Thursday, March 9, 2017

Economics of Digital Age 5: Technologies of the world unite

While the singularity focusses on AI it is a distraction from what is clearly happening every day at the moment and which wasn't present even a decade ago. That is a technological advance in one place is enabling technological advance somewhere else.

'Innovation systems' has now been replaced by 'innovation ecosystems' in the academic literature. Do we really know more - not really it is mostly just an exercise in talking about ' innovation systems' sounds dated so 70s. I am going to be pointed - I truly do not believe you can have an innovation ecosystem - you can have technology ecosystems but not innovation ecosystems in the geographic sense it is most often used. Clusters is also out of fashion, so we can't use that term either.

The point of ecosystems if anybody bothered to read the ecology literature is that they are so multidimensional. There are population dynamics, energy cycles nutrient cycles food web dynamics, shock and resilience dynamics. When it is used in innovation circles it typically means "do we have the right institutional blocks' in place.

If we were really interested in ecosystems we would be trying to figure out how AI is fuelling autonomous cars and how autonomous cars will rewire cities. Now to be fair this is happening - MIT labs and others have been doing some incredible modelling of possible scenarios with autonomous cars. But that is because it is such an obvious example - the problem is we need more and we need to think how to build an idea of the whole - how do different technologies possibly interact at the economic level.

What is clearly coming is multiple waves of change crashing in on us almost simultaneously. However, publishing cycles remain slow and policy makers are trained in ways that are now decades out of date.

It gets mighty complicated. In a recent article The Economist pointed out that http://www.economist.com/news/briefing/21717365-wind-and-solar-energy-are-disrupting-century-old-model-providing-electricity-what-will  while renewable energy is coming online there are design problesm with the grid itself and as renewables drive down cost it gets less attractive to build the new grids. If you are temped to blow this off as "The Economist" then you should read this by the ABC in Australia on the South Australia power grid situation.

 So while the electricity grids are not built for significant amounts of renewable power, electricity demand will only increase because of new technologies increasing the viability of using batteries/ electricity in an ever wider range of products (IoT, cars, trucks, drones, robots etc etc.)


Monday, January 23, 2017

Economics of Digital Age 4: Measuring the Technology Transformed Economy

Of late I have been struggling to come to terms with the modern technology economy.


A bit of a history lesson



Back when I started in this game there was data on:


  • R&D by business, governments, universities and non-profits
  • R&D personnel by same classification
  • Patent data
  • Publication data


....and then we would mine economic structure data to create information on trade patterns and clusters etc. This is what I have specialised in for 25 plus years. All of the data was supplied by official agencies.

But over the last three years the landscape, it seems to me, has changed dramatically. Back in the 1990s, if we looked at high technology industries (high R&D intensive activities) aerospace rolled out a new aircraft every decade or so and pharmaceuticals companies were and still are notoriously slow to move products from research to market.

IT/computers and mobile phones was thus the sexiest thing to watch - and the number of articles reflects this. Search Research Policy for these terms and any other phrase you care to think of and the results will not surprise you

This is all very fine up until about 2008. The IPhone came out in 2007, Uber launched in 2009. The autonomous mining equipment in Australia, that I have already posted about elsewhere, really started to become a serious game changer in 2008.

Today, there is AI, block chain, big data, translation software etc etc.

I've compiled the following list.



The OECD has published this:




What we are seeing is a revolution in technology that is changing the very structure of the economy. These are not always obvious changes. For example renewable energy is beginning to make a different and contribute to energy grids around the world. Consumers can become producers of energy in smart micro-energy based grids.

It seems that our national accounts based view of economic activity just cannot take account of what is happening.


So What do I suggest?

I think we need to focus data collection and analysis, at least for the near future, on three aspects of the thing formerly called the economy.

1. The tech itself
2. the companies
3. skills, employment and income

The tech

For decades now we have ignored the development of actual technologies, preferring instead to think of 'innovation'. The result is today while there is avalanche of stuff coming, or as Richard Florida tweeted in 2016 a series of 'nested transformations' - for the most part we are all at sea because we don't know what is going on. 

So therefore, let us go back to basics and make things concrete again - let's analysis and compile technology statistics and work out how to compare them. So for example how fast are solar technology efficiency rates changing, how fast is new load capacity being added and what share of the total is this.

Autonomous cares - how fast are they being developed and as soon as they hit the road what is their share vs the installed base share - as we might call it.

etc.

The companies

I think it is clear now that the new mega technology companies are something out of science fiction - we need better data on these companies. But we also need better data on organisational platforms of the economy.  I do not think this needs further justification, it is obvious.

