I am currently trying to figure out how to spend the next semester – I have no courses to teach (for once), plenty of sabbatical time banked up, and a need to get seriously up to speed not just on the current state of tech evolution, but also on putting things in perspective.
So this (hat tip to Bjørn Olstad) podcast was a great inspiration:
This is an extremely wide ranging conversation (more than two hours) and fascinating in many dimensions, not least the way these guys communicate. It reminds me of a passage in Cryptonomicon where Waterhouse (the elder) and Turing communicate by “[…not] talking so much as mentioning certain ideas and then leaving the other to work through the implications. This is a highly efficient way to communicate; it eliminates much of the redundancy […]”. This is done at roughly 1.6x of normal conversation speed and is a delight for someone whose mind tend to wander off when things get too slow.
It also shows that much changes, but much is also the same – for instance, anyone building tools will inevitably discuss the tools they use to build those tools, and I get flashbacks to hearing Eric Raymond discuss key bindings in EMACS or Don Knuth explaining why he built TeK. LLMs, to me, is not so much something revolutionary as the next evolutionary step in our way of interacting with information – we still have work to do on the reward mechanisms, for instance, and we need to figure out a way of asserting scientific authority, so that the most popular and important LLM-based clones will be that of Steven Pinker rather than Steve Bannon. Which actually is kind of important.
Anyway, I really like the vision of building real tutors – and finding the distillation algorithm that matches the explanation to the student, whether you are learning for fun or immediate use.
Digression: As a first-year student, I was given a book of microeconomics, which tried to explain marginal cost through an elaborate example of someone growing tomatoes and selling them, wordily going through pages of text discussing the cost implications of adding another plant, etc. I read and reread it and felt my head swimming, then found a footnote after about 10 pages saying: “For those who have had calculus, the marginal cost is the derivative of the cost function.” I thought “Well, why didn’t you say so right away?” Building a tools that condenses formulaic academic papers into brilliant lunch table explanations – one of the many ideas in this interview – seems to me both a very worthy vision and a method for doing something about the academic research process, where the medium very much has become, if not the message, and least the reward mechanism.
Oh well. But it would be fun to assign this interview for my tech strat course next year – it would go over the head of many students, but for some of them, it would be a great inspiration.
And as a teacher, that is the most you can aspire to, methinks.
Time for some reflection after having designed and taught the new EMM (Executive Master of Management) course “The Value-Creating Board”, arranged for the first time in the fall of 2024.
The course has been a pleasure to develop and teach. As of today, BI has a number of basic management courses, either alone or in collaboration with institutions such as the Norwegian Confederation of Trade Unions (NHO) or the Norwegian Agricultural Cooperative. With the change in Norwegian law requiring at least 40% of each gender on boards – which will require around 10,000 new, female board members – it was natural to offer a board member course within BI’s Executive Master of Management program, which already has a high proportion of women.
When I develop courses, I do not start from a subject area, but rather from a description of “that”jobs” the student should be able to perform when the course is completed. I wanted to train people who could participate in boards of directors for developing companies, where the board’s role is both to have control over what is happening and to ensure focus on strategy and the future. In pedagogy, this is called ” constructive alignment ” – that is, you develop courses and teaching materials based on what is important for the students to learn (the learning objectives), not based on what you yourself want to lecture on or what is common within the subject area.
There are some things you just can’t avoid in a board course. You need to have something about legal matters – you can never escape board responsibility, and the Companies Act gives the board mandates and tasks that are not to be avoided. As I tell my students: Legal matters are not important until they are, at which point they are all that matters. You also need to have some financial knowledge – it doesn’t help to tell the Bankruptcy Court or the Tax Directorate that you’re not that good at (or interested in) accounting when your equity has evaporated. The rest is a mix of strategy, management and understanding external changes, such as new technology, the almost exploding AI, and ESG reporting and integration).
People who recruit for boards look for two things: management experience and domain knowledge. Both are knowledge areas where you can learn some principles and frameworks through textbooks, but in a board context you have to be able to put things into practice, and then you should have experience using the knowledge, not just reproducing it.
What should the course include?
