This book presents an alternative to conventional ideas about the evolution of the human intellect.

Although decision‐making algorithms are not new to medicine, the availability of vast stores of medical data, gains in computing power, and breakthroughs in machine learning are accelerating the pace of their development, expanding the range of questions they can address, and increasing their predictive power. In many cases, however, the most powerful machine learning techniques purchase diagnostic or predictive accuracy at the expense of our ability to access “the knowledge within the machine.” Without an explanation in terms of reasons or (...) a rationale for particular decisions in individual cases, some commentators regard ceding medical decision‐making to black box systems as contravening the profound moral responsibilities of clinicians. I argue, however, that opaque decisions are more common in medicine than critics realize. Moreover, as Aristotle noted over two millennia ago, when our knowledge of causal systems is incomplete and precarious—as it often is in medicine—the ability to explain how results are produced can be less important than the ability to produce such results and empirically verify their accuracy. (shrink)

_Virtue as Social Intelligence: An Empirically Grounded Theory_ takes on the claims of philosophical situationism, the ethical theory that is skeptical about the possibility of human virtue. Influenced by social psychological studies, philosophical situationists argue that human personality is too fluid and fragmented to support a stable set of virtues. They claim that virtue cannot be grounded in empirical psychology. This book argues otherwise. Drawing on the work of psychologists Walter Mischel and Yuichi Shoda, Nancy E. Snow argues that (...) the social psychological experiments that philosophical situationists rely on look at the wrong kinds of situations to test for behavioral consistency. Rather than looking at situations that are objectively similar, researchers need to compare situations that have similar meanings _for the subject_. When this is done, subjects exhibit behavioral consistencies that warrant the attribution of enduring traits, and virtues are a subset of these traits. Virtue can therefore be empirically grounded and virtue ethics has nothing to fear from philosophical situationism. (shrink)

The artificial intelligence models with machine learning that exhibit the best predictive accuracy, and therefore, the most powerful ones, are, paradoxically, those with the most opaque black-box architectures. At the same time, the unstoppable computerization of advanced industrial societies demands the use of these machines in a growing number of domains. The conjunction of both phenomena gives rise to a control problem on AI that in this paper we analyze by dividing the issue into two. First, we carry out (...) an epistemological examination of the AI’s opacity in light of the latest techniques to remedy it. And second, we evaluate the rationality of delegating tasks in opaque agents. (shrink)

Artificial intelligence (AI) systems have demonstrated impressive performance across a variety of clinical tasks. However, notoriously, sometimes these systems are 'black boxes'. The initial response in the literature was a demand for 'explainable AI'. However, recently, several authors have suggested that making AI more explainable or 'interpretable' is likely to be at the cost of the accuracy of these systems and that prioritising interpretability in medical AI may constitute a 'lethal prejudice'. In this paper, we defend the value of (...) interpretability in the context of the use of AI in medicine. Clinicians may prefer interpretable systems over more accurate black boxes, which in turn is sufficient to give designers of AI reason to prefer more interpretable systems in order to ensure that AI is adopted and its benefits realised. Moreover, clinicians may be justified in this preference. Achieving the downstream benefits from AI is critically dependent on how the outputs of these systems are interpreted by physicians and patients. A preference for the use of highly accurate black box AI systems, over less accurate but more interpretable systems , may itself constitute a form of lethal prejudice that may diminish the benefits of AI to - and perhaps even harm - patients. (shrink)

_A critical introduction to Hegel's metaphysics and philosophy of nature._.

In two experiments (total N=693) we explored whether people are willing to consider paintings made by AI-driven robots as art, and robots as artists. Across the two experiments, we manipulated three factors: (i) agent type (AI-driven robot v. human agent), (ii) behavior type (intentional creation of a painting v. accidental creation), and (iii) object type (abstract v. representational painting). We found that people judge robot paintings and human painting as art to roughly the same extent. However, people are much less (...) willing to consider robots as artists than humans, which is partially explained by the fact that they are less disposed to attribute artistic intentions to robots. (shrink)

Clark Glymour, Richard Scheines, Peter Spirtes and Kevin Kelly. Discovering Causal Structure: Artifical Intelligence, Philosophy of Science and Statistical Modeling.

