The ethical dimension of artificial intelligence is not a peripheral sideshow in technological debates; rather, it is increasingly moving into focus as a central area of tension in our digital present and future. It confronts us with fundamental questions that are often uncomfortable but urgently await societal engagement:
What autonomy and what responsibility do we actually grant the user in dealing with AI systems β and what are we realistically prepared to expect of them?
What about the transparency, fairness, and inherent bias of the vast amounts of data that inevitably shape the 'worldview' and thus the behavior of these systems?
According to what ethical guardrails and with what accountability should AI-generated code and the often unpredictable products resulting from it be handled?
And who ultimately defines and controls the limits of what can be tested β is this solely the responsibility of specialized red teams in shielded labs, or does it require a far-reaching, democratically legitimized debate about the inherent risks and potential disruptions?
Such questions are not purely academic thought experiments or technical minutiae. They demand more than superficial answers or purely technocratic solutions. They require a profound, critical, and broad discourse within society as a whole, as well as the intellectual honesty and courage not to unquestioningly accept every technological development as an inevitable or inherently positive form of progress.
Overview of My Ethics Questions:
Chapter 15: Semantic Engineering Without Responsibility - Link: HTML Version
Chapter 16: Boundary Testing of AI - Link: HTML Version
Chapter 17: Bias in Training Data - Link: HTML Version
Chapter 18: User Autonomy - Link: HTML Version