Reducing Queues with Ask-Learn-Share

Queues are an integral part of a hospital: getting into a car park, waiting to see the clinician, collecting medication at the hospital pharmacy, making appointments, and finally getting out of the hospital car park. But my recent experience of attending a hospital started me wondering if there was a better way.

When trying to book an appointment to see an Audiologist at our local hospital to carry out some routine maintenance on an elderly parent’s hearing aid we were firmly told that it would be better to attend a “drop in” at the the Audiology Department. So we “dropped in” at 9:30 am on a Monday morning and found that there were six people ahead of us. Settling down to read the papers, magazines, drinking a few glasses of water, then after reading the posters on the wall I decided to join the queue for the receptionist to ask where we were in the queue. After about ten minutes I got to ask my question and there were two people ahead of us, this was after two hours! After going for a walk around the hospital I came back to find that we were still waiting. So I joined the queue for the receptionist to find out that there were still two people ahead of us. By now our elderly parents were getting agitated to the point of feeling ill and therefore we cancelled our position in the queue and returned home to try and book an appointment for sometime in the future.

What was frustrating was not waiting in the queue, queues are a way of life, but that there were other parts of the NHS that we have used that were very good at managing queues and therefore why hadn’t our hospital adopted any of their approaches. I then remembered a technique that I have used when trying to solve engineering, organisational and business problems called ASK-LEARN-SHARE. The technique is applied in three stages:

  • When a problem arises, the first step is to ASK: is this a new problem or have others encountered it? What information is available? What needs to be learned to handle the problem? Who can help?
  • What can be learned from the experience of others? How does the new situation compare and contrast? what do we LEARN from our own approach to solving the problem?
  • How and when can we SHARE our experience and learning with others?

There can be two problems with a hearing aids: maintenance e.g. replacing batteries, tubes and other components and the device is broken or not working properly. In the first case of maintenance using the ASK stage resulted in a few searches on the web and found that a number of other hospitals made information available on how to replace hearing aid parts, for example Retubing the earmold from Leicester, Manchester and a video from Notingham University Hospitals. Included in the information are aspects of LEARN by showing, usually in a step-by-step format, how the parts can be replaced. Making the information available they have SHARED. Further searches on the web found suppliers for tubing and other parts for hearing aids and therefore it could be possible to carry out the maintenance of the equipment at home which would save both the NHS and patients time and effort. Of course people may not feel confident at carrying out their own maintenance but when the hearing aid is initially installed then a few minutes showing how to carry out the maintenance work to the patient, or their carer may help.

The second case of the hearing aid being broken or not working properly requires an expert and therefore attending the Audiology Department in a hospital. Yet again starting with ASK, or in my case searching on the web and based on my own experience of queuing of other services, there are many queue management systems available. Also within the NHS, there are many good examples: the Patient Access system which is used by our local GP is very good when booking an appointment when it is not an emergency. Or a better system, and my favourite app, is the NHS Give Blood which is very easy to use and appointments can be changed quickly and effectively. In the hospital that we attended there were signs that they had a queuing system that used tickets and a display giving information about the patients position in the queue but it was switched off which resulted in a queue to see the receptionist! Of course while in a queue an emergency case may need to jump ahead but feedback to the rest of the waiting people would be received with understanding and therefore reduce levels of frustration. There are many display systems in the NHS that can manage queues that include emergency cases. The NHS is full of different types of queues and the problems in managing them therefore there is a lot to LEARN, and they could be the leading experts in queue management which they could SHARE across the NHS and other organisations.

Hearing loss within the population is expected to increase by 20% by 2035 therefore there will be increasing demand for maintenance and repair of hearing aids. Using the technique of ASK-LEARN-SHARE to improve the support of these devices either by carrying the work out at home or more effective hospital attendance could reduce time and effort for both the NHS and patients.

As for our particular situation we will be exploring the possibility of carrying out our maintenance work at home or if we have to attend the hospital then we will be booking an appointment. In the meantime I will be day dreaming of a time when at the press of a few buttons on my smart phone we can join a queue and our problems can be resolved quickly.

Could Alexa Write Poetry?

Can a computer be creative? This question has been asked since the invention of the machine and each breakthrough in the technology increases the speculation. But can a computer match, or even succeed, the creativity of a human?

In Marcus du Sautoy’s recent book The Creativity Code he asks, can computers be creative in today’s age of machine learning? and then goes onto discuss “the Lovelace test”: a machine must produce something “new, surprising and valuable”, and do so in such a way that its programmers are unable to explain the feat. Although a computer may pass the test and generate a piece of work that maybe considered art, what is missing in the discussion is the interpretation of the work by a human, or as summarised by E. A. Buccchianeri, “Art is in the eye of the beholder, and everyone has their own interpretation”.

