Category Archives: Academically speaking

Key myths about analytics

My excellent colleagues Alessandra Luzzi and Chandler Johnson have pointed me to this video, a keynote speech from 2015 by Ken Rudin, head of analytics at Facebook:

This is a really good speech, and almost an advertisement for our course Analytics for Strategic Management, which starts in two days (and, well, sorry, it is full, but will be arranged again next year.)

In the talk (starting about 1:30 in), Ken breaks down four common myths surrounding Big Data:

  1. Big Data does not necessarily imply use of certain tools, in particular Hadoop. Hadoop can sift through mountains of data, but other tools, such as relational databases, are better at ad hoc analysis once you have structured the data and determined what of the data that is interesting and worth analyzing.
  2. Big Data does not always provide better answers. Big Data will give you more answers, but, as Rudin says, can give you “brilliant answers to questions that no one cares about.” He stated the best way to better answers to formulate better question, which requires hiring smart people with “business savvy” who will ask how to solve real business problems. Also, you need to place the data analysts out in the organization, so they understand how the business runs and what is important. He advocates an embedded model – centrally organized analysts sitting geographically with the people they are helping.
  3. Data Science is not all science. A lot of data science has an “art” to it, and you have to have a balance. Having a common language between business and analytics is important here – and Facebook sends its people to a two-week “Data Camp” to learn that. You ned to avoid the “hippo” problem – the highest paid person’s opinion – essentially, not enough science. The other side is the “groundhog” issue – based on the movie – where the main character tries to win the girl by gradual experimentation. Data is like sandpaper – it cannot create a good idea, but it can shape it after it has been created.
  4. The goal of analytics is not insights, but results. To that end, data scientists have to help making sure that people act on the analysis, not just inform them. “An actionable insight that nobody acts on has no value.”

To the students we’ll meet on Tuesday: This is not a bad way of gearing up for the course. To anyone else interested in analytics and Big Data: This video is recommended.

(And if you think, like I do, that his sounds like the discussion of what IT should be in an organization 20 years ago – well, fantastic, then we know what problems to expect and how to act on them.)

Cases: How to prepare for and learn from them

My versatile and creative colleague Hanno Roberts and I have made a series of five videos on case learning and preparation, originally for students at the BI/Fudan MBA program. This teaching method is difficult both for teacher and student, but highly rewarding provided you give it proper attention – which means effective preparation. Hanno and I talk about the goal of case teaching, how students can prepare individually, how to prepare as a group, how to go through the case discussion in the classroom, and then we sum up with some strategies for how to retain what you have learned.

Hanno and I did these videos against a green-screen, with little preparation – we basically met, outlined a structure with some keywords, decided broadly on who should say what, and dove right into it. Most of the videos were shot once, and then the very capable Milosz Tuszko edited them, added background, logos and keywords.

The updated videos are a less wooden than the previous version, methinks, and available in high resolution and with better sound. We clarified the differences between my version of case teaching and Hanno’s (both work, by the way). Over the years the original videos have been much watched – hopefully, our students (and others) will watch them carefully, and the result will be better case teaching, more learning, and an even more enjoyable experience teaching.

Details about each video below the fold…

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Teaching in China – some reflections

I am just back from teaching a four-day module (called IT management and eBusiness, though I might change that title somewhat) at the BI-Fudan MBA program.

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picture2017This is just about the 15th time I teach in China, all of it in cooperation with Fudan University, which gives me some cause to reflect on how teaching in China has changed – all seen from my rather narrow perspective, of course, but still. Just as the Shanghai Bund view has changed (the pictures are from 1990 to 2010) so have the participants, contents and business environment of my courses.

The students have changed: In 2004, the age range and English proficiency of the students varied much more. About two thirds of the class had rather rudimentary English skills, I had to simplify the language, and the Chinese co-teacher spent a lot of time explaining concepts and partially translating what I did. This is not any longer – gone are the days when Chinese students would sit quietly and avoid your gaze. Now they participate more or less like students anywhere in the world. English skills still vary, but not any more than they do in any European country. The co-teacher (this time the very capable Dr. Wei Xueqi, left of me in the picture) still has one hour of Chinese teaching every day after I am done, but spends more time discussing and less time translating.

The course has changed: I used to lecture much more, focus more on basic concepts and methods. Now I use cases (five in this course, plus one for the in-class exam) and the students analyze and present, challenging each others’ conclusions. I now basically use the same teaching method (heavy on case teaching) in this course as I do in any other course at a M.Sc. or MBA level I teach.

The business environment of Shanghai and China has changed. In 2004, China’s business environment was firmly divided into FDI (foreign direct investment) and SOE (state owned enterprises) and the management culture, measures and methods were very different. Copying was rampant and you sometimes felt as if you were introducing capitalism to an audience where a sizable portion of the students were unsure whether it was a good idea. Not so any more: The students now all have experience with international business, frequently with much more experience than my Norwegian students, particularly when it comes to production and industrial planning. A larger and larger portion of the class works in service industries and in online enterprises, something which I have reflected in choice of cases and examples.

I used to go to China because it was different and therefore interesting. Now I go there because it is interesting – but not so different. At least not in the classroom.

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.