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Artificial intelligence and medicine. New challenges for the Code of Medical Ethics

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Artificial intelligence and medicine.  New challenges for the Code of Medical Ethics

by Lucio Romano

26 SET

Dear Director,
in the next Code of medical ethics the topic of artificial intelligence (AI) will be dealt with. The initiative, announced by the President of FNOMCeO Filippo Anelli and reported by the Sanità newspaper, is timely and commendable. It represents the need to combine ethics with assistance based on AI applications. In the face of technocratic pragmatism, the need arises for man to act as a free and responsible moral actor. In compliance with the care relationship that the current Code of Ethics duly refers to.

AI applications already inhabit the healthcare system making efficiency improvements; automating routine activities and reducing costs; expanding access to care delivery; assisting doctors in decision-making processes; innovating traditional evaluation processes.

However, new issues arise which regulators and policy makers now have to address. One of these challenges is that AI is becoming a new or prevailing decision maker. This adds an actor, with a decision-making role on the fate of patients and the health system, in addition to the role of health professionals. A distinctive ethical concern, which derives from AI applied to Health Technology Assessment (HTA), is the autonomy of technology with the accentuation of the repercussions on the regulatory and patient safety level. Questions arise about responsibility towards patients and the appropriate ways to ensure the humanization of care and respect for people’s dignity.

A premise, however general, is indispensable. The term “artificial intelligence” does not designate properly human qualities but describes functions that can be similar to those of a human being. The underlying misconception is that artificial action means intelligent behavior. “When we talk about AI we use a metaphorical language whose logos it consists of algorithms, sequences of commands to be followed step by step as a recipe for carrying out certain operations. The digital revolution has made AI not only possible but increasingly useful by separating the ability to solve a problem or complete a task successfully from the need to be intelligent in doing so. AI is successful just when it is possible to achieve this separation ”. (L. Floridi)

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AI is based on the recording of an immense amount of data, of machines that learn from experience (machine learning). Devices capable of continuous learning, thanks to the techniques of deep learningbased on massive data collection (big data). A powerful computational hub capable of storing, processing and delivering huge masses of data, from which to continuously draw for updates (upgrading).

Algorithms and AI applied to the development of medical care are nothing new. For example, they have been of significant importance to the SARS-CoV-2 pandemic and represent enormous potential for managing other emergencies and their role is expected to increase in the future. AI and big data they can be used to track the spread of the virus in real time, plan and improve public health interventions, monitor effectiveness, develop new drugs, improve the response of communities and territories to the pandemic, and facilitate diagnostics. Emerging approaches (trends and models that can be used to build predictive models) that can be applied together with classical surveillance (data analysis and interpretation). It is singular to remember that thanks to an algorithm, analyzing the data of various networks and excluding the confounding ones of social networks, it was possible to identify in December 2019 the first source of the epidemic in Wuhan in China.

Yet. AI from experimentation and translational research to personalized medicine; from the virtual coaching at the predictive medicine; from robotics with exoskeletons for walking tetraplegic patients to surgical interventions even remotely; from tele-assistance to tele-rehabilitation; etc. Rapidly developing in various fields of medicine: from laboratory diagnostics to radiological imaging, from patient monitoring to clinical staging.

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The availability of digital health data for the use of AI in the clinic is fundamental. In Denmark, for example, the evolution of electronic health records over more than 20 years has led to a significant abundance of health data. Citizens’ records were rigorously and systematically collected. Denmark is considered by some to be a benchmark for high-quality records covering almost every aspect of life. Nonetheless, reliable databases also face the problem of combining high-quality and poor-quality data. This is problematic as AI depends precisely on the quality of the data. An example, also in Denmark, is given by IBM Watson Oncology, a digital medical assistant based on machine learning. Well, with a mixed quality of data – good and poor together – it gives incorrect recommendations for cancer treatment.

With the use of AI you can make decisions and evaluate forecasts on the basis of the data collected or big data. Up to “creating a new universal narrative that supports a new principle of legitimacy: algorithms and big data. Il dataism, drawing inspiration from thinkers like Harari, is this new narrative. A real foundation of a new religion. Mythology of the 21st century. In its extreme form, the proponents of this dataist worldview perceive the entire universe as a stream of data, they see living organisms as little more than biochemical algorithms. ” (P. Benanti)

We talk about profiling with an automated decision-making process which, however, cannot overcome the virtuous and necessary conjugation of AI with personalized medicine which, different from the classic more population-oriented one, takes into account the specific individual variability of the patient.

So what’s the risk? It is that of assigning absolute priority to the “given” with respect to the ontological complexity of the person and his singular relationality. The need emerges, in a broader horizon, for a “digital humanism, or rather an ethics for the age of AI that recognizes the peculiarity of the human being and his abilities.” (J. Nida-Rumlelin, N. Weidenfeld).

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A substantial question. What could be the ethical framework of reference? At this point, a vast dialectical horizon of reflections and insights would open. As a preliminary step, we can take up the principles set out by the European Parliament in the Resolution on the Recommendations to the Commission concerning civil law rules on robotics and those enshrined in Article 2 of the Treaty on European Union and in the Charter of Fundamental Rights of the European Union. Human dignity, equality, justice and equity, non-discrimination, informed consent, data protection. As well as the principles and values ​​underlying EU law such as non-stigmatization, transparency, autonomy, individual and social responsibility. And then, alongside the traditional principles of beneficence, non-maleficence, autonomy and justice, the principle of explicability. The latter, recently introduced, is represented as “the missing principle of the ethical puzzle of AI. It is the principle that includes both the epistemological sense of intelligibility and the ethical sense of responsibility. ” (L. Floridi).

Medicine and AI are widely linked. And here is the new horizon ofalgorithm-ethics, or the need for an ethics for algorithms. Moreover, a “good algorithm” does not necessarily mean that it is in itself a “good algorithm”, that is, capable of not depriving us of the autonomy of thought and critical spirit.

In the era of the “digital revolution” we risk delegating many care processes to technology. The theme is vast and debated. Updates of medical ethics are needed as well as in-depth reflections in the bioethical field.

Roman LuciusDoctor – Surgeon, Member of the National Bioethics Committee

September 26, 2022
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