Identifying Criteria for the Evaluation of the Implications of Brain Reading for Mental Privacy

Contemporary brain reading technologies promise to provide the possibility to decode and interpret mental states and processes. Brain reading could have numerous societally relevant implications. In particular, the private character of mind might be affected, generating ethical and legal concerns. This paper aims at equipping ethicists and policy makers with conceptual tools to support an evaluation of the potential applicability and the implications of current and near future brain reading technology. We start with clarifying the concepts of mind reading and brain reading, and the different kinds of mental states that could in principle be read. Subsequently, we devise an evaluative framework that is composed of five criteria-accuracy, reliability, informativity, concealability and enforceability-aimed at enabling a clearer estimation of the degree to which brain reading might be realistically deployed in contexts where mental privacy could be at stake. While accuracy and reliability capture how well a certain method can access mental content, informativity indicates the relevance the obtainable data have for practical purposes. Concealability and enforceability are particularly important for the evaluation of concerns about potential violations of mental privacy and civil rights. The former concerns the degree with which a brain reading method can be concealed from an individual's perception or awareness. The latter regards the extent to which a method can be used against somebody's will. With the help of these criteria, stakeholders can orient themselves in the rapidly developing field of brain reading.

Hypnotizability and Performance on a Prism Adaptation Test

The susceptibility to hypnosis, which can be measured by scales, is not merely a cognitive trait. In fact, it is associated with a number of physiological correlates in the ordinary state of consciousness and in the absence of suggestions. The hypnotizability-related differences observed in sensorimotor integration suggested a major role of the cerebellum in the peculiar performance of healthy subjects with high scores of hypnotic susceptibility (highs). In order to provide behavioral evidence of this hypothesis, we submitted 20 highs and 21 low hypnotizable participants (lows) to the classical cerebellar Prism Adaptation Test (PAT). We found that the highs' performance was significantly less accurate and more variable than the lows' one, even though the two groups shared the same characteristics of adaptation to prismatic lenses. Although further studies are required to interpret these findings, they could account for earlier reports of hypnotizability-related differences in postural control and blink rate, as they indicate that hypnotizability influences the cerebellar control of sensorimotor integration.

Machine Learning Against Terrorism: How Big Data Collection and Analysis Influences the Privacy-Security Dilemma

Rapid advancements in machine learning techniques allow mass surveillance to be applied on larger scales and utilize more and more personal data. These developments demand reconsideration of the privacy-security dilemma, which describes the tradeoffs between national security interests and individual privacy concerns. By investigating mass surveillance techniques that use bulk data collection and machine learning algorithms, we show why these methods are unlikely to pinpoint terrorists in order to prevent attacks. The diverse characteristics of terrorist attacks-especially when considering lone-wolf terrorism-lead to irregular and isolated (digital) footprints. The irregularity of data affects the accuracy of machine learning algorithms and the mass surveillance that depends on them which can be explained by three kinds of known problems encountered in machine learning theory: class imbalance, the curse of dimensionality, and spurious correlations. Proponents of mass surveillance often invoke the distinction between collecting data and metadata, in which the latter is understood as a lesser breach of privacy. Their arguments commonly overlook the ambiguity in the definitions of data and metadata and ignore the ability of machine learning techniques to infer the former from the latter. Given the sparsity of datasets used for machine learning in counterterrorism and the privacy risks attendant with bulk data collection, policymakers and other relevant stakeholders should critically re-evaluate the likelihood of success of the algorithms and the collection of data on which they depend.

Realising Meaningful Human Control Over Automated Driving Systems: A Multidisciplinary Approach

The paper presents a framework to realise "meaningful human control" over Automated Driving Systems. The framework is based on an original synthesis of the results of the multidisciplinary research project "Meaningful Human Control over Automated Driving Systems" lead by a team of engineers, philosophers, and psychologists at Delft University of the Technology from 2017 to 2021. Meaningful human control aims at protecting safety and reducing responsibility gaps. The framework is based on the core assumption that human persons and institutions, not hardware and software and their algorithms, should remain ultimately-though not necessarily directly-in control of, and thus morally responsible for, the potentially dangerous operation of driving in mixed traffic. We propose an Automated Driving System to be under meaningful human control if it behaves according to the relevant reasons of the relevant human actors (tracking), and that any potentially dangerous event can be related to a human actor (tracing). We operationalise the requirements for meaningful human control through multidisciplinary work in philosophy, behavioural psychology and traffic engineering. The tracking condition is operationalised via a proximal scale of reasons and the tracing condition via an evaluation cascade table. We review the implications and requirements for the behaviour and skills of human actors, in particular related to supervisory control and driver education. We show how the evaluation cascade table can be applied in concrete engineering use cases in combination with the definition of core components to expose deficiencies in traceability, thereby avoiding so-called responsibility gaps. Future research directions are proposed to expand the philosophical framework and use cases, supervisory control and driver education, real-world pilots and institutional embedding.

