Michał Klincewicz

Gloria Andrada and Adam J. Carter—“Mind-Technology Problem s for Know-How Anti- Intellectualism,” 2025—use the Mind-Technology problem (MTP) framework (Clowes, Gärtner, and Hipólito 2021) as a basis for theorizing about skills and know-how. More specifically, they focus on anti-intellectualism about know-how, so the view that S knows how to do X in virtue of S having the ability to intentionally X. Anti-intellectualism is contrasted with intellectualism about know-how, so the view that S knows how to do X in virtue of knowing that something is the case or knowing some fact (Stanley and Williamson 2011; Bengson and Moffett 2007). Here, I set MTP aside to focus on Andrada and Carter’s theorizing itself, which does an excellent job highlighting what is and is not at stake when smart technologies aim to improve humans from a moral perspective. First, they list a number of generic questions about an ability and the technology related to it, which can be used to interrogate the ontological, normative, and epistemological features of that relationship. Second, their paper implicitly raises questions about the role of socio-cultural context in our theorizing about technologically-enabled abilities. Thirdly, they bring the debate about intellectualism and anti-intellectualism about abilities to bear directly on important current topics in the philosophy of technology.

We are faced with false information (misinformation) and corrections regularly. Typically, we have no problem correcting misinformation. However, there are individual differences in how effective people are in correcting misinformation and in the scope and magnitude of the influence of misinformation after correction. Understanding individual differences can shed light on the mechanisms that underlie these effects. Here, we asked participants to read fictitious news articles that were later corrected to test their memory of each and identified patterns in user generated text and participants' attitudes that are related to memory performance. Individuals with high negative sentiment selectively remembered corrections better when they were in line with their prior beliefs. Individuals who were selectively better at remembering corrections in line with their beliefs also showed distinct patterns of moral values expressed in what they wrote. This contributes to our understanding of why some people are better at correcting misinformation and how this relates to confirmation bias in memory. Furthermore, this research paves the way for future research on the psychological and neural effects of misinformation.

Expert video game players exhibit unique behaviors compared to their less experienced counterparts. Such behaviours may also influence physiological aspects such as blinks and eyelid movements. In this study, we used the Eye Aspect Ratio (EAR) signal from a webcam to investigate the complex dynamics of eyelid movements among players with different levels of expertise in Tetris. We measured complex dynamics using recurrence quantification analysis (RQA) based measures (Determinism, Laminarity, Average Diagonal Line, and Trapping Time). Our results show that expert Tetris players display more complex patterns in their eyelid behaviour, but also that some of the measures obtained using RQA correlate directly with player actions (keys pressed) and events in Tetris (numbers of lines cleared). This study provides the first example of a direct connection between RQA measures extracted from the EAR signal and behavior displayed in a game. Our results also demonstrate the potential of using RQA measures extracted from the EAR in analysing human behavior during other screen-presented tasks.

This study examines the interplay between choice blindness and moral decision-making through the design and implementation of a decision-driven adventure game called Lost Civilization. Choice blindness, a phenomenon where individuals fail to detect changes in their decisions, was investigated within a controlled narrative environment featuring moral dilemmas in total, 56 participants (24 female, ages 18–35) engaged with the game, which subtly manipulated one of their moral decisions. The findings reveal that the majority (37) of participants did not detect the manipulation, underscoring the potential of games as tools for studying moral cognition and agency. Logistic regression analysis and machine learning models demonstrated significant correlations between undetected manipulations and participants’ gender as well as specific moral foundation scores based on Jonathan Haidt’s and Oliver Scott Curry’s dictionaries, suggesting deeper psychological underpinnings of decision-making processes. This research highlights the utility of video games in expanding the scope of choice blindness studies and advancing our understanding of ethical agency in interactive contexts.