Given that a board course can be everything and nothing – because the board is responsible for the entire company, without the mandate to go into the details – I chose to define the content of the course by recruiting a great team , who then contributed what they knew best.
The most important person to recruit was definitely Berit Svendsen , who I wanted as a development partner and co-teacher. Berit is the former CEO of Telenor Norway, and as extensive experience as a top manager, board member and chairperson. Berit has been present for most of the course, has contributed with comments, presentations, guidance and not least by letting me draw on her fantastic network. To top it all, she was named Board Chair of the year during the course, which certainly provides unmatched legitimacy!
I found the rest of the team at BI: Thomas Borgen, former CEO of Danske Bank and Board Chair of Kongsberg Digital, contributed his experience and network of contacts both as a senior manager and board member, as well as interesting lectures on the role of the board in strategy execution and risk management. Tore Bråthen, perhaps Norway’s foremost authority on corporate law, contributed his unparalleled legal expertise on board responsibilities, as well as a thorough and reflective perspective on what the new sustainability regulation entails. And Ketil Hveding contributed the basic, but oh so important economic understanding and a perspective on the challenges of small and medium-sized enterprises. Ketil also plays a key role in taking things from BI’s existing management course into this course. I also look forward to taking some of what we – and the students – have worked on and using it to enrich the courses we already have. And not least: I asked nicely to have Mari Berg Henie as the course coordinator – she is not just structured and knowledgeable, but also the koordinator of my other Exec courses, which makes life considerably easier for all involved.
Otherwise, the course has drawn on a great set of guest speakers, both to provide a grounded perspective on what it means to sit on a value-creating board, but also to lay a foundation for further development of the course: It is only when you hear from those who have the shoes on that you know what is important and relevant. (Constructive alignment, again…).
Guest speakers have been:
Eivind Reiten, who spoke about the relationship with the owners. Eivind is the chairman of the board of directors of, among others, the Kongsberg group and one of Norway’s most experienced board and business leaders. His perspective on how to relate to owners – he has been widely criticized because he does not want to take dictation from state owners – was particularly interesting because he based his argument not on politics, but on the Norwegian Companies Act, which states that one cannot treat owners differently, and that a claim from an owner, however large, requires a decision from a general assembly. He taught the students that the board has decision-making authority that must be used on behalf of all “stakeholders” of a company, not just owners.
Gyrid Skalleberg Ingerø is a former CFO of Telenor and the Kongsberg Group and an extremely experienced board member. She shared her vast experience, very concretely, about what one should and should not do as a valuable board member, down to details about how to stay updated on competitors, industry and technology, how to handle conflicting interests, finances, and risk. Not least, she gave good advice on what to think about if you are offered a board position, including the risks it entails (and which are rarely talked about).
Øystein Moan, former CEO and now working chairman of the Visma Group, participated in a webinar from his new home in Switzerland, and spoke about Visma’s development, strategy and his role as working chairman (a role that is quite unusual in Norway, at least for larger companies.) He demonstrated how strategy formulation, learning and execution in a long-term perspective yields results – and provided good perspectives from a corporate strategic view, for instance by having interlocking board memberships for subsidiaries, seen from a board and senior management perspective.
Jan-Erik Hareid, founder and managing partner of the early growth stage venture capital company Alliance Venture, spoke about the phases of a company’s development and what you look for in board members in the different phases. He gave the investor perspective, and talked a lot about the importance of recruiting and following up on the people who will actually develop companies.
Thomas Evensen is CEO of OrgBrain , which is both a scale-up company (and thus interesting with the board challenges that entails), but also a company providing a digital platform for board work. This gives him first-hand insight into the many dilemmas that boards of directors in small and medium-sized companies have to deal with. And he gave us just that: What is happening in small companies, what do they have to deal with – and how can they recruit and use board members when they have fewer resources (people and money) to do things formally?
Case as term paper
Board work is, in my view, basically problem-solving, best learned through solving many problems and eventually developing an ability to recognize things and apply experience from one problem to another. I use case teaching to teach the students this – but there are not many cases about board work today, either internationally or in Norway. That is why I have chosen to let the students’ project assignments be to create cases – find a business that is facing a challenge where the board must get involved, the problem is complicated, and there are several alternative measures to choose from.
