique in that it synthesises the knowledge of a range of experts and takes a systemic, evidence-based view of the problem.  In the words of the co-chairs of the project:

How this document differs from the hundreds of articles and opinion pieces on this issue is that this report specifies the evidence on which it is based, it is produced by researchers who are experts and leaders in their area, and it engages the broadest range of disciplines – from mathematicians, to virologists, to philosophers.

Over a three-week period, this taskforce has debated and discussed, disagreed, and agreed, edited and revised its work over weekdays and holidays, Good Friday and Easter. All remotely. All with social distancing…

…It is research collaboration in action – a collective expression of a belief that expert research can help Government plot the best path forward…

Given the wide geographical distribution of the team and the requirement for social distancing, it was clear that the team needed an online collaboration platform that enabled collective deliberation. Traditional online methods would not have worked for a group this large. As noted in the report:

Standard remote collaboration methods, such as circulating drafts by email, have many drawbacks such as the difficulty of keeping track of document versions, integrating edits and comments on many different versions, and ensuring that everyone can see the latest version. It seemed clear this approach would struggle with an expert group as large as the Roadmap Task Force.

The steering committee therefore decided to give SWARM a go.

As noted in the previous section, SWARM works on the principle that a group should canvas multiple approaches and then collectively settle on the best one, a principle summarised by the term contending analyses. The benefit of such an approach is evident in the report in that it outlines two distinct strategies for recovery:

  1. Elimination: as the term suggests, this strategy aims at eliminating the virus within the country. This is the lowest risk approach and is technically feasible for a relatively isolated country like Australia. However, the cost in terms of time, effort and money is substantial. Moreover, a strict implementation of this approach would bar international travel for an unrealistically long duration.
  2. Controlled Adaptation: this involves controlling the infection within the country to a level that does not overwhelm the healthcare system. This is less expensive in terms of time, effort and money, but the outcome is also less certain. However, as the taskforce points out, this could lead to restrictions being eased as early as May 15th, a choice that the government had made before the report was released. This decision is understandable given the cost of extended restrictions; however, it isn’t clear at all how they will handle the inevitable resurgence of the disease down the line. The report considers how things could develop as a result of this decision.

The report aims to provide a balanced case for the two options, and also emphasises that in terms of implementation, the options have considerable overlap. For instance, there are three requirements for the success of either:

  1. Early detection and supported isolation
  2. Travel and border restrictions.
  3. Public trust, transparency and civic engagement.

It should be clear that all three require massive government involvement and support. To this end, the taskforce has formulated an ethical framework that should guide government decision-making and policy. The framework comprises of the following six principles:

  1. Democratic accountability and the protection of civil liberties.
  2. Equal access to healthcare and social welfare.
  3. Shared economic sacrifice.
  4. Attentiveness to the distinctive patterns of disadvantage.
  5. Enhancing social well-being and mental health.
  6. Partnership and shared responsibility

An ethical framework should serve as a check on policy-making that might disadvantage specific groups. If followed, the six principles listed above will ensure that policies are fair to all sections of the community, both in terms of burdens and benefits This is perhaps the trickiest part of policy-making.

Finally, the taskforce has formulated six imperatives (essential rules) that should guide the actual implementation of a recovery. They are:

  1. The health of our healthcare system and its workers.
  2. Preparing for relaxation of social distancing.
  3. Mental health and wellbeing for all.
  4. The care of indigenous Australians.
  5. Equity of access and outcomes in health support.
  6. Clarity of communication.

Each of the above requirements, ethical principles and rules for action are unpacked in detail in the full report and summarised in the executive brief.

How the project unfolded

The Roadmap process was a bold experiment. The Group of Eight had never attempted to pull together such a large report, with so many participants and diverse perspectives, in such a short time, and where no face-to-face meeting was possible. The SWARM platform, still a research prototype, had never previously been used to address a real problem, let alone a problem of this scale and importance.

The project had a steering committee consisting of the project chairs, Professor Shitij Kapur and Go8 CEO Vicki Thomson, and two reasoning experts from the Hunt Lab, Drs. Tim van Gelder and Richard de Rozario.  The committee proposed a project design which would involve two weeks working on the SWARM platform, followed by a week of off-platform final report drafting by a small group from the Go8. The two weeks on SWARM would involve the panel of experts working on 9 major topics, corresponding to the anticipated major sections of the final report, such as “How and when to relax social distancing.” It was expected that the experts would distribute themselves across the topics, with “emergent teams” coalescing to work on producing a draft report for each section. Week 1 on SWARM would be mostly “exploratory” thinking, with panelists mostly posting Resources, comments and chat. Week 2 would be mostly “synthetic” thinking, with emergent teams posting early draft Reports for each topic, and collaboratively refining the most promising drafts. In Week 3, these draft section reports would be integrated into a single overall final report.

