Category Archives: Academically speaking

Computational thinking notes

Grady_BoochNotes from Grady Booch‘ presentation on Computational Thinking, and ACM Webinar, February 3, 2016 (4617 people attended, in case you wondered.)

Note: This is real-time notetaking/thought-jotting. Lots of errors and misrepresentations. Deal with it.

This will be a different way of thinking – and perhaps to think differently about the profession of software development. Recommends Yuval Harari Sapiens, talks of the cognitive revolution, the agricultural revolution, the scientific revolution. Babbage as citizen scientist, begin to see a new way of thinking: Computational thought. Boole had a similar set of ideas, took it from mechanization to laws of thought – tries to investigate the operations of the mind by which reasoning is done.

I can’t shoe a horse, but can build a 3D rendering of one, and then produce a virtual horse in Avatar. Why? Our ways of thinking addresses what is necessary to survive in the world we live in. We have different relationship to time: With the cognitive revolution, we had slow ways of measuring time, such as seasons, the scientific revolution gave us theories of time – and a frantic obsession with ever smaller measures of time. If the ways of thinking we had in previous lives where appropriate then, what are the ways we should think now?

Jeanette Wing – introduced computational thinking in CACM: Computational thinking as the thought processes that are involved in formulating a problem and expressing a solution in a way so that a computer – human or machine – can carry it out. To be able to do that will be increasingly important to succeed in today’s world – it will help you shape the world and live in this world.

Computing started out as human computers (mostly women), then a gradual mechanization and, indeed, industrialization of computing with ever more rigid processes, eventually digitalization of it (via punch cards). Businesses gradually starting to reshape itself as a result of computational thinking – and businesses changing computation. Sciences beginning to use computational thinking. Around WWII it also began to change the ways we went to and won wars. (Again, many women, see the documentary “Top Secret Rosies“.) The computational thinking drove our imagination beyond what the computers could do, beyond what we do in the present.

In the 60s and 70s, computational thinking started to reshape society – but it was compartmentalized – the “programming priesthood.” The SAGE was one of the first personal computers, example of interfaces learning from war. Largest systems of its kind, forced us forward in UI, hardware and software. The 360 and others broke computational thinking out of the chosen few – Margaret Hamilton coined “software engineering”. Finally personal with the PC – representing a state change. omtroducing devices that forced people to think in computational ways, forcing us to adapt to the machine. Current state: Outsourcing part of our brains to smartphones – computers that happen to have an app for dialing – computational going from numerical to symbolic to imaginatined realities. Computational thinking is beginning to erode our thinking about old imagined realities, such as governments and organizations.

I think the idea of the singularity is fundamentally stupid – when and if it comes, we will have become computers ourselves anyway, according to Rodney Brooks. This forces us to think about what it is to be human. How does computational thinking change how we look at the world.

In terms of software development, the changes has been from mathematical to symbolic to imagined realities. We are not only building imagined realities, but stepping inside them and living in them.

The fundamental premise of science is that the cosmos is understandable; the fundamentalt premise of our domain is that the cosmos is computable. We enter the world with the understanding that anything we can dream, we can compute.

Gödel taught us that there are things that are unknowable, but that does not diminish the importance of scientific thinking. There are similar things that are uncomputable, the computational thinking is still powerful and can push the world forward. The scientific process suggest that we have a trajectory towards a simplified, standard model. In computation, we go the other way: Start with something simple and make it incredibly complex.

What does it mean to see the world as computable? The first assumption is that the cosmos is discrete, or at least computationally finite. I can make reasonable assumptions about reality that means I can do powerful things. It may not be totally, but near enough that it is useful.

Secondly, I assume the world is based on information, which means I can look at the world through data. DNA and cellular mechanisms can be computed. The lens of information allows us to derive powerful theories. The dark side what is happening in CRISPR, genetic manipulation without knowing the consequences. Incredible power but incredible responsibility.

Third, data is an abstraction of reality. We can use all these powerful tools, but in the end we are building an abstraction of the world. Can build them and begin to rely upon them, but the other side of computational thinking realizes that this is not reality, it is just our view of it. A model is a model.

We use algorithms to form abstractions, but now can hand over without waiting, because we can depend on our ability to generate an algorithm to represent the world. Look at BabyX, from University of Auckland.

The importance of scale, from Feynman‘s Room at the bottom article. But we can also build imaginary realities that are larger than the universe itself. Computing is universal – can be used everywhere, spreads to any manifestation of execution: computational physics, chemistry, biology, psychology, sociology … and gradually computational philosophy. Has spread itself in ways that has changed everything – but maybe this way of thinking is just the threshold of the next way of thinking?

The earliest ways of thinking evolved as a means of bringing more certainty and predictability to an uncertain and unpredictable world. Scientific thinking evoleved to understand the world. Computational thinking has evolved as a means of controlling the world at a level of fidelity once reserved for gods.

Computational thinking has changed how we look at the world. That is to be celebrated, and we should encourage non-programmers to understand how it works. But let’s not forget what it means to be human in this world.

Some questions:

  • Are we falling into the “modelling the world in terms of current technology” trap? Yes, let us be self-aware of the limits of this thinking. We are assuming that evolution is computation on DNA, but it is only an abstraction – what if there is something wrong and it is not the correct model. BTW: Nick Bostrom and intelligence – I disagree that computation can create life, but lets explore it.
  • How does new forms of teamwork (as with email) change our ability to solve problems? Not a sociologist, but fascinating that the same social structures show up in our imagined worlds. 10K years out? Don’t know, but some adaptation may have happened. No matter what, we need trust – the degree of trust forms the basis for any organization and what you can do with it. I believe that anything we do in this space is shaped by human need.
  • What about genetic programming – will computers be able of compuational thinking? First off – computers write their own programs now, including manipulating their environment. But most of the stuff in neural networks is dealing with the perception side of the world, we can’t go meta on those neural networks. Second – is the mind computable? Yes, I believe it is, but see one of the computing documentary we are making.
  • Can computing create art with meaning? Listen to the classical pianist Emily Howell, but Emily is an algorithm. Computers can create art, but we create our own meaning.
  • Does outsourcing your brain to smartphones inhibit our ability to do computational thinking. See Sherry Turkle, it does change our brain, refactors it. It is a dance between us and our devices, and that will continue for a long time.

Recording will be at learning.acm.org/webinar.