Two leaders in the field offer a compelling analysis of the current state of the art and reveal the steps we must take to achieve a truly robust artificial intelligence. Despite the hype surrounding AI, creating an intelligence that rivals or exceeds human levels is far more complicated than we have been led to believe. Professors Gary Marcus and Ernest Davis have spent their careers at the forefront of AI research and have witnessed some of the greatest milestones (...) in the field, but they argue that a computer beating a human in Jeopardy! does not signal that we are on the doorstep of fully autonomous cars or superintelligent machines. The achievements in the field thus far have occurred in closed systems with fixed sets of rules, and these approaches are too narrow to achieve genuine intelligence. The real world, in contrast, is wildly complex and open-ended. How can we bridge this gap? What will the consequences be when we do? Taking inspiration from the human mind, Marcus and Davis explain what we need to advance AI to the next level, and suggest that if we are wise along the way, we won't need to worry about a future of machine overlords. If we focus on endowing machines with common sense and deep understanding, rather than simply focusing on statistical analysis and gatherine ever larger collections of data, we will be able to create an AI we can trust--in our homes, our cars, and our doctors' offices. Rebooting AI provides a lucid, clear-eyed assessment of the current science and offers an inspiring vision of how a new generation of AI can make our lives better. (shrink)

Artificial intelligence represents a key technology being inbuilt into evermore products. Research investigating attitudes towards artificial intelligence surprisingly is still scarce, although it becomes apparent that artificial intelligence will shape societies around the globe. To better understand individual differences in attitudes towards artificial intelligence, the present study investigated in n = 351 participants associations between the Affective Neuroscience Personality Scales (ANPS) and the Attitudes towards Artificial Intelligence framework (ATAI). It could be observed that in particular (...) higher levels of SADNESS were associated with higher negative attitudes towards AI (fearing AI). The findings are discussed in this work from an evolutionary perspective because primary emotional systems—according to Affective Neuroscience Theory—represent tools for survival, which have been homologously conserved across mammalian species including homo sapiens. (shrink)

It is a popular view thatpractical deliberation excludes foreknowledge of one's choice. Wolfgang Spohn and Isaac Levi have argued that not even a purely probabilistic self-predictionis available to thedeliberator, if one takes subjective probabilities to be conceptually linked to betting rates. It makes no sense to have a betting rate for an option, for one's willingness to bet on the option depends on the net gain from the bet, in combination with the option's antecedent utility, rather than on the offered (...) odds. And even apart from this consideration, assigning probabilities to the options among which one is choosing is futile since such probabilities could be of no possible use in choice. The paper subjects these arguments to critical examination and suggests that, appearances notwithstanding, practical deliberation need not crowd outself-prediction. (shrink)

This article is an update of our previous article in this SGJ journal, titled: On Gödel's Incompleteness Theorem, Artificial Intelligence & Human Mind. We provide some commentary on the latest developments around AI, humanoid robotics, and future scenario. Basically, we argue that a more thoughtful approach to the future is "techno-realism.".

Habitual actions unfold without conscious deliberation or reflection, and yet often seem to be intelligently adjusted to situational intricacies. A question arises, then, as to how it is that habitual actions can exhibit this form of intelligence, while falling outside the domain of paradigmatically intentional actions. Call this the intelligence puzzle of habits. This puzzle invites three standard replies. Some stipulate that habits lack intelligence and contend that the puzzle is ill-posed. Others hold that habitual actions can (...) exhibit intelligence because they are guided by automatic yet rational, propositional processes. Others still suggest that habits guide intelligent behaviour without involving propositional states by shaping perception in action-soliciting ways. We develop an alternative fourth answer based on John Dewey’s pragmatist account of habit. We argue that habits promote intelligent behaviour by shaping perception, by forming an interrelated network among themselves, and by cooperating with the environment. (shrink)