People

The trouble we are seeing in the world with Brexit and Trump reminds us that people matter. We have been so focused on GDP and industries we have forgotten that humanity still craves a "good life". A sense of worth and value, a sense of contributing to the whole.

Take that away and there will again be mass conflict. We must return to being interested in the lives of real people.

Summary

Please stop talking about innovation and return again to focus on what changes are happening to whom and on what scale. Policy frameworks depend upon it.


Wednesday, June 22, 2016

Economics of Digital Age 3: Dis-intermediation & Re-intermediation


The term dis-intermediation gets banded around alot in this early cyber revolution period but what does it mean and how can you show it.


So Wikipedia has the following rather limited definition of intermediation.
Intermediation involves the "matching" of lenders with savings to borrowers who need money by an agent or third party, such as a bank.[1]
If this matching is successful, the lender obtains a positive rate of return, the borrower receives a return for risk taking and entrepreneurship and the banker receives a return for making the successful match.[1] If the borrower's speculative play with the funds provided by the bank does not pay off, the bank can face significant losses on its loan portfolio,[1]and if the bank fails its depositors can lose some of their money if the deposits are not insured by a third party.
In fact with vision, and vision is needed here we need to expand the concept of intermediation to just about any scenario you can think of where there is an actor interposed between step 1 and step 3. So ingrained in us are conventional concepts of human work - most scenarios will not even look like intermediation - they only become so when digital technologies offer new possibilities.

So let us illustrate the concept.

Figure 1.




This gives us a basic template to see what happens when we change the dynamics of the economy.
At the highest level we can observe what happens to entire 'industry complexes' when a digital substitute marketplace is created.

Figure 2.


Pre-2000 there was a substantial industry constructed around music - agents, labels, studios, physical media manufacturing (records, tapes and then CDs) and then the retailers.

However, along came napster and later iTunes and what have we got left.

Fig 3.


What we see here is that Apple iTunes has dis-intermediated the music industry and re-intermediated music as well. It now offers a direct route for artists and traditional music industry operations must go through it to get to the customers. This process has dramatically shrunk the tradition commercial music complex.

Now we can apply this to any example. For example a worker driving a truck. Pre-2000 this idea that the driver is an intermediation point would be treated as complete nonsense - now not so much.

Fig 4.



Fig 5.

We can now move to a scenario when mining companies can dis-intermediate this value chain.


This may look dramatic and that is the point. This logic of dis-intermediation and re-intermediation is intrinsic to digital technologies and we had better start designing data around this concept to understand it better.


Monday, April 11, 2016

Economics of the Digital Age 1 - maintenance

Just some musings today of future costs rather than benefits.

So as a follower of innovation studies and also a collector of serious attempts to look into the future it seems to me that one of the serious flaws in the way we bean count is to only focus on growth. It always seems that studies overshoot the future partly for lack of technical advance but partly because they undervalue the economics of the system. These dimensions are inextrricably link - make enough technical advance and the economics improve - however perhaps the upfront costs of that technical advance are too high to begin with.

It seems to me that in understanding this conundrum our national accounts have categories which are next to useless in the modern economy.

So for example I have often wondered about the accumulated techno-system in societies. So inspired by the great read https://aeon.co/essays/innovation-is-overvalued-maintenance-often-matters-more
here are a few jottings.

That blog immediately triggered so many tangential thoughts. Assimov's comments in the Foundation trilogy that as the Galactic Empire slowly collapsed it could not longer maintain its technologies.

Another was a throw away comment in the current U.S. 'great wall' debate about the cost of maintaining the wall. http://www.cnbc.com/2015/10/09/this-is-what-trumps-border-wall-could-cost-us.html includes an estimate of $750m - per annum for maintenance. If the wall cost $12b even without accounting for inflation you are paying for the equivalent of a new wall every 16 years.

Out of sheer curiosity I looked up the accounts of the local public transport body and it was hard to discern what their actual final maintenance costs are.

But let's just assume that gradually over time not only are our societies accumulating more infrastructure but that as technology is more fully embedded the costs rise.

How to read the image. As we rarely discard technologies entirely or when we do, we replace them with ever more complicated ones. So we add to the techno-system and rarely take away. If you read the chart vertically you can read it that past structures are past onto future generations. Roads build pre-1950 are largely still in use today as entities and locations although they have been upgraded in quality significantly. Therefore the pre-1950s column goes vertically upwards. In the pre-millennial period we started introduced significantly new and varied technologies and we currently stand on the cusp of IOT of things. The graph tries to take account of some efficiencies and productivity improvements from gains from embedded technology - but there will still be more of it. 