 

The Facebook method of dealing with complexity

Computer systems used to be weak, so we had to make their world simple and standardized. They now can handle almost endless complexity—but we still need to understand how to make the world simple, so we don’t risk burdening the majority of users with the needless complexity of the few. One way of doing this is to adopt Facebook’s approach of “Yes, No and It’s Complicated.”

Read the rest of the essay at ACM Ubiquity’s blog.

The future of Norwegian education, if we only dared

If Norway marketed itself more effectively, they could suck the brightest and best students from the UK and America, improve their universities reputation and force the UK and US to rethink their education policies for the benefit of the people in all the countries concerned.

This from the excellent blog post “What caused you to move to Norway, Sir?” by Paul Beaumont.

I certainly think Norwegian universities could do just that. When it doesn’t happen, it is largely because of provincial thinking and lack of marketing acumen. This needs to change.

That is all.

The Double from toy to tool

There is a lot of writing about how computers (in this case, referred to as “robots”) will take over the role of the teacher (as well as many other jobs) these days. I have my own robot, from Double Robotics, and it is gradually becoming a tool rather than a toy – and it allows me to extend my reach, rather than automate my job. Granted, so far it has mainly been used for experiments and demonstrations (below, a picture from a meeting of an ICT industry organisation in Norway) but better access and a few technology upgrades have made it much more reliable and gradually into something that is useful rather than just fun.

The practical issues with the Double have been numerous, but have largely been solved. Here they are:

  • The Double required a lot of manual intervention before I could use it – specifically, it was in my office, and the department administrator would have to unlock my office and unplug it to let it out. This was solved by acquiring a docking station and positioning the Double out in the public area of my department (next to the mailboxes, as it happens.) I was worried that someone would make away with it (or steal the iPad) but both are password protected and besides, the department requires an ID card to get in. This has also meant that other department members can use the Double – one colleague has severe allergies and has to go to his mountain cabin for several weeks in the spring every year, he used the Double to attend seminars.
  • The speaker and microphone did not work well. Out of the box, the Double uses the speaker and mike from the iPad. The speaker was too weak, and the iPad microphone picks up too much noise as well as conversations all around rather than what is in front of you. Initially, I solved the speaker problem by using a Bluetooth speaker, but it was on a separate charger and did not work very well. Double Robotics came up with an Audio Kit upgrade which largely has solved the problem – I can now generate enough clear sound that I can use the Double for lecturing, and the directional mike filters out some of the noise and ambient conversations to make communication much more natural.
  • Thirdly, the iPad will sometimes go offline because of interruptions, chiefly because of software updates. This means it will not be able to set up a connection, and needs a manual restart. This was fixed by running the Double app in a Guided Access mode (found under Settings>General>Accessibility>Guided Access), a way of setting the iPad to only run one app only, uninterrupted by software upgrades, messages and other distractions.
  • Fourth, the sound sometimes disappears on the iPad altogether. This may actually be a physical problem (it has been banged about a bit, and the metal part behind the sound buttons is a weak spot), but was fixed by allowing the physical sound controls to be run in Guided Access mode, and then asking whoever I was talking to to turn up the sound if necessary.
  • Fifth and last, the wi-fi connection drops for about 30 seconds every time I go from one wireless router to the next, which happens all the time in our large office building. I solved this by using the cell connection instead. It still has dead spots some places in the building (despite our telecom vendor, NetCom, being headquartered very close to us) but I am beginning to know where they are. It is also solvable by setting up a VLAN, something that requires cooperation from the IT department and which I haven’t gotten around to quite yet.

All in all, I am beginning to find the Double a useful tool. Next time I am invited to speak on TV, I’ll consider sending it down to the studio in a taxi, just to see the reaction. Like many digital solutions, true productivity does not come until everything is digital – for instance, i wanted to use the Double for an early meeting with students last week, but found I couldn’t do it because the door to the department would be locked and there was no way I could unlock it remotely. So I ended up going in for the FTF meeting anyway, even if it was the only thing I needed to be in the office for that day.

A second observation is that the Double elicits all kinds of thoughtful (and less thoughtful) comments from grown-ups, mainly along the lines of how surprisingly natural this is but how traditional face to face is better, alienation etc. etc. The younger element takes to it naturally – my cousin’s eight year old daughter, seeing her Dad in the Double, responded with a “Hi Dad” as the most natural thing in the world.

And thirdly – one obvious use of the Double would be to ship it to wherever I am supposed to be, so I can give a talk remotely. I gave a talk in Bordeaux two days ago. Bordeaux is complicated to get to from Oslo, and the trip ended up taking three days. I could have sent the Double, but a) I think my physical presence helped the talk, and b) the Double has a large lithium-ion battery, and you can’t ship those on airplanes. Consequently, the Double is a tool for making me stay in place while moving about, rather than the other way around.

A BI degree for expats!

The Executive Master of Management degree is now offered in English at BI Norwegian Business School – just the thing for the ambitious expat!

BI Norwegian Business School has a very popular executive education degree called the Executive Master of Management. The school offers a range of EMM courses, each lasting about a year and consisting of 5-6 modules of 3-4 days each. Put together three of these courses (with some exceptions) and you have a degree. (Well,there are a few other requirements, such as one of the courses taken with a slightly more substantial thesis, You can take more than one course concurrently, though I think taking more than two would be pushing it, at least if you have a job as well).

I like teaching in these courses (especially one called Strategisk Forretningsutvikling og Innovasjon), but they have, so far, required you to be able to speak Norwegian (with the exception of International Management.) From this fall, however, we have created two more courses taught in English, so that you now can qualify for the degree without having to learn Norwegian.

The courses are

I hope this troika will be an attractive package to foreigners in Norway (as a matter of fact, I have been arguing for this for some time, and am very pleased that it is now available) – so if you know someone living and/or working in Norway who are in the market for a relevant and interesting executive business degree, please alert them to this opportunity!

Trapping the wily professor

(This was published in European Business Forum, BCG’s attempt to create their own version of the Harvard Business Review, in 2004. Issue 19, to be exact. Reproduced here, lightly edited, because, well, it is very hard to find and I would like to make it available.)

Trapping the wily professor
A hunting guide for the enterprising executive

Espen Andersen, 2004

Recently, I attended a meeting of senior HR executives – primarily CLOs (Chief Learning Officers) – from large European companies. The participants were all engaged in designing and/or running various forms of management training and education in their companies, and a discussion about how to deal with outside suppliers – particularly business schools – came up. A key problem, it transpired, was getting the good professors to engage in company programs. While the schools were more than willing to sell their branded and packaged programs, most corporations wanted something tailor-made, designed to achieve a specific corporate learning goal. Furthermore, they wanted it tailor-made by the big names – that is, the professors the students were likely to know. This had proved very difficult. These were big, prestigious companies – why couldn’t they get the big, prestigious professors?

