Confounding Factors

Illustration from Inventing the Future (Burgess Shale and Emerald Lake)
InDesign document
©2019 Charlene Brown

Forecasting the future is made more difficult by confounding factors such as:

·         Disruptive technology/innovations: Are today’s disruptive transformations (block chain, genome sequencing, robotics, energy storage, AI) comparable to the disruption caused by railways, automobiles, electricity, computers or the internet?

·        Black swan events: unpredictable, massive impact, highly improbable, eg. 9/11, collapse of the
Soviet Union, Covid-19

·        Wild cards: low probability, high impact events.  The difference between Black Swans and Wild Cards is that Wild Cards are imaginable (ie predictable to a certain extent), temperature increases, Halley's Comet, 2008 financial crisis, religious conflicts, financial unicorns (or alicorns), pandemics, wars, and tipping points (abrupt actions of a complex system which has become unstable). 

Using wildcards in disruptive innovation ideation sessions can enrich discussions and help people to imagine 'what if?'

        

        

 

 

Forecasting the Future on Zoom

Illustration from Inventing the Future (Gabriola Island)
InDesign document
©2019 Charlene Brown

I won`t attempt to summarize everything I learned in a ‘Forecasting the Future’ class at UVic that I Zoom-attended earlier this month.  Actually I did try to summarize everything, but ended up with way more information than I’d ever try to squeeze onto this blog.  So I’ll just write about the three topics that relate to Predictive Visualization – Complex Systems, Confounding Factors and the Role of Artificial Intelligence.

Complex Systems:

A system is complex if it has diversity, connection, and interdependence.

·         Non-adaptive complex systems follow rules of behavior and equations of physics, and can be modeled and predicted.  Climate projections are non-adaptive complex systems that should be relatively easy to model, except for some randomness and chaos.

In climate modeling, parameterization – a succinct mathematical description of a complex process – can replace factors like randomness and chaos that are too small-scale or complex to be represented physically.  Millennials would describe parameterization as a hack, by which they would mean a clever, subtle, even mystical computer program – a digital poem, rarely appreciated by non-hackers.

·         Adaptive systems adopt new rules when circumstances change and are harder to model and predict.

Chaos theory deals with adaptive complex systems whose behavior is highly sensitive to slight changes in conditions, so that small alterations can result in unintended consequences. Techniques are emerging to make predictions using chaos theory

An Actual Predictive Visualization

 

Unmet GHG Reduction Targets*
Watercolour, marker and computer
2021 Charlene Brown

 Actual and projected increasing GHG emissions are represented by the solid and dotted black line, with optimistic GHG reductions that didn’t materialize shown in cyan dots.  A couple of surprises which led to economic downturns resulting in sharp reductions in emissions have been labeled in magenta. Surprises vary greatly in the degree to which they may be understood and anticipated.  Visualization and even chaos theory may point the way.

 *Derived from Émissions de GES du Canada: Cibles non-atteintes, produced by Équiterre in 2018. 

Incorporating surprises into Predictive Analytics

Not a Predictive Visualization
Watercolour
© 2019 Charlene Brown

Computers are capable of pattern recognition, trend analysis, extrapolation and prediction if the task can be formulated and solved mathematically.

But surprises – Black Swans or Wild Cards such as Alicorns – can alter the data.  When that happens, computerized analytics must yield to common sense, imagination, heuristic exploration of possibilities and visualization.

I’ll write more about these and other surprises in a blog post about my recent Future Forecasting class at the University of Victoria.

 

Renewable Energy Rant

Wind Farm in Southern Alberta
Watercolour and crayon
©2016 Charlene Brown

Outdated analyses of the climate change mitigation potential of various technologies refer to ‘renewable’ alternatives to fossil fuels.  In these analyses, biofuels (or biomass), which do not result in significant GHG emission reductions* are combined with other renewables (solar, wind, tide) that have huge potential to make significant GHG reductions, and nuclear energy, which is a whole different class with unique disadvantages (public perception) and advantages (remote location can greatly reduce need for transmission lines or pipelines). 

‘Renewables’ should not be considered as a group with similar climate-change mitigation potential.  Alternatives to fossil fuels should be described as low-carbon, clean or green. These alternate energy sources include nuclear and do not include biofuels.

* Originally, biofuels were viewed as inherently carbon-neutral, assuming the carbon dioxide plants absorb from the air as they grow completely offsets, or neutralizes, the CO₂ emitted when fuels made from plants burn. However, this offset is largely negated by the GHGs emitted during the cultivation, harvesting, transportation, and refining processes.  When burned for power generation or heating, biofuels emit about the same amount of GHGs as fossil fuels.

Data Analytics

Click on image to enlarge

Data Visualization
Mixed media, computer-altered
©2020 Charlene Brown

In trying to convince some of my grandchildren that data analytics skills will be important for everybody, no matter what their career choice or field of study, it’s occurred to me it might be worthwhile to update my own understanding of data analysis.  And to explore the advantages of data visualization. 

The painting above is a visualization of the future effect on GHG emissions caused by three policy alternatives in transitioning off fossil fuels:

1.       no changes
2.       carbon tax increasing slightly
3.      greatly increased carbon taxes

It shows how data visualization can distill large data sets into visual graphics and make it easier to understand complex relationships and predict trends.

As with most projections of the results of policy decisions, these are based on rational extrapolations of observed effects of various fuel types (represented above by different coloured bands) used to produce heat and generate electricity energy, assuming no surprises.

I’ll look at the possibility of adding surprises to these visualizations soon, but first I will write a short ‘Renewable’ Energy Rant.

 

Hard to believe how much we got around four years ago…

Bagh-e Fin, seen from the Safavid Pavilion
Watercolour and oil pastel
© 2021 Charlene Brown

This exquisite garden, one of many UNESCO World Heritage sites we visited in Iran, dates back to the early Safavid era (16^th century CE). With its symmetrical proportions, towering cypress and sycamore trees, spring fed turquoise-tiled pools and fountains, it is renowned as being the very epitome of the Persian garden and its evocation of heaven.

This year we’re hoping that we’ll soon be able to take our first trip off Vancouver Island since Christmas of 2019.

 

Reworking another sketch from four years ago

Takht-e Soleyman (Throne of Solomon)
Watercolour and oil pastel
©2021 Charlene Brown

Originally the site of a Zoroastrian fire temple built in the 3^rd century CE, Takht-e Soleyman is situated on the rim of a calcium-rich spring on a hill formed by the outflow from the spring.   The complex was fortified and established as a summer palace by Mongol Ilkhanid invaders in the 8^th century and eventually influenced the development of Islamic architecture when the Ilkhanid rulers converted to Islam.

When our group from the Art Gallery of Greater Victoria visited the site high in the Alborz Mountains, springtime flowers were beginning to appear, and an overnight snowfall had covered some of the surrounding orchards.

Here is the link to my blog post about the original sketch of Takhte-e Soleyman (which has been computer-abstracted).

 

 

Haven’t been anywhere lately, so I’m reworking some sketches from four years ago

Kandovan
Watercolour, oil pastel and computer
©2021 Charlene Brown

We arrived at this 800-year-old village in East Azerbaijan Province of Iran in early April 2017 on an archaeological tour organized by the Art Gallery of Greater Victoria. The architecture here is similar to that of Cappadocia, Turkey, about 1000 km to the west. 

There was still a lot of crusty snow between the conical volcanic rock dwellings but there were definite signs of spring by the stream below the village.

Click here to read my blog post about the original sketch of Kandovan.