The students have responded very well, I must say, and the case list looks like this:
a nationally critical internet and telecom provider that experiences an outage of half of its capacity, possibly due to sabotage, and must figure out the board’s role before, during and after such an event.
a small IT services company struggling with growth in a tight financial situation, having to consider both professionalizing the board and management, and using co-ownership to recruit and retain the right resources.
a manufacturing company, the cornerstone of a small community, that is experiencing a weak economy and that the corporation that owns them is starting to talk about closing it down.
a trading company in the cosmetics and wellness sector that sees new competitors on the horizon, and must consider whether the incumbent board – consisting of old friends – and strategy are appropriate in a world where things are not as easy and pleasant anymore.
a family-owned manufacturing company that finds their newly appointed general manager – with extensive experience in the company – resigning his position to move to a newly established competitor, on significantly better terms.
a small, independent bank that must consider whether it is possible to continue as a small, independent and local business in a world where new, costly requirements for reporting and resource use (sustainability, anti-money laundering, cybersecurity) are constantly increasing and can more easily be borne by a larger business or through an alliance.
A small specialist healthcare provider that must decide whether to be a non-profit or a commercial enterprise, with the organizational and cultural changes that will entail. The situation creates a divided board, and the chairman must navigate a complicated landscape.
A water park started as a public-private partnership must balance between the stock market and the cathedral: Should it focus on commercial activity or continue a riskier existence as a primary public welfare service?
A company developing electric aircraft must make difficult strategic choices in relation to technology development, investors, and the market situation.
A company that provides infrastructure services must consider that some of their employees (and employees within subcontractor companies) may be classified as a security risk because they come from certain countries, or have family members who do. The board and management must consider what measures can be taken, balancing national security considerations with employee rights.
A small company that has developed a software system is struggling to get out of the “valley of death,” a situation that is not made any easier by insisting that it is in a scale-up phase without having profitable customers. A potential chairperson must decide whether this is something to invest in or not – and whether to take the position at all.
Exam
In addition to the cases, I have – for the first time in many years – held a “closed book” exam, where students come in, take an exam without aids (they use PCs with a locked browser.) I don’t like traditional exams – they are expensive, the pedagogical effect is debatable, and they introduce possible complications (students who for some reason cannot get to the exam venue, technical difficulties, etc.) and unnecessary stress. However, BI is obliged to maintain some control over whether the students – individually – have actually learned something. Group assignments introduce the possibility of free riders, home exams can be solved by ChatGPT and other large language models.
So, exam it was. I chose to make it with relatively simple and clear questions, about key topics in the course (“What does it mean that equity has been lost, and what is the board’s responsibility in such a situation”). The purpose of an exam is simply to check that the students have understood the main points of the course, not to get bogged down in esoteric details. That is why I also plan for the students to be given a certain number (5, this time) of questions, of which they will have to answer a smaller number (this time 4). This prevents the student from sitting there and not remembering some detail or another and feeling crushed because of it.
Further development
Post-implementation, we have found the course content to be fairly complete – no haven’t found any major gaps in the curriculum or things that absolutely should have been included. If anything, we should perhaps have more about companies in development phases, something about board membership remuneration and opportunities to use stock options and other mechanisms for adjusting goals and incentives for the board and management. We should also have more practical information about sustainability and sustainability reporting, and also something more about how a board should relate to and actually do before and in a bankruptcy situation. Theory-wise, we could have had more about principal-agent issues (in addition to discussions about corporate governance), but the theoretical apparatus there often ends up in situations that are relatively esoteric from a Norwegian perspective.
The most important element will be to develop learning activities that allow students to gain some form of experience of board work and board assessments. I believe in case teaching, and several of the cases described above have the potential to become very good teaching cases, which are in short supply. The process around writing the cases (which I will continue) could be tightened up and better documented.
The course will next be held in the fall of 2025. Some feedback from students is on LinkedIn ( here , here , here and here , for example.)
I’m really looking forward to the next time – and if you need good board members, I have many good candidates to offer!