Coming from the supply side of this relationship, can see the difficulties these managers have – so I herewith offer a little guide to hunting down and keeping that rarest of animals, the business-savvy and interesting professor. A warning, though: This is not a task to be approached lightly. Hunting requires knowledge of the prey itself, its living environment, and its reward structures. It requires patience and a keen sense of observation, as well as an ability to communicate with the natives – or at least not to offend them too much.

First: Hunt professors on your turf, not theirs. The best place to hunt for professors is not through the business school sales channels. Instead, invite the professor to come into your company to give a short talk on some very specific point of interest – half an hour is fine – at some small executive meeting, with lunch and informal discussions thereafter. Pay the professor for the presentation. If there is no chemistry, you have listened to a (hopefully) interesting presentation and the professor has made a little money and is likely to think of your company with benevolence. Incidentally, the best referrers of professors are other professors – so use the occasion to extend your network. Carefully cultivated, most professors will come when you call and leave you alone when you want them to.

Second: Avoid the obvious blunders. This should go without saying, so the experienced professor-hunter may want to disregard this paragraph. However, any high-powered and dynamic business executive can unknowingly scare away the wily professor without meaning to – the equivalent of putting on aftershave before the hunt and then wondering why you never see any prey. Professors are academics, and you hunt them because they are. Consequently, never use the word “academic” to mean “irrelevant”, “hypothetical” or “impractical”. Never refer to them as “educators” (in academic cynical parlance, an “educator” is someone forced to live by teaching and writing readable articles because he or she can’t do research and write unreadable articles.) And never – never ever – ask them to include that interesting best-seller (“Who drank my café latte?”) you saw in the airport bookshop to their syllabus. Professors are extremely jealous of outside intellectual competition, and anyone preferring the Heathrow School of Management to them is treated with extreme suspicion, if not outright hostility.

Third: Don’t devolve problems to intermediaries. Typically, the CLO seeking a management education program interacts with a relationship manager from the business school. This person is pleasant, nicely attired and means well, will sell you the standard programs and tell you what you want to hear, but is incapable of trapping the wily professor on your behalf. If you want a program out of the ordinary, talk to the person most critical for its success – and that better be the professor, because if program responsibility lies with the salesperson, you are in trouble. That being said, the school’s relationship manager is very useful as a support person – so let your own support person deal with him or her, and make sure that the minute any content issues spring up, the problem is escalated to you – and the professor. (And, by corollary, don’t fall into the trap of becoming an intermediary yourself, as when a business colleague needs a program and asks you to set it up.)

Fourth: Ask not what the professor can do for you, but what you can do for the professor. Professors are not motivated by money. Actually, that is a whopping big lie – they certainly are, but it needs to come in a form palatable to the world they inhabit. Doing executive education does not help a professor in his or her career – at best, it earns him or her non-tradable brownie points for helping the school. What counts in the academic hierarchy – at least officially – is publishing what to the layman appears as unreadable articles in obscure journals read by few and remembered by even fewer. These articles are created through back-breaking work and qualified through an evaluation process that makes Purgatory feel like a day at the beach. To do the work, the professor needs money, in the form of research grants. To get through the evaluation, he or she needs data, obtained by getting access to corporations. If you can give the professors research money and access to data (i.e., your company,) they will happily create executive education programs as part of the research process. They will even teach them. (It is possible to bag a few professors through money alone, primarily the younger ones, but on a repeated basis this will yield a lower quality of prey).

Fifth: It is not what you say, it is what you do. The above will attract and retain professors, but will not earn their undying love. To achieve that, you need to follow through and do what they say. Professors seeing their theories listened to and applied will do anything you ask of them – sit on your Board, talk to your executives, co-write career-enhancing articles with you in trade magazines and even listen to your suggestions for making their theories better. The danger herein lies in that you may go native yourself – and what a tragedy that would be.

So there you are – to bag a professor, start by wining and dining them, paying them for a small presentation, then lure them with money and access to provide you with tailor-made and interesting executive programs. It is easy. You can start now. My email is here.

How to write a teaching case

I am currently – with colleagues Mikael Lönnborg and Gerhard Schjelderup – editing what we hope to be a book of Scandinavian teaching cases. In a meeting in Stockholm recently, I was asked to explain what it takes to write a teaching case. I gave my opinion, we had a very interesting discussion. Here is my (very rough and off the cuff) opinion about what it takes (in reality, how a teaching case differs from a research case).

Why are you writing this case?
Cases are written for a teaching purpose – and to write a teaching case, you need to have a teaching objective in mind. It is not enough to have an interesting company. Even the best company story needs to have a pedagogical point, a theory or dilemma to illustrate. So don’t write a teaching case just because you happen to know someone in a really interesting company – it does need to be a good story, but it also need to have a purpose.

The standard outline
Cases – particularly the standard HBS case – follow an outline that can seem rather trite, but which is very effective. It is something like this:

  • 0.5 page: Intro: The protagonist is introduced, typically pondering a question of some importance. The idea is to tell the students from which perspective the case is written, to set the scene – and that is all there is to it.
  • 1 – 1.5 pages: Description of the company – not the whole history, but the relevant details, explaining what the company is doing, how they make their money. Most companies are to a very large degree formed by their history, so the relevant parts need to be told.
  • 1 page: Industry. Companies exist within a context, and you need to set it. Explain the industry, its evolution, and the company’s position within it. Do it succinctly, but leave more detail in than what is strictly necessary.
  • 1 – 5 pages: Specific issue. This is the meat of the case, the issue at hand, the story to ponder. Make sure you tell it logically and cooly, not leaving anything out, but also conveying the complexity of the situation.
  • 0.5 page: Conclusion, typically with the protagonist wondering what to do, often with some sort of event (board meeting, etc.) where he or she has to present a solution to the problem.

Most cases are just that – one case. You can have a B case and even a C case, but keep them short, since they have to be handed out and read in class. The B case should explain what the company did and perhaps introduce a new problem, the C case, if necessary, should bring some sort of closure, explaining what eventually happened. In my experience, it is very hard to get discussion after a C case – the students become exhausted. As a novice case writer, especially if you are writing about a company with a long history, it can be tempting to create a long string of small cases, but in practice this seldom works well – for one thing, it forces the discussion into a very predictable path.

