Input: Task: contrast the claim using the given text. Claim: AI assistants are able to understand and perfectly respond to all human emotions. [SEP] Text: Lambiase, Anger, Emotion, and Arrhythmias: from Brain to Heart. 2011. 2. 8. 00:53:40 Brain, Uncertainty & Categories Dr. Barrett elucidates her scholarly investigations, offering an intricate portrayal of her methodology designed to comprehend the intricacies of the human brain and its role in the genesis of emotional phenomena. Dr. Barrett commences her inquiry by focusing on the evolutionary, developmental, and anatomical facets of the nervous system, which form the basis for the concepts she introduces. Based on the findings of Dr. Barrett's study, it may be inferred that the brain operates as an ongoing system of categorization, which is not solely influenced by external inputs, but also by impulses emanating from the body's sensory surfaces. The cognitive process of inferring causal relationships is not consciously performed, by the brain; instead, it depends on prior experiences and memories to make informed predictions. Active participation in this procedure, it efficiently generates categorizations of prospective outcomes and approaches for implementing tangible activities. The incorporation of these particular categories aims to reduce any possible ambiguity, which is a crucial element in attaining maximum metabolic efficiency. Dr. Barrett underscores the inherent significance of this process, which undergoes ongoing alterations across time rather than remaining static at certain moments. The cognitive processes associated with the brain's selection mechanisms and the integration of external information play a crucial role in improving accurate inferential reasoning about the sources of sensory signals. Consequently, these activities play a role in the development of perceptual experiences that are linked to external occurrences [9]. Figure 6. Cognitive mechanism of the brain during the learning process [9]. 9. Zhou, K. , et al. , on a Brain-Mechanism. Cognitive Computation, 2020. 12. 9. 01:03:57 Brain & Summaries; Emotions as “Multimodal Summaries” During a discourse conducted on the podcast, Dr. Barrett explores the cognitive operation of the brain as a signal processor. The author places significant emphasis on the ongoing cognitive processing of neuronal impulses within the brain, as well as its ability to differentiate between valuable information, referred to as signal, and irrelevant sensory input, known as noise, within the surrounding environment. The utilization of various cues, such as eye gaze, is a prevalent practice among individuals to effectively convey information and differentiate between relevant signals and irrelevant disturbances. [SEP] Justify:

Output: The text contrasts the claim by discussing Dr. Barrett's investigations into the human brain's processing of emotions and sensory information. It highlights that the brain categorizes outcomes based on prior experiences and does not create conscious inferences. This implies that understanding emotions is a complex process reliant on human cognitive functions and suggests that AI assistants, which operate differently than human brains, may not perfectly understand or respond to all human emotions.


Input: Task: pass the claim using the given text. Claim: Language can serve as a marker of identity and cultural heritage. [SEP] Text: плінарний науковий збірник об’єднує студії з історії, мовознавства та літературознавства. [SEP] Justify:

Output: The text is not relevant to the claim as it simply states that a plenary scientific collection unites studies from history, linguistics, and literary studies. It does not discuss the role of language in identity or cultural heritage.


Input: Task: corroborate the claim using the given text. Claim: AI is being used to process data from sensors and cameras in autonomous vehicles to navigate streets safely. [SEP] Text: In addition, the vehicle manufacturer also has their own self-drive vehicle project partnering with a technology company called Cruise. They started with a car provided by and modified it with multiple sensors such as cameras, RADARs, and LIDARs in order to add autonomous features to it. Artificial intelligence technology, 3D and 2D mapping, and obstacle detection systems make the care as autonomous and secure as possible. However, the hardware and the specifications of the vehicles are not publicly available for researchers, making the previously mentioned companies have an important limitation in this survey. This is a handicap for the purpose of this paper because there is no information available, and it is not possible to give a clear analysis of the sensor technology that each company is using. 3. 4 Public Transportation. For public transportation purposes, the implementation of autonomous vehicles to enhance the development of this area in different countries could be revolutionary. Sometimes, it is an issue to develop good public transportation systems, but artificial intelligence can step in to improve and create smoother and safer systems for public transportation. Some researchers started to analyze potential projects in different cities and how different territories could adapt to this type of technology [17] while reviewing the economic implications of these projects and how the government could be considering such alternatives. In fact, some technology companies started implementing different self-driving projects in some cities to test these vehicles for public transportation, some of these are shuttles and autonomous buses [18]. (Volvo): The biggest implementation for public transportation purposes using autonomous vehicles could be the bus. The implementation for automation could be problematic due to the size of a bus but some companies like Volvo started projects to be able to provide a fully autonomous bus. However, the company is still conducting tests in order to guarantee a working vehicle to be able to start developing it into the mass market. Some methods and systems have been progressing and adding them to some of the electric buses created by Volvo and provided to researchers to develop some systems that could then turn the bus into an autonomous vehicle. In Ref. [19], a variety of sensors is used to develop a fusion and give the bus the possibility to drive by itself. The research presented uses optical encoders installed in the wheels of the vehicle to collect velocity data which is then useful to stop the vehicle and regulate its velocity properly. Some proximity sensors are used to detect near objects and vehicles to give some data to the car that could be helpful for a break assistance system. [SEP] Justify:

Output: The text corroborates the claim by detailing the use of artificial intelligence alongside various sensors (such as cameras, RADARs, and LIDARs) to enable the autonomous features of vehicles, enhancing their navigation capabilities. It emphasizes that AI technology is integral to both obstacle detection and the overall functionality of autonomous systems, supporting the assertion that AI is critical in processing sensor data for safe navigation.


