AI for Healthcare Robotics

Eduard Fosch-Villaronga, Hadassah Drukarch

• Editore: CRC Press
• Anno: 2022
• ISBN:
  9781000570830
• Edizione: 1
• Argomento: Ciencia de la computación
• Categoria: Inteligencia artificial (IA) y semántica

What is artificial intelligence (AI)? What is healthcare robotics? How can AI and healthcare robotics assist in contemporary medicine?

Robotics and AI can offer society unimaginable benefits, such as enabling wheelchair users to walk again, performing surgery in a highly automated and minimally invasive way, and delivering care more efficiently. AI for Healthcare Robotics explains what healthcare robots are and how AI empowers them in achieving the goals of contemporary medicine.

1 __________ DEFINING THE DOMAINS OF ROBOTICS AND ARTIFICIAL INTELLIGENCE

DOI: 10.1201/9781003201779-2

1.1 The Importance of Definitions

Precise terminology has always been important. Even if definitions are not an outcome in itself but merely a single step in the long process of understanding, terms, words, and vocabulary, in general, are still the primary reference we acknowledge and to which we turn to define and understand concepts, ideas, and notions. In one of his six works, Topics, the Greek philosopher Aristotle already identified the importance of definitions and adequate terminology, which became a central part of his philosophy. Definitions were also an important matter for his teacher Plato and the Early Academy. In fact, concerns related to the adequacy of definitions and correct terminology are at the center of the majority of Plato’s dialogues, some of which put forward methods for finding definitions for the understanding of this world. For Aristotle, a definition should be defined as ‘an account which signifies what it is to be for something.’ This phrase and its many variants point out a crucial element in understanding the role and importance of definitions in our understanding of the world; giving a definition is saying, of some existent thing, what it is, and not simply specifying the mere meaning of a word. Put simply: Definitions formulate their essence.

In general terms, definitions are called into existence to create more clarity and avoid misunderstandings when discussing a particular subject. However, not all concepts are easy to describe. For instance, consider the term emotion. Everyone knows what emotions are until asked to provide a definition. Likewise, there are also many definitions for what we understand as intelligence. Even experts do not seem to agree on what intelligence is when they are asked to define it. Something similar happens with the word robot or with the phrase artificial intelligence. Still, knowing the precise terminology is crucial, especially when we try to apply and understand the same concepts in different contexts.

This is particularly noticeable in those fields intersecting law and new technologies, where the use and meaning of words differ entirely in different contexts and according to the communities by which they are used. For instance, consider both the legal and computer science domains. In the legal field, the term transparent is generally defined as ‘easy to perceive or detect.’ However, it seems that the Oxford Dictionary also highlights that within the context of computing, this term means ‘of a process or interface functioning without the user being aware of its presence.’ While both fields thus extensively make use of the term transparency, they both understand and apply this term in completely different ways (Felzmann et al., 2019). This causes much confusion because the term as used by the former community seems to be juxtaposed to the understanding the latter has attributed to the very same concept and vice versa. In this particular context, this confusion could lead to developers not fulfilling the legal requirements that the law imposes with respect to transparency and explainability in domains such as data protection or artificial intelligence (AI) regulation.

Especially in today’s rapidly evolving society, it is not always possible to anticipate all possible developments and to adequately define them once they present themselves. This has especially proved to be a huge cause for concern where various domains intersect with one another, such as already indicated above for the domains of technology, law, and healthcare. For these fields to interact harmoniously, it will be necessary to gain a clear understanding of and clarify the components making up the transition towards digital healthcare. This, first, calls for a clarification of some of the general terminologies at the center of this complex interaction: robots and AI, autonomy levels, and human–robot interaction (HRI). Based on this understanding, Chapter 2 continues to delve deeper into the domain of healthcare robotics.

1.2 Guiding Your Way in the World of Healthcare Robotics: General Terminology

1.2.1 Robots

Similar to what we identified with emotions, it seems that everyone knows what a robot is, until asked to give a definition (Fehr & Russell, 1984; SPARC, 2015; Simon, 2017). Etymologically speaking, the word robot derives from the archaic Czech word robota, and means ‘forced, serf labor.’ The word robot was introduced into the English vocabulary for the first time after the play ‘Rossumovi Univerzální Roboti’ (Rossum’s Universal Robots, R.U.R.), written by Karek Čapek in 1920, and staged in New York in 1922 (Čapek, 2004). R.U.R. was a play, for which Čapek invented the word robot, and involved a scientist named Rossum who discovered the secret of creating human-like machines which he then produces and distributes worldwide through a newly established factory. At the same time, another scientist decides to make the robots more human, which he does by gradually adding such traits as the capacity to feel pain. Roboti were human-like machines that were supposed to serve humans and do their tedious work but eventually came to dominate them completely. With his play, Čapek wanted to criticize the mechanization of human workers as a result of the industrial revolution (Horáková & Kelemen, 2003). Today, the Oxford dictionary reads ‘a machine resembling a human being and able to replicate certain human movements and functions automatically.’