The no-nos
A good case should be a description of an interesting situation, frequently a decision point – and nothing else. This means that there should be no theory and no discussion of the case in the case itself. Save that for the teaching note, or write a separate academic article about it. Not only does this make the case more realistic, it also means it can be used for more purposes than the one initially envisioned. This can be quite challenging for the traditional academic writer – but ist is actually good practice to only present the facts (though, of course, which facts you choose to present constitute a discussion of sorts).

When teaching students how to analyze a case, I always start by saying that for most business situations, if is useful to begin the analysis with the assumption that people are not stupid and not evil. Consequently, when you write a case, make sure it has no heroes and no villains. If a case has a clear-cut hero or villain, it is a sign that you have not done enough research. Write things so that the students can see the issue from many perspectives.

Dramatic structure
A really well written case has dramatic structure – there is a beginning, a middle that builds up the story, and a really compelling issue at the end. The best cases are almost like a detective story, where you have to dig deep into the analysis to find surprising and sometimes counter-intuitive conclusions. One example of a “detective story” case is Fabritek 1992*, a very old (first published 1969, rewritten by Jan Hammond) case about a quality control issue in a small mechanical workshop. (Hat tip to Robert D. Austin, eminent case teacher, for making me aware of this case and showing me how to teach it.) The case is excellent because it starts with the company (strategic level), proceeds to describe a new situation and a new process (organizational or business logic level) and then introduces the problem (operational level.) Analyzing the operational details leads to one conclusions, which can then be discussed in terms the organization and its business logic, which can then be placed into a strategic context. The case is excellent because it allows links between these levels – and also teaches the students that the devil indeed resides in the details, and that you as a manager better be very close to how the business you are leading works and makes money.

iPremier-front-pageA second case which shows quality and innovation is iPremier, written by Robert D. Austin and Jeremy C. Short, the first and only graphic novel (cartoon) case I am aware of. The story is about a small online gift company being attacked by hackers, exposing glaring gaps in their security procedures and forcing managers at various levels to make some really hard decisions. The graphic format is excellent in making the various characters real (though they, on average, tend to be way too good-looking for a normal business situation), illustrates technical issues in a way that is very understandable even by non-technology students, and has a cracking good storyline with a B and a C case. I like to introduce a few technical cases in my courses because, well, I don’t think there is enough technology in business schools, and this cases answers very well because it illustrates that certain technical decisions very much require top management attention – ignore (or mindlessly delegate) technology understanding and responsibility at your peril. The graphic format also provides a welcome break from the standard case verbiage, which can be a trifle dour on occasion.

Details, details, details!
Research cases – the kind that is published in refereed journals – tend to be written from a very specific viewpoint, and only facts pertaining to that perspective is included, often in a very abstract format. A teaching case is the direct opposite: It needs lots of details, frequently made available as exhibits (graphs, pictures, documents, tables, etc.) placed at the end, after the main text. A teaching case writer, when visiting a company to write about it, needs to notice the small details, much like a really good journalist does. I tell my students that they should prepare each case so well that they feel like they have worked in the case company – and to allow them to do that, you need to provide the operational details necessary. (Incidentally, having more details than strictly necessary has the added benefit of making the case realistic – in the real world, you have to decide what is important and what is not.)

Doing it – and reading about it.
grandongillI am not aware of many books about how to write a good teaching case, with one exception: Grandon Gill (pictured), professor at University of South Florida and an excellent case teacher, has written a book called Informing with the case method, which is available for free download in PDF, MOBI and EPUB format from his web site. It has lots of details, tips and tricks, not just about case writing, but also about case teaching and course planning. (For the latter, of course, I am duty bound to recommend Bill Schiano’s and my book Teaching with Cases: A Practical Guide.)

Last but definitely not least: Don’t underestimate how much work writing a proper business case is. Getting the details right, describing the dramatis personae, and making the storyline compelling is quite a challenge, in many dimensions different from the traditional academic article. On the other hand, should you get it right, you will have a very effective teaching tool for many years to come.

Good luck!

ACM Ubiquity’s Singularity Symposium

ACM Ubiquity, of which I have the honor of serving as an Associate Editor for a number of years, has a symposium (a collection of essays around a theme) on the Technological Singularity. I have been the editor responsible for this one, and the essays are as follows (I’ll make these live links as they are published):

  1. Opening Statement by Espen Andersen
  2. The Singularity and the State of the Art in Artificial Intelligence by Ernest Davis, NYU
  3. Human Enhancement—The Way Ahead by Kevin Warwick, University of Reading
  4. Exponential Technology and The Singularity by Peter Cochrane
  5. Computers versus Humanity: Do we compete? by Liah Greenfeld and Mark Simes, Boston University
  6. What About an Unintelligent Singularity? by Peter J. Denning, Naval Postgraduate School, editor ACM Ubiqity
  7. Closing Statement: Reflections on A Singularity Symposium by Espen Andersen

You can read about the background for the symposium in my opening statement – but, in short, I could not get a clear and concise explanation of whether the singularity will happen (and when), so I set about getting a number of smart people to give their perspective. Enjoy!

Case teaching when you are not at Harvard

Our book is out!
bookcover2Bill Schiano and I have written a book, Teaching with Cases: A Practical Guide, officially launched today at Harvard Business Publishing, available as paperback or PDF (304 pages).

Bill and I are both passionate about case teaching and use it whenever possible. We have aimed the book at the kind of people we were 18 years ago: Teachers wanting to use case teaching, but finding ourselves in institutions where case teaching is not the dominant teaching method. (We actually wanted to name the book Case teaching when you are not at Harvard, but saner minds intervened.)

There are a few books on how to do case teaching available, but common to them is that they are a) rather philosophical and abstract in their advice, and b) take the institutional environment for granted – i.e., they assume that you are at a school, such as Harvard Business School, Wharton, INSEAD or University of Western Ontario, where case teaching is the norm, the students are brilliant and fiercely competitive, classrooms are made for case teaching and excellent teaching is valued by the administration (and the promotion committees.)

We wanted the book to be relentlessly practical – what to wear to class, how to deal with disruptive students, how to get students to prepare, how to grade participation. We also wanted the book to address how to create the necessary infrastructure for case teaching with little or no administrative support, down to how you create name cards (let the students do it or use a spreadsheet/mail-merge function) and class chart (take a photo of the students holding their name cards, print it in weak grayscale for after-class note-taking.)