— is the title of a talk I will give for EGN internasjonal this Thursday May 27. at 0900-1000 Central European time. The talk (which will be a conversation between me and the CEO of EGN Group, Jonatan Persson) will be about why Tesla may be a threat to large parts of the car industry, including a dive into just what the real difference (according to me) is between Tesla and the more traditional car manufacturers (electric or not.)
The webinar is open for anyone interested – you will find a description here and registration here.
Last year (with Chandler Johnson and Alessandra Luzzi) and this year (with Chandler, Jadwiga Supryn and Prakash Raj Paudel), I teach a course called Analytics for Strategic Management. In this course executive students work on real projects for real companies, applying various forms of machine learning (big data, analytics, whatever you want to call it) to business problems. Here is a list (mostly anonymised, except for public organizations) list from this year:
One group wants to use machine learning to predict fraud in public security contracts in a developing country
A credit agency wants to predict which of their customers will pay their bills by the end of the month
An engineering company wants to predict the number of hours needed to meet demand for each month in each department
One group wants to predict housing prices within Oslo, to help house sellers get a realistic estimate of what their property is worth
A higher education provider wants to predict which students are likely to fail or not qualify for an exam, to be able to intervene early
A couple of municipalities want to predict who will accept a kindergarten allocation or not
A telecommunications company wants to predict which customers will churn
An Internet product company wants to predict necessary capacity for picking and shipping work every day
One group wants to predict the likelihood of a road closing due to bad weather, in order to warn truck drivers so they can detour
One group wants to predict the future financial health of companies based on employee engagement numbers
One group wants to predict efficiency of production in a wind power park
And last year we had these projects:
An investment company wanted to predict bankruptcies from media events
Ruter, Oslo’s public transportation authority wanted to predict the number of passengers (for each station, to great precision) for one line on the metro
A telecommunications company wanted to predict customer feedback scores from analyzing customer interactions (so the customer does not have to answer a survey afterwards)
The Norwegian Health directorate wanted to predict general physician “fastlege” churn
A commercial TV station wanted to predict subscriber churn
An insurance company wants to identify customers likely to buy a group insurance package
An online gaming company wanted to predict customer churn
A large political party wanted to predict membership churn
One group wanted to start a company based on using machine learning to diagnose hearing problems
A large retail chain wanted to predict churn based on customer purchase patterns
At BI Norwegian Business School, we are (naturally and way overdue, but a virus crisis helps) moving all exams to digital. This means a lot of changes for people who have not done that before. One particular anxiety is cheating – normally not a problem in the subjects I teach (case- and problem oriented, master/executive, small classes) but certainly is an issue in large classes at the bachelor level, where many answers are easily found online, the students are many, and the subjects introductory in nature.
Here are some strategies to deal with this:
Have an academic honesty policy and have the students sign it as part of the exam. This to make them aware of they risk if they cheat.
Keep the exam time short – three hours at the max – and deliberately ask more questions than usual. This makes for less time for cheating (by collaborating) because collaboration takes time. It also means introducing more differentiation between the students – if just a few students manage to answer all questions, those are the A candidates. Obviously, you need to adjust the grade scale somewhat (you can’t expect all to answer everything) and there is an issue of awarding students that are good at taking exams at the expense of deep learning, but that is the way of all exams.
Don’t ask the obvious questions, especially not those asked on previous exams. Sorry, no reuse. Or perhaps a little bit (it is a tiring time.)
Tell the students that all answers will be subjected to an automated plagiarism check. Whether this is true or not, does not matter – plagiarism checkers are somewhat unreliable, have many false positives, and require a lot of afterwork – but just the threat will eliminate much cheating. (Personally, I look for cleverly crafted answers and Google them, amazing what shows up…).
Tell the students that after the written exam, they can be called in for an oral exam where they will need to show how they got their answers (if it is a single-answer, mathematically oriented course) or answer more detailed questions (if it is a more analysis- or literature oriented course). Who gets called in (via videoconference) will be partially random and partially based on suspicion. Failing the orals results in failing the course.
When you write the questions: If applicable, Google them, look at the most common results, and deliberately reshape the questions so that the answer is not one of those.
Use an example for the students to discuss/calculate, preferably one that is fresh from a news source or from a deliberately obscure academic article they have not seen before.