This definition has taken different shapes and forms in different communities, especially in the engineering one. For more technical definitions, some authors use classical definitions such as ‘machines, situated in the world, that sense, think and act.’ Others, like the International Standard Organization (ISO), define robots as ‘actuated mechanism(s) programmable in two or more axes with a degree of autonomy, moving within its environment, to perform intended tasks.’ (ISO 8373:2012).

Although naming a thing is to acknowledge its existence as separate from everything else that has a name (Popova, 2015), there are nonetheless many terms that do not have a legal definition. Some legal scholars in the United States (U.S.) have defined a robot as a ‘constructed system that displays both physical and mental agency but is not alive in the biological sense’ (Richards & Smart, 2016). The Japanese Electric Machinery Law (1971) defined an industrial robot as an ‘all-purpose machine, equipped with a memory device and a terminal device (end-effector), capable of rotation and of replacing human labour by the automatic performance of movements’ (Mathia, 2010).

In this respect, Bertolini and Palmerini gave a relevant definition in the context of the EU Robolaw project in 2014: ‘A machine, which (1) may be either provided of a physical body, allowing it to interact with the external world, or rather have an intangible nature – such as a software or program – (2) which in its functioning is alternatively directly controlled or simply supervised by a human being, or may even act autonomously in order to (3) perform tasks, which present different degrees of complexity (repetitive or not) and may entail the adoption of not predetermined choices among possible alternatives, yet aimed at attaining a result or provide information for further judgment, as so determined by its user, creator or programmer, (4) including but not limited to the modification of the external environment, and which in so doing may (5) interact and cooperate with humans in various forms and degrees’ (Bertolini & Palmerini, 2014).

In 2017, the European Parliament (EP) called on the European Commission (EC) to take regulatory action – in the form of a Directive and on the basis of arts. 225 and 114 TFEU – with respect to robots and AI (European Parliament, 2017). In it, the EP acknowledged that, at that time, there was no EU definition for ‘cyber-physical systems,’ ‘autonomous systems,’ and ‘smart autonomous robots.’ Accordingly, the EP recommended the EC establishing a definition for such systems taking into consideration the following characteristics:

1. The acquisition of autonomy through sensors and/or by exchanging data with its environment (inter-connectivity) and the trading and analyzing of those data.
2. Self-learning from experience and by interaction (optional criterion).
3. At least a minor physical support.
4. The adaptation of its behavior and actions to the environment.
5. And the absence of life in the biological sense.

The EC defined robots as ‘AI in action in the physical world.’ They also called it embodied AI. For them

a robot is a physical machine that has to cope with the dynamics, the uncertainties and the complexity of the physical world. Perception, reasoning, action, learning, as well as interaction capabilities with other systems are usually integrated in the control architecture of the robotic system.

To make it simpler, for this book we define a robot as ‘a movable machine that performs tasks either automatically or with a degree of autonomy’ (ISO 8373:2012; Richards & Smart, 2016; Fosch-Villaronga & Millard, 2019). Examples of robots include robotic manipulators to pick boxes or help build cars, self-driving cars, trucks or vans, drones, socially assistive robots, robotic vacuum cleaners, or conversational agents.

1.2.2 Artificial Intelligence

Humans have long imagined other types of lives and intelligence. A famous example of this can be traced back to the 1818 novel Frankenstein written by English author Mary Shelley. This well-known novel tells the story of Victor Frankenstein, a young scientist who creates a sapient creature in an unorthodox scientific experiment, thereby imagining the creation of new types of life and inspiring many generations to come in following similar paths. AI is a concept from computer science, based on statistics, and is tightly related to pattern recognition. Although it is difficult to pinpoint, the roots of AI can probably be traced back to the second half of the 20th century, and although the emergence and further development of AI have brought society new hope and massive benefits, increasingly we are being faced with their dangers too. To quote Mary Shelly’s Frankenstein in this regard,

I had worked hard for nearly two years, for the sole purpose of infusing life into an inanimate body. For this I had deprived myself of rest and health. I had desired it with an ardor that far exceeded moderation; but now that I had finished, the beauty of the dream vanished, and breathless horror and disgust filled my heart.

Shelley (2018)

It was in 1942 that the famous American Science Fiction writer Isaac Asimov responded to these concerns through his short story, Runaround, which revolves around the Three Laws of Robotics:

1. A robot may not injure a human being or, through inaction, allow a human being to come to harm.
2. A robot must obey the orders given to it by human beings except whe...