Hopster lists among the potential targets of technologically induced social disruption ‘social relations, institutions, epistemic paradigms, foundational concepts, values, and the very nature of human cognition and experience’ (2021, 1). This is quite a heterogeneous list; it is not immediately obvious what unifies these objects as potential targets of disruption, if anything.

Psychiatry includes the assessment and diagnosis of illness and disorder within a largely interpersonal communicative structure involving physicians and patients. In such contexts, AI can help to spot patterns and generate predictions, e.g. using ‘big data’ analysis via statistical learning-based models. In these ways, AI can help to automate more routine steps, improve efficiency, mitigate clinician bias, offer predictive potential, including through analysis of neuroscientific data.

The paper delves into the intersection of virtue ethics, postphenomenology, and technology to explore the roles ethical virtues may play in technological design. It employs the neo-Aristotelian praxeological methodology from Alasdair MacIntyre, focusing on the virtues of the moral agent as an independent practical reasoner but also as a socially and biologically dependent animal. It also integrates contributions from Ihde’s and Verbeek’s Postphenomenology, which explore morally and technologically mediated agents. 

The increased rationalisation of biotechnological engineering leads to a decontextualised production process of many well-known flavours and fragrances, such as vanillin, patchouli and stevia. A range of sophisticated production pathways decouples the production of ingredients from the original plant. This so-called biomanufacturing is fueled by technologies such large scale sequencing and metabolic engineering which allow for the precise design of micro-organisms.

Given the impressive performance and widespread adoption of large language models (LLMs), there is a pressing need to explain how these systems work and what information they use for their predictions. This would not only allow us to better predict and control their behavior, thereby increasing their trustworthiness, but also help gain insight into the internal processes underlying linguistic behavior in LLMs. 

In this paper, I consider an important question in the philosophy of AI. Does the fact that we cannot know how an AI reaches its conclusions entail that we cannot reasonably trust it? I argue that it does not.

The relationship between trust and transparency, whether in AI or elsewhere, appears quite puzzling. It seems unreasonable to trust that which is opaque, but too much transparency renders trust superfluous, for trust requires some degree of uncertainty and vulnerability. 

The current call for explainable AI (XAI) is most often framed as an answer to the so-called black box problem of machine learning. Following this conceptualisation of the problem, the recent effectiveness of many machine learning (ML) based systems comes at the cost of intelligibility: the more accurate AI performs the less understandable it becomes to humans. Accordingly, XAI is seen as the endeavour to whiten the black box, so that society can profit from the latest AI success without endangering being alienated.

This presentation is situated within the MyDigiTwin (MDT) consortium, a research project aiming to create a Digital Twin (DT), where Dutch citizens, including patients, can compare their health data (e.g., heart rate, weight, exercise) to existing big datasets. The platform will implement Artificial Intelligence (AI) models to predict a person’s risk of cardiovascular disease (CVD).

The concept ‘refusal’ in relation to Artificial Intelligence (AI) has attracted increased attention (e.g., Pereira, 2021). The overturning of Roe v Wade in 2022, ending the right to abortion in the U.S., led Pro-choice advocates to develop Chatbot Charley (2024) to refuse this decision. Charley confidentially provides information regarding safe abortions and trustworthy doctors. It gives access to networks of knowledge critical to political concerns such as bodily autonomy, privacy, and epistemic justice.

Recent advancements in artificial intelligence (AI) have demonstrated significant promise in the field of medicine. From disease diagnosis to personalized treatment plans, AI has the potential to revolutionize the healthcare industry. However, as with any emerging technology, there are questions about how to quantify the benefits and trade-offs of AI in medicine. One of the biggest challenges in assessing the benefits of AI in medicine is determining how to measure “uncertainty”. Biomedical and computer engineering define and measure uncertainty differently.

In Niklas Luhmann’s systems theory (Luhmann, 1995), society is characterized by an array of functionally differentiated subsystems comprising of communication. Included among these subsystems are the scientific subsystem, the technological subsystem, the moral subsystem and so on. Each of these subsystems is unique and conceives of problems in society by making use of their own logic, resulting in a situation where each subsystem presents different solutions to problems in society.

Too often privacy and security are considered to be opposed values. But a more realistic balance between these two can be realized when we acknowledge that both concepts have different meanings. They root in various forms of surveillance, that are embedded in western culture. 

In an influential paper, Verbeek has suggested to expand the (post-)phenomenological repertoire of describing human-technology relations with the cyborg relation to capture what is at stake when “the human and the technological actually merge rather than ‘merely’ being embodied” (Verbeek, 2008, p. 391). According to Verbeek, a new entity emerges when humans use implanted technologies such as neurotechnology, antidepressants, or pacemakers.

Algorithmic hiring technologies, i.e. Artificial Intelligence (AI) tools for Human Resource Management (HRM) that are used to find and select candidates for job openings, have been increasingly used to improve recruitment efficency. However, these tools have also been proven to perpetuate discrimination for marginalised groups in society.

In climate ethics, many have worried about the potential injustices arising from large-scale implementation of Carbon Dioxide Removal (CDR). To date, most of this discussion has focused on one particular form of CDR, the bioenergy-based BECCS technique. However, the IPCC's Sixth Assessment Report estimates that ‘nature-based’ forms of CDR such as afforestation and reforestation, soil carbon sequestration, and agroforestry have significant removal potentials, as well as potential co-benefits for local communities and biodiversity.

Moral progress and technological progress do not necessarily go hand in hand. The twentieth century is a prime example in this regard. According to various commentators (Mitcham 1994; Ihde 1990; Verbeek 2011), the atrocious two world wars and the growing environmental impact of technological societies spread among many postwar philosophers a critical view of modern technology. Certainly, material progress (mainly produced thanks to economic and scientific-technological advancement) does not equate to progress towards a more humane world.

