This article develops a conceptual framework for regulating Artificial Intelligence (AI) that encompasses all stages of modern public policy-making, from the basics to a sustainable governance. Based on a vast systematic review of the literature on Artificial Intelligence Regulation (AIR) published between 2010 and 2020, a dispersed body of knowledge loosely centred around the “framework” concept was organised, described, and pictured for better understanding. The resulting integrative framework encapsulates 21 prior depictions of the policy-making process, aiming to achieve gold-standard societal (...) values, such as fairness, freedom and long-term sustainability. This challenge of integrating the AIR literature was matched by the identification of a structural common ground among different approaches. The AIR framework results from an effort to identify and later analytically deduce synthetic, and generic tool for a country-specific, stakeholder-aware analysis of AIR matters. Theories and principles as diverse as Agile and Ethics were combined in the “AIR framework”, which provides a conceptual lens for societies to think collectively and make informed policy decisions related to what, when, and how the uses and applications of AI should be regulated. Moreover, the AIR framework serves as a theoretically sound starting point for endeavours related to AI regulation, from legislation to research and development. As we know, the (potential) impacts of AI on society are immense, and therefore the discourses, social negotiations, and applications of this technology should be guided by common grounds based on contemporary governance techniques, and social values legitimated via dialogue and scientific research. (shrink)

In this paper, I draw on Hannah Arendt’s notion of ‘banality of evil’ to argue that as long as AI systems are designed to follow codes of ethics or particular normative ethical theories chosen by us and programmed in them, they are Eichmanns destined to commit evil. Since intelligence alone is not sufficient for ethical decision making, rather than strive to program AI to determine the right ethical decision based on some ethical theory or criteria, AI should be concerned with (...) avoiding making the wrong decisions, and this requires hardwiring the thinking activity as a prerequisite for decision making. (shrink)

What is the best overarching ethical principle to give a possible future superintelligent machine, given that we do not know what the best ethics are today or in the future? Eliezer Yudkowsky has suggested that a superintelligent AI should have as its goal to carry out the coherent extrapolated volition of humanity (CEV), the most coherent way of combining human goals. The article discusses some problems with this proposal and some alternatives suggested by Nick Bostrom. A slightly different proposal is (...) then suggested, which I argue solves the problems better than Yudkowsky’s proposal. (shrink)

As AI is linked to more and more aspects of our lives, the need for algorithms that can take decisions that are not only accurate but also fair becomes apparent. It can be seen both in discussions of future trends such as autonomous vehicles or the issue of superintelligence, as well as actual implementations of machine learning used to decide whether a person should be admitted in certain university or will be able to return a credit. In this paper, we (...) will use Dreyfus’ account on ethical expertise to show that, to give an AI some ability to make ethical judgements, a pure symbolic, conceptual approach is not enough. We also need the ability to make sense of the surroundings to reframe and define situations in a dynamic way, using multiple perspectives in a pre-reflective way. (shrink)

The article examines the challenges involved in the process of developing artificial ethical agents. The process involves the creators or designing professionals, the procedures to develop an ethical agent and the artificial systems. There are two possibilities available to create artificial ethical agents: (a) programming ethical guidance in the artificial Intelligence (AI)-equipped machines and/or (b) allowing AI-equipped machines to learn ethical decision-making by observing humans. However, it is difficult to fulfil these possibilities due to the subjective nature of ethical decision-making. (...) The challenge related to the developers is that they themselves lack training in ethical skills. The creators who develop an artificial ethical agent should be able to foresee the ethical issues and have knowledge about ethical decision-making to improve the ethical use of AI-equipped machines. The suggestion is that the focus should be on training professionals involved in the process of developing these artificial systems in ethics rather than developing artificial ethical agents and thereby attributing ethical agency to it. (shrink)