In recent years, there has been growing optimism about the potential of conversational agents, such as chatbots and social robots, in mental healthcare. Their scalability offers a promising solution to some of the key limitations of the dominant model of treatment in Western countries. However, while recent experimental research provides grounds for cautious optimism, the integration of conversational agents into mental healthcare raises significant clinical and ethical challenges, particularly concerning the partial or full replacement of human practitioners. Overall, this theoretical paper examines the clinical and ethical implications of deploying conversational agents in mental health services as partial and full replacement of human practitioners. On the one hand, we outline how these agents can circumvent core treatment barriers through stepped care, blended care, and a personalized medicine approach. On the other hand, we argue that the partial and full substitution of human practitioners can have profound consequences for the ethical landscape of mental healthcare, potentially undermining patients’ rights and safety. By making this argument, this work extends prior literature by specifically considering how different levels of implementation of conversational agents in healthcare present both opportunities and risks. We argue for the urgent need to establish regulatory frameworks to ensure that the integration of conversational agents into mental healthcare is both safe and ethically sound.

We report on an application of three multivariate time series classification methods, Hive-Cote 2.0, MiniRocket, and Mr-Petsc, to gaze and eyelid movement data to classify expertise. Our methods can be used to noninvasively monitor performance and identify experts using low-grade equipment. The test case was Tetris, which is a video game in which players arrange falling blocks to clear horizontal lines with increasing points and difficulty as the game advances. In addition to being able to classify the expert players, we can attribute the patterns within a time series that led to a prediction with Mr-Petsc. This allows us to describe eye behavior that is associated with expertise. This method can be used in any performance classification that involves screen-based activity that is accompanied by eye movement recordings, for example with a webcam.

At least since Francis Bacon, the slogan “knowledge is power” has been used to capture the relationship between decision-making at a group level and information. We know that being able to shape the informational environment for a group is a way to shape their decisions; it is essentially a way to make decisions for them. This paper focuses on strategies that are intentionally, by design, impactful on the decision-making capacities of groups, effectively shaping their ability to take advantage of information in their environment. Among these, the best known are political rhetoric, propaganda, and misinformation. The phenomenon this paper brings out from these is a relatively new strategy, which we call slopaganda. According to The Guardian, News Corp Australia is currently churning out 3000 “local” generative AI (GAI) stories each week. In the coming years, such “generative AI slop” will present multiple knowledge-related (epistemic) challenges. We draw on contemporary research in cognitive science and artificial intelligence to diagnose the problem of slopaganda, describe some recent troubling cases, then suggest several interventions that may help to counter slopaganda.

This paper reviews some reasons for us believing that dreams are phenomenally conscious experiences. I point out that if dreams would be such then one should be able to draw analogies between them and waking conscious experiences at the level of folk psychology, behavior, and neuroanatomy. Instead, we find disanalogies at all these levels, so while we may have no strong reason to accept that dreams are unconscious, we have good reason to think they are different from conscious experiences. A safer bet is to think that they form a distinct sui generis psychological category. Sleep science should wait for consciousness science and until then treat its subject matter as distinct.

Advocates of moral enhancement through pharmacological, genetic, or other direct interventions sometimes explicitly argue, or assume without argument, that traditional moral education and development is insufficient to bring about moral enhancement. Traditional moral education grounded in a Kohlbergian theory of moral development is indeed unsuitable for that task; however, the psychology of moral development and education has come a long way since then. Recent studies support the view that moral cognition is a higher-order process, unified at a functional level, and that a specific moral faculty does not exist. It is more likely that moral cognition involves a number of different mechanisms, each connected to other cognitive and affective processes. Taking this evidence into account, we propose a novel, empirically informed approach to moral development and education, in children and adults, which is based on a cognitive-affective approach to moral dispositions. This is an interpretative approach that derives from the cognitive-affective personality system (Mischel and Shoda, 1995). This conception individuates moral dispositions by reference to the cognitive and affective processes that realise them. Conceived of in this way, moral dispositions influence an agent's behaviour when they interact with situational factors, such as mood or social context. Understanding moral dispositions in this way lays the groundwork for proposing a range of indirect methods of moral enhancement, techniques that promise similar results as direct interventions whilst posing fewer risks.