Input: Task: contrast the claim using the given text. Claim: AI assistants are able to understand and perfectly respond to all human emotions. [SEP] Text: This mode of communication is commonly employed to support the cognitive development of individuals, particularly newborns, by aiding in the identification and differentiation of pertinent information. The neuronal architecture of the brain undergoes a gradual metamorphosis in which intricate sensory data is consolidated into higher-level conceptual representations as signals cross the cognitive pathways. According to the research conducted by Dr. Barrett, it has been determined that the cortex assumes the role of representing these summaries. The process of summarization involves increasing levels of abstraction and reducing the dimensionality of the summaries, resulting in the formation of a hierarchical sequence of summaries. Dr. Barrett presents a comprehensive analysis of emotional categories, such as "anger," which are demonstrated to encompass a wide range of sensory and motor characteristics. These qualities may demonstrate significant variances across diverse individuals' experiences. Essentially, these abstract emotional categories serve as inclusive phrases that span a range of sensory-motor patterns associated with a particular emotional concept [10]. Figure 7. Cognitive and behavioral flexibility [10]. 10. Uddin, L. Q. , Cognitive and behavioural flexibility: neural mechanisms and clinical considerations. Neuroscience, 2021. 22(3): p. 167-179. 10. 01:14:45 Emotional Granularity, During a podcast conversation between Dr. Barrett and Andrew Huberman, the notion of emotional granularity was discussed. This concept relates to the cognitive process utilized by the brain's system for constructing categories. Dr. Barrett emphasizes the significance of the brain in its capacity as a signal processor, consistently discerning between signals that convey meaningful information and noise that signifies extraneous material from the surrounding milieu. The primary inquiry pertains to the optimal degree of specificity at which the brain needs to establish its categorization. The brain exhibits a diverse array of categorization processes when it engages in the classification of emotional experiences. These processes encompass broad classifications such as "threat," as well as more specific categorizations like "anger," "fear," or "frustration. " According to Dr. Barrett's opinion, the basic objective of the brain is to achieve a state of equilibrium by establishing discrete categories that possess a sufficient degree of accuracy to be deemed meaningful. Nevertheless, the primary objective of this endeavor is to mitigate the presence of superfluous intricacies that may impede efficacy or result in an overwhelming cognitive burden. [SEP] Justify:

Output: The text contrasts the claim by discussing the cognitive processes involved in categorizing emotions, emphasizing that emotional experiences are diverse and can vary significantly across individuals. Dr. Barrett's research indicates that the brain processes and categorizes emotions into hierarchies, suggesting that the understanding of emotions is complex and not perfect. The mention of emotional granularity and the classification of emotions such as 'anger,' 'fear,' or 'frustration' indicates that there is a limitation to the granular understanding of emotions, which counters the claim that AI assistants can perfectly respond to all human emotions.


Input: Task: pass the claim using the given text. Claim: Language can serve as a marker of identity and cultural heritage. [SEP] Text: Історичний блок репрезентують дослідження актуальних проблем історії, а також розвідки про відомих людей та їх значення у формуванні української державності. Мовознавчі студії розкривають передусім проблеми з історії української мови та діалектології. [SEP] Justify:

Output: The text is irrelevant to the claim as it discusses historical research and the significance of well-known figures in the formation of Ukrainian statehood, along with studies on the history of the Ukrainian language and dialectology, without addressing the role of language as a marker of identity or cultural heritage.


Input: Task: corroborate the claim using the given text. Claim: AI is being used to process data from sensors and cameras in autonomous vehicles to navigate streets safely. [SEP] Text: LIDAR sensors are also being utilized for obstacle detection motives. 221 is a mid-range LIDAR that has a considerably lower price compared to the sensors already mentioned in this study. There are also some more recent experiments and trials supported by for developing a sustainable autonomous bus that could circulate in smart cities such as Europe or Asia. Some proposals were presented in Ref. [20] using a Bus to include autonomous features with different types of sensors such as ultrasonic, cameras, and optical sensors. The authors provided methods and systems focusing on just one type of sensor but as well with a sensor fusion approach. Each sensor excels in its specific domain, and they are all useful for some specific situations that are needed to be considered for autonomous vehicle development since safety and high performance are a requirement to guarantee the satisfaction and overall safety of the clients. However, it is important to mention that the experiment does not take into consideration of abnormal weather conditions or other situations rather than clear weather. It is crucial for this type of automotive technology to address such situations because drivers and passengers can encounter them frequently. (Navya): Unlike Volvo, some other startups and relatively smaller companies got into the business of redesigning the public transportation industry by implementing autonomous features to buses and shuttles. Navya is a technology company specialized in designing and building autonomous vehicles. They created a project of an autonomous shuttle for public transportation purposes in smart cities around the world. has been designed to carry up to 15 passengers on public and private roads. It is intended to work autonomously at all times to facilitate transportation for passengers in different situations and places. They dispose of a cutting-edge technology with a data fusion of cameras, LIDAR sensors, GPS, and odometry to guarantee precision and safety for the users [21]. The vehicle is implementing 10 LIDAR sensors for 2D and 3D mapping purposes to guarantee a proper obstacle and vehicle detection and map the environment. The sensors employed are Velodyne VLP 360 deg (multi-layers), (multi-layers), (multi-layer), and (single layer). The combination of multiple LIDAR sensors from different brands is highly effective due to the cost variation and to gather different specifications that each one of these sensors is offering. VLP 360 deg would ideally be installed at the top of the vehicle, in front and back to cover a 360-deg benchmark and get all the data possible to build 3D maps. [SEP] Justify:

Output: The text corroborates the claim by detailing the use of various sensors including LIDAR, cameras, and GPS in autonomous vehicles. It specifically mentions that Navya is using a data fusion approach which combines these sensors to enhance obstacle detection and mapping, thus supporting safe navigation for autonomous vehicles in smart cities.