Paradoxical response to an emotional task: trait characteristics and heart-rate dynamics

The present study evaluated the heart-rate dynamics of subjects reporting decreased (responders) or paradoxically increased relaxation (nonresponders) at the end of a threatening movie. Heart-rate dynamics were characterized by indices extracted through recurrence quantification analysis (RQA) and detrended fluctuation analysis (DFA). These indices were studied as a function of a few individual characteristics: hypnotizability, gender, absorption, anxiety, and the activity of the behavioral inhibition and activation systems (BIS/BAS). Results showed that (a) the subjective experience of responsiveness is associated with the activity of the behavioral inhibition system and (b) a few RQA and DFA indices are able to capture the influence of cognitive-emotional traits, including hypnotizability, on the responsiveness to the threatening task.

Body sway modulation by hypnotizability and gender during low and high demanding postural conditions

The cognitive trait of hypnotizability, associated with the proneness to accept suggestions, exhibits several physiological correlates including the modulation of sensorimotor integration and, in particular, of postural control. In this respect, we have shown that, at eyes closure, healthy subjects with high hypnotizability scores (highs) having their feet 2 cm apart show larger and faster body sway with respect to low hypnotizable individuals (lows). The aim of the present study was to investigate whether hypnotizability modulates body sway during slightly more demanding and very difficult postural conditions such as feet together bipedal posture and one legged stance, respectively. The Center of Pressure (CoP) Area, mean Velocity, the CoP mean position (Xmean, Ymean) and its variability (SDx, SDy) in the frontal and sagittal planes were acquired in 18 highs (9 females) and 18 lows (9 females). Results showed that the previously observed lows' smaller and slower body sway was not present any longer. Nonetheless, hypnotizability interacted with gender in the modulation of the variability of the CoP movement in the frontal plane during both the bipedal feet together posture and one legged stance, as significant gender differences were observed only among lows. In conclusion, results confirm a role of hypnotizability in sensorimotor integration and support the relevance of hypnotic assessment in clinical settings, as hypnotizability may be responsible for part of the postural variability.

Superethics Instead of Superintelligence: Know Thyself, and Apply Science Accordingly

The human species is combining an increased understanding of our cognitive machinery with the development of a technology that can profoundly influence our lives and our ways of living together. Our sciences enable us to see our strengths and weaknesses, and build technology accordingly. What would future historians think of our current attempts to build increasingly smart systems, the purposes for which we employ them, the almost unstoppable goldrush toward ever more commercially relevant implementations, and the risk of superintelligence? We need a more profound reflection on what our science shows us about ourselves, what our technology allows us to do with that, and what, apparently, we aim to do with those insights and applications. As the smartest species on the planet, we don't need more intelligence. Since we appear to possess an underdeveloped capacity to act ethically and empathically, we rather require the kind of technology that enables us to act more consistently upon ethical principles. The problem is not to formulate ethical rules, it's to put them into practice. Cognitive neuroscience and AI provide the knowledge and the tools to develop the moral crutches we so clearly require. Why aren't we building them? We don't need superintelligence, we need superethics.

Human-machine coordination in mixed traffic as a problem of Meaningful Human Control

The urban traffic environment is characterized by the presence of a highly differentiated pool of users, including vulnerable ones. This makes vehicle automation particularly difficult to implement, as a safe coordination among those users is hard to achieve in such an open scenario. Different strategies have been proposed to address these coordination issues, but all of them have been found to be costly for they negatively affect a range of human values (e.g. safety, democracy, accountability…). In this paper, we claim that the negative value impacts entailed by each of these strategies can be interpreted as lack of what we call Meaningful Human Control over different parts of a sociotechnical system. We argue that Meaningful Human Control theory provides the conceptual tools to reduce those unwanted consequences, and show how "designing for meaningful human control" constitutes a valid strategy to address coordination issues. Furthermore, we showcase a possible application of this framework in a highly dynamic urban scenario, aiming to safeguard important values such as safety, democracy, individual autonomy, and accountability. Our meaningful human control framework offers a perspective on coordination issues that allows to keep human actors in control while minimizing the active, operational role of the drivers. This approach makes ultimately possible to promote a safe and responsible transition to full automation.

Eyes on the road: brain computer interfaces and cognitive distraction in traffic

Novel wearable neurotechnology is able to provide insight into its wearer's cognitive processes and offers ways to change or enhance their capacities. Moreover, it offers the promise of hands-free device control. These brain-computer interfaces are likely to become an everyday technology in the near future, due to their increasing accessibility and affordability. We, therefore, must anticipate their impact, not only on society and individuals broadly but also more specifically on sectors such as traffic and transport. In an economy where attention is increasingly becoming a scarce good, these innovations may present both opportunities and challenges for daily activities that require focus, such as driving and cycling. Here, we argue that their development carries a dual risk. Firstly, BCI-based devices may match or further increase the intensity of cognitive human-technology interaction over the current hands-free communication devices which, despite being widely accepted, are well-known for introducing a significant amount of cognitive load and distraction. Secondly, BCI-based devices will be typically harder than hands-free devices to both visually detect (e.g., how can law enforcement check when these extremely small and well-integrated devices are used?) and restrain in their use (e.g., how do we prevent users from using such neurotechnologies without breaching personal integrity and privacy?). Their use in traffic should be anticipated by researchers, engineers, and policymakers, in order to ensure the safety of all road users.