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The Ethics of AI: Navigating the Moral Landscape

A wide range of stakeholders are involved in the development and application of AI: governments, corporations, researchers, universities, associations and non-profit organizations. These actors need to collaborate on how social, economic and political issues intersect with AI technology. Often, they must also consider the ethical implications of their decisions.

The question of whether the human mind can be digitized and turned into a computer program or algorithm is one of the most complex questions of AI ethics. While the answer to this question may seem trivial, it is a central issue for the future of our civilization (Seay 2017).

Science fiction has been playing with the idea of ethical AI for a while now, most notably in Spike Jonze’s 2013 film Her, where a user falls in love with his operating system. However, this is only a small part of the story. AI has the potential to influence our lives in many other ways, including in medicine and business, as well as influencing our culture, society and economy. This makes it even more important to think about how we should design AI systems and what the consequences of their use could be.

In his 2010 book Best VPN Services of 2024 The Moral Landscape, neuroscientist Sam Harris offers a framework for addressing these issues. He describes the concept of a “moral landscape” as a conceptual space representing all possible experience. The peaks of this landscape represent the heights of well-being, while the valleys represent the depths of suffering. According to Harris, there is no single best way to live, but different cultures and ethical practices can move people across this landscape.

Despite this, most of the ethical goals outlined in various guidelines remain to be largely unachieved or are being undermined by other trends. These include safety and cybersecurity, the science-policy link, public awareness of AI risks, fostering diversity in AI and social cohesion, the protection of whistleblowers, transparency and openness, or the military AI arms race (Lonsdale 2018).

The problem of opaqueness is exacerbated by the fact that AI is anthropomorphised, which leads to misplaced conceptions of its moral agency. In addition, the lack of mechanisms to enforce ethical principles means that there is no eminent threat from unethical AI – which has the effect of stifling its own growth.

To overcome this challenge, it is necessary to change the way we look at ethics in general and AI ethics specifically. Instead of focusing on checkbox guidelines technology website that seek to subsume as many cases as possible under the same universal principle, we need to build a more situation-sensitive approach, focusing on virtues and personality dispositions, knowledge expansions, responsible autonomy and freedom of action. In other words, we need to transform ethical discourse from a deontologically oriented, action-restricting ethic based on universal abidance of rules and laws into microethics that are sensitive to specific situations and technical assemblages. This will require a substantial shift from the description of technological phenomena to the creation of tangible bridges between abstract values and technical implementations.