Category Archives: Digital reflections

Singularity redux

From Danny Hillis: The Pattern on the Stone, which I am currently reading hunting for simple explanations of technological things:

Because computers can do some things that seem very much like human thinking, people often worry that they are threatening our unique position as rational beings, and there are some who seek reassurance in mathematical proofs of the limits of computers. There have been analogous controversies in human history. It was once considered important that the Earth be at the center of the universe, and our imagined position at the center was emblematic of our worth. The discovery that we occupied no central position – that  our planet was just one of a number of planets in orbit around the Sun – was deeply disturbing to many people at the time, and the philosophical implications of astronomy became a topic of heated debate. A similar controversy arose over evolutionary theory, which also appeared as a threat to humankind’s uniqueness. At the root of these earlier philosophical rises was a misplaced judgment of the source of human worth. I am convinced that most of the current philosophical discussions about the limits of computers are based on a similar misjudgment.

And that, I think, is one way to think about the future and intelligence, natural and artificial. Works for me, for now. No idea, of course, whether this still is Danny’s position, but I rather think it is.

Norway and self-driving cars

(This is a translation (with inevitable slight edits) from Norwegian of an op-ed Carl Störmer (who, in all fairness, had the idea) and I had in the Norwegian business newspaper Dagens Næringsliv.)

A self-driving future

Espen Andersen, BI Norwegian Business School and Carl Störmer, Jazzcode AS

Norway should become the world’s premier test laboratory for self-driving cars.

Norway needs to find new areas of development after oil – and we should go for something the whole world wants, where we have local advantages, and where we will develop deep and important knowledge even if the original idea does not succeed. We suggest that Norway should become the world’s premier test laboratory for self-driving cars – a “moon landing” we can develop far further than what we have been able to do from our expertise in sub-sea petroleum extraction.

1280px-tesla_model_s_26_x_side_by_side_at_the_gilroy_superchargerSelf-driving cars will do for personal transportation what e-mail has done for snail mail. Tesla-founder Elon Musk says Teslas will drive themselves in two hears – they already can change lanes and park themselves in your garage. The “summon“-function (a “come here”-command for your car) could, in principle, work across the entire USA.

An electrical self-driving vehicle will seldom par, choose the fastest or most economical route, always obey the traffic laws, and emit no pollutants. A society with self-driving cars can reduce the number of cars by 70-90%, free up about 30% more space in large cities, reduce traffic accidents by 90%, and drastically reduce local air pollution.

Google’s self-driving carsgoogle_self_driving_car_at_the_googleplex have driven several million kilometers without self-caused accidents, but there are still many technical problems left to solve. The cars work well in the well marked and carefully mapped roads of sunny California. The self-driving cars drive well, but the human drivers do not. But we cannot execute a sudden transition – for a long time, human and automated drivers will have to coexist.

Norway has unique advantages as a lab. In Norway, we can develop our own self-driving cars, but also be the first nation to really start using them. We do not have our own car industry to protect, we are quick to purchase and start to use new technologies, we are such a small country that decision paths are short, and should an international company make a marketing blunder in Norway, the damage will be limited to a very small market. We can easily change our laws to allow for testing of self-driving cars: Oslo, Bergen, Trondheim and Stavanger has enough traffic issues and large enough populations to suffice for a serious experiment. As a nation, we are focused on environmental issues, innovation and employment.

Norway’s bad road standard is an advantage. Norway has plenty of snow and ice, bad weather and bad roads. Today’s self-driving cars need clear road markings to be able to drive safely. But Norway has world leading capabilities in communication and coordination technology: The oil industry has learned how to continuously position ships in rough seas with an accuracy of about five centimeters. Telenor is a world-leading company in building robust mobile phone networks in complicated terrain. Technology developed for Norwegian conditions will work anywhere in the world.

Norway needs self-driving cars more than most nations. Norway is the world’s richest and most equal country, creating a modern welfare state through automation and technology-based productivity improvements. The transportation industry is over-ripe for automation. The technology can maintain productivity growth and offer a new life for many people – the blind, the old and the physically handicapped – who do not have access to cheap and simple transportation today. It will create many jobs – think before and after the smart phone here – that can be created based on abundant and cheap transportation.