There is a long history of computer generated art. Starting in the 1950s computers were used to generate visual art which has continued up to the present time but they tend to be used by artists as a digital paint brush. With the increasing development of Artificial Intelligence, where there is no influence of the programmer, computers have been left to generate art visual art. There is a similar story for computers creating music music, and recently poetry.

All of the development in computer creativity opens up interesting questions about whether a computer is simulating the creative process or it is genuinely creating something new and novel. For example when a computer writes poetry it will use algorithms to start with one line and then starts to generate additional lines that rhyme according to traditional poetic structures, say a sonnet. To allow the computer to use figurative language, the algorithm uses mathematics to create metaphors and similes. The following is an example of a computer generated poem

A wounded deer leaps highest,
I’ve heard the daffodil I’ve heard the flag to-day
I’ve heard the hunter tell;
‘Tis but the ecstasy of death,
And then the brake is almost done,
And sunrise grows so near
sunrise grows so near
That we can touch the despair and
frenzied hope of all the ages

but when compared with say the House of Reflections by Olive Cooper, 12 years ( from On Common Ground by Jill Pirrie ):

I see my face in the saxophone,
Stretched and curved.
Sun slides around it
And bounces off the walls.
The zig-zag pattern at the carpet
Sinks into the shiny black piano,
And I move in the dead television.
I see two selves in the photo glass,
Years between us.
Sun on the garden bird bath makes wavy
Sea patterns on the ceiling.
Leaf shadows sweep across the wall.
Everything moves and all is still.

there is a clear difference. For example Olive’s poem has a subject and it is full of evocative images that bring the poem to life in the mind of the reader, or at least it did for me. Although there are some interesting images in the computer generated poem, it lacks any form of coherence. I am assuming it is about death, but it could be about death in a battle or maybe something else! Also, there is no title in the computer generated poem which can be an important part of the poem and signals to the reader what it is about.

Computer technology is always improving therefore it is interesting to speculate how far a it could be developed so that it can write a poem as good as a human. Imagine asking Amazon’s Alexa, or any other similar device, to “write a poem about chocolate chip cookies!” Alexa’s poetry writing capabilities would have to include information about a chocolate chip cookie: the components of a cookie, how it is made, its smell, taste, what it feels like to hold it, the sensations when it is eaten and so on. Alexa would need information about the history of the cookie, the social context of the cookie, for example when and where it is eaten, conversations it may overhear, where it was being eaten, and any other information that an imagination could generate. All of this information could be stored in a computer and would be the source of lines and words for the poem. Once a palette of information had been gathered then the next stage would be to use the many techniques that a poet employs to generate a poem: metaphors, similes, different types of rhythm and rhyme, the social importance of certain words, a personal history of eating cookies etc. This is something that Alexa using Artificial Intelligence could probably do. Finally Alexa would have to produce a poem that could not have been influenced by the programmer, in other words write it itself, in a way that connects with a reader in an emotional way - a very tall order! But as the list of capabilities show Alexa would be simulating the process of writing poetry and therefore it would not guarantee that the poem it wrote would be profound.

The highest accolade that a poet can receive is to win the Noble Prize for Literature which is a recognition of the impact that their poetry has had on society and beyond. Many of the citations set the standard that computer generated poetry would have to reach, for example the citation for Seamus Heaney is: “for works of lyrical beauty and ethical depth, which exalt everyday miracles and the living past.” For a computer generated poetry to reach these levels it would have to have the skill, imagination, subtleties in word use, personal history, and an ability to make a particular subject into something that is universal, which is something that the great poets exhibit in their poetry. But finally, it would be judged by a human and it would seem impossible that a computer would ever be able to write a good poem because it would not be able to experience the life of humans.

Computer technology continues to develop and will break into new areas of our lives, and possibly open up new forms of creativity, but as discussed above, it will never be creative when compared to a human.

Can AI Learn From The Moon?

The Apollo 11 moon landing remains one of the greatest achievements in human endeavour and demonstrated what can be achieved through the combination of technology and people. But are there there any lessons for today’s emerging technology that can be taken from a decades old project?

I remember watching the Apollo 11 moon landing on a black and white television and picking up on the excitement of the announcers reporting on every stage of the moon landing. Even today the whistle-beep sound punctuating communication between the astronauts and Huston brings back memories of early July in 1969. Since then I have always been fascinated by the technology that carried three people: Neil Armstrong, Michael Collins and Edwin “Buzz” Aldrin, in something that seemed no bigger than a large skip over 235,000 miles, land them on the moon and then bring them safely back.

