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Online questionnaires that use crowdsourcing platforms to recruit participants have become commonplace, due to their ease of use and low costs. Artificial intelligence (AI)-based large language models (LLMs) have made it easy for bad actors to automatically fill in online forms, including generating meaningful text for open-ended tasks. These technological advances threaten the data quality for studies that use online questionnaires. This study tested whether text generated by an AI for the purpose of an online study can be detected by both humans and automatic AI detection systems. While humans were able to correctly identify the authorship of such text above chance level (76% accuracy), their performance was still below what would be required to ensure satisfactory data quality. Researchers currently have to rely on a lack of interest among bad actors to successfully use open-ended responses as a useful tool for ensuring data quality. Automatic AI detection systems are currently completely unusable. If AI submissions of responses become too prevalent, then the costs associated with detecting fraudulent submissions will outweigh the benefits of online questionnaires. Individual attention checks will no longer be a sufficient tool to ensure good data quality. This problem can only be systematically addressed by crowdsourcing platforms. They cannot rely on automatic AI detection systems and it is unclear how they can ensure data quality for their paying clients. [ABSTRACT FROM AUTHOR]

This article uses a novel method—the Imitation Game—to search for lasting ethnic biculturalism. I address the case of Finland-Swedes and the Finnish-speaking majority in Finland. While it is known that most Finland-Swedes are fluent in two languages, Swedish and Finnish, the question remains whether they are fluent in two respective cultures. The Imitation Game investigates biculturalism and alternative acculturation paths as a function of cultural competences. As part of a mixed-methods analysis, I introduce the Group Relations Graph as a comparative framework to pinpoint acculturation paths based on whether members of the minority can exhibit competence in minority and majority culture. The findings display acculturation as a dynamic process of multiple concurrent acculturation paths: the studied groups are assimilated with respect to values and experiences, and separated in terms of knowledge and linguistic style. Finland-Swedes are a powerful minority group with both the resources and the intention to maintain a unique Finland-Swedish culture, yet in terms of cultural competences they appear indistinguishable from the Finnish-speaking majority—except for within the context of an ethnic enclave institution. Ultimately, the article posits a pessimistic assessment for the possibility of lasting biculturalism and, by extension, a multicultural society. [ABSTRACT FROM AUTHOR]

Online questionnaires that use crowdsourcing platforms to recruit participants have become commonplace, due to their ease of use and low costs. Artificial intelligence (AI)-based large language models (LLMs) have made it easy for bad actors to automatically fill in online forms, including generating meaningful text for open-ended tasks. These technological advances threaten the data quality for studies that use online questionnaires. This study tested whether text generated by an AI for the purpose of an online study can be detected by both humans and automatic AI detection systems. While humans were able to correctly identify the authorship of such text above chance level (76% accuracy), their performance was still below what would be required to ensure satisfactory data quality. Researchers currently have to rely on a lack of interest among bad actors to successfully use open-ended responses as a useful tool for ensuring data quality. Automatic AI detection systems are currently completely unusable. If AI submissions of responses become too prevalent, then the costs associated with detecting fraudulent submissions will outweigh the benefits of online questionnaires. Individual attention checks will no longer be a sufficient tool to ensure good data quality. This problem can only be systematically addressed by crowdsourcing platforms. They cannot rely on automatic AI detection systems and it is unclear how they can ensure data quality for their paying clients.

Artificial intelligence (AI) technology, such as Chat Generative Pre-trained Transformer (ChatGPT), is evolving quickly and having a significant impact on the higher education sector. Although the impact of ChatGPT on academic integrity processes is a key concern, little is known about whether academics can reliably recognise texts that have been generated by AI. This qualitative study applies Turing's Imitation Game to investigate 16 education academics' perceptions of two pairs of texts written by either ChatGPT or a human. Pairs of texts, written in response to the same task, were used as the stimulus for interviews that probed academics' perceptions of text authorship and the textual features that were important in their decision-making. Results indicated academics were only able to identify AI-generated texts half of the time, highlighting the sophistication of contemporary generative AI technology. Academics perceived the following categories as important for their decision-making: voice, word usage, structure, task achievement and flow. All five categories of decision-making were variously used to rationalise both accurate and inaccurate decisions about text authorship. The implications of these results are discussed with a particular focus on what strategies can be applied to support academics more effectively as they manage the ongoing challenge of AI in higher education. Implications for practice or policy: • Experienced academics may be unable to distinguish between texts written by contemporary generative AI technology and humans. • Academics are uncertain about the current capabilities of generative AI and need support in redesigning assessments that succeed in providing robust evidence of student achievement of learning outcomes. • Institutions must assess the adequacy of their assessment designs, AI use policies, and AI-related procedures to enhance students' capacity for effective and ethical use of generative AI technology. [ABSTRACT FROM AUTHOR]

