I feel that I am moving to the next level of experience with online meetings but I am unsure that it will address the slow down in productivity and a loss of creativity being reported by most leaders of research groups to whom I have spoken recently. About a month ago, we organised an ‘Away Day’ for all staff in the School of Engineering with plenary presentations, breakout groups and a Q&A session. Of course, the restrictions induced by the pandemic meant that we were only ‘away’ in the sense of putting aside our usual work routine and it only lasted for half a day because we felt a whole day in an online conference would be counter productive; nevertheless, the feedback was positive from the slightly more than one hundred staff who participated. On a smaller scale, we have experimented with randomly allocating members of my research team to breakout sessions during research group meetings in an attempt to give everyone a chance to contribute and to stimulate those serendipitous conversations that lead to breakthroughs, or least alternative solutions to explore. We have also invited external speakers to join our group meetings – last month we had a talk from a researcher in Canada. We are trying to recreate the environment in which new ideas bubble to the surface during casual conversations at conferences or visits to laboratories; however, I doubt we are succeeding. The importance of those conversations to creativity and innovation in science is highlighted by the story of how Emmanuelle Charpentier and Jennifer Doudna met for the first time at a conference in Puerto Rico. While wandering around San Juan on a warm Caribbean evening in 2011 discussing the way bacteria protect themselves against viruses by chopping up the DNA of the virus, they realised that it could be turned into molecular scissors for cutting and editing the genes of any living creature. They went home after the conference to their labs in Umea University, Sweden and UC Berkeley respectively and collaborated round the clock to implement their idea for which they won this year’s Nobel Prize for Chemistry. Maybe the story is apocryphal; however, based on my own experience of conversations on the fringes of scientific meetings, they are more productive than the meeting itself and their loss is a significant casualty of the COVID-19 pandemic. There are people who point to the reduction in the carbon footprint of science research caused by the cancellation of conferences and who argue that, in order to contribute to UN Goals for Sustainable Development, we should not return to gatherings of researchers in locations around the world. I agree that we should consider our carbon footprint more carefully when once again we can travel to scientific meetings; however, I think the innovations required to achieve the UN Goals will emerge very slowly, or perhaps not all, if researchers are limited to meeting online only.
If you looked closely at our holiday bookshelf in my post on August 12th 2020, you might have spotted ‘The Living Mountain‘ by Nan Shepherd [1893-1981] which a review in the Guardian newspaper described as ‘The finest book ever written on nature and landscape in Britain’. It is an account of the author’s journeys in the Cairngorm mountains of Scotland. Although it is short, only 108 pages, I have to admit that it did not resonate with me and I did not finish it. However, I did enjoy the Introduction by Robert MacFarlane and the Afterword by Jeanette Winterson, which together make up about a third of the book. MacFarlane draws parallels between Shepherd’s writing and one of her contemporaries, the French philosopher, Maurice Merleau-Ponty [1908-1961] who was a leading proponent of existentialism and phenomenology. Existentialists believe that the nature of our existence is based on our experiences, not just what we think but what we do and feel; while phenomenology is about the connections between experience and consciousness. Echoing Shepherd and in the spirit of Merleau-Ponty, MacFarlane wrote in 2011 in his introduction that ‘we have come increasingly to forget that our minds are shaped by the bodily experience of being in the world’. It made me think that as the COVID-19 pandemic pushes most university teaching on-line we need to remember that sitting at a computer screen day after day in the same room will shape the mind rather differently to the diverse experiences of the university education of previous generations. I find it hard to imagine how we can develop the minds of the next generation of engineers and scientists without providing them with real, as opposed to virtual, experiences in the field, design studio, workshop and laboratory.
I suspect that artificial intelligence is somewhere near the top of the ‘Hype Curve’ [see ‘Hype cycle’ on September 23rd, 2015]. At the beginning of the year, I read Max Tegmark’s book, ‘Life 3.0 – being a human in the age of artificial intelligence’ in which he discusses the prospects for artificial general intelligence and its likely impact on life for humans. Artificial intelligence means non-biological intelligence and artificial general intelligence is the ability to accomplish any cognitive task at least as well as humans. Predictions vary about when we might develop artificial general intelligence but developments in machine learning and robotics have energised people in both science and the arts. Machine learning consists of algorithms that use training data to build a mathematical model and make predictions or decisions without being explicitly programmed for the task. Three of the books that I read while on vacation last month featured or discussed artificial intelligence which stimulated my opening remark about its position on the hype curve. Jeanette Winterson in her novel, ‘Frankissstein‘ foresees a world in which humanoid robots can be bought by mail order; while Ian McEwan in his novel, ‘Machines Like Me‘, goes back to the early 1980s and describes a world in which robots with a level of consciousness close to or equal to humans are just being introduced to the market the place. However, John Kay and Mervyn King in their recently published book, ‘Radical Uncertainty – decision-making beyond numbers‘, suggest that artificial intelligence will only ever enhance rather replace human intelligence because it will not be able to handle non-stationary ill-defined problems, i.e. problems for which there no objectively correct solution and that change with time. I think I am with Kay & King and that we will shortly slide down into the trough of the hype curve before we start to see the true potential of artificial general intelligence implemented in robots.
Recently, I visited a local artist to choose a painting for a birthday present. He showed me a pair of small oil paintings in which I had expressed an interest via photographs he had sent me by email. I agreed to buy both of them and then we drifted into his studio where he showed me the pieces he was working on. There were many unfinished paintings and he described how difficult it was to finish some of them. He measured the time taken on some of them in months and, for a few, in years. I was struck by the similarity with scientists who indulge in slow-motion multi-tasking and switch between research projects in different fields, often leaving something unfinished to focus on something else and then returning to pursue the original research topic [‘Slow-motion multi-tasking leading to productive research‘ on September 19th, 2018]. I suspect both artists and scientists who indulge this approach are looking to achieve ‘a perfect balance of their conscious and unconscious life’ out of which Barbara Hepworth believed ideas are born and realized [see ‘Ideas from a balanced mind‘ on August 24th, 2016].