A daily routine

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I have been writing a weekly post for this blog since January 2013.  That’s more than 400 posts, which I thought sounded pretty impressive until I read about the Gentle Author who has been publishing daily since 2010 on spitalfieldslife.com.  That’s more than 4000 stories; so, I am not prolific by comparison.  And, the Gentle Author has promised to post 10,000 pieces which apparently will take until 2037.  I am unsure whether I will still be writing a weekly post in 2037 or even 2027; but, I plan to carry on for the moment.  Last week I read about another daily routine that has been sustained for nearly 40 years by Nancy Floyd.  She has been taking a daily photograph of herself since 1982 and plans to continue to her deathbed.  Her self-portrait series is available on her website and was recently featured in the FT Weekend magazine on August 8/9, 2020.  On the one hand, I am in awe of people who have the self-discipline to maintain such a daily activity; while on the other hand, I feel that there is too much I want to do and think about to stop everyday to take time out to write a blog post or snap a self portrait.  The photograph shows a portrait of me taken by my youngest daughter earlier this month – perhaps the first in series.

Where is AI on the hype curve?

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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.

The picture shows our holiday bookshelf.

Success is to have made people wriggle to another tune

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Shortly before the pandemic started to have an impact in the UK, I went to our local second-hand bookshop and bought a pile of old paperbacks to read.  One of them was ‘Daisy Miller and Other Stories’ by Henry James (published in 1983 as Penguin Modern Classic).  The title of this post is a quote from one of the ‘other stories’, ‘The Lesson of the Master’, which was first published in 1888.  ‘Success is to have made people wriggle to another tune’ is said by the successful fictional novelist, Henry St George as words of encouragement to the young novelist Paul Ovett.  It struck a chord with me because I think it sums up academic life. Success in teaching is to inspire a new level of insight and way of thinking amongst our students; while, success in research is to change the way in which society, or at least a section of it, thinks or operates, i.e. to have made people wriggle to another tune.

Thinking in straight lines is unproductive

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I suspect that none of us think in straight lines.  We have random ideas that we progressively arrange into some sort of order, or forget them.  The Nobel Laureate, Herbert Simon thought that three characteristics defined creative thinking: first, the willingness to accept vaguely defined problems and gradually structure them; second, a preoccupation with problems over a considerable period of time; and, third, extensive background knowledge. The first two characteristics seem strongly connected because you need to think about an ill-defined problem over a significant period of time in order to gradually provide a structure that will allow you to create possible solutions.    We need to have random thoughts in order to generate new structures and possible solutions that might work better than those we have already tried out; so, thinking in straight lines is unlikely to be productive and instead we need intentional mind-wandering [see ‘Ideas from a balanced mind‘ on August 24th, 2016].   More complex problems will require the assembling of more components in the structure and, hence are likely to require a larger number of neurons to assemble and to take longer, i.e. to require longer and deeper thought with many random excursions [see ‘Slow deep thoughts from planet-sized brain‘ on March 25th, 2020] .

In a university curriculum it is relatively easy to deliver extensive background knowledge and perhaps we can demonstrate techniques to students, such as sketching simple diagrams [see ‘Meta-knowledge: knowledge about knowledge‘ on June 19th, 2019], so that they can gradually define vaguely posed problems; however, it is difficult to persuade students to become preoccupied with a problem since many of them are impatient for answers.  I have always found it challenging to teach creative problem-solving to undergraduate students; and, the prospect of continuing limitations on face-to-face teaching has converted this challenge into a problem requiring a creative solution in its own right.

Source:

Simon HA, Discovery, invention, and development: human creative thinking, Proc. National Academy of Sciences, USA (Physical Sciences), 80:4569-71, 1983.