Robots
Ingrained into our collective consciousness through sci-fi books, film and TV were visions of these robots shouldering our household chores, liberating us to chase creative passions and relish moments with loved ones.
Only for reality to humble us and now we argue with a self-checkout machine that the item is, in fact, in the bagging area.
What is a robot?
There is, no fast and ready definition of a robot. One definition is that a robot is “A machine resembling a human being and able to replicate certain human movements and functions automatically” which most of us will think of the as guy in the picture below.
The broadest while remaining accurate definition of a robot that I’ve been able to find is from speculative designer James Auger;
“It [a robot] can sense its environment. It can compute decisions based on this sensory information. It can act on these decisions (e.g. through mechanical or electronic means) “
James Auger
Where did “robot” come from?
Only really useful in a pub quiz or if you’ve run out of things to say at a dinner with only engineers as guests
The modern term robot derives from the Czech word robota (meaning “forced labour” or “serf”), used in Karel Čapek’s play R.U.R. Rossum’s Universal Robots (1920). The play’s robots were manufactured humans, heartlessly exploited by factory owners until they revolted and ultimately destroyed humanity…not much has changed in a hundred years.
What are they up to these days?
Delivery Robots
Autonomous delivery robots are able to take precious cargo around a warehouse or a town. A few cities are already implementing them to see how they do. However, in public, they could be considered a treasure chest on wheels.
Could they be trusted to deliver care packages and medicine to loved ones?
Soft (and sometimes wearable) Robotics
As it sounds, instead of metal and gear robotics, soft robotics can be made of inflatable material. These are being developed as a lightweight solution to help with upper limb strength and dexterity and people retain their independence longer. Alternatively, they could be used to give you instant hunky biceps.
Surgical Robots
Remote precision surgery with minimal trauma to the patient. Usually costly, equipment is coming down in price. Could it be something that a hospice of the future could offer as a part of a specialist treatment?
Social Robots
Companionship and connection. Social robots are being used in lots of different ways to be a friend to someone, to remind them of their routines, and to keep your doctors updated with your condition. Would you want one in your home?
Humanoid Social Robot
Animal Social Robot
Micro+Nanobots
Things are getting really small, but their ambitions are massive. A way to tackle illnesses precisely without hurting healthy cells in the body, at least in theory. There’s still a lot we don’t know and a lot that could go wrong.
In many of the examples above you may already be able. to see quick applications in a hospice context. However that was a lot to take in all at once, you may have a lot of thoughts about each one of these types of robots that would be useful to jot down here.
Artificial Intelligence
AI has been portrayed as all knowing and coldly logical without bias, usually resulting in a dialogue which states that for the survival of civilisation and the planet, all. humans. must. die.
In reality it’s the wizard behind advertising suggestions and predictive text such as ‘You may also like’ and then suggest 5 different toilet seats to me like I’m ducking collecting them now.
What is Artificial Intelligence?
Artificial Intelligence (AI) is an umbrella term for computer software that mimics human cognition in order to perform complex tasks and learn from them. It’s as easy and complicated as that.
What is AI up to these days?
A lot… but here are the three main types of AI we will look at so you know when we combine it with a cybernetic assassin and send it back in time to kill Sarah Connor, which type of AI it will be!
Machine Learning (ML)
Machine learning is a branch of artificial intelligence (AI) that focuses on teaching computers to learn and make decisions without being explicitly programmed for each specific task. It’s like giving computers the ability to learn from experience and improve their performance over time.
Have you ever noticed when you’ve been looking for something on the internet and then you keep getting adverts for similar things? That’s Machine Learning.
Deep Learning (DL)
Deep learning is a specific type of machine learning that is inspired by how our brains work. It is a way for computers to learn and make decisions by imitating the structure and function of the human brain’s neural networks. This is how The Terminator operated…
Natural Language Processing (NLP)
NLP is a specific field of machine learning that involves teaching computers to understand, interpret, and generate human language in a way that is meaningful and useful. There are a growing number of free websites on which you can use NLPs. Most notable is ChatGPT by OpenAI. Give it a go yourself, its quick sign up and costs nothing to use.
I personally find it quite useful as a thinking partner, it does not give perfect answers but it’s good at checking your thinking blindspots.
For inspiration, you could ask:
“Can you summarize the Magna Carta?”
“Write me a poem about the most beautiful egg in the world”
“I have to write a web page about AI, what do I do?”
Limitations: ChatGPT only knows up to 2022, it is text-based so this particular NLM can’t paint you a picture but others can like Dall-E 2 also by OpenAI, and doesn’t have access to the internet so you can’t ask it to book for you the cheapest flights to Barbados.
What can they do in the hospice?
- Early Detection and Diagnosis: Leveraging medical data, AI becomes Sherlock Bones (…they can’t all be zingers), detecting subtle disease indicators within images and records. By recognizing intricate patterns in these images from data, it can trigger medical interventions, potentially preventing conditions from progressing to advanced stages and improving patient prognoses.
- Generate, Adapt, and Predict Care Plans: AI and healthcare data can help create dynamic care plans that are finely tuned to individuals and their preferences. These plans evolve in response to changing health and personal data. This combo of personalization and foresight optimizes treatment strategies.
- Specialized Pharmaceuticals Creation and Prescription: In the realm of pharmaceuticals, AI acts as a catalyst for innovation. It swiftly identifies promising drug candidates by scrutinizing molecular structures, a process that once consumed years. Moreover, AI assists clinicians by considering multifaceted patient information, suggesting tailored medications with precision and minimizing the risk of adverse interactions.
- Combining with Robots and Wearable Devices: The convergence of AI, robots, and wearable devices may transform patient care. Robots, guided by AI, perform intricate surgeries and provide attentive support to medical teams. Simultaneously, wearable devices gather real-time health data, which AI interprets to furnish insights and early warnings, allowing for proactive interventions and reducing the need for frequent hospital visits.
What can’t they do?
- ‘Common Sense’ Understanding: AI struggles to grasp everyday things we know, like how to act in situations. It can miss basic knowledge that people find easy, making it tricky for AI to make smart choices in new or unusual situations. AI might read, “People fall in love at first sight,” and think it’s about people physically falling down when they meet, which is only really true at Concert Square at around 2am on a Friday night.
- Understanding Big Cause and Effect: AI has trouble seeing how big actions lead to big results. It can’t understand complex chain reactions like humans do, making it less skilled at predicting long-term outcomes. If AI sees that selling ice cream increases drownings, it could wrongly think ice cream causes accidents, not realizing it’s because both happen in hot weather.
- Morals and Recognizing Bias: AI doesn’t know what’s right or wrong on its own. It can copy biases from the data it learns from, which is human-created so it will essentially perpetuate that human bias. For instance, an AI hiring system might reject names common in certain cultures because it learned from biased data, unknowingly favouring certain groups.
- Human Connection: While AI can talk like us, it doesn’t truly feel emotions or understand feelings like people do. It can’t replace the warmth and understanding that comes from connecting with other humans. AI can chat, but it won’t truly feel happy for you when good things happen, or understand why you’re sad when something goes wrong.
- Take All Jobs: It just can’t.
Activities
We’d like you to hear some of the pros, cons, opportunities, and concerns you may have about any of the technology that you have read about above or possibly technology you have not seen here today but are interested in its application to the hospice service.
However, we have to be official with this so if you haven’t filled out a participant consent form for our online workshops yet please do so now and email it to me at a.tibbles@liverpool.ac.uk before continuing.
Once that is done you can fill out the forms below to your heart’s content as many times as you like.
The Inclusionaries Lab 