BackgroundHealthcare providers have to make ethically complex clinical decisions which may be a source of stress. Researchers have recently introduced Artificial Intelligence (AI)-based applications to assist in clinical ethical decision-making. However, the use of such tools is controversial. This review aims to provide a comprehensive overview of the reasons given in the academic literature for and against their use.MethodsPubMed, Web of Science, Philpapers.org and Google Scholar were searched for all relevant publications. The resulting set of publications was title and (...) abstract screened according to defined inclusion and exclusion criteria, resulting in 44 papers whose full texts were analysed using the Kuckartz method of qualitative text analysis.ResultsArtificial Intelligence might increase patient autonomy by improving the accuracy of predictions and allowing patients to receive their preferred treatment. It is thought to increase beneficence by providing reliable information, thereby, supporting surrogate decision-making. Some authors fear that reducing ethical decision-making to statistical correlations may limit autonomy. Others argue that AI may not be able to replicate the process of ethical deliberation because it lacks human characteristics. Concerns have been raised about issues of justice, as AI may replicate existing biases in the decision-making process.ConclusionsThe prospective benefits of using AI in clinical ethical decision-making are manifold, but its development and use should be undertaken carefully to avoid ethical pitfalls. Several issues that are central to the discussion of Clinical Decision Support Systems, such as justice, explicability or human–machine interaction, have been neglected in the debate on AI for clinical ethics so far.Trial registrationThis review is registered at Open Science Framework (https://osf.io/wvcs9). (shrink)

As organizational leaders worry about the appalling low percentage of people who feel engaged in their work, academics are trying to understand what causes an increase in engagement. We collected survey data from 231 team members from two organizations. We examined the impact of team members’ emotional intelligence (EI) and their perception of shared personal vision, shared positive mood, and perceived organizational support (POS) on the members’ degree of organizational engagement. We found shared vision, shared mood, and POS have (...) a direct, positive association with engagement. In addition, shared vision and POS interact with EI to positively influence engagement. Besides highlighting the importance of shared personal vision, positive mood, and POS, our study contributes to the emergent understanding of EI by revealing EI’s amplifying effect on shared vision and POS in relation to engagement. We conclude by discussing the research and practical implications of this study. (shrink)

We describe a strategy for integration of data that is based on the idea of semantic enhancement. The strategy promises a number of benefits: it can be applied incrementally; it creates minimal barriers to the incorporation of new data into the semantically enhanced system; it preserves the existing data (including any existing data-semantics) in their original form (thus all provenance information is retained, and no heavy preprocessing is required); and it embraces the full spectrum of data sources, types, models, and (...) modalities (including text, images, audio, and signals). The result of applying this strategy to a given body of data is an evolving Dataspace that allows the application of a variety of integration and analytic processes to diverse data contents. We conceive semantic enhancement (SE) as a lightweight and flexible process that leverages the richness of the structured contents of the Dataspace without adding storage and processing burdens to what, in the intelligence domain, will be an already storage- and processing-heavy starting point. SE works not by changing the data to which it is applied, but rather by adding an extra semantic layer to this data. We sketch how the semantic enhancement approach can be applied consistently and in cumulative fashion to new data and data-models that enter the Dataspace. (shrink)

The question 'What is intelligence?' may seem simple to answer, but the study and measurement of human intelligence is one of the most controversial subjects in psychology. For much of its history, the focus has been on differences between people, on what it means for one person to be more intelligent than another, and how such differences might have arisen, obscuring efforts to understand the general nature of intelligence. These are obviously fundamental questions, still widely debated and (...) misunderstood. New definitions of intelligence and new factors affecting intelligence are frequently being described, while psychometric testing is applied in most large industries.IQ and Human Intelligence provides a clear, authoritative overview of the main issues surrounding this fascinating area, including the development of IQ tests, the heritability of intelligence, theories of intelligence, environmental effects on IQ, factor analysis, relationship of cognitive psychology to measuring IQ, and intelligence in the social context. The clear, accessible style and numerous explanatory boxes make this the ideal text for advanced undergraduate and graduate students in psychology. Online Resource CentreThe Online Resource Centre to accompany IQ and Human Intelligence features the following resources:For registered adopters of the text:- Figures from the book, available to downloadFor students:- Hyperlinks to primary literature articles cited in the and 'Further Reading' sections of the book. (shrink)

This study examines factors impacting ethical behavior of 103 hospital nurses. The level of emotional intelligence and ethical behavior of peers had a significant impact on ethical behavior of nurses. Independence climate had a significant impact on ethical behavior of nurses. Other ethical climate types such as professional, caring, rules, instrumental, and efficiency did not impact ethical behavior of respondents. Implications of this study for researchers and practitioners are discussed.