Consider giving sub-groups of students different numbers to work from – either automatically (different questions allocated through the exam system) or by having questions like “If your student ID ends in an even number (0,2,4,6,8) answer question 2a, otherwise answer question 2b” (use the student ID, not “birthday in January, February, March…” as this will be the only marker you have.) The questions may have the same problem, but with small, unimportant differences such as names, coefficients or others. This makes it much harder to collaborate for the students. (If you do multiple questions in an electronic context, I assume a number of the tools will have functionality for changing the order of the questions – it would, frankly, astonish me if they did not – but I don’t use multiple choice myself, so I don’t know.
Consider telling the students they will all get different problems (as discussed above) but not doing it. It still will prevent a lot of cheating simply because the students believe they all have different problems and act accordingly.
If you have essay questions, ask the students to pick a portion of them and answer them. I do this on all my exams anyway – give the students 6 questions with short (150 words) answers and ask them to pick 4 and answer only those, and give them 2 or 3 longer questions (400 words or so) and ask them to answer only one. (Make it clear that answering them all will result in only the first answered will be considered.) Again, this makes cheating harder.
Lastly: You can’t eliminate cheating in regular, physical exams, so don’t think you can do it in online exams. But you certainly can increase the disincentives to do so, and that is the most you can hope for.
Department for future ideas
I have always wanted to use machine learning for grading exams. At BI, we have some exams with 6000 candidates writing textual answers. Grading this surely must constitute cruel and unusual punishment. With my eminent colleague Chandler Johnson I tried to start a project where we would have graders grade 1000 of these exams, then use text recognition and other tools, build an ML model and use that to grade the rest. Worth an experiment, surely. The project (like many other ideas) never took off, largely because of difficulties of getting the data, but perhaps this situation will make it possible.
Last Thursday, I was supposed to teach a class on technology strategy for a bachelor program at the University of Oslo. That class has been delayed for a week and (obviously) moved online. I thought about doing it video conference, but why not make a video, ask the students to see it before class? Then I can run the class interactively, discussing the readings and the video rather than spending my time talking into a screen. Recording a video is more work, but the result is reusable in other contexts, which is why I did it in English, not Norwegian. The result is here:
To my teaching colleagues: The stuff in the middle is probably not interesting – see the first two and the last five minutes for pointers to teaching and video editing.
For the rest, here is a short table of contents (with approximate time stamps):
0:00 – 2:00 Intro, some details about recording the video etc.
2:00 – 27:30 Why technology evolution is important, and an overview of technology innovation/evolution processes
6:00 – 9:45 Standard engineering
9:45 – 12:50 Invention
12:50 – 15:50 Structural deepening
15:50 – 17:00 Emerging (general) technology
17:00 – 19:45 Substitution
19:45 – 25:00 Expansion, including dominant design
31:30 – 31:45 BREAK! (Stop the video and get some coffee…)
31:45 – 49:40 Disruption
31:45 – 38:05 Introduction and theory
38:05 – 44:00 Excavator example
44:00 – 46:00 Hairdresser example
47:00 – 47:35 Characteristics of disruptive innovations
47:35 – 49:40 Defensive strategies
49:40 – 53:00 Things take time – production and teaching…
53:00 – 54:30 Fun stuff
This is not the first time I have recorded videos, by any means, but it is the first time I have created one for “serious” use, where I try to edit it to be reasonably professional. Some reflections on the process:
This is a talk I have given many times, so I did not need to prepare the content much – mainly select some slides. for a normal course, I would use two-three hours to go through the first 30 minutes of this video – I use much deeper examples and interact with the students, have them come up with other examples and so on. The disruption part typically takes 1-2 hours, plus at least one hour on a specific case (such as the steel production). Now the format forces me into straight presentation, as well as a lot of simplification – perhaps too much. I aim to focus on some specifics in the discussion with the students.
I find that I say lots of things wrong, skip some important points, forget to put emphasis on other points. That is irritating, but this is straight recording, not a documentary, where I would storyboard things, film everything in short snippets, use videos more, and think about every second. I wanted to do this quickly, and then I just have to learn not to be irritated at small details.
