I have written in the past about my research on the development and use of digital twins. A digital twin is a functional representation in a virtual world of a real world entity that is continually updated with data from the real world [see ‘Fourth industrial revolution’ on July 4th, 2018 and also a short video at https://www.youtube.com/watch?v=iVS-AuSjpOQ]. I am working with others on developing an integrated digital nuclear environment from which digital twins of individual power stations could be spawned in parallel with the manufacture of their physical counterparts [see ‘Enabling or disruptive technology for nuclear engineering’ on January 1st, 2015 and ‘Digitally-enabled regulatory environment for fusion power-plants’ on March 20th, 2019]. A couple of months ago, I wrote about the difficulty of capturing tacit knowledge in digital twins, which is knowledge that is generally not expressed but is retained in the minds of experts and is often essential to developing and operating complex engineering systems [see ‘Tacit hurdle to digital twins’ on August 26th, 2020]. The concept of tapping into someone’s mind to extract tacit knowledge brings us close to thinking about human digital twins which so far have been restricted to computational models of various parts of human anatomy and physiology. The idea of a digital twin of someone’s mind raises a myriad of philosophical and ethical issues. Whilst the purpose of a digital twin of the mind of an operator of a complex system might be to better predict and understand human-machine interactions, the opportunity to use the digital twin to advance techniques of personalisation will likely be too tempting to ignore. Personalisation is the tailoring of the digital world to respond to our personal needs, for instance using predictive algorithms to recommend what book you should read next or to suggest purchases to you. At the moment, personalisation is driven by data derived from the tracks you make in the digital world as you surf the internet, watch videos and make purchases. However, in the future, those predictive algorithms could be based on reading your mind, or at least its digital twin. We worry about loss of privacy at the moment, by which we probably mean the collation of vast amounts of data about our lives by unaccountable organisations, and it worries us because of the potential for manipulation of our lives without us being aware it is happening. Our free will is endangered by such manipulation but it might be lost entirely to a digital twin of our mind. To quote the philosopher Michael Lynch, you would be handing over ‘privileged access to your mental states’ and to some extent you would no longer be a unique being. We are long way from possessing the technology to realise a digital twin of human mind but the possibility is on the horizon.
More than a decade ago, when I was a Department Head for Mechanical Engineering, people used to ask me ‘What is Mechanical Engineering?’. My answer was that mechanical engineering is about utilising the material and energy resources available in nature to deliver goods and services demanded by society – that’s a broad definition. And, mechanical engineering is perhaps the broadest engineering discipline, which has enable mechanical engineers to find employment in a wide spectrum areas from aerospace, through agricultural, automotive and biomedical to nuclear and solar energy engineering. Many of these areas of engineering have become very specialised with their proponents believing that they have a unique set of constraints which demand the development of special techniques and accompanying language or terminology. In some ways, these specialisms are like the historic guilds in Europe that jealously guarded their knowledge and skills; indeed there are more than 30 licensed engineering institutions in the UK.
In an age where information is readily available [see my post entitled ‘Wanted: user experience designers‘ on July 5th, 2017], the role of engineers is changing and they ‘are integrators who pull ideas together from multiple streams of knowledge’ [to quote Jim Plummer, former Dean of Engineering at Stanford University in ‘Think like an engineer‘ by Guru Madhaven]. This implies that engineers need to be able work with a wide spectrum of knowledge rather than being embedded in a single specialism; and, since many of the challenges facing our global society involve complex systems combining engineering, environmental and societal components, engineering education needs to include gaining an understanding of ecosystems and the subtleties of human behaviour as well as the fundamentals of engineering. If we can shift our engineering degrees away from specialisms towards this type of systems thinking then engineering is likely to enormously boost its contribution to our society and at the same time the increased relevance of the degree programmes might attract a more diverse student population which will promote a better fit of engineering solutions to the needs of our whole of global society [see also ‘Where science meets society‘ on September 2nd 2015).