In previous lectures, I already brought several weak points of Artificial Data processing to your attention. Today we'll have a closer look at ethics concerning AI.
One of the most prominent ethical concerns surrounding AI is its potential to reinforce or increase societal biases. AI systems are trained on large datasets, and if these datasets contain biased information, the AI can perpetuate these biases.
It is humans that select the datasets with which AI systems are trained. The female body is different from the male body, but most diagnostics are based on the male body.
If you feed such datasets into AI apps for diagnosis, it can lead to biased and incorrect conclusions. I have read for instance that a heart attack in a female can seriously differ from the one in a male.
The story we already know is, that facial recognition systems have been shown to perform poorly on non-white faces, leading to disproportionate errors for minority groups.
Just imagine that such a facial recognition system is used to answer questions like: Is this person reliable, can I give him a loan, is he or she fit for the job?
And what about fairness? Suppose you have an AI machine that distributes food. Five hungry children, of which two haven't had a meal in a week, push the button.
They all get one kilogram of rice. The basic principle is equality for all. That is fair. But shouldn't the AI machine also haven't checked the level of hunger per person,
and give the most hungry children more than the other three? Wouldn't that be more fair? This leads to an ethical debate about whose definition of fairness should be prioritized in cases where different groups have conflicting perspectives.
Another key ethical issue is the potential for AI to infringe on individual privacy. AI technologies, particularly those used in surveillance, can collect and analyze vast amounts of personal data.
Governments and corporations are increasingly utilizing AI-powered systems to monitor citizens, track consumer behavior, and even predict criminal activity.
While these tools can enhance public safety and improve services, they also raise concerns about mass surveillance and the erosion of privacy rights.
And next the question: who is responsible? AI systems often operate with a level of autonomy that raises questions about accountability.
In traditional systems, humans are responsible for the decisions they make, but in AI-driven systems, the decision-making process is often opaque.
When an AI makes an error—whether it is a self-driving car causing an accident or a healthcare algorithm making a wrong diagnosis—determining who is responsible can be difficult.
Is it the developers, the users, the manufacturers, or the AI itself? Or to put it in more American terms: who can we sue? :-)
One of the most fundamental social-political issues could be the following. The main question to begin with is: What is the role of a company in society?
In this capitalist neo-liberal era the answer is simple: maximization of profits and keeping the shareholders happy and making them richer.
Within this context, the employees are just the tools to achieve this goal. They cost money, so if we can replace them with much cheaper AI systems, let's fire the employees.
But does a company only exist to make profits? Doesn't it also have a responsibility towards its employees in a social sense? This question is hardly ever asked these days,
but in the past (ca 1900), the Dutch company PHILIPS and the mining companies in Limburg said "Yes" and they built houses, sports facilities, and schools for their workers.
Nowadays we are impressed by the performance of narrow AI apps and the developers promise us a golden future with AI, but when you look at these few questions,
that I presented, there still is a lot of work to do. The ethical challenges posed by AI are complex and multifaceted, requiring a careful balance between technological innovation and societal values.
Addressing these challenges will require collaboration between technologists, ethicists, policymakers, and the public to develop frameworks that promote fairness, transparency, accountability, and human welfare.
Thank you for your attention again....
Main Sources:
MacMillan The Encyclopedia of Philosophy, 2nd edition
TABLE OF CONTENT -----------------------------------------------------------------
1 - 100 Philosophers 9 May 2009 Start of
2 - 25+ Women Philosophers 10 May 2009 this blog
3 - 25 Adventures in Thinking 10 May 2009
4 - Modern Theories of Ethics 29 Oct 2009
5 - The Ideal State 24 Febr 2010 / 234
6 - The Mystery of the Brain 3 Sept 2010 / 266
7 - The Utopia of the Free Market 16 Febr 2012 / 383
8. - The Aftermath of Neo-liberalism 5 Sept 2012 / 413
9. - The Art Not to Be an Egoist 6 Nov 2012 / 426
10 - Non-Western Philosophy 29 May 2013 / 477
11 - Why Science is Right 2 Sept 2014 / 534
12 - A Philosopher looks at Atheism 1 Jan 2015 / 557
13 - EVIL, a philosophical investigation 17 Apr 2015 / 580
14 - Existentialism and Free Will 2 Sept 2015 / 586
15 - Spinoza 2 Sept 2016 / 615
16 - The Meaning of Life 13 Febr 2017 / 637
17 - In Search of my Self 6 Sept 2017 / 670
18 - The 20th Century Revisited 3 Apr 2018 / 706
19 - The Pessimist 11 Jan 2020 / 819
20 - The Optimist 9 Febr 2020 / 824
21 - Awakening from a Neoliberal Dream 8 Oct 2020 / 872
22 - A World Full of Patterns 1 Apr 2021 / 912
23 - The Concept of Freedom 8 Jan 2022 / 965
24 - Materialism 7 Sept 2022 / 1011
25 - Historical Materialism 5 Oct 2023 / 1088
26 - The Bonobo and the Atheist 9 Jan 2024 / 1102
27 - Artificial Intelligence 9 Feb 2024 / 1108