That being said, this is a major time sink. The video is about 55 minutes long. Recording took about two hours (including a lot of fiddling with equipment and a couple of breaks). Editing the first 30 minutes of the video took two hours, another hour and a half for the disruption part (mainly because by then I was tired, said a number of unnecessary things that I had to remove.)
Using the iPad to be able to draw turned out not to be very helpful in this case, it complicated things quite a bit. Apple’s SideCar is still a bit unpredictable, and for changing the slides or the little drawing on the slides I did, a mouse would have been enough.
Having my daughter as audience helps, until I have trained myself to look constantly into the camera. Taping a picture of her or another family member to the camera would probably work almost as well, with practice. (She has heard all my stories before…)
When recording with a smartphone, put it in flight mode so you don’t get phone calls while recording (as I did.) Incidentally, there are apps out there that allow you to use the iPhone as a camera connected to the PC with a cable, but I have not tested them. It is easy to transfer the video with AirPlay, anyway.
The sound is recorded in two microphones (the iPhone and a Røde wireless mic.) I found that it got “fatter” if I used both the tracks, so I did that, but it does sometime screw up the preview function in Camtasia (though not the finished product). That would also have captured both my voice and my daughter’s (though she did not ask any questions during the recording, except on the outtakes.)
One great aspect of recording a video is that you can fix errors – just pause and repeat whatever you were going to say, and the cut it in editing. I also used video overlays to correct errors in some slides, and annotations to correct when I said anything wrong (such as repeatedly saying “functional deepening” instead of “structural deepening”.) It does take, time, however…
My excellent colleague Ragnvald Sannes pointed out that this is indicative of how teaching will work in the future, from a work (and remuneration) perspective. We will spend much more time making the content, and less time giving it. This, at the very least, means that teachers can no longer be paid based on the number of hours spent teaching – or that we need to redefine what teaching means…
I have come to learn that there are no boring industries – one always finds something interesting in what at first may looks fairly mundane. And that is something I am trying to teach my students, as well.
Andrew Camarata is a young man who works for himself with excavators, bulldozers, gravel, stone, earthworks and so on. He lives and runs his business in the Hudson Valley just south of Albany, New York and in the winter he does, among a lot of other things, snow plowing.
In this video, he will tell you almost everything there is to know about how to plow snow commercially in rural United States and make money from it.
The interesting point about this video (and a lot of other videos he has made, he has a great following on Youtube) is that he provides a very thorough understanding of business design: In the video, he talks about acquiring and maintaining resources, understanding customers (some are easy, others difficult, you need to deal with both), administration and budgeting, ethics (when to plow, when not to), and risk reduction (add the most complicated jobs with the greatest risk of destroying equipment last in the job queue, to reduce the consequences of breakdowns).
For a business student, this is not a bad introduction to business, and Camarata is certainly a competent businessman. In fact, I see nothing here that is not applicable in any industry.
When it also comes in a pedagogically and visually excellent package, what’s not to like?
David Trafford and Peter Boggis are those kinds of under-the-radar strategy consultants that ever so discreetly (and dare I say, in their inimitable British way) travel the world, advising enormous companies most civilians have never heard of about such issues as how to organise your internal departments so that they are capable of responding to technical change. (I should know, because I worked with them, first in CSC and then in the Concours Group, between 1994 and 2009.)
Now David and Peter have begot a book, Beyond Default, that provides a perspective on strategy and organisational change less built on fashionable frameworks than on solid experience. Their focus is on how organisations fail to see changes in their environment and develop strategies – real strategies – to adapt to them. The reasons are many, but most important is the fact that organisations have developed processes and measures to do what they currently do, and the focus on those particulars does not permit stepping back and seeing the bigger picture. Instead, companies carry on towards a “default” future – and, crucially, that future may be declining. Companies need to know what they don’t know and what they do not have the capabilities to do – and to acquire those capabilities when necessary. To do that, the authors advocate experiential learning – seeing for yourself what the future looks like by seeking it out, preferably as a group of managers from the same organisation experiencing and reflecting together.