The Imitation Game is a new method and, as such, it is important to show that its results are plausible and replicable. We tested this by conducting Imitation Games on religion in a range of European countries, returning approximately 12 months later to repeat the research. The idea was that non-Christian members of strongly Christian countries would find it easy to pass as members of the practicing majority because Christian beliefs and practices would be ubiquitous. In more secular countries, the expectation was that non-Christians would find it harder to pass as Christian because religious practices are less visible. We show that, despite some anomalous results, the data are consistent with expectations derived from survey data and that the claim to have replicated the results can be supported. We also suggest that our experiences show that questions of replication in the social sciences cannot be resolved by statistical meta-analysis alone. [ABSTRACT FROM AUTHOR]

What do producers know about their audiences, how do they know it, and how does this knowledge inform their output? Recent research has tackled these questions as they relate to journalists and social media users, but few studies have put their knowledge to the test, never mind with the audience's help. This study does so by conceptualizing the producers' orientation to, and tacit knowledge of their audiences, and by introducing the Imitation Game methodology to media and communication studies. It reports on a study that tested whether Radio-Canada producers could pass as members of their audience to actual members acting as judges. In 12 imitation games comprising dialogue around 63 questions, producers convincingly mimicked audience members on knowledge, preference, and biographical questions, and nearly so on opinion questions. Their critical reflections and plausible accounts of reception practice generally confounded judges across question types, thus demonstrating the method's promise. [ABSTRACT FROM AUTHOR]

Alan Turing’s 1950 imitation game has been widely understood as a means for testing if an entity is intelligent. Following a series of papers by Diane Proudfoot, I offer a socio-technological interpretation of Turing’s paper and present an alternative way of understanding both the imitation game and Turing’s concept of intelligence. Turing, I claim, saw intelligence as a social concept, meaning that possession of intelligence is a property determined by society’s attitude toward the entity. He realized that as long as human society held a prejudiced attitude toward machinery—seeing machines a priori as mindless objects—machines could not be said to be intelligent, by definition. He also realized, though, that if humans’ a priori, chauvinistic attitude toward machinery changed, the existence of intelligent machines would become logically possible. Turing thought that such a change would eventually occur: He believed that when scientists overcome the technological challenge of constructing sophisticated machines that could imitate human verbal behavior—i.e., do well in the imitation game—humans’ prejudiced attitude toward machinery will have altered in such a way that machines could be said to be intelligent. The imitation game, for Turing, was not an intelligence test, but a technological aspiration whose realization would likely involve a change in society’s attitude toward machines. [ABSTRACT FROM AUTHOR]

Given the difficulties of defining "machine" and "think", Turing proposed to replace the question "Can machines think?" with a proxy: how well can an agent engage in sustained conversation with a human? Though Turing neither described himself as a philosopher nor published much on philosophical matters, his Imitation Game has stood the test of time. Most understood at that time that success would not come easy, but few would have guessed just how difficult engaging in ordinary conversation would turn out to be. Despite the proliferation of language processing tools, we have seen little progress towards doing well at the Imitation Game. Had Turing instead suggested ability at games or even translation as a proxy for intelligence, his paper might have been forgotten. We argue that these and related problems are amenable to mechanical, though sophisticated, formal techniques. Turing appears to have taken care to select sustained, productive conversation and that alone as his proxy. Even simple conversation challenges a machine to engage in the rich practice of human discourse in all its generality and variety. [ABSTRACT FROM AUTHOR]