The book is built around three concepts: Foundations (how to set up the course, contract with the students, and set up infrastructure); Flow (how to conduct the discussion in the classroom, manage time and boards, ask questions, and conclude discussions); and Feedback (how to design grading and feedback, especially participation grading.) We have extra chapters on dealing with difficult issues (much of it based on questions from participants in HBS’ case teaching seminars); how to teach quantitative and technical material; how to deal with differences in language and culture (foreign students and foreign teachers); how to prepare for the next course; how to foster case teaching at the school level (many business schools are now looking to better teaching, including case teaching, as a differentiator); and lastly, a long and detailed chapter on technologies for case teaching, including our views on how to teach cases online.

The book also includes a collection of online resources (sample syllabi, sample teaching plans, etc.) for teachers, available at teachingwithcases.hbsp.harvard.edu. We hope to grow this collection as we hear from readers and build more material ourselves.

That’s it for now – I’ll be back with excerpts, a full table of contents, and various other nuggets eventually. But given that this book has been on my mind for a couple of years now, it is a rather good day…

Elon, I want my data!

Last week I got a parking ticket. I stopped outside BI Norwegian Business School where I work, to run in and deliver some papers and pick up some computer equipment. There is a spot outside the school where you can stop for 10 minutes for deliveries. When I came out, I had a ticket, the attendant was nowhere in sight – and I am pretty sure I had not been there for 10 minutes. But how to prove that?

Then it dawned on me – I have a Tesla Model S, a very innovative car – not just because it is electric, but because it is constantly connected to the Internet and sold more as a service than a product (actually, sold as a very tight, proprietary-architecture product, much like whatever Apple is selling). Given that there is a great app where I can see the where the car is and how fast it is going, I should be able to get the log from Tesla and prove that I parked the car outside BI less than 10 minutes before the ticket was issued…

Well, not so fast. I called Tesla Norway and asked to see the log, and was politely turned down – they cannot give me the data (actually, they will not hand it over unless there is a court order, according to company policy.) A few emails back and forth have revealed that the location and speed data seen by the app is not kept by the internal system. But you can still find out what kind of driving has been done – as Elon Musk himself did when refuting a New York Times journalist’s bad review by showing that the journalist had driven the car harder and in different places than claimed. I could, for instance, use the data to find out precisely when I parked the car, even though I can’t show the location.

And this is where it gets interesting (and where I stop caring about the parking ticket and start caring about principles): Norway has a Personal Data Protection Act, which dictates that if a company is saving data about you, they not only have to tell you what they save, but you also have a “right of inspection” (something I confirmed with a quick call to the Norwegian Data Protection Authority). Furthermore, I am vice chairman of Digitalt Personvern,  an association working to repeal the EU data retention directive and know some of the best data privacy lawyers in Norway.

So I can probably set in motion a campaign to force Tesla Norway to give me access to my data, based on Norwegian law. Tesla’s policies may be American, but their Norwegian subsidiary has to obey Norwegian laws.

But I think I have a better idea: Why not, simply, ask Tesla to give me the data – not because I have a right to data generated by myself according to Norwegian law, but because it is a good business idea and also the Right Thing to do?

So, Elon Musk: Why not give us Tesla-owners direct access to our logs through the web site? We already have password-protected accounts there, storing documents and service information. I am sure some enterprising developer (come to think of it, I know a few myself, some with Teslas) will come up with some really cool and useful stuff to make use of the information, either as independent apps or via some sort of social media data pooling arrangement. While you are at it, how about an API?

Tesla has already shown that they understand business models and network externalities by doing such smart things as opening up their patent portfolio. The company is demonstrably nerdy – the stereo volume literally goes to 11. Now it is time to open up the data side – to make the car even more useful and personable.

PS: While I have your attention, could you please link the GPS to the pneumatic suspension, so I can set the car to automatically increase road clearance when I exit the highway onto the speed-bumpy road to my house? Being able to take snapshots with the reverse camera would be a nice hack as well, come to think of it. Thanks in advance! (And thanks for the Rdio, incidentally!)

Update a few hours later: Now on Boingboing!

Update Sept. 2: The parking company (Europark) dropped the ticket – didn’t give a reason, but probably not because I was parked too long but because I was making a delivery and could park there.

The disrupted history professor

Jill Lepore, Harvard HistorianProfessor Jill Lepore, chair of Harvard’s History and Literature program, has published an essay in the New Yorker, sharply critical of Clayton Christensen and his theory of disruptive innovations. The essay has generated quite some stir, including a rather head-shaking analysis by Will Oremus in Slate.

I find Lepore’s essay rather puzzling, and, quite frankly, unworthy of a professor of history, Harvard or not. At this point, I should say that I am not an unbiased observer here – clayClay is a personal friend of mine, we went through the doctoral program at Harvard Business School together (he started a year before me), he was on my thesis committee (having graduated three years ahead of me) and we have kept in touch, including him coming to Norway for a few visits and one family vacation including a great trip on Hurtigruten. Clay is commonly known as the “gentle giant” and one of the most considerate, open and thoughtful people I know, and seeing him subjected to vituperating commentary from morons quite frankly pains me.

Professor Lepore’s essay has one very valid point: Like any management idea, disruptive innovation is overapplied, with every technology company or web startup claiming that their offering is disruptive and therefore investment-worthy. As I previously have written: If a product is described as disruptive, it probably isn’t. A disruptive product is something your customers don’t care about, with worse performance than what you have, and with lower profit expectations. Why in the world would you want to describe your offering as disruptive?

That being said, professor Lepore’s (I will not call her Jill, because that seems to be a big issue for some people. But since I have met Clay (most recently last week, actually), I will refer to him as Clay)  essay shows some remarkable jumps to non-conclusions: She starts out with a very fine summary of what the theory of disruption says:

Christensen was interested in why companies fail. In his 1997 book, “The Innovator’s Dilemma,” he argued that, very often, it isn’t because their executives made bad decisions but because they made good decisions, the same kind of good decisions that had made those companies successful for decades. (The “innovator’s dilemma” is that “doing the right thing is the wrong thing.”) As Christensen saw it, the problem was the velocity of history, and it wasn’t so much a problem as a missed opportunity, like a plane that takes off without you, except that you didn’t even know there was a plane, and had wandered onto the airfield, which you thought was a meadow, and the plane ran you over during takeoff. Manufacturers of mainframe computers made good decisions about making and selling mainframe computers and devising important refinements to them in their R. & D. departments—“sustaining innovations,” Christensen called them—but, busy pleasing their mainframe customers, one tinker at a time, they missed what an entirely untapped customer wanted, personal computers, the market for which was created by what Christensen called “disruptive innovation”: the selling of a cheaper, poorer-quality product that initially reaches less profitable customers but eventually takes over and devours an entire industry.