Norway will win even if we don’t succeed. Lots of new technology has to be developed to make self-driving cars from experiment to production: For instance, software has to be developed that can handle extremely complicated situations when autonomous cars will have to share the road with tired human drivers. More importantly, lots of products and services can be built on top of self-driving cars, business models have to be developed, and many industries will be impacted. The insurance business, for instance, will have to adapt to a market with very few accidents. Even the donor organ market will be impacted – though traffic accident organs by no means make up the majority of organs available, there might be a shortage of available organs.

Norway has faced tremendous changes before. We have transited from being harvested ice to electric refrigertation (in the process enabling our large fishing and fish farming industries), from sail to steam shipping, from fixed line telephony to mobile phones. Our politicians have, quite wisely, created an electric car policy ensuring that we have the highest density of electric cars in the world (10% of all Teslas are sold in Norway.) Norway has everything to earn and very little to lose by going all in for self-driving cars.

Let’s do it!

All the cargo in the world…

I just love this map, created by Kiln, so I wanted it on my blog for easy reference:

It is rather fascinating, and clearly shows why Singapore has acquired such an important position in the world’s logistics. Click on the play button in the top right corner for a short narration. The data is from 2012, but the pattern is largely the same today.

Does someone have to die first?

double-classroomBlogpost for ACM Ubiquity, intro here:

Digital technology changes fast, and organizations change slowly: First using the technology as an automated, digitized version of the old way of doing things, then gradually understanding that in order to achieve productivity and functional breakthroughs. We need to leave the old metaphors behind. For this to happen, we need new mindsets, unfettered by the old way of using the technology. I wonder if my generation has the capability to do it.

Read the rest at ACM Ubiquity: Does someone have to die first?

Friday futuristic reading

I am not a big fan of science fiction – way too many people in tights staring at big screens – but I do like the more intellectual variety where the author tries to say something about today’s world, often by taking a single aspect of it and expanding it. So here is a short list of technology-based short stories, freely available on the interwebs, a bit of reading for anyone who feel they live in a world where the technology is taking over more and more:

  • The machine stops by E. M. Forster is the classic on what happens when we make ourselves totally dependent on mediating technology. Something to think about when you surf and Skype from your home office. Written in 1909, which is more than impressive.
  • The second variety by Philip K. Dick details a future with self-organizing weapon systems, a future where the drones take over. Written during the Cold War, but in a time where warfare is increasingly remote and apparently bloodless there is reason to think about how to enforce the “laws of robotics“.
  • Jipi and the paranoid chip is a brilliant short story by Neal Stephenson, the only sci-fi writer I read regularly (though much of what he writes is historic techno fiction, perhaps fantasy, and not sci-fi per se). It is about what happens if technology becomes self-aware.
  • Captive audience by Ann Warren Griffith is perhaps not as well written, but I like the idea: What happens in a society where we are no longer allowed to block advertising, where AdBlock Plus is theft.

There is another short story I would have liked to include, but i can’t remember the title or author. I think it was about a society where everything is designed with planned obsolescence, where a man is trying to smuggle home an artisanal (and hence, sustainable) wooden bench, but has issues with various products, including the gift wrap, which decays rapidly once it has reached its “best before” time stamp…

And with that, back to something more work-related. Have a great weekend!

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


Accenture and connected health

(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.)

Andy Greenberg is relatively new to Accenture, having a background in various technology companies involved in health and fitness monitoring.

The Internet of Things is the next era in computing, we are moving to the second half of the chessboard, Moore’s law is still active. Everything gets faster all the time, sensors cheaper, more and more connections and kinds of connections becoming available. A lot of the data growth has been driven by sensors. Smartphones everywhere, but can’t be assumed in the health space.