The fast development of synthetic media, commonly known as deepfakes, has cast new light on an old problem, namely—to what extent do people have a moral claim to their likeness, including personally distinguishing features such as their voice or face? That people have at least some such claim seems uncontroversial. In fact, several jurisdictions already combat deepfakes by appealing to a “right to identity.” Yet, an individual’s disapproval of appearing in a piece of synthetic media is sensible only insofar as the replication is successful. There has to be some form of (qualitative) identity between the content and the natural person. The question, therefore, is how this identity can be established. How can we know whether the face or voice featured in a piece of synthetic content belongs to a person who makes claim to it? On a trivial level, this may seem an easy task—the person in the video is A insofar as he or she is recognised as being A. Providing more rigorous criteria, however, poses a serious challenge. In this paper, I draw on Turing’s imitation game, and Floridi’s method of levels of abstraction, to propose a heuristic to this end. I call it the identification game. Using this heuristic, I show that identity cannot be established independently of the purpose of the inquiry. More specifically, I argue that whether a person has a moral claim to content that allegedly uses their identity depends on the type of harm under consideration. [ABSTRACT FROM AUTHOR]

Introduction: The objective of this study is to investigate the extent to which sighted persons understand thought processes of persons who are visually impaired (i.e., those who are blind or have low vision). The investigation focused on a street-crossing task. Method: Participants were 15 visually impaired persons and 21 sighted persons. The sighted group included 6 orientation and mobility (O&M) specialists and 15 individuals who represent the sighted public and have infrequent interactions with people with visual impairments. Participants provided verbal reports of their thought processes associated with a street-crossing scenario twice, once as a "non-pretender" and once as a "pretender." In the non-pretender role, participants verbalized their thinking in line with their actual state of sightedness. In the pretender role, participants with visual impairments pretended that they did not have any visual impairments, whereas sighted participants pretended that they were blind. Transcribed data were analyzed using thematic analysis, resulting in three themes with 14 subthemes. The genuine responses of visually impaired participants and the imitated responses of the sighted participants were compared using proportions of the subthemes. Results: Fisher's exact z tests demonstrated that out of the 14 subthemes, the visually impaired participants' proportions were (a) similar to those of sighted O&M specialists in 10 subthemes and (b) different from those of the other sighted participants in seven subthemes. Participants verbalized fewer thoughts when describing sighted navigation than when describing navigation as a person with visual impairment. Discussion: Sighted persons with infrequent social interaction with people who are visually impaired seem to be less successful at "pretending to be blind," indicating that they may have difficulties in adopting the perspective of people with visual impairments. Implications for Practitioners: Sighted O&M specialists develop an understanding of the cognitive processes of people who are visually impaired through training and contact. Other professionals that support these individuals (e.g., technology designers) could benefit from developing such an understanding and immersing themselves in the social life of people with visual impairments. [ABSTRACT FROM AUTHOR]

The study of the sociology of scientific knowledge distinguishes between contributory and interactional experts. Contributory experts have practical expertise—they can "walk the walk." Interactional experts have internalized the tacit components of expertise—they can "talk the talk" but are not able to reliably "walk the walk." Interactional expertise permits effective communication between contributory experts and others (e.g., laypeople), which in turn facilitates working jointly toward shared goals. Interactional expertise is attained through long-term immersion into the expert community in question. To assess interactional expertise, researchers developed the imitation game—a variant of the Turing test—to test whether a person, or a particular group, possesses interactional expertise of another. The imitation game, which has been used mainly in sociology to study the social nature of knowledge, may also be a useful tool for researchers who focus on cognitive aspects of expertise. In this paper, we introduce a modified version of the imitation game and apply it to examine interactional expertise in the context of blindness. Specifically, we examined blind and sighted individuals' ability to imitate each other in a street-crossing scenario. In Phase I, blind and sighted individuals provided verbal reports of their thought processes associated with crossing a street—once while imitating the other group (i.e., as a pretender) and once responding genuinely (i.e., as a non-pretender). In Phase II, transcriptions of the reports were judged as either genuine or imitated responses by a different set of blind and sighted participants, who also provided the reasoning for their decisions. The judges comprised blind individuals, sighted orientation-and-mobility specialists, and sighted individuals with infrequent socialization with blind individuals. Decision data were analyzed using probit mixed models for signal-detection-theory indices. Reasoning data were analyzed using natural-language-processing (NLP) techniques. The results revealed evidence that interactional expertise (i.e., relevant tacit knowledge) can be acquired by immersion in the group that possesses and produces the expert knowledge. The modified imitation game can be a useful research tool for measuring interactional expertise within a community of practice and evaluating practitioners' understanding of true experts. [ABSTRACT FROM AUTHOR]

