Category Archives: uncertainty

Virtual digitalism

Decorative image of 10 micron spheres in nanoscopeSome months ago I wrote about the likelihood that we are in a simulation [see ‘Are we in a simulation?‘ on September 28th, 2022] and that we cannot be sure whether are or not.  For some people, this will raise the question that if we are in a simulation, then what is real?  In his book, Reality+, David J Chalmers provides a checklist of properties possessed by real things, namely: existence, causal powers, mind-independence, non-illusoriness and genuineness.  The possession of these properties could be established by answering the five questions in the box below and we would expect real objects to possess one or more of these properties.  Objects that are found in a virtual world generated by a simulation are real objects because they have at least one, and often many of these properties, such as causal powers and independence from our minds.  We can consider them to be digital objects, or structures of binary information or bits.  This leads to a form of the ‘It-from-bit’ hypothesis because it implies that molecules are made of atoms, atoms are made of quarks, and quarks are made of bits – unless of course we are not in a simulation but we will probably never know for certain.

Source: David J Chalmers, Reality+: virtual worlds and the problems of philosophy, Penguin, 2022.

Image shows a self-assembly of 10 micron spheres viewed out-of-focus in bright-light optical microscope.

Are we in a simulation?

Decorative photograph of trains at terminusThe concept of digital twins is gaining acceptance and our ability to generate them is advancing [see ‘Digital twins that thrive in the real-world’ on June 9th, 2021].  It is conceivable that we will be able to simulate many real-world systems in the not-too-distant future.  Perhaps not in my life-time but possibly in this century we will be able to connect these simulations together to create a computer-generated world.  This raises the possibility that other forms of life might have already reached this stage of technology development and that we are living in one of their simulations.  We cannot know for certain that we are not in a simulation but equally we cannot know for certain that we are in a simulation.  If some other life form had reached the stage of being able to simulate the universe then there is a possibility that they would do it for entertainment, so we might exist inside the equivalent of a teenager’s smart phone, or for scientific exploration in which case we might be inside one of thousands of simulations being performed simultaneously in a lab computer to gather statistical evidence on the development of universes.  It seems probable that there would be many more simulations performed for scientific research than for entertainment, so if we are in a simulation then it is more likely that the creator of the simulation is a scientist who is uninterested in this particular one in which we exist.  Of course, an alternative scenario is that humans become extinct before reaching the stage of being able to simulate the world or the universe.  If extinction occurs as a result of our inability to manage the technological advances, which would allow us to simulate the world, then it seems less likely that other life forms would have avoided this fate and so the probability that we are in a simulation should be reduced.  You could also question whether other life forms would have the same motivations or desires to create computer simulations of evolutionary history.  There are lots of reasons for doubting that we are in a computer simulation but it does not seem possible to be certain about it.

David J Chalmers explains the probability that we are in a simulation much more elegantly and comprehensively than me in his book Reality+; virtual worlds and the problems of philosophy, published by Penguin in 2022.

Happy New Year!

Decorative photograph of sculpture of a skeletal person leading a skeletal dinosaurThis year I have written about 20,000 words in 52 posts (including this one); and, since this is the last post of the year, I thought I would take a brief look back at what has preoccupied me in 2021.  Perhaps, not surprisingly the impact of the coronavirus on our lifestyle has featured regularly – almost every week for a month between mid-March and mid-April when we were in lockdown in the UK.  However, the other topics that I have written about frequently are my research on the dynamics of nanoparticles and, in the last six months, on dealing with uncertainty in digital engineering and decision making.  I have also returned several times to innovation processes and transitioning lab-based research into industry.  While following the COP26 in early November, I wrote a series of three posts focussed on energy consumption and the paradigm shifts required to slow down climate change.  There are some connections between these topics: viruses are nanoparticles whose transport and dynamics we do not fully understand; and, digital engineering tools are being used to explore zero-carbon approaches to, for example, energy generation and air transport.  The level of complexity, innovation and urgency associated with developing solutions to these challenges mean that there are always some unknowns and uncertainty when making associated decisions.

The links below are grouped by the topics mentioned above.  I expect there will be more on all of these topics in 2022; however, the topic of next week’s post is unknown because I have not written any posts in advance.  I hope that the uncertainty about the topic of the next post will keep you reading in 2022! 