She then goes on to say that the theory is mis- and overapplied, and I (and certainly Clay) couldn’t agree more. Everyone and their brother is on an innovation bandwagon and way too many consulting companies are peddling disruption just like they were peddling business process reengineering back in the nineties (I worked for CSC Index and caught the tail end of that mania. Following this, she points out that Clay’s work is based on cases (it is), is theory-building rather than theory-confirming (yep) and that you can find plenty of cases of things that were meant to be disruptive that weren’t, or companies that were disruptive but still didn’t succeed. All very well, though, I should say, much of this is addressed in Clay’s later books and various publications, including a special issue of Journal of Product Innovation Management.

(Curiously, she mentions that she has worked as an assistant to Michael Porter‘s assistant, apparently having a good time and seeing him as a real professor. She then goes on to criticise the theory of disruptive innovation as having no predictive power – but the framework that Porter is most famous for, the five forces, has no predictive power either: It is a very good way to describe the competitive situation in an industry by offers zero guidance as to what you actually should do if you are, say, in the airline industry, which scores very badly on all five dimensions. There is a current controversy between Clay and Michael Porter on where the Harvard Business School (and, by implication, business education in general) should go. The controversy is, according to Clay, mostly “ginned up” in order to make the Times article interesting, but I do wonder what professor Lepore’s stakes are here.)

The trouble with management ideas is that while they can be easily dismissed when commoditized and overapplied, most of them actually start out as very good ideas within their bounds. Lepore feels threatened by innovation, especially the disruptive kind, because it shows up both in her journalistic (she is a staff writer with the New Yorker) and academic career. I happen to think that the framework fits rather well in the newspaper industry, but then again, I have spent a lot of time with Schibsted, the only media company in the world that has managed to make it through the digital transition with top- and bottom-line growth, largely by applying Clay’s ideas. But for Lepore, innovation is a problem because it is a) unopposed by intellectuals, b) happening too fast, without giving said intellectuals time to think, and c) done by the wrong kind of people (that is, youngsters slouching on sofas, doing little work since most of their attention is spent on their insanely complicated coffee machines, which “look like dollhouse-size factories”.) I am reminded of “In the beginning…was the command line.”, Neal Stephenson‘s beautiful essay about technology and culture, where he points out that in

… the heyday of Communism and Socialism, [the] bourgeoisie were hated from both ends: by the proles, because they had all the money, and by the intelligentsia, because of their tendency to spend it on lawn ornaments.

And then Lepore turns bizarre, saying that disruptive innovation does not apply in journalism (and, by extention, academia) because “that doesn’t make them industries, which turn things into commodities and sell them for gain.” Apparently, newspapers and academia should be exempt from economic laws because, well, because they should. (I have had quite a few discussions with Norwegian publishing executives, who seem to think so for their industry, too.)

I think newspapers and academic institutions are industries – knowledge industries, operating in a knowledge economy, where things are very much turned into commodities these days, by rapidly advancing technology for generating, storing, finding and communicating information. The increased productivity of knowledge generation will mean that we will need fewer, but better, knowledge institutions. Some of the old ones will survive, even prosper. Some will be disrupted. Treating disruptive innovation as a myth certainly is one option, but I wish professor Lepore would base that decision on something more than what appears to be rhetorical comments, a not very careful reading of the real literature, and, quite frankly, wishful thinking.

But I guess time – if not the Times – will show us what happens in the future. As for disruption, I would rather be the disruptor than the disruptee. I would have less money and honor, but more fun. And I would get to write the epitaph.

But then again, I have an insanely complicated coffee machine. And now it is time to go and clean it.

Double!

Espen-Double

Here (photo: Lene Pettersen) is my last addition to my nerd kit: A Double from Double Robotics. I suppose this is formally defined as a telepresence robot, but a simpler way to describe it is to say that it is an iPad stuck on a Segway.

I spent most of Friday fiddling around with it, exploring what it can do. It is surprisingly natural in use: It can be raised (up to about five feet) and lowered, depending on whether you want to speak to someone standing or sitting. I drove it around the BI building, and quickly found that dead network spots (it needs a constant Internet connection to work) are problematic. Also, it is not very good at switching between routers on the same wireless network – it loses connection and needs a couple of minutes to find it again. I’ll probably have to get an iPad with a 4G connection, if such a thing exists (on the other hand, with a 4G connection I could send it out of the building and down the street.) Another problem was weak sound – in a room with other people speaking, the iPad speaker is too weak. I might have to get some small battery-powered speakers and Velcro them to the kit. elevators, doors and door sills, of course, are tricky.

Here are some pictures from a little excursion around the school library (photo: Martin Uteng, Instagrammed here.). A little tricky to talk to the students (again, not enough volume) and some network issues, but at least I am getting better at driving it:

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(Yes, this is actually research. And fun at work.) The use cases for a Double are several – I could advise students and go to meetings without leaving my home office, for instance. I have done that with Skype and other video conferencing tools for ages, but this thing is much less formal and allows you to putter around and talk to people. one of my colleagues has severe allergies and spends the spring as a pollen refugee in his mountain cabin – I am sure he would love to borrow it.

Compared to a picture on a computer or projection screen this little robot is much more intuitive and humanoid – you can see in which direction it is looking, for instance. I have been told that there are a bunch of these at Stanford, and that at first they were meant to be shared – but it turns out that people want their own, so they can personalize it as I have done with the ugliest bow tie I could find. My colleagues tell me it feels much more natural to speak to me through the Double than through Skype – it is almost as if I am there.

So, some technicalities left to resolve, but this has promise. I am already scheduled to give a talk through it, while I am in the States. And yes, I have already been compared to Sheldon Cooper of The Big Bang Theory. Several times…

Scandinavian cases: Call for abstracts

With two colleagues, Gerhard Schjelderup and Mikael Lönnborg, I am trying to create a case collection, to be published as a book. We start with a call for abstracts, with a deadline of June 9. You will find the details in this PDF document.

The main idea is simply to do something about the lack of available teaching cases on Scandinavian (or, for that matter, Nordic) companies. We want cases that are like HBS cases – no theory in the case, a thorough description of an interesting company with an interesting problem. Seems simple enough, no?

See you for the workshop on October 10!