The study of the sociology of scientific knowledge distinguishes between contributory and interactional experts. Contributory experts have practical expertise—they can “walk the walk.” Interactional experts have internalized the tacit components of expertise—they can “talk the talk” but are not able to reliably “walk the walk.” Interactional expertise permits effective communication between contributory experts and others (e.g., laypeople), which in turn facilitates working jointly toward shared goals. Interactional expertise is attained through long-term immersion into the expert community in question. To assess interactional expertise, researchers developed the imitation game—a variant of the Turing test—to test whether a person, or a particular group, possesses interactional expertise of another. The imitation game, which has been used mainly in sociology to study the social nature of knowledge, may also be a useful tool for researchers who focus on cognitive aspects of expertise. In this paper, we introduce a modified version of the imitation game and apply it to examine interactional expertise in the context of blindness. Specifically, we examined blind and sighted individuals’ ability to imitate each other in a street-crossing scenario. In Phase I, blind and sighted individuals provided verbal reports of their thought processes associated with crossing a street—once while imitating the other group (i.e., as a pretender) and once responding genuinely (i.e., as a non-pretender). In Phase II, transcriptions of the reports were judged as either genuine or imitated responses by a different set of blind and sighted participants, who also provided the reasoning for their decisions. The judges comprised blind individuals, sighted orientation-and-mobility specialists, and sighted individuals with infrequent socialization with blind individuals. Decision data were analyzed using probit mixed models for signal-detection-theory indices. Reasoning data were analyzed using natural-language-processing (NLP) techniques. The results revealed evidence that interactional expertise (i.e., relevant tacit knowledge) can be acquired by immersion in the group that possesses and produces the expert knowledge. The modified imitation game can be a useful research tool for measuring interactional expertise within a community of practice and evaluating practitioners’ understanding of true experts.

Given the difficulties of defining “machine” and “think”, Turing proposed to replace the question “Can machines think?” with a proxy: how well can an agent engage in sustained conversation with a human? Though Turing neither described himself as a philosopher nor published much on philosophical matters, his Imitation Game has stood the test of time. Most understood at that time that success would not come easy, but few would have guessed just how difficult engaging in ordinary conversation would turn out to be. Despite the proliferation of language processing tools, we have seen little progress towards doing well at the Imitation Game. Had Turing instead suggested ability at games or even translation as a proxy for intelligence, his paper might have been forgotten. We argue that these and related problems are amenable to mechanical, though sophisticated, formal techniques. Turing appears to have taken care to select sustained, productive conversation and that alone as his proxy. Even simple conversation challenges a machine to engage in the rich practice of human discourse in all its generality and variety.

The Turing Test is routinely understood as a behaviourist test for machine intelligence. Diane Proudfoot (Rethinking Turing's Test, Journal of Philosophy, 2013) has argued for an alternative interpretation. According to Proudfoot, Turing's claim that intelligence is what he calls 'an emotional concept' indicates that he conceived of intelligence in response-dependence terms. As she puts it: 'Turing's criterion for "thinking" is...: x is intelligent (or thinks) if in the actual world, in an unrestricted computer-imitates-human game, x appears intelligent to an average interrogator'. The role of the famous test is thus to provide the conditions in which to examine the average interrogator's responses. I shall argue that Proudfoot's analysis falls short. The philosophical literature contains two main models of response-dependence, what I shall call the transparency model and the reference-fixing model. Proudfoot resists the thought that Turing might have endorsed one of these models to the exclusion of the other. But the details of her own analysis indicate that she is, in fact, committed to the claim that Turing's account of intelligence is grounded in a transparency model, rather than a reference-fixing one. By contrast, I shall argue that while Turing did indeed conceive of intelligence in response-dependence terms, his account is grounded in a reference-fixing model, rather than a transparency one. This is fortunate (for Turing), because, as an account of intelligence, the transparency model is arguably problematic in a way that the reference-fixing model isn't. [ABSTRACT FROM AUTHOR]