Coronavirus pandemic: ‘Distancing ourselves from each other‘ on January 13th, 2021; ‘On the impact of writing on well-being‘ on March 3rd, 2021; ‘Collegiality as a defence against pandemic burnout‘ on March 24th, 2021; ‘It’s tiring looking at yourself‘ on March 31st, 2021; ‘Switching off and walking in circles‘ on April 7th, 2021; ‘An upside to lockdown‘ on April 14th, 2021; ‘A brief respite in a long campaign to overcome coronavirus‘ on June 23rd, 2021; and ‘It is hard to remain positive‘ November 3rd 2021.

Energy and climate change: ‘When you invent the ship, you invent the shipwreck‘ on August 25th, 2021; ‘It is hard to remain positive‘ November 3rd 2021; ‘Where we are and what we have‘ on November 24th, 2021; ‘Disruptive change required to avoid existential threats‘ on December 1st, 2021; and ‘Bringing an end to thermodynamic whoopee‘ on December 8th, 2021.

Innovation processes: ‘Slowly crossing the valley of death‘ on January 27th, 2021; ‘Out of the valley of death into a hype cycle?‘ on February 24th, 2021; ‘Innovative design too far ahead of the market?‘ on May 5th, 2021 and ‘Jigsaw puzzling without a picture‘ on October 27th, 2021.

Nanoparticles: ‘Going against the flow‘ on February 3rd, 2021; ‘Seeing things with nanoparticles‘ on March 10th, 2021; and ‘Nano biomechanical engineering of agent delivery to cells‘ on December 15th, 2021.

Uncertainty: ‘Certainty is unattainable and near-certainty is unaffordable‘ on May 12th, 2021; ‘Neat earth objects make tomorrow a little less than certain‘ on May 26th, 2021; ‘Negative capability and optimal ambiguity‘ on July 7th, 2021; ‘Deep uncertainty and meta ignorance‘ on July 21st, 2021; ‘Somethings will always be unknown‘ on August 18th, 2021; ‘Jigsaw puzzling without a picture‘ on October 27th, 2021; and, ‘Do you know RIO?‘ on November 17th, 2021.

Do you know RIO?

Infrared image of group of people in meetingDuring the pandemic many political leaders have been heard to justify their decisions by telling us that they were following advice from scientists.  I think it was Thomas Kuhn who proposed that the views of a group of scientists will be normally distributed if the group is large enough, i.e., a bell-shaped curve with a few scientists providing outlying opinions on either end and the majority in the middle of the distribution [see ‘Uncertainty about Bayesian methods’ on June 7th, 2017].  So, it depends which scientist you consult as to what advice you will receive.  Of course, you can consult a group of experts in order to identify the full range of advice and seek a consensus; however, this is notoriously difficult because some voices will be louder than others and some experts will be very certain about their predictions of the future while others will be very cautious about predicting anything.  This is often because the former group are suffering from meta-ignorance, i.e., failing to even consider the possibility of being wrong, while the latter are so aware of the ontological or deep uncertainties that they prefer to surround their statements with caveats that render them difficult or impossible to interpret or employ in decision-making [see ‘Deep uncertainty and meta ignorance’ on July 21st 2021].  Politicians prefer a simple message that they can explain to the media and tend to listen to the clear but usually inaccurate message from the confident forecasters [see ‘Forecasts and chimpanzees throwing darts’ on September 2nd, 2020].  However, with time and effort, it is possible to make rational decisions based on expert opinion even when the opinions appear to diverge.  There are several recognised protocols for expert elicitation which are used in a wide range of engineering and scientific activities to support decision-making in the absence of comprehensive information.  I frequently use a form of the Sheffield protocol developed originally to elicit a probability distribution for an unknown uncertainty from a group of experts.  Initially, the group of experts are asked individually to provide private, written, independent advice on the issue of concern.  Subsequently, their advice is shared with the group and a discussion to reach a consensus is led by a facilitator. This can be difficult if the initial advice is divergent and individuals hold strong views.  This is when RIO can help.  RIO stands for Rational Impartial Observer and an expert group often rapidly reach a consensus when they are asked to consider what RIO might reasonably believe after reading their independent advice and listening to their discussion.


Anthony O’Hagan, Expert knowledge elicitation: subjective but scientific, The American Statistician, 73:Sup.1, 69-81, 2019.