Input: Task: contrast the claim using the given text. Claim: AI assistants are able to understand and perfectly respond to all human emotions. [SEP] Text: The aforementioned categories have dynamic characteristics, showcasing variations in their degree of specificity and are formulated through the brain's previous encounters, sensory stimuli, and motor responses. Hence, one could assert that the brain does not proactively construct emotional states and subsequently attribute labels to them. In contrast, the system generates classifications of prospective future acts by leveraging its vast repository of prior experiences, aiming to minimize ambiguity and facilitate effective prognostications [11]. Figure 08. Vestibular projections throughout the nervous system [11]. 11. Kearney, B. E. and R. A. Lanius, The brain-body disconnect: A somatic sensory basis for trauma-related disorders. 2022. 16. (11). 01:19:40 Brain & Compression, a podcast hosted by Andrew Huberman, Dr. Barrett delves into the intricate interplay between human responses and the physiological processes included in the categorization of information within the brain. The individual reflects on the shift from reductionist and authoritarian ways of thinking, which involve a tendency to simplify and oversimplify complicated matters and rely on binary judgments, to times where complexity plays a more significant and broader role. As per Dr. Barrett's analysis, the cognitive process of category development within the brain has a tendency towards the loss of knowledge. This process involves the consolidation of complex sensory data into more succinct and simplified characteristics. The cognitive process of the brain initiates with the initial processing of primary emotions, such as anger, fear, or perceived danger. Following this, it then proceeds to infer or suggest increasingly complex sensory and motor intricacies. The cognitive processes that take place within the neurological system extend beyond rudimentary assessments of stimuli as positive, negative, or neutral. Instead, they include the deliberate formulation of strategies for action. The brain employs prior experiences to influence the processing of current stimuli, leading to the generation of a wide range of behaviors. These activities involve the synchronization of internal physiological processes, such as the regulation of heart rate and respiration, in combination with the performance of skeletal muscular motions. The cognitive process discussed here is of significant importance as it has a profound impact on shaping our subjective view of the external environment [12]. Figure 09. Brain complexity, emotion, and perception [12]. 12. Rohr, C. , et al. , Affect and the Brain's Functional Organization: A Resting-Approach. PloS one, 2013. 8: p. e68015. [SEP] Justify:

Output: The text contrasts the claim by explaining that the cognitive processes associated with emotional understanding are complex and not straightforward, suggesting that simple systems (like AI) may struggle to interpret intricate emotional nuances. It discusses how the brain processes emotional states and develops categorizations based on previous experiences, indicating that true understanding involves more than just classification, and implying limitations for AI in comprehensively responding to human emotions.


Input: Task: pass the claim using the given text. Claim: Language can serve as a marker of identity and cultural heritage. [SEP] Text: Дослідження з літературознавства зосереджені довкола аналізу творів письменників у контексті світової історії та культури. DOI ISSN 2223-1196 Свідоцтво про державну реєстрацію Ідентифікатор в Реєстрі суб’єктів у сфері медіа R30-03117 від 14. 03. 2024 р. Періодичність 2 рази на рік Збірник індексується в міжнародних базах даних: 1. Соляр, І. , Красівський, О. , Муравський, О. (2019). Діяльність Західно-Українського товариства Ліги Націй у 1922–1924 рр. [SEP] Justify:

Output: The text is irrelevant to the claim, as it discusses research in literary studies and the analysis of writers' works within the context of world history and culture, without addressing language as a marker of identity or cultural heritage.


Input: Task: corroborate the claim using the given text. Claim: AI is being used to process data from sensors and cameras in autonomous vehicles to navigate streets safely. [SEP] Text: The other three types of sensors are placed in specific areas to cover an important function that will be used to implement features such as parking assistance, detection of objects in short and long range, etc. Cameras are then placed in the front and back of the vehicle to have a clear vision of the environment. Cameras are also used in order to ensure safety and monitor the shuttle from a distance and make sure that it is working properly. Wheel encoders are also used to check the speed of the vehicle and monitor it depending on the road, weather, and situation. Finally, a GNSS antenna is placed at the top of the vehicle that communicates with a GPS sensor to have the specific location of the shuttle every moment. The advantage for these types of shuttles is the technology and innovation that they are presenting for public transportation purposes that can then be scaled to bigger projects. Sensor fusion is effective, and the shuttle can work properly during several hours with enhanced safety with different methods of obstacle detection. However, the area used for these shuttles is very limited, and it is intended to be used in very controlled areas such as university campuses and some areas in smart cities. Since the vehicle is small, there is not enough room for more than 15 people and this is a problem if some company or government wants to start using this technology for big public transportation projects [22]. The vehicle is currently being tested in several cities as a transportation medium in campuses within a specific area. (EasyMile): EasyMile is a technology company that works on autonomous vehicle technology and solutions. Currently, they own an autonomous shuttle project that is being used in several cities across Europe, Asia, and the United States. The design of the vehicle is very similar to the Nayva shuttle presented in the previous section. It has a capacity of 15 passengers as a maximum, it can function in different adverse weather conditions such as rain, snow, and fog. The maximum speed is 45 km/h, but it has been electronically adjusted to only 25 km/h for safety purposes. In terms of sensors, there are some limitations for this company that are not beneficial for the purpose of the research. Specific hardware information is not available publicly, but details about the partnership with EasyMile and Velodyne are available. Velodyne partnered with the company to provide the latest LIDAR sensors to the project of the EZ10 autonomous shuttle. [SEP] Justify:

Output: The text corroborates the claim by discussing how various sensors, including cameras and LIDAR, are utilized in autonomous vehicles to enhance safety and facilitate navigation. It details the roles of cameras in providing a clear vision of the environment and ensuring the vehicle operates properly, which supports the assertion that AI processes data from these sensors for navigation and safety.


Input: Task: contrast the claim using the given text. Claim: AI assistants are able to understand and perfectly respond to all human emotions. [SEP] Text: (12). 01:34:29 Movement, Sensation, Prediction & present dialogue delves into the intricate cognitive process of prediction generation and experiential construction within the human brain, as explored through a joint debate between Dr. Barrett and host Andrew Huberman. also clarifies the principle that the brain generates motor plans prior to sensory awareness, and examines the concept of efference copies. These plans generate motor signals that are conveyed to both the spinal cord for prompt execution and other neurons in the brain as predictive expectations of future sensations. As a result, the subjective experience of an individual is closely intertwined with the motor plans they generate and the corresponding sensations they anticipate, prompting the brain to seek validation through actual sensory input. The presence of discrepancies between expected outcomes and actual sensory stimuli serves as the fundamental basis for the acquisition of knowledge. In his work, Dr. Barrett explores the hypothesis that ordinary occurrences can be likened to controlled hallucinations, where the brain's expectations affect one's view of the surrounding environment [13]. Figure 10. Sensory-motor integration in focal dystonia [13]. 13. Avanzino, L. , et al. , Sensory-motor integration in focal dystonia. Neuropsychologia, 2015. 79: p. 288-300. (13). 01:42:44 Feelings of Discomfort & Action Dr. Barrett emphasizes the importance of employing a flexible and contextually sensitive approach to the regulation of emotions. The selection between verbal and physical modes of emotional expression is dependent upon the particular circumstances and individual goals. Emotions have a crucial role in stimulating behavioral reactions, and there are situations in which it can be beneficial to willingly confront discomfort. It is imperative to acknowledge that the occurrence of negative emotions does not inherently indicate the existence of a problem, but rather may indicate the presence of challenging conditions. The discernment of the educational value of experiencing discomfort is of utmost importance, as it allows for the differentiation of instances in which such distress may not be conducive to learning. Furthermore, Dr. Barrett offers a personal anecdote in which she intentionally exposed herself to distress following a major surgical intervention on her spinal region. The intentional act of exposing her to various stimuli was intended to enhance her brain's ability to interpret these changing experiences. This highlights the idea that experiencing discomfort can provide valuable information and aid in the acquisition of knowledge [14]. 14. Kobylińska, D. and P. [SEP] Justify:

Output: The text contrasts the claim by discussing the complex nature of human emotions and the importance of contextual understanding in emotional regulation. Dr. Barrett emphasizes that a flexible and contextually sensitive approach is essential when responding to emotions, suggesting that emotions do not always have a straightforward interpretation or response. This implies that AI assistants, which might not possess the inherent cognitive and contextual capabilities of humans, cannot perfectly understand and respond to all human emotions.


Input: Task: pass the claim using the given text. Claim: Language can serve as a marker of identity and cultural heritage. [SEP] Text: Сторінки історії, 49, 75–84. DOI: 10. 20535/2307-5244. 49. 2019. 189557 2. Soliar, I. , Sholota K. (2019). Ukrainian issue at the Congresses in the second half of the 1920-ies (based on the periodical «Dilo»). Східноєвропейський історичний вісник, 11, 142–168. DOI: 10. 24919/2519-058x. 11. 171314 3. Murawśkyj, O, Solіar, I. (2019). Procesy społeczno-polityczne w Ukraińskiej SRR: osobliwości, tendencje, skutki (przełom lat osiemdziesiątych i dziewięćdziesiątych XX w. ). Pamięc i Sprawiedliwośc, 33, 252–270. Retrieved from: Монографії: 1. Соляр, І. Консолідаційні процеси національно-державницьких сил Західної України (1923 – 1928). Львів: Інститут українознавства ім. І. Крип’якевича НАН України, 2010. 150 с. 2. [SEP] Justify:

Output: The text does not address the claim regarding language as a marker of identity and cultural heritage. Instead, it appears to be a collection of references and titles related to Ukrainian history and politics without any direct mention or discussion of language's role in identity or heritage.


Input: Task: corroborate the claim using the given text. Claim: AI is being used to process data from sensors and cameras in autonomous vehicles to navigate streets safely. [SEP] Text: Compared to the Navya shuttle, the EZ10 is implementing RADAR sensors into their system to enhance safety and fusion of the data with the output from LIDAR sensors. This can increase the effectiveness of the shuttle by having more methods of obstacle detection that are not limited to only one type of sensor. This shuttle has different testing methods that are positive for researchers to analyze the performance of the vehicle in different situations. There are some standard scenarios for testing in places such as university campuses, industrial areas, private and public routes with a defined route. The company has several modes of transportation for the EZ10, those being Metro mode with specific routes and stop stations to drop off and pick up passengers. The bus mode has several routes and provides the possibility of stopping at the desired time requested by the passenger and an on-demand service that works similar to a taxi or an Uber, where the vehicle gets the ride request to go to a specific location specified by the passenger [23]. However, the negative aspects of the vehicle are similar to those presented with Navya, where the shuttle is functional but the capabilities are limited. Further research is necessary for future technology to adapt to bigger projects and develop a truly autonomous project of public transportation that is viable for different cities and urban areas. Autonomous Trains: Autonomous vehicles are becoming more prominent in the world, and more companies are interested in investing in these vehicles, such as train and rail companies. Public transportation needs innovation to increase effectiveness and transport the millions of passengers that are demanding these types of services. The current state of autonomous trains is based on a scale with levels of automation very similar to the ones mentioned at the beginning of the paper. The grade of automation for trains goes from levels 1 to 4. The train system is considered level 4 when the train can operate autonomously, is capable of accelerating, stopping, closing and opening doors, and detecting obstacles along the road. At the moment, the industry of autonomous trains is uncertain, most of the technology and systems to develop these types of trains are owned by the government of multiple countries in every continent. There are some trains functioning at a level 4 of automation, located principally in airports, metro systems and some larger-scale trains. The technology employed for these projects and the sensors used are not the base of this paper; most of these autonomous trains are located in closed areas or configured and built differently than with other types of autonomous vehicles. [SEP] Justify:

Output: The text corroborates the claim by discussing the implementation of RADAR and LIDAR sensors in the EZ10 shuttle to enhance safety and improve obstacle detection. The text emphasizes the importance of data fusion from different types of sensors, which aligns with the claim that AI processes data from sensors to navigate safely. It also mentions that ongoing research on testing methods for autonomous vehicles contributes to their ability to function effectively in various scenarios, reinforcing the role of AI in enhancing navigation and safety.