Artificial intelligence, or AI, is a cross-disciplinary approach to understanding, modeling, and creating intelligence of various forms. It is a critical branch of cognitive science, and its influence is increasingly being felt in other areas, including the humanities. AI applications are transforming the way we interact with each other and with our environment, and work in artificially modeling intelligence is offering new insights into the human mind and revealing new forms mentality can take. This volume of original (...) essays presents the state of the art in AI, surveying the foundations of the discipline, major theories of mental architecture, the principal areas of research, and extensions of AI such as artificial life. With a focus on theory rather than technical and applied issues, the volume will be valuable not only to people working in AI, but also to those in other disciplines wanting an authoritative and up-to-date introduction to the field. (shrink)

In their article, Sedlakova and Trachsel (2023) propose a holistic, ethical, and epistemic analysis of conversational artificial intelligence (CAI) in psychotherapeutic settings. They mainly descri...

The idea of using artificial intelligence as a support system in the sentencing process has attracted increasing attention. For instance, it has been suggested that machine learning algorithms may help in curbing problems concerning inter-judge sentencing disparity. The purpose of the present article is to examine the merits of this possibility. It is argued that, insofar as the unfairness of sentencing disparity is held to reflect a retributivist view of proportionality, it is not necessarily the case that increasing inter-judge (...) uniformity in sentencing is desirable. More generally, it is shown that the idea of introducing machine learning algorithms, that produce sentencing predictions on the ground of a dataset that is built of previous sentencing decisions, faces serious problems if there exists a discrepancy between actual sentencing practice and the sentences that are ideally desirable. (shrink)

“Only a small community has concentratedon general intelligence. No one has tried to make a thinking machine... The bottom line is that we really haven’t progressed too far toward a truly intelligent machine. We have collections of dumb specialists in small domains; the true majesty of general intelligence still awaits our attack.... We have got to get back to the deepest questions of AI and general intelligence... ” –MarvinMinsky as interviewed in Hal’s Legacy, edited by David Stork, (...) 2000. Our goal in creating this edited volume has been to?ll an apparent gap in the scienti?c literature, by providing a coherent presentation of a body of contemporary research that, in spite of its integral importance, has hitherto kept a very low pro?le within the scienti?c and intellectual community. This body of work has not been given a name before; in this book we christen it “Arti?cial General Intelligence”. What distinguishes AGI work from run-of-the-mill “arti?cial intelligence” research is that it is explicitly focused on engineering general intelligence in the short term. We have been active researchers in the AGI?eld for many years, and it has been a pleasure to gather together papers from our colleagues working on related ideas from their own perspectives. In the Introduction we give a conceptual overview of the AGI?eld, and also summarize and interrelate the key ideas of the papers in the subsequent chapters. (shrink)

The European Union Commission’s whitepaper on Artificial Intelligence proposes shaping the emerging AI market so that it better reflects common European values. It is a master plan that builds upon the EU AI High-Level Expert Group guidelines. This article reviews the masterplan, from a culture cycle perspective, to reflect on its potential clashes with current societal, technical, and methodological constraints. We identify two main obstacles in the implementation of this plan: the lack of a coherent EU vision to drive (...) future decision-making processes at state and local levels and the lack of methods to support a sustainable diffusion of AI in our society. The lack of a coherent vision stems from not considering societal differences across the EU member states. We suggest that these differences may lead to a fractured market and an AI crisis in which different members of the EU will adopt nation-centric strategies to exploit AI, thus preventing the development of a frictionless market as envisaged by the EU. Moreover, the Commission aims at changing the AI development culture proposing a human-centred and safety-first perspective that is not supported by methodological advancements, thus taking the risks of unforeseen social and societal impacts of AI. We discuss potential societal, technical, and methodological gaps that should be filled to avoid the risks of developing AI systems at the expense of society. Our analysis results in the recommendation that the EU regulators and policymakers consider how to complement the EC programme with rules and compensatory mechanisms to avoid market fragmentation due to local and global ambitions. Moreover, regulators should go beyond the human-centred approach establishing a research agenda seeking answers to the technical and methodological open questions regarding the development and assessment of human-AI co-action aiming for a sustainable AI diffusion in the society. (shrink)