The authors have a background as IT consultants, and it shows: They very much think of organisations as designed systems, with operating practices and (ideally) articulated operating principles. While eminently logical, this way of organising is hard to do – among other things, it requires thinking about organisations as tools for a purpose, and that purpose has to be articulated in a way that gives direction to its members. Thinking about your principles can make you articulate purpose, but it is very hard not to make the whole process a bit self-referential. Perhaps the key, like for Newton’s second law of thermodynamics, is to keep adding external energy, constantly identifying and understanding ramifications of technical and other change – a process that requires energy, if nothing else.
Both authors care about language and explaining and discussing what happens in a way that can be understood by the organisations they are trying to help. This means that they primarily use examples and stories, rather than frameworks (beyond simple illustrations), to convey their points. They end each chapter with a set of questions the reader can has him- or herself about the organisations they manage – and do not, in any way, try to offer simple solutions. As such, the book works best when it talks about how to explain strategic necessities and start on a strategic journey – through collective leadership, not “great man” charisma. It works less well when trying to explain strategic analysis, perhaps because the authors have too much experience to settle on a simple, all-encompassing method.
Well worth the read, not least for the senior executive trying to understand a new world and wanting an explanation held in a language that fosters understanding rather than just excitement.
(Notes from an Executive Short Program called Digitalization for Growth and Innovation, hosted by Ragnvald Sannes and yours truly, in Sophia Antipolis right now.Disclaimer: These are my notes, I am writing fast and might get something wrong, so nothing official by Accenture or anyone else.)
Cyrille Bataller is a managing director and the domain lead for Intelligent Computing, with the Emerging Technology group at Accenture. He leads Accenture’s exploration of the Cognitive Computing field
Cognitive Computing
Skilled work increasingly done by machines – doctors, lawyers, traders, professors etc. Large potential impact, also societal, but exciting new technology. Cognitive computing is IT systems that can sense, comprehend and act – and are perhaps the most disruptive technology on the horizon. They can interact with their environment, learn by training instead of coding, and can analyse and use enormous amounts of data. The quest for cognitive computing has a long history – and has had a varied history, with periods of advances and periods of setbacks, or at least less interest. We differentiate between “strong” AI – achieving consciousness – and “weak AI” – having the machine mimic certain capabilities of humans.
Accenture’s ambition has been to create a toolbox of cognitive computing capabilities under a single architecture, such as text analytics, research assistants, image analysis, multimedia search, cognitive robots, virtual agents, expert systems, video analytics, identity analytics, speech analytics, data visualisation, domain-specific calculations, recommendation systems and self-adjusting IT systems. These are all examples of human traits and capabilities as well…
Some detail – image analysis is about deep learning, using neural networks to mimic how the brain works. Use layers of increasingly complex rules to categorize complex shapes such as faces or animals. In one case, they used neural networks to recognize and classify images of cars as undamaged, some damage or totalled to an accuracy of 90%. By applying text analysis as well, this could be used by an insurance company to analyze insurance claims. Google has acquired a company called DeepMind to look at images on the web, eventually recognizing cats.
Another example is use of robotics in business operations – from minibots, companies such as XL and AutoHotKey to automate application software, to standard robots to using virtual assistants to do user support, for instance. You can have a team of robots in the cloud to work alongside your real back office. These robots can observe and learn and gradually take over or optimize these activities, such as updating documents (powerpoints, for instance). Could be used to observe how an accountant works, for instance, and issue certification based on following proper procedures. You could have 20-30 people in the back office and 100s of robots learning from them and doing the regular stuff.
Virtual agents: Amelia, handling a missing invoice situation. Amelia can understand, learn and solve problems. Generates a flowchart which can then be optimized and analyzed.
Video analytics is another application that is receiving lots of attention. One problem with CCTV videos is that they are almost only used forensically – checking a certain date and time – because nobody has time to watch the videos themselves. Can be used to count cars and recognize events, measure queuing times at customs and immigration, measure service times, monitor for lost objects on a train, analyze the age distribution on public transport, detect emotions, understand the hot and cold zones in the shopping center, find leaks in an industrial setting, etc.
The following framework (from the perspective document referenced below) shows a four-quadrant framework that can help guide companies in choosing the approach towards cognitive computing:
Last year (with Chandler Johnson and Alessandra Luzzi) and this year (with Chandler, Jadwiga Supryn and Prakash Raj Paudel), I teach a course called 
Applied Abstractions 