Input: Task: contrast the claim using the given text. Claim: AI assistants are able to understand and perfectly respond to all human emotions. [SEP] Text: Kusev, Regulation: Demands and Influence the Effectiveness of Regulatory Strategies. 2019. 10. (14). 01:50:32 Tool: Feelings of Uncertainty, Emotion, “Affect” According to Dr. Barrett, there is a distinction between feelings and emotions. Dr. Barrett emphasizes the concept that emotions are related to affective states or moods, which act as indicators of the body's sensory condition and are consistently controlled by the brain. In contrast, emotions can be understood as the cognitive mechanism by which the brain interprets or constructs a story to explain the underlying causes of sensory changes. It is crucial to acknowledge that affect is consistently present, regardless of whether it holds a prominent or subordinate place in an individual's conscious view. However, emotions can be seen as the cognitive interpretation of an affective experience. The correlation between the recognition of emotional states and the somatic sensations experienced by the body is intricately linked, and can be influenced by alterations in the body's physiological condition. According to Dr. Barrett, individuals have the capacity to cultivate the skill of reinterpreting their affective perceptions, so modifying their emotional experience through the process of reevaluating the significance attributed to the observed sensations. By using well-defined classifications and embracing a versatile perspective on comprehending emotional encounters, individuals have the ability to transform their affective states into useful reservoirs of knowledge and meaningful indicators for adaptive behavior [15]. Figure 11. Emotion-processing-related brain activity [15]. 15. Spies, M. , et al. , Default mode network deactivation during emotion processing predicts early antidepressant response. Translational Psychiatry, 2017. 7: p. e1008. (15). 02:01:18 Tool: & Attention; this intellectually engaging conversation, Dr. Barrett and the host delve into the notion of augmenting the multifaceted nature of individuals' emotional and sensory experiences. Dr. Barrett skillfully demonstrates the topic by employing illustrative examples from the field of art and drawing upon her personal experiences. Dr. Barrett provides a detailed explanation of the process involved in altering the dimensionality of emotions. This process involves the reclassification of experiences using alternative techniques of categorization and a shift in attention toward identifying more nuanced details. The discussion revolves around the importance of flexible perception and empathy, highlighting the idea that people's understanding of the world is shaped by the interaction between external stimuli and their cognitive functions. [SEP] Justify:

Output: The text contrasts the claim by elaborating on the complexity of emotions and the distinction between feelings, affect, and cognitive interpretations as explained by Dr. Barrett. It suggests that understanding and interpreting emotions requires nuanced cognitive processing and the ability to reinterpret affective states, implying that AI assistants, which do not possess this deeply interconnected cognitive mechanism, may not be able to perfectly understand or respond to human emotions.


Input: Task: pass the claim using the given text. Claim: Language can serve as a marker of identity and cultural heritage. [SEP] Text: Соляр, І. Зовнішні орієнтації національно-державницьких партій Західної України (1923 – 1939). Львів: Інститут українознавства ім. І. Крип’якевича НАН України, 2011. 356 с. Розділи в колективних монографіях: 1. Соляр, І. Між ідеями негації Польської держави і здобуття автономії. Галичина і Волинь у складі міжвоєнної Польщі редкол. : Вісин В. , Голик Р. , Голубко В. та ін. Харків: Фоліо, 2017. С. 44–110. 2. Соляр, І. [SEP] Justify:

Output: The text is irrelevant to the claim, as it consists of bibliographic references to publications and does not address the role of language in identity and cultural heritage in any manner.


Input: Task: corroborate the claim using the given text. Claim: AI is being used to process data from sensors and cameras in autonomous vehicles to navigate streets safely. [SEP] Text: Online sales and e-commerce are internalized in any company that could sell any type of product to their customers. Logistics companies could benefit from advanced technology to be more efficient and be able to manage time and resources in a better way. Autonomous vehicles could be introduced in the industry to automate some of the processes regarding transportation and delivery to customers [35]. Some researchers have determined some of the outcomes and potential positive and negative consequences of implementing autonomous vehicles in the logistics industry. There are not many big projects of autonomous vehicles for this industry, but it is emerging quickly because newer and more advanced technology would help many companies to work more effectively [36]. Mercedes-Truck: Mercedes-Benz is planning on deploying one of their biggest projects regarding autonomous vehicles in 2025. This project is also being developed with the truck company Daimler. They plan to introduce a self-driven truck implementing a driver assistance system that will be able to take control of the vehicle during long hours of driving on the highway. Since truck drivers are constantly facing high traffic density, the company is willing to minimize those constraints. is a system that has been developed to guarantee safety and move the different autonomous trucks throughout the highways, regulating their speed limit. Currently, the prototype is being tested on public roads in Germany and the United States. In the future, the purpose of this technology is to connect several autonomous trucks with established vehicle-to-vehicle communication using a satellite connection [37]. In terms of sensors, the vehicle is equipped with the latest technology on RADAR sensors and cameras. It is important to mention that the prototype is not implementing LIDAR sensors for their autonomous system compared to most of the other technology companies that are implementing LIDARs for 3D mapping and environment recognition. However, the has on both sides with a 170-deg field of view (FOV) and a range of 60 m, a single short-range RADAR with a 130 deg FOV and a range of 70 m, a single Camera with a 45-deg FOV and a range of 100 m, and a full range radar placed at the front of the vehicle with an 18-deg FOV and maximum range of 250 m. All sensors get data and information about the environment such as pedestrians, traffic signals, and vehicles [38]. There are advantages related to the implementation of these sensors for autonomous trucks. [SEP] Justify:

Output: The text corroborates the claim by detailing how autonomous trucks are equipped with advanced sensors and cameras that gather data about their environment. It states that these sensors help the vehicles detect pedestrians, traffic signals, and other vehicles, which is essential for safe navigation on the roads. This aligns with the claim that AI processes this data to navigate safely.


Input: Task: contrast the claim using the given text. Claim: AI assistants are able to understand and perfectly respond to all human emotions. [SEP] Text: The acknowledgment of these variations has the potential to foster empathy and a deeper understanding of other perspectives. The interaction indicated above highlights the idea that broadening one's cognitive and emotive capacities can lead to a more profound and adaptable involvement with life [16]. Figure 12. of From the Internal and Shape the Perception [17]. 16. Martínez-Pernía, D. , et al. , “I am feeling tension in my whole body”: An experimental phenomenological study of empathy for pain. 2023. 13. 17. Harricharan, S. , M. C. McKinnon, and R. A. Lanius, of From the Internal and Shape the Perception and the World in the Aftermath of Trauma: Implications for PTSD. 2021. 15. (17). 02:08:36 Affect, Allostasis & Analogy Dr. Barrett delves into the complex interaction between sensory systems, specifically touch and proprioception, and their neuronal integration with motor control processes inside the brain. Furthermore, the author expands upon this notion by applying it to the domains of visual perception and auditory perception, emphasizing the considerable influence these sensory modalities exert on the brain's regulation of motor functions. The brain relies heavily on sensory signals to regulate various physiological systems, including but not limited to the circulatory, respiratory, and gastrointestinal systems. The understanding of these messages is not achieved through immediate grasping, but rather entails a process of converting them into affective emotions and fundamental physiological experiences. The aforementioned emotions function as a cognitive mechanism employed by the brain to provide a concise and fundamental evaluation of the body's metabolic condition, functioning as a concise overview of the body's overall energy allocation. When the human body is functioning at its optimal level, individuals often experience a state of comprehensive physical and mental contentment. Conversely, in situations where the human body is operating at a level below its maximum efficiency, individuals may experience noticeable feelings of tiredness or physical unease. Dr. Barrett provides a pertinent illustration to elucidate this phenomenon, drawing a parallel between the regulation of physiological processes and the oversight of a fiscal budget. Dr. Barrett underscores the significance of recognizing the correlation between effect and the brain's perception of the metabolic status of the body. [SEP] Justify:

Output: The text contrasts the claim by discussing the complexity of human emotions and the brain's processing of sensory inputs and their relation to physiological states. It suggests that understanding emotions involves a cognitive mechanism and a process of converting sensory signals into affective experiences, implying that AI assistants may not have the capacity to perfectly respond to all human emotions.


Input: Task: pass the claim using the given text. Claim: Language can serve as a marker of identity and cultural heritage. [SEP] Text: Спроби консолідації політичних сил Наддніпрянщини і Галичини (1920–1923). Революція, державність, нація: Україна на шляху самоствердження (1917–1921). Київ, 2017. С. 87–95. 3. Соляр, І. Ідея консолідації в громадсько-політичному житті Західної України в 1920–1923 рр. Взаємодія інституцій держави і громадянського суспільства наук. ред. Соляр І. Я. Львів: Інститут українознавства ім. І. Крип’якевича НАНУ, 2017. С. 231–240 та ін. [SEP] Justify:

Output: The text does not address the claim regarding language as a marker of identity and cultural heritage. Instead, it discusses political consolidation efforts in Ukraine during the early 20th century, which is unrelated to the concept of language and its cultural implications.


Input: Task: corroborate the claim using the given text. Claim: AI is being used to process data from sensors and cameras in autonomous vehicles to navigate streets safely. [SEP] Text: Since this specific model is a semi-autonomous truck intended to assist the driver during the trip, less sensors are needed. This prototype does not implement LIDAR sensors, which are commonly used for this type of autonomous technology. Since there is only a need to monitor close surroundings mostly when driving on highways, RADAR sensors are capable of retrieving all data necessary for the vehicle to function at a close distance. RADARs are also capable of giving high accuracy for poor weather conditions [39]; however, it is important to notice that the lack LIDAR sensors can also impact the performance of the vehicle. LIDARs could provide a more clear obstacle detection with 3D mapping and a larger FOV than RADARs. usually do not provide a good classification of objects, and due to the low resolution of the images, it could be harder for the autonomous truck to scan the environment without a LIDAR [40]. Truck: is one of the other autonomous truck prototypes expected to be deployed commercially in 2025, along with the Mercedes-Benz autonomous truck. This company, however, was the first to introduce and get approval to test a semi-autonomous truck on a national highway in the United States. Sensors for this autonomous truck are similar to the ones encountered in the Mercedes-Benz truck previously explained. Truck has a front bumper with a RADAR scanning system with short- and long-range RADARs. Long-range RADAR has a range of 820 feet and a 18-deg FOV, and the short-range RADAR has a range of 230 feet and a 130-deg FOV. In addition, there is a stereo camera located at the back of the truck with a range of 328 feet with a 45-deg FOV horizontal by 27-deg FOV vertical. These sensors communicate with the system which with the given data executes lane stability, collision avoidance, speed, control, braking, and automatic steering [41]. 4 study carefully analyzes sensor configuration for different types of vehicles with various functionalities that are used among several industries. 1, there is an organized structure to compare sensor configurations and provide advantages and disadvantages. Sensors are classified among vehicle types, industries, and levels of automation. This table shows, indeed, the main purpose of this paper is to find specific sensor configurations that will perform better than others in multiple changing scenarios. [SEP] Justify:

Output: The text corroborates the claim by illustrating how a semi-autonomous truck uses various sensors, including RADAR and cameras, to monitor its surroundings and execute critical functions like lane stability, collision avoidance, and automatic steering. These capabilities indicate that AI processes sensor data to enhance navigation safety in autonomous vehicles.


Input: Task: contrast the claim using the given text. Claim: AI assistants are able to understand and perfectly respond to all human emotions. [SEP] Text: The regulation of emotions typically entails the modulation of affective states rather than altering their significance, thereby elucidating the involvement of the brain in exerting influence over the body's metabolic condition [18]. 18. Schmitt, C. M. and S. Schoen, Interoception: A Multi-of Participation in Daily Life. Front Neurosci, 2022. 16: p. 875200. (18). 02:15:41 Depression, “Emotional Flu” Dr. Barrett explores the complex interaction between sensory systems, specifically touch and proprioception, and their integration with motor control processes within the brain. Additionally, the author provides additional explanation regarding this notion by expanding its utilization in the domains of visual perception and auditory perception, emphasizing the substantial influence these sensory modalities exert on the brain's regulation of motor functions. The brain relies significantly on sensory information to regulate various physiological systems, including but not limited to the circulatory, pulmonary, and gastrointestinal systems. The understanding of these messages is not achieved through rapid comprehension, but rather entails a process of converting them into emotional responses and basic physiological sensations. The aforementioned emotions function as a cognitive mechanism employed by the brain to provide a concise and fundamental evaluation of the body's metabolic condition, functioning as a concise overview of the body's overall energy allocation. When the human body is functioning optimally, individuals often experience a state of comprehensive physical and mental well-being. Conversely, in instances where the human body is operating at a level below its maximum potential, individuals may experience discernible sensations of weariness or bodily unease. Dr. Barrett provides an illustrative instance to elucidate these phenomena, drawing a parallel between the regulation of physiological processes and the oversight of a fiscal budget. Dr. Barrett underscores the significance of recognizing the correlation between affect and the brain’s evaluation of the metabolic condition of the body. The regulation of emotions typically entails the modification of emotional states rather than altering their significance, hence emphasizing the influence of the brain on the body's metabolic condition [19]. Figure 13. Emotion regulation and the salience network [20]. 19. Williams, J. H. G. , et al. , A sensorimotor control framework for understanding emotional communication and regulation. Rev, 2020. 112: p. 503-518. 20. Pinto, A. M. , et al. , Emotion regulation and the salience network: a hypothetical integrative model of fibromyalgia. [SEP] Justify:

Output: The text contrasts the claim by discussing the complex interaction of sensory systems and the brain's regulation of emotions. It emphasizes that the understanding of emotional responses does not occur through 'rapid comprehension' but requires a conversion process into emotional responses and physiological sensations. This implies that AI, which does not possess the biological capability for emotional understanding and processing that humans have, cannot perfectly respond to all human emotions.