Nudges, tweaks in choice environments that predictably steer behavior without restricting options, can be either self-regarding (benefiting the nudgee) or other-regarding (other aims such as organ donation, charity, tax compliance). Other-regarding nudges, on which we focus here, have been claimed to preserve moral worth and participate in cultivating moral virtues.

Philosophers have been interested in how technological change can drive changes in values and many have also proposed that particular causal histories can vindicate or debunk our confidence in certain values. For either inquiry we need robust evidence of technologically induced value change and of the causal mechanisms behind it. In my paper I offer such evidence of technology-driven value change and propose a vindicating argument for this value.

“Technosocial disruption” affects “deeply held beliefs, values, social norms, and basic human capacities”, “basic human practices, fundamental concepts, [and] ontological distinctions” (Hopster 2021: 6). For this reason, it is also referred to as “deep disruption” (ibid.). It brings about different kinds of uncertainty, including “conceptual ambiguity and contestation, moral confusion, and moral disagreement” (ibid.: 7). Among such deep disruptions are disruptions of fundamental concepts.

Modern life is characterised by a shared belief that we are moving forward, that ‘we’ – that is, humanity – are progressing to a better life. Even those people who demonstrate to point at the serious global problems we are currently facing – and there are still many of these, such as climate change, war, pandemics, racism, and social injustice – appear to entertain the belief that we can divert potential catastrophes if we are willing to act.

Naturalistic moral epistemologists have recently argued that there are distinct social factors and forces under which moral progress – or regress – are likely to occur. According to Smyth (in prep.) current technological trends in many societies are conducive to moral regress: whereas once technology freed humans and encouraged the formation of new ends and experiences, much of it now forces humans down conditioning pathways where we end up pursuing remarkably simple and uniform goals. In this presentation I criticize Smyth’s assessment on three philosophical grounds.

In his re-interpretation of Hegel’s Philosophy of Right, Axel Honneth (2014) builds a theory of justice which places the political public sphere as a central component for establishing what he calls ‘social freedom’ (individual autonomy realized in institutions and practices of mutual recognition).

Currently, there is significant concern about how AI-driven media platforms feature a logic of reactive and affective interaction, emotional mobilization, and moral outrage rather than lucid, political argumentation. Further, there is rising debate about whether platform companies take advantage of the unrelenting human hunger for bonding, reward, and the bestowal of esteem, exploiting vital needs for recognition as a monetizable vulnerability.

This talk examines the limitations of recognition theory by arguing that it takes relations between adults as paradigmatic. It challenges how Honneth’s three modes of recognition apply to children and use the example of educational AI to question how technologies should recognize children’s needs, rights and social contributions. First, children may not have yet fully acquired the capacity to recognize their needs. They often require guidance and care to do so and express their experiences of neglect.

This discussion addresses the question of how being subjected to pattern recognition by AI affects the possibilities of identity formation. Recognition theory explores how a subject (individually and collectively) shapes the self, its sense of dignity and esteem in its relationships with others (Honneth, Taylor). If we replace the ‘Other’ in the recognition relationship with artificial intelligence, questions arise about what we lose and what we gain in terms of social recognition. Is pattern recognition equivalent to patterned identity?

Hegel’s analysis of the “struggle for recognition” can be used to understand human-technology relations from a political perspective. This political perspective can consequently help us to appreciate how technologies like robots can come to have a role in political life through our ability to experience solidarity with such technologies, due to the recognition that technologies serve roles in society functionally equivalent to the social roles of humans.

Our research reevaluates postphenomenological theory by focusing on the often-neglected aspects of technological malfunctions and failures. We introduce concepts to scrutinize these critical facets, suggesting that postphenomenology inadequately addresses the significance of malfunctioning devices. Understanding these failures, we argue, is essential to fully appreciate the societal impact of disruptive technologies. This analysis aims to enrich postphenomenology and encourage further exploration into human-technology interactions.

In this talk I will provide an answer to the following question: how do sex robots confirm Lacanian psychoanalytic conceptions of (sexual) objectification and subjectivity that condition sexual relations with human others as well as with robots? 
A Lacanian understanding of sexual relations is predicated on the aphorism that the sexual relation does not exist: objectification is conditional for any (sexual) relation to take place since it is only possible to encounter human and robotic others as partial objects and never as whole entities or full subjects. 

Much of our world is imperceptible to us – “us” being humans. “Umwelt,” originally proposed by Jakob Johann von Uexküll, describes the world as experienced by an individual organism. Our worlds are both composed and limited by what we are capable of sensing. Our limitations have been exploited to generate invisible conveniences such as sonar and wireless technologies. However, we are not the only occupants of the planet and what is invisible to us has proven time after time to be harmfully present to our fellow species.

Several researchers have argued that the online environment makes people (especially women) more vulnerable to objectification. In this talk I argue that this is a special case of what I call technological objectification: the way in which technologies enable to treat oneself or someone else as an object. The aim of this talk is twofold. On the one hand, I suggest that technological objectification comes in degrees, and that arguably not every form of objectification is (equally) problematic.

Postphenomenology’s recognition that technological artifacts play an active role in our lives by mediating our experiences and actions in the world has proved a powerful perspective for the analysis of what things do. Part of this consists of bringing to light theretofore un(der)recognized ethical impacts of specific technologies. However, when it comes to then informing us on what to do in light of those developments, postphenomenological theorizing has been relatively silent, i.e., steps towards developing an ‘ethics of technological mediation’ have been limited.