We need to capture the data, and we can’t send it all away – so we have to do data analytics on the edge, i.e. do analysis right away. You have to think about some things, such as engineers designing for engineers is not a good thing, and that if you can do something – such as connecting a device – it does not necessarily mean that you should do it. However, there will be 25 to 50b connected devices in the next few years – and it can deliver value. Tesla, for instance, can update its cars  instead of recalling them, improving customer satisfaction and saving money. An Airbus can send messages about needed parts, in the future they will be 3D printed at the airport before they land. There is a large gap between how many CEOs think IoT is important and how many have any kind of capability to do it.

IoT has enormous potential in health care. We have an aging population – and that is true of the health providers as well. Patients have different expectations: “health consumers are becoming consumers, comparing their experience not to the last doctor’s visit, but the last time they bought something on Amazon”. Spending on healthcare is increasing, as is the number of connected and connectable devices.

IoT enables connected health services, including merging the experience at home and at hospital, feeding data from home and feeding treatment from hospital to home after a hospital stay. The key is to understand the complexity of where people are at different times and manage accordingly, as opposed to thinking that they are either one kind of patient and another – we are all different types of patients at one time or another. Key is to focus on preventing readmission to hospital, but there might be more value in managing the healthy population – focusing only on the high risk patients may not be the right strategy. (Dee Edington – Zero Trends). It is not just about getting the ill well, but keeping the well well.

Moore’s law works both for fitness devices and medical devices. For fitness devices, wireless offloading of data makes a real difference, the holy grail is when the data offload disappear completely, if something monitors you all the time and alerts you to do something then you are more likely to use it. Medical devices have been more about diagnosis, now moving into monitoring and adherence. Proteus Digital Health, for instance, has a smart pill that monitors that it is being taken, for instance. Problem is that you need to wear a patch, and the first drug it is being applied to is one for schizophrenia – in other words, the patients that are most likely to be paranoid… There is also work done with smart devices, such as asthma inhalers, which can track how much it is used, geolocate, match to other people using inhalers same day, track pollen count etc. Find covariation from individual and communal data.

Healthcare players need to understand consumer expectations – Disney spent more than one million on wristbands to make the interaction with their parks much more frictionless. Healthcare providers should do the same thing – help their patients navigate through their services – including hospitals – to make the experience more seamless. This is happening in the pharmaceutical space: About half of all presecriptions are either not filled or taken incorrectly. Some names: Gecko Health, Propeller Health, Adherium, Inspiro medical.

When you add connectivity to the mix, it changes everything. One challenge is that even though the value is clear, the person receiving it may not be the one paying for it. This means that many device innovations are seen by their creators as a way to be unique, that will change over time because the value is much bigger of things being standardized and more widely distributed. You also need to standardize to the lowest common denominator from a connectivity perspective. Security is obviously an important issue as well.

Q: How do you make a secure app, how do you handle security?

Andy: Only a minority has a code on their phone, so you need a separate login. Security has be be part of the design from the very beginning. The biggest piece of guidance is to understand that.

Q: Can you see health care become completely digitalized?

Andy: Health care will always have a large human element, and there are huge hurdles in interoperability, but in between 5 and 10 years we will see significant action. The technology is not the problem any more, it is all about adoption.

Francis: We are stuck in a fee for service model that is, in my opinion, broken. Should move to a value model, and digitization can help with that.

Q: Where will we see the first real use of it?

Andy: Already seeing that, pockets of it. Maybe the most interesting and recent adaptation is the use of telemedicine about mental health. The VA hospitals are doing that to allow face-to-face conversations with clients with mental health issues. The key here is having payers pay for this as legitimate treatment. Remote monitoring is coming along. Change in payment models and health plans that change prices if you carry a device also drives this.

Q: The nordics are a bit of digital laggards – what will happen here?

Andy: The nordics tend to be ahead in technology and behind in business models. The aging population is a driver and Asia is a big area for that. Regulatory constraints are going to be a big hurdle, some countries are so high on privacy that they make it almost impossible to even try. Payment is important – if governments say they are willing to pay for making the elderly stay home longer, then it will come.