So over time the costs of maintenance rise - but it is difficult to determine whether this is proportionate or disproportionate to the rest of the economy. We know that in the USA it is failing. In Europe where taxes are higher infrastructure maintenance is better.

Of course early on councils and governments will embed sensors on everything from water mains to roads - but here is the question - what will break first the sensor or the pipe. If it is the pipe how quickly will cash strapped councils replace the sensor.

With the current obsession with new technology - we only study the system around the production of the new technology - not the technology system itself. Oh and BTW costs are only one element - you actually have to have a techno-system that values education for the skills necessary to maintain the societal infrastructure.

Tuesday, March 22, 2016

Technology in Economic Space Time


Any regular or irregular reader of this blog will realise that one of the goals of this blog is to explore non traditional concepts and language for describing the economy and the relationship with technology. The dominant language at present is 'innovation' and the academic discipline is 'innovation studies. This is I believe to greater or lesser extent fostering confusion about the topic. Technology remains in my view a problematic entity in society and economics. Treating it like land, labour or capital I believe is not helpful because technology conditions and transforms the others. It is not simply a production variable nor something meaningful to count as X% of firms launched new products last year.

My principle concern is that there is a great deal of muddled language where technology and innovation are almost used interchangeably. Further, technology has been subsumed within economic growth studies and impact but surely it does more that grow the economy it bends its shape.

Technology is more than just one thing - it is many things simultaneously. It is our creation and therefore it can be studied like we do with nature - biology and ecology, as a single organism, with DNA - heritage and history. It can be studied in 'food webs' in relation to economic structure - supply chains and so forth. It can be studied within the ecosystem of other technologies of greater and lesser scale, scope and dimensionality. Back here http://econscapes.blogspot.ca/2013/08/macro-innovation-1-introduction.html I explored the idea that technology should be seen as an ecosystem that is interdependent and modifies the 'environment' ie. the linkages between other systems around it. That is one image of technology - but at the macroeconomic level it is not simple enough.

The idea of 'general purpose technologies" exists but has never really taken off, and there is Keven Kelly - technium which hasn't caught on either.

It is interesting that at this moment when 'technology and economics are now almost synonymous there may just be the start of a movement to go back to rethink technology.

Beyond Innovation: Technology, Institution, and Change as Categories for Social Analysis. By Thomas Kaiserfeld. New York: Palgrave Macmillan, 2015.
Pp. 174. $67.50.Technology and Culture, Volume 57, Number 1, January 2016, pp.
244-245 Reviewed by Benoit Godin.

So onto this blog.
The latest concept has been playing in my head for a long time but received some impetus with the first measured gravity waves.

So here is another way to conceptise technology - as 'mass' in economic space time.

Space Time



I found this great youtube video of the space time concept.  https://www.youtube.com/watch?v=MTY1Kje0yLg Dan Burns explains his space-time warping demo at a PTSOS workshop at Los Gatos High School, on March 10, 2012.>

So what is Economic Space Time

Imagine if could measure all the dimensions that are important for understanding the dynamics of economies. Economies are not singularities that move through time - always essentially the same. What is made (incl services - everything), where it is made and how it is made changes radically across time - this we could call economic space time.

Naturally to understand economic space time we need to measure tot just income, but how people make their money, the production systems etc etc ... In short we would be able to then approximate the underlying 'technology' of the economy at particular points in time. But could we simplify this by looking at the 'waves' generated by new technologies.


Economic Space Time circa 1960

Put your mind back to the 1960s the US manufacturing economy was at its zenith - thousands of people were employed in factories. The big companies - resources and manufacturing employed many thousands of employees. I actually went looking for the numbers but they are hard to determine. If I can calculate some I will put them on this blog.


Economic Space Time circa 2016

So what about today. The top companies ( http://fortune.com/fortune500  ) are Walmart, Exxon Mobile, Chevron, Berkshire Hathaway and then Apple.

If we pick on Apple as the first company that makes products - yes I know petroleum is a product but not in the same way.

Apple has nearly 100,000 employees and an un-numbered 000s in its elongated supply chain which is a part of the modern economy. We also don't know how many people do contract work for Apple.

To make the point about supply chains even stronger, General Motors is no 6 on the list. Is has just more than twice the number of employees than Apple.

Amazon one of the born digital companies has 154000 employees.