The steering committee planned to closely monitor progress over the first two weeks and, if/as necessary, modify the process. The project did unfold largely as planned, but the steering committee had to intervene mid-late in the second week when it was apparent that some topics lacked emergent teams with “critical mass,” and in some cases even where critical mass had developed, the teams needed some guidance and prodding to deliver an adequate section report. At this point, the committee, and in particular one of the Chairs, Shitij Kapur, convened a series of zoom meetings meetings the emergent teams, and developed with them a plan for finalising their section reports. From that point on, most work on the draft section reports was done, over just a few days, using more traditional collaboration techniques, such as as circulating a Word document and communicating by email.

Thus, as things turned out, the process was a novel hybrid of a pure SWARM platform-based approach, and more standard methods. The steering committee were committed from the outset to expediency in getting the intended result (a high-quality final report) rather than being “purist” about the approach being used. The use of more traditional collaboration tools and methods later in the process, was driven by a number factors, including some limitations in the SWARM platform (most importantly, the lack of a “track changes” function in the platform’s document editor), and the natural tendency for people to revert to habits and reflexive behaviours when under great pressure.  It was clear, however, that the SWARM platform played a crucial role in the first half, allowing participants range across all topics, share lots of ideas and discussion, form emergent teams, and at least start drafting reports.

Whither collaborative reasoning?

The Roadmap project highlights the value of collaborative reasoning platforms like SWARM. It is therefore appropriate to close with a few thoughts on how such platforms can help organisations build internal capability to deal with complex issues that they confront – for example, developing a strategy in an uncertain environment (such as the one we are in currently).

The first point to note is that such problems require stakeholders with diverse viewpoints and skills to work collaboratively to craft a solution. Long-time readers of this blog will know that I advocate tools like Issue-Based Information System (IBIS) to help such groups reach a consensus on problem definition, and thus settle issues around “Are we solving the right problem?” or “How should we approach this issue?” However, once the problem is defined by consensus, the group needs to solve it. This is where platforms like SWARM are particularly useful.

Although SWARM was designed for the intelligence community, the Roadmap  project shows that it can be used in other settings. As another example, Tim van Gelder notes  that citizen intelligence (where ordinary citizens collaborate on solving intelligence problems) is becoming a thing, but lacks a marketplace. As a possible solution, he envisages the creation of a Kaggle-like platform for complex problems (rather than data problems). He notes that there are challenges around setting up such platforms, but there is interest from large private (non-intelligence) organisations. New deployments of the platform are already underway.

The problems organisations confront in the post-Covid world will be more complex than ever before. There are those who believe such problems will yield to computational approaches that rely primarily on vast quantities of data.  However, complex situations cannot be characterised by data alone, so computational approaches will need to be augmented by human sensemaking and reasoning. The success of the Roadmap to Recovery project demonstrates that platforms like SWARM can help organisations tackle such problems by harnessing the power of collaborative reasoning.

Note: For more information on SWARM, please visit the Hunt Lab for Intelligence Research.

Acknowledgement: My thanks to Dr. Tim van Gelder for reviewing a draft version of this article and for contributing the section on how the project unfolded.

Written by K

May 26, 2020 at 8:39 am

The worth of an education – a metalogue

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To be prepared against surprise is to be trained. To be prepared for surprise is to be educated.” – James Carse in Finite and Infinite Games.

Prospective student: How much do your students earn after they graduate?

Teacher: I’m sorry, I don’t know.

Prospective student: What do you mean? Don’t you keep track of what students do after they complete the program?

Teacher: Yes, we do, but we don’t ask them how much they earn. It is not the kind of question one asks….

Prospective student:  I know that, but shouldn’t you be gathering hard data on outcomes?

Teacher:  Of course, and we gather a range of data including the roles they get on graduation and how they progress in their careers.

Prospective student:  OK, but that doesn’t help me. How do I know that your degree is worth the hefty fees you charge?  If I’m investing that much, I must be sure of a decent return.

Teacher:  One cannot be certain about anything in life, there are never any guarantees. However, it’s perfectly reasonable to expect value from your education, so let me ask you – what would you consider a decent return?

Prospective student:   Hmm, a good job, I guess.

Teacher: Well, you heard from some of our alumni this evening.  They are currently employed as professionals in the field, and most of them got their jobs while studying or soon after completing their degree.

Prospective student: Yes, but you are unlikely to invite those who would say negative things about the program or those who have failed to get jobs.

Teacher: Fair enough, there are a few of those.

Prospective student: Well, that’s just my point. How do I know it will work for me?

Teacher:  You don’t!  Getting a job is an indirect effect of a good education.

Prospective student: I’m not sure I follow.

Teacher: An analogy might help clarify what I mean by indirect, Bill Gates did not become a multi-billionaire by setting out to become one. He became one by following his interests, his passion.