If one is going to compile a catalogue of the central concerns of Gulliver’s Travels, it goes without question or hesitation that the concept of reason looms large, if not possessing the uppermost priority, in Jonathan Swift’s authorial agenda. Swift is not only interested in reason insofar as practical rationalities, rational practicalities, and moral mores are concerned but also in the nature and constitution of reason itself. Thus, the purpose of this paper is to look at Swift’s treatment of the nature and constitution of reason and rationality in two of the Gulliver’s voyages: viz. the journeys to Brobdingnag and Balnibarbi. What is intriguing is that Swift seems to anticipate in the former voyage Alan Turing’s Imitation Game and in the latter voyage Turing’s idea of computational mechanization of intelligence, where he relates the two tales with diametrically opposite sentiments. The discussion of Swift’s anticipations is then set against the backcloth of the vicissitudes of the idea of Logical Machine from William of Soissons in the twelfth century to Alonzo Church’s Theorem and David Hilbert’s broad-ranging Entscheidungsproblem in the twentieth century. [ABSTRACT FROM AUTHOR]

We describe the main classes of non-signalling bipartite correlations in terms of states on operator system tensor products. This leads to the introduction of another new class of games, called reflexive games, which are characterised as the hardest non-local games that can be won using a given set of strategies. We provide a characterisation of their perfect strategies in terms of operator system quotients. We introduce a new class of non-local games, called imitation games, in which the players display linked behaviour, and which contain as subclasses the classes of variable assignment games, binary constraint system games, synchronous games, many games based on graphs, and unique games. We associate a C*-algebra C ∗ (G) to any imitation game G , and show that the existence of perfect quantum commuting (resp. quantum, local) strategies of G can be characterised in terms of properties of this C*-algebra. We single out a subclass of imitation games, which we call mirror games, and provide a characterisation of their quantum commuting strategies that has an algebraic flavour, showing in addition that their approximately quantum perfect strategies arise from amenable traces on the encoding C*-algebra. [ABSTRACT FROM AUTHOR]

This article describes the use of a mixed methods research approach to explore the dynamics of social group construction with Imitation Game experiments. More specifically, we analyzed in which ways, and how effectively, people draw boundaries in social interaction. That is, we studied ways in which people distinguish between group members and outsiders. Our study included a group of active Christians (n = 20) and nonreligious individuals (n = 19) in Finland. We conceptualized the Imitation Game as a mixed data collection instrument because it combines both qualitative and quantitative data in an integrated manner. As part of our analysis, we introduce an indicator called the Sequential Identification Ratio (SIR), which is an indicator of how accurately participants draw boundaries in the Imitation Game. The results based on the SIR indicate that group boundaries are established with 4 different strategies: experiential, epistemic, axiological, and linguistic. Finally, we show how a mixed methods researcher can conduct a form of quantitizing to use both quantitative and qualitative aspects of Imitation Game data. [ABSTRACT FROM AUTHOR]

The frequency of occurrence of step length in the migratory behaviour of various organisms, including humans, is characterized by the power law distribution. This pattern of behaviour is known as the Lévy walk, and the reason for this phenomenon has been investigated extensively. Especially in humans, one possibility might be that this pattern reflects the change in self-confidence in one’s chosen behaviour. We used simulations to demonstrate that active assumptions cause changes in the confidence level in one’s choice under a situation of lack of information. More specifically, we presented an algorithm that introduced the effects of learning and forgetting into Bayesian inference, and simulated an imitation game in which two decision-making agents incorporating the algorithm estimated each other’s internal models. For forgetting without learning, each agents’ confidence levels in their own estimation remained low owing to a lack of information about the counterpart, and the agents changed their hypotheses about the opponent frequently, and the frequency distribution of the duration of the hypotheses followed an exponential distribution for a wide range of forgetting rates. Conversely, when learning was introduced, high confidence levels occasionally occurred even at high forgetting rates, and exponential distributions universally turned into power law distribution.