This study aimed to identify real-life experts working for a port authority and lay people (students) who played The Sustainable Port, a serious game aiming to simulate the dynamics occurring in a port area. To achieve this goal, we analyzed eye gaze data collected noninvasively using low-grade webcams from 28 participants working for the port authority of the Port of Rotterdam and 66 students. Such data were used for a classification task implemented using a MiniRocket classifier, an algorithm used for time-series classification. The classifier reached an F1 score of 0.75 (SD = 0.07), a PR AUC of 0.73 (SD = 0.14), and an ROC AUC of 0.75 (SD = 0.15) providing evidence that it is possible to identify real-life experts about maritime port management using data that can be obtained from a webcam. We speculate that the gaze direction used to train the MiniRocket may contain relevant information about the cognitive processes and decisions occurring throughout the gameplay. We suggest that the methods here presented not only can be used to detect experts playing simulations, such as serious games, but also to identify experts tackling screen-presented tasks.

Serious games are an effective method of reproducing aspects of the complex interplay between environments and stakeholders in business situations. In the game we describe here, The Sustainable Port, players experience what it is like to make decisions in such a complex environment. Their aim in the game is to grow the Port of Rotterdam while keeping economic growth in balance with sustainability goals. In this study, we assessed whether experienced Port of Rotterdam employees (PoR employees) show different psychophysiological patterns, and more specifically EAR-derived features, compared to students. We did this on the assumption that physiological patterns will tell us something about how people who are familiar with the environment of the Port of Rotterdam, more specifically Port of Rotterdam employees, make decisions compared to those lacking such familiarity.Our sample consisted of 28 PoR employees and 65 students, all of whom played The Sustainable Port game and had their faces recorded with a camera. The Eye Aspect Ratio was extracted from these recordings and then from those we extracted EAR-derived features. Our results show that Port of Rotterdam employees perform better than students and that the two groups are characterized by different physiological variations in their EAR-derived features. A logistic regression model used to identify PoR employees and students obtained an F1 score of 0.62, a PR AUC score of 0.64, and a ROC AUC score of 0.70. performing significantly above baseline suggesting the effectiveness of using EAR-derived features for this task. Our interpretation was further confirmed by a pseudo-R2 score used to evaluate the goodness of fit of a logistic regression model on the entire dataset. We found that Port of Rotterdam employees had a lower variation in blink rate per minute (blinks/m) and higher variation in the root mean square difference of successive difference in blinks (RMSSD), the consecutive difference between two continuous blinks. Moreover, this study shows that our methods were robust enough to negate the effects of confounders, such as biological sex and age that affect some other studies that analyze blinks.

Existing ethical guidelines that aim to guide the development of mental health apps tend to overemphasize the role of Western conceptual frameworks. While such frameworks have proved to be a useful first step in introducing ethics to a previously unregulated industry, the rapid global uptake of mental health apps requires thinking more deeply about the diverse populations these apps seek to serve. One way to do this is to introduce more intercultural ethical perspectives into app design and the guidelines that aim to encourage best practices. In addition to this, existing ethical guidelines can also benefit from the ethical scholarship from the feminist and disability traditions, both of which highlight specific ethical considerations for vulnerable users. Rethinking the ethical responsibilities of mental health app designers through the prisms of feminism, disability studies, and intercultural philosophy leads us to a more global and inclusive set of ethical considerations in app design. This white paper explores what existing guidelines for the regulation of mental health apps are missing. It also explores how these guidelines could be improved for users who inhabit an increasingly diverse and globalized world.

In this paper, we report on the development of The Sustainable Port video game, which aims to simulate the complex dynamics and decisions occurring in the present and future development of a port area considering environmental aspects (CO2 emissions) and profit. To evaluate if this game fulfills its purpose, we asked 75 students and 34 employees at the Port of Rotterdam (PoR) to play The Sustainable Port. Our results show that PoR employees score higher than students suggesting a transfer between real-life experience of being an employee in the port and performance in the game. Furthermore, port participants reported that The Sustainable Port can be successfully used to start discussions about the future of the Port of Rotterdam and to raise awareness about the complexity characterizing the decision-making processes occurring in a port environment. Our results, taken together, provide evidence of the effectiveness of The Sustainable Port in simulating dynamics occurring in port development and give us optimism about future applications.