Input: Task: pass the claim using the given text. Claim: Language can serve as a marker of identity and cultural heritage. [SEP] Text: Редакційна колегія Акіллі Алессандро (Achilli Alessandro), доктор філософії, Українські студії, Університет ім. Монаша у Мельбурні, Австралія (1800 Monash (666 274), Australia) Alessandro. Achilli@monash. edu Achilli, А. (2016). “As a Poet he is known to all of Russia”. A rather Fruitful Malentendu: Rilke and Spiridon Drožžin. Zeitschrift für Slawistik, 61(2), 215–228. DOI: 2. Achilli, А. (2015). Taras Ševčenko in the prose and poetry of Vasyl’ Stus. Studi Slavistici, 12, 317–331. DOI: 10. 13128/Studi-Slavis-17985. Retrieved from: Achilli, А. (2013). Subject as a Poet in the Works of Marina Cvetaeva, Rilke. Studi Slavistici, 10(1), 129–148. [SEP] Justify:

Output: The text lists academic works and-related details of Achilli Alessandro but does not provide any information regarding language as a marker of identity and cultural heritage. Hence, it is irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: AI is being used to process data from sensors and cameras in autonomous vehicles to navigate streets safely. [SEP] Text: With that being said, after evaluating advantages and disadvantages for sensors configurations, a set of recommendations is proposed for specific vehicle types and functionality reasons. Table 2 is presenting several sensor configurations that could perform significantly better than other solutions in different scenarios performing multiple tasks. Personal vehicles are the most demanding in terms of technology, and these vehicles should take advantage of the LIDAR technology for highly advanced autonomous cars. This is intended to give precision and increase safety for passengers. Buses, shuttles, and, trucks can benefit from similar sensor configurations with cameras and sensors that have a high FOV to anticipate accidents due to the difficulty of stopping bigger vehicles. Drones are small vehicles that would not require too many sensors. and IMUs are fundamental to monitor weather changes and for object detection. Drones can be customized for different tasks. Finally, robots are not demanding in terms of sensors, RADARs and cameras can work perfectly with several types of tasks. Table 1Comparison of autonomous vehicles technologies IndustryCompanyCamera countLIDAR countRADAR countUltrasonic countRange of coverageLevel of automationAdvantagesDisadvantagesPersonal vehiclesTesla [9,10]80112Cameras (360-deg FOV), RADAR 160-m of rangeSociety of (SAE) Level 2Lower costs for using ultrasonic sensors to detect objects. By having less autonomous features, safety monitoring is easier for Tesla, and ultrasonic sensors are vulnerable to jamming and spoofing attacksLimitation for ultrasonic sensors can misbehave or not function properly. Limiting possibilities using this hardware will help improve the project to a higher level of automationPersonal vehicles[11,12]12560360-deg FOV and a range of 300 m. Cameras with a range of 500 mSAE Level 4Reduced costs by 90% by using unique LIDARs. Greater flexibility using the with its features such as 95-deg FOV and minimum range of 0 open data set for testing purposes that increases probabilities of innovationLimited testing locations in extreme weather conditions. Smart cities as only target market. Modes of use for are limited to Auto-Taxi service which is restricting advanced testing methodsPersonal vehicles[13,14]5235LIDAR with 360-deg FOV and covering 300 mSAE Level 4Variety of sensors creates diversity and takes advantage of different technologies. for specific scenarios helps reducing costs. [SEP] Justify:

Output: The text corroborates the claim by discussing various sensor configurations, including LIDAR, cameras, and RADAR, specifically mentioning their application in personal vehicles and other types of autonomous transport. It highlights how these technologies enhance navigation and safety, which supports the assertion that AI processes data from sensors to facilitate safe navigation.


Input: Task: contrast the claim using the given text. Claim: All personal AI assistants are completely secure from data breaches and hacking. [SEP] Text: Futures – “Commodification Bets” All the to AI Published online by Press: 18 September 2024 [Opens in a new window]Eduard Fosch-Villaronga [Opens in a new window] and[Opens in a new window] Show author details Marco Giraudo* Affiliation: University of Turin, Turin, Fosch-Villaronga Affiliation: University of : University of Leiden, Leiden, Netherlands * Corresponding author: Marco Giraudo; Email: marco. giraudo@unito. it 0. 35 mb) View PDF [Opens in a new window] Save to to Save to This 10. 1017/glj. 2024. 29 [Opens in a new window] This is an 4. 0/), which permits unrestricted re-use, distribution and reproduction, provided the original 2024. Published by Press on behalf of the Journal A. of technological innovations based on AI fuel narratives of unprecedented economic and social progress in every possible imaginable field: from healthcare to retail, from the stock market to marketing and advertising, from farming to sports. Footnote 1 The novelty of AI tools makes their related impact on society unknown or difficult to be known, as it is often masked under a veil of extreme short term efficiency bearing on the stability of their legal foundations. Footnote 2 At the same time, forms of folie normative (or regulatory madness) and the adoption of countless resolutions, ethical guidelines, standards, and laws—often contradictory—and unclear, further blur the visibility over the legal robustness of the foundations of AI-powered business. It is unsurprising therefore that AI tools are marketed in a context of legal uncertainty oftentimes through the use of innovative contractual solutions to secure legal entitlements to perform such new activities and attract further investments in these newly emerging markets. Footnote 3 Over time, such technological waves are often accompanied by legal shockwaves arising from formal and substantive conflicts between claimed legal entitlements to market new products and counterclaims to protect the prevailing legal order. Footnote 4 Many times, the exaggerated expectations of the legal sustainability of innovative solutions that accompany the commercial release of new products are contradicted by widespread recognition of adverse effects in terms of fundamental rights and democratic order, as well as other constitutionally protected interests. [SEP] Justify:

Output: The text contrasts the claim by indicating that the novelty and legal uncertainties surrounding AI tools create a context where their safety and reliability are questionable. It explicitly mentions that 'the novelty of AI tools makes their related impact on society unknown or difficult to be known,' implying that these tools, including personal AI assistants, are not guaranteed to be completely secure from breaches and hacking.


