This short essay is part of an assignment of the Research Ethics and Integrity I attended at King's College during my PhD in Data-driven Healthcare. Research is by definition the area in which we explore what is still unknown in the process of generating new knowledge. Today in the biomedical sector, which is now more active than ever, there is a duality that has rarely occurred in the past.
Knowledge of the medical sector itself is only part of the innovation process because today, thanks to technological evolution, research also involves the very methods that are used to generate knowledge.
In particular, the statistical and computing methodologies developed during the second half of the twentieth century and, even more so in the last 20 years, have dramatically changed not only the search for knowledge of individual sectors, but also the way in which this knowledge is generated.
My personal research activity is based on artificial intelligence methodologies applied to clinical research; in fact, this explains the focus of this text on these methods and on the ethical aspects connected to them.
Medical research is probably one of the noblest sectors which, however, has also been the scene of questionable practices in both good and bad faith throughout history.
If in the years preceding the technological boom, medical research was based solely on the individual observation of medical scholars, today this is no longer true.
The study of ever larger populations (also due to the incredible increase in world population of the last century), the increase in the number of cultured researchers interested in scientific discovery and the explosion of technological tools of the last decades have introduced into medical research a series of new problems never even hypothesized before.
Today medical research is proceeding at a fast-paced thanks to the diffusion of new technologies, but the speed with which technology evolves is not reflected in the speed with which researchers are able to adapt to it, just as it is not reflected in the ability of the population to understand the increasingly complex methodologies used to obtain new knowledge.
The times when medical research was carried out only one patient at a time is a long way off. The ability we have today to measure even the smallest and most hidden details of human biology and physiology is so fast and massive that the main limitation to research is the imagination of the researcher himself.
In this context, there are therefore two main concerns that it is important to underline.
First of all, researchers today are empowered by methodologies and technologies never seen in history that give them the possibility of collecting an incredibly high and detailed amount of data at very low cost, even on extremely private and personal aspects.
Secondly, the patient, who by definition is in a situation of discomfort and need, is on average unable by culture to understand the amount of information that their data can represent and, above all, the number of ways in which those who have that data can use them to their advantage.
In this context, representing the former of the parts, I am increasingly aware that more important than knowledge of the domain, be it of a medical or mathematical / methodological nature, must be the basic motivation of every research activity.
The almost unlimited possibility that we have today to conduct research (from data collection to analysis methodologies) can lead today to increasingly greater impacts, both positively, when the research is conducted correctly, and negatively, when ethical aspects are neglected.
In particular, collecting data is now easier than ever, but in the same way, it is easy both to tamper with it and to circumvent the source of the data so that it is released for biased purposes.
The complexity and scale with which today's data are collected often makes it impossible to retrace their path to the source and thus verify their quality and the appropriateness with which they were generated and collected.
The study of the "path" of data from the source to the search result is so important that there is an entire branch of information technology dedicated to it which is called Data Provenance. This shows how increasingly complicated it is to ensure the correct and ethical use of data.
The ease with which we risk going off the rails of ethical and correct research therefore makes it necessary to reinforce these two concepts by default.
The need to reinforce the ethical foundations on which we carry out our research work is necessary not only out of respect for those who allow us to use their data to do our job, but also because nowadays it is becoming increasingly easy and risky to go beyond the limits that ethics suggests, being it on purpose or by mistake.
Feel free to engage in a conversation below leaving a comment or sending me an email at davide@davideferrari.blog
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