Mechanisms of Techno-Moral Change: A Taxonomy and Overview.

The idea that technologies can change moral beliefs and practices is an old one. But how, exactly, does this happen? This paper builds on an emerging field of inquiry by developing a synoptic taxonomy of the mechanisms of techno-moral change. It argues that technology affects moral beliefs and practices in three main domains: decisional (how we make morally loaded decisions), relational (how we relate to others) and perceptual (how we perceive situations). It argues that across these three domains there are six primary mechanisms of techno-moral change: (i) adding options; (ii) changing decision-making costs; (iii) enabling new relationships; (iv) changing the burdens and expectations within relationships; (v) changing the balance of power in relationships; and (vi) changing perception (information, mental models and metaphors). The paper also discusses the layered, interactive and second-order effects of these mechanisms.

The foundations of a policy for the use of social robots in care.

Should we deploy social robots in care settings? This question, asked from a policy standpoint, requires that we understand the potential benefits and downsides of deploying social robots in care situations. Potential benefits could include increased efficiency, increased welfare, physiological and psychological benefits, and experienced satisfaction. There are, however, important objections to the use of social robots in care. These include the possibility that relations with robots can potentially displace human contact, that these relations could be harmful, that robot care is undignified and disrespectful, and that social robots are deceptive. I propose a framework for evaluating all these arguments in terms of three aspects of care: structure, process, and outcome. I then highlight the main ethical considerations that have to be made in order to untangle the web of pros and cons of social robots in care as these pros and cons are related the trade-offs regarding quantity and quality of care, process and outcome, and objective and subjective outcomes.

A shallow defence of a technocracy of artificial intelligence: Examining the political harms of algorithmic governance in the domain of government.

Artificial intelligence (AI) has proven to be superior to human decision-making in certain areas. This is particularly the case whenever there is a need for advanced strategic reasoning and analysis of vast amounts of data in order to solve complex problems. Few human activities fit this description better than politics. In politics we deal with some of the most complex issues humans face, short-term and long-term consequences have to be balanced, and we make decisions knowing that we do not fully understand their consequences. I examine an extreme case of the application of AI in the domain of government, and use this case to examine a subset of the potential harms associated with algorithmic governance. I focus on five objections based on political theoretical considerations and the potential political harms of an AI technocracy. These are objections based on the ideas of 'political man' and participation as a prerequisite for legitimacy, the non-morality of machines and the value of transparency and accountability. I conclude that these objections do not successfully derail AI technocracy, if we make sure that mechanisms for control and backup are in place, and if we design a system in which humans have control over the direction and fundamental goals of society. Such a technocracy, if the AI capabilities of policy formation here assumed becomes reality, may, in theory, provide us with better means of participation, legitimacy, and more efficient government.

Challenging the Neo-Anthropocentric Relational Approach to Robot Rights.

When will it make sense to consider robots candidates for moral standing? Major disagreements exist between those who find that question important and those who do not, and also between those united in their willingness to pursue the question. I narrow in on the approach to robot rights called relationalism, and ask: if we provide robots moral standing based on how humans relate to them, are we moving past human chauvinism, or are we merely putting a new dress on it? The background for the article is the clash between those who argue that robot rights are possible and those who see a fight for robot rights as ludicrous, unthinkable, or just outright harmful and disruptive for humans. The latter group are by some branded human chauvinists and anthropocentric, and they are criticized and portrayed as backward, unjust, and ignorant of history. Relationalism, in contrast, purportedly opens the door for considering robot rights and moving past anthropocentrism. However, I argue that relationalism is, quite to the contrary, a form of neo-anthropocentrism that recenters human beings and their unique ontological properties, perceptions, and values. I do so by raising three objections: 1) relationalism centers human values and perspectives, 2) it is indirectly a type of properties-based approach, and 3) edge cases reveal potentially absurd implications in practice.

Healthcare Digitalisation and the Changing Nature of Work and Society.

Digital technologies have profound effects on all areas of modern life, including the workplace. Certain forms of digitalisation entail simply exchanging digital files for paper, while more complex instances involve machines performing a wide variety of tasks on behalf of humans. While some are wary of the displacement of humans that occurs when, for example, robots perform tasks previously performed by humans, others argue that robots only perform the tasks that robots should have carried out in the very first place and never by humans. Understanding the impacts of digitalisation in the workplace requires an understanding of the effects of digital technology on the tasks we perform, and these effects are often not foreseeable. In this article, the changing nature of work in the health care sector is used as a case to analyse such change and its implications on three levels: the societal (macro), organisational (meso), and individual level (micro). Analysing these transformations by using a layered approach is helpful for understanding the actual magnitude of the changes that are occurring and creates the foundation for an informed regulatory and societal response. We argue that, while artificial intelligence, big data, and robotics are revolutionary technologies, most of the changes we see involve technological substitution and not infrastructural change. Even though this undermines the assumption that these new technologies constitute a fourth industrial revolution, their effects on the micro and meso level still require both political awareness and proportional regulatory responses.

Correction to: The Parasitic Nature of Social AI: Sharing Minds with the Mindless.

The original version of this article unfortunately contained a mistake.

The Parasitic Nature of Social AI: Sharing Minds with the Mindless.

Can artificial intelligence (AI) develop the potential to be our partner, and will we be as sensitive to its social signals as we are to those of human beings? I examine both of these questions and how cultural psychology might add such questions to its research agenda. There are three areas in which I believe there is a need for both a better understanding and added perspective. First, I will present some important concepts and ideas from the world of AI that might be beneficial for pursuing research topics focused on AI within the cultural psychology research agenda. Second, there are some very interesting questions that must be answered with respect to central notions in cultural psychology as these are tested through human interactions with AI. Third, I claim that social robots are parasitic to deeply ingrained human social behaviour, in the sense that they exploit and feed upon processes and mechanisms that evolved for purposes that were originally completely alien to human-computer interactions.

Science as a Vocation in the Era of Big Data: the Philosophy of Science behind Big Data and humanity's Continued Part in Science.

We now live in the era of big data, and according to its proponents, big data is poised to change science as we know it. Claims of having no theory and no ideology are made, and there is an assumption that the results of big data are trustworthy because it is considered free from human judgement, which is often considered inextricably linked with human error. These two claims lead to the idea that big data is the source of better scientific knowledge, through more objectivity, more data, and better analysis. In this paper I analyse the philosophy of science behind big data and make the claim that the death of many traditional sciences, and the human scientist, is much exaggerated. The philosophy of science of big data means that there are certain things big data does very well, and some things that it cannot do. I argue that humans will still be needed for mediating and creating theory, and for providing the legitimacy and values science needs as a normative social enterprise.