The present narrative review seeks to unravel where we are now, and where we need to go to delineate the active ingredients in psychotherapy delivered by conversational agents (e.g., chatbots). While psychotherapy delivered by conversational agents has shown promising effectiveness for depression, anxiety, and psychological distress across several randomized controlled trials, little emphasis has been placed on the therapeutic processes in these interventions. The theoretical framework of this narrative review is grounded in prominent perspectives on the active ingredients in psychotherapy. Based on search terms derived from various theoretical perspectives, we conducted a systematic literature search of four scientific databases and identified 17 studies. Across the selected studies, three themes emerged: relationship variables, emotional venting, and cognitive factors. While methodological issues compromise the epistemic value of this evidence base, core questions also remain to be answered. Such questions include, but are not limited to, whether humans can form affectionate bonds to inanimate beings and whether these kind of mental health treatments should be understood as psychotherapy or something else. Researchers should therefore be cautious when applying theories of psychotherapy in the realm of conversational agents. We conclude the paper by introducing recommendations for future research, which we hope will help instigate methodologically sound studies in this field.

In this chapter we take stock of some of the complexities of the sprawling field of AI ethics. We consider questions like "what is the proper scope of AI ethics?" And "who counts as an AI ethicist?" At the same time, we flag several potential uses and abuses of AI ethics. These include challenges for the AI ethicist, including what qualifications they should have; the proper place and extent of futuring and speculation in the field; and the dilemmas concerning how we use our public and academic resources.

This study aimed to evaluate if eye blinks can be used to discriminate players with different performance in a session of Nintendo Entertainment System (NES) Tetris. To that end, we developed a state-of-the-art method for blink extraction from EAR measures, which is robust enough to be used with data collected by a low-grade webcam such as the ones widely available on laptop computers. Our results show a significant decrease in blink rate per minute (blinks/m) during the first minute of playing Tetris. After having defined 3 groups of proficiency based on in-game performance (Novices, Intermediates, and Experts) we found out that expert players display a significantly lower decrease in blinks/m compared to novices during the first minute of gameplay, which shows that Tetris players' proficiency can be detected by looking at eye blinks/m variations during the early phase of a game session. This difference in blinks/m is observed throughout the entire game session, which supports the general conclusion that proficient Tetris players have a lower decrease in blinks/m, even when playing more difficult levels. Finally, we offer some interpretations of this effect and the relationship that our results may have with the visual cognitive workload experienced during the gameplay.

The aim of this study was to test whether an online video game can be used to investigate planning ability and whether fluid intelligence, objective numeracy, and subjective numeracy are predictive of game performance. Our results demonstrate that fluid intelligence is particularly important, which is in line with previous non-game-based studies that show a relationship between classical planning tests and fluid intelligence. Video games have been previously used for research into cognitive processes and taking them online facilitates data collection on a larger scale. Online video games also afford data collection without the expense and stress of a laboratory environment. For these reasons, using online video games to investigate human cognition is a promising alternative to the classic cognitive paradigms used in laboratories.

In this study, we predict the different levels of performance in a Nintendo Entertainment System (NES) Tetris session based on the score and the number of matches played by the players. Using the first 45 seconds of gameplay, a Random Forest Classifier was trained on the five keys used in the game obtaining a ROC_AUC score of 0.80. Further analysis revealed that the number of down keys (forced drop) and the number of left keys (left translation) are the most relevant keys in this task, showing that by merely including the data from these two keys our Random Forest Classifier reached a ROC_AUC score of 0.83.We conclude that the keylogger data during the early phases of a game session can be successfully used to predict performance in longer sessions of Tetris.

