BioethicsCPH

Our current research focus is on the future developments of family relationships. Where will this development lead? Where should it lead? Will and should there still be families at the end of this century and if so, what form will and should family ties take? This question is especially crucial given, at the same time, the precious partial bonds that families give rise to but also the inequality that we perpetrate and try to justify through partiality.

Is technological innovation spinning out of control? Within one week in 2018, social media was revealed to have had huge undue influence on the 2016 presidential elections in the United States; while the first fatality from self-driving cars was recorded. What’s paradoxical about these understandable fears of machines taking over control through software, robots and AI, is that often new technology is introduced for the very purpose of improving our control over a certain task. This is what Ezio Di Nucci calls the ‘control paradox’.

Di Nucci also brings this notion to bear on politics: we delegate power and control to political representatives in order to improve democratic governance. However, recent populist uprisings have shown that voters can feel disempowered and neglected by this system. Through the notion of the control paradox, the author shows how this lack of direct control within representative democracies could be motivating populism and argues that a better understanding of delegation is a possible solution.

This is the basic idea behind the book “The Control Paradox: from AI to Populism” which Ezio Di Nucci, the PI of bioethicsCPH, is currently writing.

We are, as a society, increasingly delegating tasks to algorithms and so-called AI (Artificial Intelligence), from healthcare to transportation, from the military to the criminal justice system, from financial services to commerce, from entertainment to social media. The more data these algorithms are fed, the better are they supposed to work, with more recent developments – so called machine learning – pointing to the possibility that some algorithms are able to teach themselves new connections from data without any further input from human programmers. Influential cognitive scientists are claiming that machine learning platforms are able to “figure it out on their own, by making inferences from data”.

Only within healthcare, there are now pathology algorithms tasked with classifying biopsy slides; GoogleBrain algorithms are being used for diagnosing diabetic retinopathy; Watson is being deployed as a decision support system which ranks oncological therapeutic options; and there are many more instances of how algorithms and AI are being used within healthcare. Healthcare, which will be TEMA’s focus, is itself only one of the many domains where algorithms are being deployed, from self-driving cars to social networks. Recently there have also been widely publicized episodes which have raised the question of whether we might be giving too much control to AI systems.

We are responsible for and teach in the following courses at the Faculty of Health and Medical Sciences of the University of Copenhagen:

Medicine Bachelor: Ethics and Philosophy of Medicine

Public Health Master: Advanced Bioethics

Health Informatics Bachelor: Ethics and Philosophy of Technology