As a part of their normative theory of expertise, Harry Collins and Robert Evans proposed that interactional expertise forms the third kind of knowledge, located between formal propositional knowledge and embodied skills. Interactional expertise refers to the capability to grasp the conceptual structure of another's social world, and it is expressed as the ability to speak fluently the language spoken in that social world. According to their theory, it is a key concept of sociology, because it refers to the understanding and coordination of joint actions between members of different social groups. Collins and Evans have further claimed that minority social group members tend to outpace majority social group members in terms of interactional expertise. Drawing on ethnomethodology, we detail the ways in which interactional expertise is displayed and revealed in experiments. This allowed us to specify the underlying reasons for the distribution of interactional expertise between social groups. Our results indicate that the difference between the groups depends on whether a group is either actively maintained or a passive latent category, because interactional expertise provides for not only the crossing of social boundaries but also their maintenance. The minority social group members' greater interactional expertise or competence is therefore proven to be illusory. [ABSTRACT FROM AUTHOR]

Hesitancy and refusal of vaccines preventing childhood diseases are spreading due to 'pseudo-rational' behaviours: parents overweigh real and imaginary side effects of vaccines. Nonetheless, the 'Public Health System' (PHS) may enact public campaigns to favour vaccine uptake. To determine the optimal time profiles for such campaigns, we apply the optimal control theory to an extension of the susceptible-infectious-removed (SIR)-based behavioural vaccination model by d'Onofrio et al. (2012, PLoS ONE , 7, e45653). The new model is of susceptible-exposed-infectious-removed (SEIR) type under seasonal fluctuations of the transmission rate. Our objective is to minimize the total costs of the disease: the disease burden, the vaccination costs and a less usual cost: the economic burden to enact the PHS campaigns. We apply the Pontryagin minimum principle and numerically explore the impact of seasonality, human behaviour and latency rate on the control and spread of the target disease. We focus on two noteworthy case studies: the low (resp. intermediate) relative perceived risk of vaccine side effects and relatively low (resp. very low) speed of imitation. One general result is that seasonality may produce a remarkable impact on PHS campaigns aimed at controlling, via an increase of the vaccination uptake, the spread of a target infectious disease. In particular, a higher amplitude of the seasonal variation produces a higher effort and this, in turn, beneficially impacts the induced vaccine uptake since the larger is the strength of seasonality, the longer the vaccine propensity remains large. However, such increased effort is not able to fully compensate the action of seasonality on the prevalence. [ABSTRACT FROM AUTHOR]

The nature and role of social groups is a central tension in sociology. On the one hand, the idea of a group enables sociologists to locate and describe individuals in terms of characteristics that are shared with others. On the other, emphasizing the fluidity of categories such as gender or ethnicity undermines their legitimacy as ways of classifying people and, by extension, the legitimacy of categorization as a goal of sociological research. In this paper, we use a new research method known as the Imitation Game to defend the social group as a sociological concept. We show that, despite the diversity of practices that may be consistent with self‐identified membership of a group, there are also shared normative expectations – typically narrower in nature than the diversity displayed by individual group members – that shape the ways in which category membership can be discussed with, and performed to, others. Two claims follow from this. First, the Imitation Game provides a way of simultaneously revealing both the diversity and 'groupishness' of social groups. Second, that the social group, in the quasi‐Durkheimian sense of something that transcends the individual, remains an important concept for sociology. [ABSTRACT FROM AUTHOR]

We construct a model of strategic imitation in an arbitrary network of players who interact through an additive game. Assuming a discrete time update, we show a condition under which the resulting difference equations converge to consensus. Two conjectures on general convergence are also discussed. We then consider the case where players not only may choose their strategies, but also affect their local topology. We show that for the prisoner's dilemma, the graph structure converges to a set of disconnected cliques and strategic consensus occurs in each clique. Several examples from various matrix games are provided. A variation of the model is then used to create a simple model for the spreading of trends, or information cascades in (e.g., social) networks. We provide theoretical and empirical results on the trend-spreading model. [ABSTRACT FROM AUTHOR]

Since Turing proposed the first test of intelligence, several modifications have been proposed with the aim of making Turing's proposal more realistic and applicable in the search for artificial intelligence. In the modern context, it turns out that some of these definitions of intelligence and the corresponding tests merely measure computational power. Furthermore, in the framework of the original Turing test, for a system to prove itself to be intelligent, a certain amount of deceit is implicitly required which can have serious security implications for future human societies. In this article, we propose a unified framework for developing intelligence tests which takes care of important ethical and practical issues. Our proposed framework has several important consequences. Firstly, it results in the suggestion that it is not possible to construct a single, context independent, intelligence test. Secondly, any measure of intelligence must have access to the process by which a problem is solved by the system under consideration and not merely the final solution. Finally, it requires an intelligent agent to be evolutionary in nature with the flexibility to explore new algorithms on its own. [ABSTRACT FROM AUTHOR]