Monday, August 22, 2016

A challenge for Google’s Deep Mind: solving the Jevons Paradox

Note: this post was originally published on The Fifth Estate on 16 August 2016. 

Google has announced that it has used Deep Mind, the neural network computing developed by its AI research company, to reduce the energy used for cooling its data centres by 40 per cent. Sounds impressive, until you realise that Google’s energy use is doubling every year.

Data centres are not very efficient for several reasons:
  1. Servers are generally inefficient, producing lots of heat
  2. Just cooling them uses a huge amount of power
  3. The companies running data centres are rewarded for responding quickly to demands on server uses. They are not rewarded for saving energy, therefore they keep energy use at a maximum continuously
  4. With the inexorable expansion of “cloud computing”, this trend is set to continue
So while Google’s announcement sounds great let’s look at what is actually happening to data centre energy use – in fact energy use in ICT generally. And it’s not good.

Even if data centres did use energy efficiently their overall use is still increasing at a greater rate. Google’s total power usage appears to have increased by a factor of 12 in the last four years, almost doubling every year.

It likes to boast about its use of renewable energy. It recently purchased 781 megawatts of solar and wind power to power its data centres. But the company also says renewable energy makes up just 37 per cent of its usage and with a total of 1.2 gigawatts of renewable energy, that makes its total data centre usage around 3.2GW.

But this itself is in the context of Google’s overall energy usage this year, estimated to be 48.927GW [for source see comments to the article linked to above].

The worldwide explosion of data centres and their increasing energy usage is a direct result of the spread of smart phones, tablets, apps and video-on-demand. We expect all of these things fast and free and that is what is fuelling the expansion.

The number of annually produced smartphones is expected to rise between 2010 and 2030 from around 350 million to around 3000 million units, and for tablets from 50 to 560 million units.

A worst-case projection for the global use of energy in ICT puts it at as much as 51 per cent of global electricity and 23 per cent of the globally released greenhouse gas emissions in 2030. Totally unsustainable? Right.

The Jevons Paradox

We seem to be seeing another example of the Jevons Paradox, the conundrum proposed by economist William Stanley Jevons. First postulated in the 1860s, it states that increases in efficiency will not result in savings, instead they will result in more expenditure or consumption.

Jevons argued, in his prescient 1865 book The Coal Question, that the effective and efficient use of energy leads to an increase in energy consumption. In his words:


Increased energy efficiency tends to increase energy consumption by two means. First, increased energy efficiency makes the use of energy relatively cheaper, thus encouraging increased use (the direct rebound effect). Second, increased energy efficiency leads to increased economic growth, which pulls up energy use for the whole economy (the indirect effect). It applies to energy efficiency and resource efficiency.

When people save money on saving energy they have extra capital. This inevitably gets spent resulting in more consumption. The same applies to saving money on manufacturing products by reducing the amount of resources needed. More products get produced. Economists and environmentalists often use the amount of spending as a proxy for energy consumption or ecological footprint. The only way to really reduce environmental impacts is to spend, or consume, less.

As a whole, we on our beautiful unique planet Earth are already using two planets’ worth of resources and our numbers are rising, expected to reach 10 billion by the end of the century. This includes a growing middle class that is consuming more and more, causing some minerals and other resources expected to run out according to their relative rarity over the next century.

You can see why this is a vitally important problem to solve. It is a subset of the problem: how do we give everybody an equally of good standard of life given limited resources on the planet?

A question of entropy

Ultimately it is a question of entropy. For example, urban living can be seen as an entropy accelerator: resources are depleted and downgraded and the limited availability of low entropy energy is their ultimate constraint and a constraint on long-term well-being. Local air pollution and global climate change are a high entropy expression of burning fossil fuels to power lifestyles.

Another example is the problem of entropy of recycling materials. When recycled, most wastes come out of the end of the process as a lower-level product. Take electronic waste as one example, or paper as another (during recycling the fibres become smaller and so the paper is more fragile).

Circular systems, as used in nature, where there is no waste, need to be devised. If nature provides an example where entropy does not increase, can we apply this to industrial processes and human practices?

Now that would really be something for the Google geniuses who devised the algorithms for Deep Mind and learning artificial intelligence.

Mustafa Suleyman, the co-founder of Deep Mind, is already on record as saying that it may be possible to apply their algorithms to other scenarios.

“There’s lots of other applications outside of Google”.

Really? Life outside Google? You surprise me.

Further reading:

A simple introduction to the subject of entropy, pollution, the economy and human survival is found in this article: Energy consumption and entropy release in the biosphere.

For the brave, a more complex mathematical introduction is available in this academic paper: The Impact of Entropy Production and Emission Mitigation on Economic Growth.

David Thorpe is the author of:

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