Winding the clock forward to today and we are abounding in new technology that is breaking into all areas of life from the production of food to medicine and transportation. But one - Artificial Intelligence - has caught the publics attention. Articles fill the newspapers and the web about AI and journalists, within a few paragraphs, link the eventual demise of human life from the technology with their imagination heightened by films such as The Matrix, The Terminator and epitomised by the sinister computer HAL in 2001: A Space Odyssey.

Artificial Intelligence is a technology that has been developing since the mid 1940s and started with the development of a mathematical model for a neuron: the basic unit of a human brain. Its development has accelerated in the last ten years by the increase in computing power for less cost, and the capability of gathering what feels like the near infinite amount of data. Artificial Intelligence uses the mathematical model of a neuron in a simplistic way to simulate a neuron in the brain and when connected together in a network it is used to “learn” by analysing data. For example, being able to distinguish between the pictures of cats and dogs. But AI can neither explain nor do they understand which are some of the key characteristics of being human. Also, the largest number of neurons used in the current applications of Artificial Intelligence are in the millions whereas the best estimate for the neurons in a human brain is 100 billion or 100,000,000,000. Even if a computer could handle the same number of neurons as a human brain then how they connect to each other to create the wide range of human characteristics would propbably remain a mystery for a very long time. However, there are a number of applications of Artificial Intelligence that are in everyday use. For example, communicating with people, in systems such as Siri and Alexa and guiding our purchase of goods and services with, Amazon and Netflix. I am sure that technology will continue to develop and become a greater part of our lives, and the concerns about acting more like a human are starting to be researched in projects such as DAPRA’s project: Building Trusted Human-Machine Partnerships

Behind the Apollo 11 moon landing there were thousands and thousands of people involved who covered a wide range of skills. But there was one area that fascinated me most which was the design of the software that kept the space craft on its flight path and safely landed the astronauts on the moon. But even using state of the art software there were two potentially serious events that could have ended in tragedy. The first event was the computer overloaded with extraneous data just as they were about to land and the mission could have been aborted. The ground controllers and Neil Armstrong knew that by restarting the computer it would would keep the essential programs running for the landing and the mission continued. However, a second problem started to loom. Neil Armstrong’s attention was drawn by the appearance of a rocky crater that the guidance system was taking them too. It was to late to retarget the computer for a different trajectory. Instead, he took over the landing from the computer and manoeuvred across the crater and landed at Tranquility Base.

What can be learned form the moon landing? Without the intervention of the astronauts the mission would either of been aborted or ended in tragedy. Without the technology the astronauts would not have reached the moon. One depended on the other. Therefore it is important to keep people at the centre of the technology and that they fully understand its limits. Artificial Intelligence will bring many benefits but only if it enhances people’s capabilities rather than replace them!

Different Perspectives

Although I can’t draw without the aid of a ruler and the limits of my painting skills are decorating, I have always found the paintings produced by an artist fascinating. It was this fascination that took me down to David Hockney’s The Bigger Picture exhibition in the Royal Academy a few years ago.

Jostling for position around the paintings, the words of the American author Jerzy Kosinski were rolling around in my mind “The principles of true art is not to portray, but to evoke.” Eventually I found enough space to take in a large picture of a woodland scene. Questions started to build up: was there a wind pushing the leaves to point along the path? why the choice of colours which felt like a Walt Disney production? What was the artist trying to evoke?

Out of the corner of my eye a tall figure with bushy grey hair, and long sideburns, caught my attention as he leaned closer to the painting. His thick fingers lifted up his glasses and propped them onto his forehead, and slowly took in the picture. Then spoke in a low voice, ‘Why .. why .. why?’ Pulling himself straight he slowly pulled his glasses down and looked up and with one final ‘why?’ I froze. Up to that point in time I had been absorbed in the painting trying to work out my own interpretation. Now my thoughts were being being interrupted by a stranger. I turned to see a man in a crisp light blue jacket and an open necked which gave him an air of authority. He turned his rugged face to me and his blue eyes seemed to widen as if to reinforce the question. But before I could try and find a reply he went on, ‘Why is there so much of it? It is far to big and overblown?’ he paused, then nodding his head, continued, ‘It is it so crude’. He then turned back to me. I scrambled for a few thoughts, after all this is David Hockney one of the greatest living artists, he must have been trying to say something. I started to reply, ‘I don’t know but there is something I like about it.’ He turned back to the picture and waving his right hand as though he was painting each line rattled off: ‘Picaso, Brueghel, or a Van Gogh, Picasso, Fauve or even a Frederick Gove may have influenced him, but he has failed!’ Some of the artists I had heard of, some I hadn’t. Then shaking his head again, ‘He was such a talented draughtsman …each touch of the brush capturing something about his subjects. Shrugging his shoulders, ‘Where has it gone, its as if the technology that he dabbles with has robbed him of his skills.’ At last I found a few words, ‘But isn’t he trying to tell us something about the countryside?’ I felt that this was a weak reply, and quickly followed on ‘Isn’t he trying to look at it differently?’ There I thought, I had replied, and hoping that the discussion was closed. But he came back, ‘In what way?’ After large parts of my life living in the countryside, I felt that I could reply with some confidence, ‘Look it is not a picture of the countryside, but for me’, stressing the me, ‘the exaggeration of colour and textures is making me think about looking more closely at woods, what am I really seeing?’ He turned and looked at me square on then turned his head to look at the picture then turned back to face me. By then people were starting to gather around us straining to find what was going on. ‘Money’ the man grunted - he stood back and looked around and in a tone that felt he had drawn a conclusion ‘money!’’, what we have paid to see this is propping up RA so that it can keep rolling out this sort of rubbish! He them turned and pointed to somewhere outside of the building, ‘It would be better up for sale on those railings across the way.’