MOOC and me: Reflections on a Coursera course

On April 10, I signed up for a course on network theory and analysis with professor Matthew Jackson of Stanford University. That was about one week into the course, which started April 1, so I will have to hurry to finish some of the assignments. The course is both a test in online coursing for me – not that I think I am at a stage where I should create on, but it could be interesting to try – and I chose this particular one because it is a field in which I have brushing knowledge (I have read Burt’s Structural Holes: The Social Structure of Competition, for instance) but never have systematically undertaken any training or done any math.

Signing up was very easy: Name, email address and a password, no cost, off we go. The web site is very simple, well, here we go. Estimated work 3-6 hours per week. Will see if I can make that, especially if I am blogging on the side…

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The course (at least the intro) is delivered with a set of slides and the instructor superimposed over them, using on-screen drawing (using a tablet pen, it looks like) drawing lines around or between concepts. The ability to speed up the presentation is useful – I can still follow it at 1.5x normal speed, and used that to rush through some of the examples I had heard before and some of the more self-explanatory slides. There are some problems with the transmission – occasionally, the screen will be garbled (especially when there is movement on the screen, such as the instructor drawing on the slides, which means that I will have to print out the slides for the next week’s lectures, when the formulas become more complicated. i will also have to start taking notes by hand, since my typed comments can’t keep up with the presentation when it comes to creating formulas and drawing diagrams.

The course uses open-source network software (Pajek) and the first homework assignment dealt with basic network attributes such as diameter, density, and average paths. Not too hard so far, but i have a graduate education from an English-speaking university and some intuitive understanding of the topic (plus experience in fiddling with software until it works, including screwing up the Pajek configuration and fixing it by simply erasing the config file and starting over.)

On the positive side, I might be just in the right market segment: Someone who is interested in the topic but does not have the time to sign up for a course in it. Wonder how many other academics there are out there who see MOOCs as a great way to update themselves on a related field…

I’ll be back with more observations in a few weeks, assuming I haven’t dropped out – which many students tend to do in these courses.

The political process of getting innovation done

Innovation is often about politics. Together with my excellent colleague Ragnvald Sannes I run a course called Strategic Business Development and Innovation (it is done in Norwegian, but if you are interested, we would be glad to export the concept, in English), where we take groups of students through an innovation process (with their own, very real, projects) over two semesters. The course is done in cooperation with Accenture’s Technology Lab in Sophia Antipolis and is one of the most enjoyable things I do as a teacher.

Anyway. This note is to discuss something which came up in a web conference today – the political side of doing innovation. Many of the students we have come from public organizations, from the health care industry, or from educational or research-based institutions. In all of them (well, actually, in all organizations, but more so in those where profit is not the yardstick that trumps everything) politics are important, to the point where a project’s success depends on it. Since a number of our students also are engineers and/or IT people, with a very straightforward and rationalistic view of how things should be done (if the solution is better than the current one, well, then why don’t we adopt it?), I need to explain the nature of political processes in organizations.

I am not an expert in that particular field, but I have been involved in a few projects where politics have been important – and have found the work of March, Cohen and Olsen very useful – not just as theory, but also as a very practical checklist. These three professors are famous for the Garbage Can Model, explained in the classic article Cohen, M. D., J. G. March and J. P. Olsen (1972). “A Garbage Can Model of Organizational Choice.” Administrative Science Quarterly 17(1). This article (which can be found here) is cited more than 6000 times and makes a lot of sense to me, but the it is not easy to understand (and that is not just because the specification of the model is in Fortran source code.) It posits that politically oriented organizations (they studied universities in particular, which for most purposes are anarchies) makes decisions by constructing “garbage cans” (one for each decision) and that the garbage can is a meeting point for choices, problems, solutions, and decision makers (participants), heavily dependent on energy. Decisions seek decision makers, solutions seek problems, and vice versa. Getting things done in such an environment means constructing these garbage cans and filling them with the right combination of problems, solutions, choices and participants.

This sounds rather theoretical, and is. Fortunately, March and Olsen wrote an (in my opinion) excellent book (Cohen, M. D. and J. G. March (1986). Leadership and Ambiguity: The American College President. Boston, MA, Harvard Business School Press.) a few years later, with less theory and more application. Based on interviews with a number of university presidents as well as their garbage can model, they discuss the nature of getting things done in a university environment, where there is ambiguity of purpose, power, experience and success. They finish with a list of eight basic tactics for getting things done – probably at the instigation of Harvard Business School Press, which primarily caters to business people and want applicability, not just description.

I have found this list tremendously useful when trying to get decisions made – and have observed others doing this both very well and very badly. Here it is, with their points in boldface and my (probably imperfect, it is a few years since I read this) interpretation appended:

  1. Spend time. Getting things done will take time – you need to talk to people, create language, make people see your point. If you are not willing to spend that time, you might make some decisions, but people will not follow them. Decision making is social, so decision makers in these environments need to be. The winners in political organizations are often those with the most time – which is why many universities are dominated by the administration rather than the faculty, who have other calls for their time and do not come in to the office every day. (See this cartoon for an excellent description).
  2. Persist. One of the most frustrating things (I have seen this when businessmen come in to lead political organizations, several times) in a political setting is the decisions seldom seem to really be taken – there might be a decision, but every time it comes up, it get revisited. In other words, a decision made can always be raised again – so never give up, you can always get the organization to reconsider, either the same decision directly or the same decision dressed up in new language.
  3. Exchange status for substance. As someone said at some point, it is amazing what you can get done if you are prepared to forgo recognition for it. There are many leaders who want to look good and make decisions, but don’t have the knowledge or energy to do so. Make decisions easy for them – you can get a lot done if you make decision-makers look good in the process.
  4. Facilitate opposition participation. Rather than trying to overpower the opposition, find ways for them to participate in the new way of doing things. This is one of the reason why processes and fields frequently get renamed – to allow groups to continue doing what they are doing or want to do, but in new contexts.
  5. Overload the system (to change decision making style). Decision-making time expands to fill the entire time available (alternatively, a normal meeting is over when everything is said, an academic meeting is over when everything has been said by everyone.) By giving the system lots of decisions to make (i.e., many ), this style changes – and you can get your decision through because nobody has enough time or energy to give it the full treatment.
  6. Provide garbage cans. Provide arenas for discussion as distractions, to consume energy from decision-makers.
  7. Manage unobtrusively. You can get things changed by changing small things, and in succession. I have seen examples where you get a strategic goal set up that everyone can agree to but few define (“make us a more knowledge-based organization”), get resources allocated to it, and then propose lots of projects under this heading – which now is about fulfillment of a strategy (albeit redefined) rather than an entirely new strategic direction.
  8. Interpret history. Volunteer to write meeting minutes, and distribute them late enough that most participants have forgotten the details. History, traditionally, is written by the winners (except, perhaps, for the Spanish Civil War,) but you can make it the other way around – that you become the winner by writing history.