Advocates of moral enhancement through pharmacological, genetic, or other direct interventions sometimes explicitly argue, or assume without argument, that traditional moral education and development is insufficient to bring about moral enhancement. Traditional moral education grounded in a Kohlbergian theory of moral development is indeed unsuitable for that task; however, the psychology of moral development and education has come a long way since then. Recent studies support the view that moral cognition is a higher-order process, unified at a functional level, and that a specific moral faculty does not exist. It is more likely that moral cognition involves a number of different mechanisms, each connected to other cognitive and affective processes. Taking this evidence into account, we propose a novel, empirically informed approach to moral development and education, in children and adults, which is based on a cognitive-affective approach to moral dispositions. This is an interpretative approach that derives from the cognitive-affective personality system (Mischel and Shoda, 1995). This conception individuates moral dispositions by reference to the cognitive and affective processes that realise them. Conceived of in this way, moral dispositions influence an agent's behaviour when they interact with situational factors, such as mood or social context. Understanding moral dispositions in this way lays the groundwork for proposing a range of indirect methods of moral enhancement, techniques that promise similar results as direct interventions whilst posing fewer risks.

In this chapter we identify three potentially morally problematic behaviours that are common among users of dating and hook-up apps (DHAs) and provide arguments as to why they may or may not be considered (a) in a category of their own, distinct from similar behaviours outside of DHAs; (b) caused or facilitated by affordances and business logic of DHAs; (c) as indeed morally wrong. We also consider ways in which morally problematic behaviours can be anticipated, mitigated, or even prevented by analysis of the ethical and moral dimensions of technologies and their afforded uses. Finally, we offer some possible directions for future work on these topics in particular and on the ethical consequences of DHAs in general.

In this study, we analyzed the blinking behavior of players in a video game tournament. Our aim was to test whether spontaneous blink patterns differ across levels of expertise. We used blink rate, blink duration, blink frequency, and eyelid movements represented by the Eye Aspect Ratio (EAR) to train a machine learning classifier to discriminate between different levels of expertise. Classifier performance was highly influenced by features such as the mean, standard deviation and median EAR. Moreover, further analysis suggests that blinking rate and blink duration are likely to increase along with the level of expertise. We speculate this may be indicative of a reduction in cognitive load and lowered stress of expert players. In general, our results suggest that EAR and blink patterns can be used to identify different levels of expertise of video game players.

The perceived duration of an interval depends on numerous aspects of the passed event both endogenous, including physiological arousal, level of wakefulness, attention, and surprise, as well as exogenous such as valence, salience, or context in the environment. There is some evidence that "time-giving" cues from the environment (zeitgebers) are coupled with time perception. The movement of the sun on the horizon was demonstrated to affect interval perception in a study conducted by Schatzschneider et al. (2016) claiming that the sun’s motion is a zeitgeber that influences time perception. In the present study, we undertake the first to our knowledge replication of this effect, extending the analysis to confounding aspects of the used paradigm. We aimed to test the effect of immersion, cognitive load, and changes in the speed of the sun on the horizon of the virtual environment on the perceived interval duration. We did not replicate the original effect, as reported by Schatzschneider et al., however, we did find that the perceived duration of an interval was affected by cognitive load, fatigue, and unpleasant symptoms caused by VR. In our analysis, we used Bayesian statistics to support our conclusion and offer its results as having some important consequences for the field.

In this study, we extracted facial action units (AUs) data during a Hearthstone tournament to investigate behavioural differences between expert, intermediate, and novice players. Our aim was to obtain insights into the nature of expertise and how it may be tracked using non-invasive methods such as AUs. These insights may shed light on the endogenous responses in the player and at the same time may provide information to the opponents during a competition. Our results show that player expertise may be characterised by specific patterns in facial expressions. More specifically, AU17 (chin raiser), AU25 (lips apart), and AU26 (jaws drop) intensity responses during gameplay may vary according to players' expertise. Such results were obtained by training a random forest classifier to test whether we can use these three AUs alone to accurately detect players' expertise. The classifier reached 0.75 accuracy on 5-fold cross-validation, after balancing the class weights, and 0.85 after having applied the Synthetic Minority Over-sampling Technique (SMOTE) function. These results suggest that AUs can be effectively used to discriminate different levels of expertise in competitive video game players.