JP Morgan Chase Institute recently released a fascinating report on income volatility and other information using big data analytics of JP Morgan Chase bank accounts. The most interesting reading relates to the platform economy participation.

Although 1 percent of adults earned income from the Online Platform Economy in a given month, more than 4 percent participated over the three-year period.

The Online Platform Economy was a secondary source of income, and participants did not increase their reliance on platform earnings over time. Labor platform participants were active 56% of the time. While active, platform earnings equated to 33% of total income

Source: 

Paychecks, Paydays, and the Online Platform Economy February 2016
https://www.jpmorganchase.com/corporate/institute/report-paychecks-paydays-and-the-online-platform-economy.htm


So at this point you are thinking - 1/3 of the income for 1 percent of adults, that not much in the scheme of things is it. And that was the view of The Economist

Such reforms, though, would be relevant to only a tiny fraction of the workforce. JPM’s data suggest that most ondemand workers use apps to supplement their income, rather than as a replacement for a fulltime job. On average, labour platforms provided only one third of ondemand workers’ incomes. And their participation was often sporadic; almost half of those who start working on a labour platform stop within a month. Earnings from Uber and the like are strongly correlated with negative shocks to incomes from other sources (capital platforms are used much more consistently). That suggests people use
apps to smooth bumps in their earnings, which are frequent: more than half of JPM’s customers have seen their incomes swing by at least 30% in a month. Volatility in pay is largely responsible. Perhaps conventional jobs are not so great after all.

But just a moment

Just how significant is one percent of the labour force? Well.... As I have been reading through the report by JP Morgan Chase Institute I realise I need to read it much more closely as it refers to 'adults'. That is is a very much larger pool of people than conventional statistics of workforce.

For comparison in Canada 1.6 percent of employment by industry is in agriculture. A further 1.6 are employed in Mining. As a percentage of adult population that may drop a bit and we get closer to the 1 percent.

So when you hear only 1 percent are employed in the 'gig' or 'task' just keep in mind that number is bigger than you think.


So what is the point: 'technology waves'

When the steam engine was invented, enabling power and the factory system it changed the economy - not just grew output and productivity.

Today with the growing digitalisation it is obvious the economy is change shape again. This is not new it is in the papers everyday.

The point is no single way of understanding those changes not single language is powerful enough to capture the scale scope and significance of change and we should give up trying.  Lets be heterodox is our rich descriptions of change.








Wednesday, June 24, 2015

The Technium is getting more interesting


Way back here I was critical of Kevin Kelly's Technium concept.

Okay, so I am not going to retract those comments but it is time to amend them.
Kelly continues to work on the idea and it is getting more interesting as he add addition concepts.
You can listen to the talk with the link below or if you go to the Long Now you can watch it on the web.






So these are the big new addition to the Technium concept.

1) Big math of “zillionics” ---beyond yotta (10 to the 24th) to, some say, “lotta” and “hella.”
Basically Kelly's point is that we do not have words in the language for the numbers that digital technology is generating - global digital memory capacity, web scale etc.

2) New economics of the massive one-big-market, capable of surprise flash crashes and imperceptible tectonic shifts. 
The more autonomous, the more that either the machines will make unexpected choices or individuals will work out ways of gaming the system. Kelly claims in the talk that nobody knows the cause of the flash crash. However, the Commodity Futures Trading Commission of the U.S. claims that a single individual was significantly responsible. Link.

3) New biology of our superorganism with its own large phobias, compulsions, and oscillations. 
With new organisms come new illnesses. Look at the problems viruses can cause or cyber attacks. Perhaps Kelly goes to far, but he could be right. It is certainly an interesting thought experiment to seethe global economy from this perspective - new strengths and new vulnerabilities. We think we know what the economy is but perhaps alongside the World Bank, we need a World Economic Health Organisation.

4) New minds, which will emerge from a proliferation of auto-enhancing AI’s that augment rather than replace human intelligence. 
Kelly nicely makes a case for weak AI and against strong AI. But even weak AI will drive change  which we can't imagine.

5) New governance. One world government is inevitable. Some of it will be non-democratic—”I don’t get to vote who’s on the World Bank.“ To deal with planet-scale issues like geoengineering and climate change, “we will have to work through the recursive dilemma of who decides who decides?” We have no rules for cyberwar yet. We have no backup to the Internet yet, and it needs an immune system.
Big thinking, and we are falling further and further behind where the technology is.


What I like about this talk is not the details, its the the big thinking, it is a few sketches on a napkin but industry, government and academics are limited by their institutional histories. Only someone of Kelly's statute can get a conversation like this going.