(After writing most of this I found this blog post by David Maister which summarizes this much better than me, in the context of professional service firms): Understanding politics is very much about recognizing these tactics and using them. It may seem Machiavellian, but then Machiavelli was one of the first political theorists and knew what he was talking about.

And now I feel a need to see the next episode of House of Cards on Netflix. Garbage cans in action…

Peter G. Neumann in New York Times

Peter G. Neumann is one of my heroes – a computer science and security expert with a sense of humor (his dry comments on the Risks Digest are legendary), inventive solutions to problems (he once built a keyboard with two pedals (for “alt” and “ctrl”) to deal with carpal tunnel syndrome) and far-reaching views on most things. He is currently profiled in New York Times, including the story of the RTM Worm, which I remember clearly, and where the RISKS Forum played a role in analyzing and stopping it.

I remember an email exchange with Peter in the mid-nineties, when I was writing a research report on knowledge management for CSC Research Services. Peter has been running the email list RISKS forever (I signed up for it sometime in 1985) and when asked about how to find people to do such a job in a corporate setting he replied:

The bottom line is that moderating a newsgroup wisely takes serious dedication to, familiarity with, and commitment to the subject matter and willingness to put oneself into an intrinsically sensitive position. It does not work well if someone is arbitrarily assigned to the task.

In other words – if you want social media to work in a company, let people loose and then support the leaders that emerge, rather than try to replicate the current organization in the new medium. Not a bad insight to have 15 years ago – before this social media thing started.

Thinking long and hard on fast and slow

Thinking, Fast and SlowThinking, Fast and Slow by Daniel Kahneman
My rating: 5 of 5 stars

If you are only going to read one book on psychology this decade – this should be it!

Daniel Kahneman’s new book Thinking Fast and Slow is one of those books you intend to read while taking notes, then just blow through it knowing full well you’ll have to go back and re-read it at least once per year just to swap it all in again. It sums up a lifetime of research into the surprisingly irrational ways we humans make decisions. Kahneman is a founder of experimental economics and received a Nobel price for it.

The book gives an overview of the various ways we make decisions, illustrated with many counterintuitive examples. Its central premise is that humans have two different decision systems: System 1, which is intuitive, fast, and easy, and System 2, which is rational, effortful, and lazy. We can also divide human models into two: Econs (classic Economic Man) and Humans (subject to all of Kahneman’s follies, and then some). And we have two selves: The experiencing self (living in the present) and the remembering self (living in the interpreted past).

Kahneman lays out these concepts, then show, through examples and research summaries, how they interact and influence our decisions. The intellectual stimulation and the practical implications for how we make the important and not so important decisions in our lives are immense – as an example, check this blog post on pricing experiments.

Highly recommended!

(more notes to follow, methinks)

(If you want a really good review – read Freeman Dyson in the New York Review of Books.)

View all my reviews

How students search

David Weinberger has posted his notes from a very interesting session at Berkman that I for some reason missed – Alison Head’s presentation of studies of students’ information search behavior from the Project Information Literacy project. The findings confirm a lot of what I would have thought just by observing my own (young adult) children’s search behavior, or, for that matter, my own. Wikipedia is used a lot, and quite intelligently, in the beginning of a search. You talk to librarians and other people to get the vocabulary necessary for a search. And students (and everyone else) wants one database, not many.

Jeff Jarvis on his public parts

(taking notes from a presentation at Harvard Law School’s Berkman Center, December 6, 2011)

(David Weinberger has a much better writeup.)

Jeff Jarvis rake thin, grey-haired, dressed in black and bearded, and has had cancer, but any similarity with Steve Jobs stops there. His latest book, Public Parts, advocates more openness in a time concerned with privacy yet somehow unable to press that “like” button on Facebook.

His key point is that the tools of publicness need to be protected – and though privacy and publicness is not in opposition – and his fear that privacy concerns are misapplied and sometimes dangerous.

When Kodak was invented, there were articles written about “fiendish Kodakers” lying in wait, and the cameras were banned in some public parks. Anxiety about privacy goes back to the Gutenberg press, microphones, video cameras. Society is looking for norms, but legislates to keep the past, in terms of the past.

The tools of making publics: Habermas said public discourse started in coffee houses in the 18th century as a counterweight to government power. It was ruined by mass media. Now we have the tools of publicness, and we get things like Occupy Wall Street. Jeff started (after a few glasses of Pinot Noir) the #fuckyouwashington tag, which spawned a platform with more than 110,000 tweets.

The Gutenberg parentheses: Before Gutenberg, knowledge was non-linear, with Gutenberg it became linear, after Gutenberg it is non-linear and the knowledge we revere is the net. Danish professors arguing that the transition into Gutenberg was hard, and the transition out of it will be equally hard. Web content still shaped as analogues of the past.

Had to understand what privacy is – first take was that it had something to do with control. Came to think that privacy is an ethic. This means that publicness is also an ethic, an ethic of sharing information. Sharing his prostate cancer, including impotence, on the web. Hard to do, but got tremendous value out of it.  Various people contributed to the blog, telling things that the doctors won’t say, etc.

We need to learn from young people how to control sharing. Danah Boyd: COPA requires companies not to keep information about children younger than 13. But more than 50% of 12-year olds had Facebook – “on the internet everyone’s 14.” Sullivan principles (developed for apartheid) may help: Rules for companies to operate in South Africa.

Jarvis propose some principles:

  1. We have the right to connect.
  2. We have the right to speak.
  3. We have the right to assemble and to act.
  4. Privacy is an ethic of knowing
  5. Publicness is an ethic of sharing
  6. Our institutions’ information should be public by default, secret by necessity
  7. What is public is a public good
  8. All bits are created equal
  9. Internet must stay open and distributed

Fear that governments and companies will take this away.

Various questions in the question round – but the discussion didn’t really take off.

Jeff comes off somewhat like his books: Well articulated and with many interesting and well described examples, but I keep looking for some more analysis and less description. More depth, simply, not just a plea that openness is good and we need to develop norms on how to handle it. But the “history of the private and the public” part of his book is very good. And it does make for an interesting read.