It is easier to talk frankly to a person whom one trusts. It is also easier to agree with a scientist whom one trusts. Even though in both cases the psychological state that underlies the behavior is called ‘trust’, it is controversial whether it is a token of the same psychological type. Trust can serve an affective, epistemic, or other social function, and comes to interact with other psychological states in a variety of ways. The way that the functional role of trust changes across contexts and objects is further complicated when communities and individuals mediate it through technologies, and even more so when that mediation involves artificial intelligence (AI) and machine learning (ML). In this chapter I look at the ways in which trust in institutions, and specifically the medical profession, is affected by the use of AI and ML. There are two key elements of this analysis. The first is a disanalogy between institutional trust in medicine and institutional trust in science (Irzik and Kurtulmus 2021, 2019; Kitcher 2001). I note that as AI and ML become a more prominent part of medicine, trust in a medical institution becomes more like trust in a scientific institution. This is problematic for institutional trust in medicine and the practice of medicine, since institutional trust in science has been undermined by, among other things, the spread of misinformation online and the replication crisis (Romero 2019). There is also a strong analogy between the psychological state of the person who trusts a scientific report or testimony and the psychological state of a patient who trusts individual recommendations made by a medical professional in a clinical setting. In both cases, institutional trust makes it less likely that a mistake or malfeasance will result in reactive attitudes, such as blame or anger, directed at other individual members of that institution. However, it also renders people vulnerable enough to blame the institution itself. This, with time, can erode trust in the institution and naturally leads to policy recommendations that aim to preserve institutional trust. I survey two ways in which that can be done with institutional trust in medicine in the age of AI and ML.

This chapter examines the possibility of using AI technologies to improve human moral reasoning and decision-making, especially in the context of purchasing and consumer decisions. We characterize such AI technologies as artificial ethics assistants (AEAs). We focus on just one part of the AI-aided moral improvement question: the case of the individual who wants to improve their morality, where what constitutes an improvement is evaluated by the individual’s own values. We distinguish three broad areas in which an individual might think their own moral reasoning and decision-making could be improved: one’s actions, character, or other evaluable attributes fall short of one’s values and moral beliefs; one sometimes misjudges or is uncertain about what the right thing to do is in particular situations, given one’s values; one is uncertain about some fundamental moral questions or recognizes a possibility that some of one’s core moral beliefs and values are mistaken. We sketch why one might think that AI tools could be used to support moral improvement in those areas, and describe two types of assistance: preparatory assistance, including advice and training supplied in advance of moral deliberation; and on-the-spot assistance, including on-the-spot advice and facilitation of moral functioning over the course of moral deliberation. Then, we turn to some of the ethical issues that AEAs might raise, looking in particular at three under-appreciated problems posed by the use of AI for moral self-improvement: namely, reliance on sensitive moral data; the inescapability of outside influences on AEAs; and AEA usage prompting the user to adopt beliefs and make decisions without adequate reasons.

Kunstmatige intelligentie (AI) en systemen die met machine learning (ML) werken, kunnen veel onderdelen van het medische besluitvormingsproces ondersteunen of vervangen. Ook zouden ze artsen kunnen helpen bij het omgaan met klinische, morele dilemma’s. AI/ML-beslissingen kunnen zo in de plaats komen van professionele beslissingen. We betogen dat dit belangrijke gevolgen heeft voor de relatie tussen een patiënt en de medische professie als instelling, en dat dit onvermijdelijk zal leiden tot uitholling van het institutionele vertrouwen in de geneeskunde.

In this paper, we report on an experiment with The Walking Dead (TWD), which is a narrative-driven adventure game where players have to survive in a post-apocalyptic world filled with zombies. We used OpenFace software to extract action unit (AU) intensities of facial expressions characteristic of decision-making processes and then we implemented a simple convolution neural network (CNN) to see which AUs are predictive of decision-making. Our results provide evidence that the pre-decision variations in action units 17 (chin raiser), 23 (lip tightener), and 25 (parting of lips) are predictive of decision-making processes. Furthermore, when combined, their predictive power increased up to 0.81 accuracy on the test set; we offer speculations about why it is that these particular three AUs were found to be connected to decision-making. Our results also suggest that machine learning methods in combination with video games may be used to accurately and automatically identify complex decision-making processes using AU intensity alone. Finally, our study offers a new method to test specific hypotheses about the relationships between higher-order cognitive processes and behavior, which relies on both narrative video games and easily accessible software, like OpenFace.