The application of artificial intelligence technology has evolved into an influential endeavor to improve firm performance, but little research considers the relationship among artificial intelligence capability, management, driven decision making, and firm performance. Based on the resource-based view and existing findings, this paper constructs a higher-order model of AIC and suggests a research model of e-commerce firm AIC and firm performance. We collected 394 valid questionnaires and conducted data analysis using partial least squares structural equation modeling. As a (...) second-order variable, AIC was formed by three first-order variables: basic, proclivity, and skills. AIC indirectly affects firm performance through creativity, AIM, and AI-driven decision making. Firm creativity, AIM, and AIDDM are essential variables between AIC and firm performance. Innovation culture positive moderates the relationship between firm creativity and AIDDM as well as the relationship between AIDDM and firm performance. Environmental dynamism positive mediates the connection between AIM and AIDDM. Among the control variables, firm age negatively affects firm performance, and employee size does not. This study helps enterprises leverage AI to improve firm performance, achieve a competitive advantage, and contribute to theory and management practice. (shrink)

Insights into the intelligence throughout the natural and technical environment, in the fabric of our devices and dwellings, in our clothes, and under our skin. Is there a way to understand the materials that surround us not as passive objects, but as other intelligences interacting with our own? In Parallel Minds, expert in materials science and nanotechnology Laura Tripaldi delivers not only detailed insights into the properties and emergent behaviors of matter as revealed by state-of-the-art chemistry, synthetic biology, and (...) nanotech, but also a rich philosophical reflection that crosses the frontier between nature and culture, where the most cutting-edge scientific syntheses resonate with ancient myth. The result is a technomaterial bestiary full of unexpected encounters with “strange minds”—from cobwebs to kevlar and carbon fibre, from centaurs to amoebas to arachnids, from polycephalic slime to resonating plasmons, from viruses to golems. Parallel Minds reveals the intelligence at large throughout the natural and technical environment, in the fabric of our devices and dwellings, in our clothes, and even under our skin. Full of lateral ideas and unexpected images, Tripaldi’s book imbues the study and synthesis of materials with a new urgency. For not only do the materials that surround us participate actively in the construction of the world in which we live, but harnessing their ability to interact intelligently with their environment could be the key to the future of our species. (shrink)

This study examined 4-year-olds’ problem-solving under different social conditions. Children had to use water in order to extract a buoyant object from a narrow tube. When faced with the problem ‘cold’ without cues, nearly all children were unsuccessful. But when a solution-suggesting video was pedagogically delivered prior to the task, most children succeeded. Showing children the same video in a non-pedagogical manner did not lift their performance above baseline and was less effective than framing it pedagogically. The findings support ideas (...) central to natural pedagogy, 148–153, 2009). They also challenge the Cultural Intelligence hypothesis, according to which only humans’ social, but not their physical, cognition differs qualitatively from that of great apes. A more radical, transformative variant of the Cultural Intelligence hypothesis is suggested according to which humans’ physical cognition is shaped by their social nature and must therefore be recognized as equally distinctive as their social cognition. (shrink)

People with higher levels of emotional intelligence (EI: adaptive emotional traits, skills and abilities) typically achieve more positive life outcomes, such as psychological wellbeing, educational attainment, and job-related success. Although the underpinning mechanisms linking EI with those outcomes are largely unknown, it has been suggested that EI may work as a ‘stress buffer’. Theoretically, when faced with a stressful situation, emotionally intelligent individuals should show a more adaptive response than those with low EI, such as reduced reactivity (less mood (...) deterioration, less physiological arousal), and faster recovery once the threat has passed. A growing number of studies have begun to investigate that hypothesis in respect to EI measured as both an ability (AEI) and trait (TEI), but results are unclear. To test the ‘stress-buffering’ function of EI, we systematically reviewed experimental studies that explored the relationship between both types of EI and acute stress reactivity or recovery. By searching 4 databases, we identified 45 eligible studies. Results showed that EI was only adaptive in certain contexts, and that findings differed according to stressor type, and how EI was measured. In terms of stress reactivity, TEI related to less mood deterioration during sports-based stressors (e.g. competitions), physical discomfort (e.g. dental procedure), and cognitive stressors (e.g. memory tasks), but did not appear as helpful in other contexts (e.g. speeches). Furthermore, effects of TEI on physiological stress responses, such as heart rate, were inconsistent. Effects of AEI on subjective and objective stress reactivity were often non-significant, with high levels detrimental in some cases. However, data suggest that both higher AEI and TEI relate to faster recovery from acute stress. In conclusion, results provide mixed support for the stress-buffering effect of EI. Limitations and quality of studies are also discussed. Findings could have implications for EI training programmes. (shrink)