Prospective student: [a tad irritated] I still don’t get it.

Teacher: The objective of education is not to train you for a vocation…although, if you do things right, you are almost certain to get a job, and a good one at that. The aim of education is personal transformation, to broaden your perspective and thus enable you to look anew at the things you do at work and, possibly, even in life. Another aim is to prepare you to become that buzzword: a lifelong learner. No university can teach you those things, but they can help you learn them.

Prospective student: “personal transformation” sounds wonderful but terribly vague. Could you give me an example?

Teacher: Well, you’ve just heard from a few of our alumni and I could tell you many more stories. The thing is, I don’t think it is helpful to hear second-hand stories – their journeys are theirs, not yours. The story I’m interested in right now is yours: what you’re thinking, what you do and where you want to go.

Prospective student: OK. I’m a financial analyst [Editor’s note: feel free to substitute your current profession here] and I want to be a data scientist. Will this course enable me to become one?

Teacher: It could, but whether or not it actually does depends largely on you.

Prospective student: That’s not an answer.

Teacher: It is, and it’s an honest one. No course will make you a data scientist. And if any university tells you they can, they’re lying. What a good university course will do is help you learn the technical and non-technical skills that will enable you to become a data scientist.  Whether you learn or not depends on you. The responsibility for your personal transformation lies largely with you. All we can do is show you the way.

Prospective student: so, do you cover … [student recites a litany of data science languages and techniques].

Teacher: Yes, we cover them.

Prospective student:  Won’t doing those make me a data scientist?

Teacher: No. If tech skills are all you are after, I’d strongly suggest you don’t join our program…or any other university program for that matter. Instead, head off to one of the good online data science education providers and save yourself a whole lot of money.

Prospective student: Huh?

Teacher:  A good face-to-face program at a university covers a whole lot more than tech. For example, there are certain tacit skills and dispositions that are critical to becoming a good data scientist. These skills have to do with problem finding rather than technical adeptness or problem solving.  A good university course will give you opportunities to gain experience in doing that.

Prospective student; Problem finding? What’s that?

Teacher: In university assignments you’re given readymade problems that you can go off and solve. In real life, however, you are rarely given a problem. More often, you are presented with a situation from which you must extract or formulate a problem before you solve it. That’s not always a straightforward process because every situation is unique in its details.

Prospective student: If every situation is unique then there is no formula to deal with it.

Teacher: Exactly! These skills have to be taught indirectly – by putting students in safe-to-fail situations in which they can learn how to deal with the ambiguity inherent in them

Prospective student: But won’t that be throwing students into a situation they’re unprepared for.

Teacher: Although they may not admit it, most consultants – even experienced ones – rarely feel totally in control when dealing with new clients. It’s good to experience that kind of ambiguity early in one’s career, even if it is a second career. Every consulting engagement is a learning experience. This ties in with what I mentioned earlier – becoming a lifelong learner.

Prospective student: So how do you prepare students to deal with these types of scenarios?

Teacher: Through carefully crafted technical and non-technical subjects, with assignments that make them think rather than just do. To do well in the assignments you will have to think things through, try different approaches and even make judgement calls.

Prospective student: Judgement calls?

Teacher:  Yes, that’s right. You will find that the biggest issues when doing data science in the real world are not technical, rather they are about dealing with ambiguous situations in which you don’t have a well-defined problem or adequate data.  Then there are ethical issues that are becoming ever more important today. There are big corporations that completely ignore the ethical implications of what they do. Just because you can do something, it doesn’t mean you should.  All these issues involve judgement calls in which data is of little or no help.

Prospective student: Hmm, I didn’t realise there were so many facets to being a data scientist. Thanks, you’ve given something to think about.

Teacher: No worries…and good luck, I hope you find what you’re looking for.

 

 

Afterword:

HR gurus and consultants continually pontificate about the future of work. The ground reality for many mid-career professionals is that the future of their work is highly uncertain, much of the uncertainty being fuelled by the perception that data-related technologies are going to “disrupt” established industries. Among other things, this has led to an unprecedented demand for courses that teach data-related skills.

What is often left unsaid, however, is the transition to data science – or any profession for that matter – involves more than just picking up technical skills. The biggest missing piece (in my opinion) is the ability to make sense of ambiguous situations. This is a tacit skill that is difficult, if not impossible, to teach but can be learnt given the right environment and attitude. The university ought to provide the environment, the student the attitude.

Note: A metalogue is a dialogue that unfolds in such a way that the structure of the conversation turns out to be illustrative of the issue being discussed. The anthropologist Gregory Bateson coined the term.  Here is a metalogue written by him.

Written by K

February 18, 2020 at 5:40 am

Posted in Metalogues, Organizations, sensemaking

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