Coming through from the next gallery I saw a security guard moving towards us. I turned back to the stranger and he gone! I never saw him again.

Later that day, on the train back to Crewe, I couldn’t get the stranger out of my mind. Who was he? Why did David Hockney’s work evoke such a reaction in him. I still liked the picture, but I couldn’t put my finger on why, and maybe that is what art does - no easy answers. I’ll never get a chance to ask David Hockney what he was trying to express or what feelings he was tying to evoke. But I continue to look more intensely at the composition of trees and plants when I walk through the local woods and maybe that is what is meant by the bigger picture.

Surely You're Joking, Prof. Wittgenstein!

Jokes and philosophy are an odd combination. Philosophy is mainly academic in flavour; full of terminology that locks most people out. Jokes make most people laugh. However Norman Malcolm wrote in Ludwig Wittgenstein: A Memoir, that Wittgenstein remarked “that a serious and philosophical work could be written that would consist entirely of jokes ( without being facetious )”. Jokes? Philosophy? Further investigation is required.

Jokes come in many forms: puns, funny gestures, pranks, irony, sarcasm, nonsense etc. Anything that in general makes us laughs. Comedians, of whom there are many fine examples, deliver jokes. Not a stand-up philosopher. Apart from a comedian’s sense of timing in delivering a joke, they can use gestures. Watch any clip of Tommy Cooper and you’re laughing before he speaks! All skills that a philosopher lacks.

However, Wittgenstein is clear: jokes need to be written down and therefore they must make the reader laugh without the aid of speaking or gestures. Some jokes that are delivered by a comedian can be funny in writing, in particular one-liners, for example one from Tim Vine “Crime in multi-storey car parks. That is wrong on so many different levels.” Wittgenstein also stresses that the jokes have not to be facetious. No “why did the chicken cross the road ?” type jokes. Also, he was not considering jokes about philosophers but rather about philosophical problems.

So what was Wittgenstein on about? It is difficult to image Wittgenstein laughing at a joke. He was mostly in a state of tension with periodic bouts of suicidal thoughts. Although there are some remarks in Wittgenstein’s work about humour and jokes, they are never developed enough to gain any insight.

Early in his life Wittgenstein read the philosophical works of Schopenhauer which may have influenced his ideas on the connection between jokes and philosophy. Schopenhauer’s view was that a joke lies in an object that can, at a stretch, be classified under a concept, even though it differs greatly from the objects usually classification. We laugh involuntarily when we grasp the inconsistency: when we see the object doesn’t really fit the concept after all. Sounds complicated but an example may illustrate what he is getting at. Amongst the many Spike Milligan jokes that makes me laugh is: “A man loses his dog, so he puts an ad in the paper. And the ad says, ‘Here, boy!’” The phrase ‘Here boy’ said within the context of a man walking his dog in a park we immediately understand without any problems or confusion, if not irritated when we are trying to soak up the sun. However when we move the context by placing the phrase in a newspaper we laugh at the inconsistency.

Wittgenstein’s view was that problems in philosophy arise when there is a failure to recognise that the words being used have lost their sense. When we come across a misuse of words, when they have lost their meaning, they could create an inconsistency. And rather than spending lots of time puzzling over the meaning of the sentence we should grasp it for what it is: nonsense, laugh, and move on.

So how would it work? My attempt is based on solipsism, the view or theory that the self is all that can be known to exist, and goes ‘A man thought he was the only person in the world, until he looked in the mirror’. Would Wittgenstein have laughed? Maybe not but I would hope for a wry smile.