Input: Task: pass the claim using the given text. Claim: Language can serve as a marker of identity and cultural heritage. [SEP] Text: DOI: Борчук Степан, доктор історичних наук, професор, професор кафедри всесвітньої історії ЗВО «Прикарпатський національний університет імені Василя Стефаника» (вул. Шевченка, 57, м. Івано-Франківськ, 76018, Україна) borchuk_s@ukr. net Borchuk, S. , Khytrovska, Yu. (2019). History of Relations of Masonry and Church in the – Centuries. Український історичний журнал, 4, 118–135. Retrieved from: 2. Borchuk, S. (2017). The first completed Ukrainian encyclopedia of modern times. Danubius, 35 (Supliment: Modernity, Post-modernity, Communism, Post-communism. Contributions, supplementary issue), 129–140. Retrieved from: 3. Borchuk, S. (2017). Ukrainian encyclopaedic tradition of the 20th century. Codrul Cosminului, 23(2), 273–290. [SEP] Justify:

Output: The text provided does not address the claim regarding language as a marker of identity and cultural heritage. Instead, it presents a bibliographic citation of various works by Borchuk without discussing the relationship between language and identity. Therefore, it is considered irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: AI is being used to process data from sensors and cameras in autonomous vehicles to navigate streets safely. [SEP] Text: Good results according to the data for safety measuresSwitching to low-resolution LIDARs for price reasons can negatively affect performance. have low resolution and a visibility accuracy of 60%. precision is needed because RADARs are not capable of detecting non-metallic objects in dangerous weather conditions5 [15,16]2454N/ASAE Level 3Implementation of solid-state LIDARs that are cheaper and more effective than mechanical LIDARs. Precise 3D mapping and point cloud up to 250 m. Great sensor fusion between 12 sensorsTesting limitations for the prototype and adaptation to real-life. Gab between information available and the current state of the project. Limited mapping after reaching 250 mPersonal vehiclesArgo AI, Cruise9220LIDARs with a 360-deg FOV and a range up to 400 mN/ASpecific sensor information is not publicly available. Main limitation for the research and the main reason why there are not clear advantagesN/APublic transports (buses)Volvo [19,20]6322LIDAR with 160-deg FOV and a range of 200 mSAE Level 2Different types of sensors are tested and implemented to gather the maximum information possible. For an autonomous vehicle with this size it is necessary to increase the number of sensorsPrototype has not been tested in different weather conditions that could have influence over the performance of the busPublic transports (shuttles)Navya [21,22]21000with a 360- and 180-deg 4Technology employed can be scaled to develop bigger projects. Sensor fusion is accurate and effective with enhanced safety systems and obstacle detection methodsThe space of the vehicle is very limited (up to 15 passengers). Testing areas are limited and controlled (campuses, airports, smart cities). The technology has not been tested in bigger-scale vehicles. This could create a limitation when building a project with a bigger passenger capacity(Shuttles)EasyMile [23]3210LIDAR with 360-deg FOV and 250-m range. Front and lateral cameras with a range up to 300 mSAE Level 4A great variety of modes for its use (Metro mode, bus mode, on-demand mode). EZ10 project is implementing RADAR sensors for data fusion and safetySimilar disadvantages compared with Navya. The shuttle is functional, but the capabilities are limited. [SEP] Justify:

Output: The text corroborates the claim by discussing the implementation of various sensors, including LIDARs and cameras, which are essential for gathering data in autonomous vehicles. It highlights the importance of sensor fusion and the accuracy needed for safe navigation, directly supporting the assertion that AI processes data from these sensors to enhance safety measures in self-driving vehicles.


Input: Task: contrast the claim using the given text. Claim: All personal AI assistants are completely secure from data breaches and hacking. [SEP] Text: Footnote 5 As a result, some AI products are already being rejected outright, either by the intervention of law enforcement agencies or by judicial pronouncements retroactively declaring them unlawful. For example, facial recognition technologies or AI-based virtual friendship services have been banned in some jurisdictions by the courts and likely confirmed by legislative action. Footnote 6 In economic terms, many investors may soon face significant losses as a result of the outright prohibition of markets that they had imagined to be “legal” and whose legal foundations eventually “disappear” because they are found to be incompatible with some fundamental rights and democratic public order. Yet, many investors and policymakers seem unconcerned about the potential economic and political consequences of increasing uncertainty about the stability of the legal foundations of AI-based products, as if the legal rules announced by courts or enforcement decisions by specialized agencies in the EU or the FTC in the U. S. do not affect the economic value of new activities and services. Footnote 7 Such disregard for the legal dynamics and increasing inalienability of the entitlements being traded is in striking contrast to what would be expected of investors faced with such profound fluctuations in legal uncertainty within an industry. Footnote 8 All the more so when we consider the lack of learning from similar legal-economic patterns that have been playing out for more than a decade in the context of the first phase of information capitalism, whose legal foundations are currently in a stalemate. Footnote 9 For a long time now, economic actors have been unfettered by faltering legal claims to commodify personal data, the “new currency of the Internet. ”Footnote 10 Even there, despite widespread warnings about the legal dangers of “everydayness as a commercialization strategy,” we have witnessed a sustained flow of investment into an industry whose core resource has long been suspected of not qualifying as a “commodity. ”Footnote 11 Today, the entire industry is hanging by a thread, riding on what appears to be a cluster of “legal bubbles,” as legal support for the commodification of personal data diminishes and surveillance practices become increasingly costly, if not prohibited. And yet, with no apparent rational explanation, the very same private actors whose behavioral commodification bets are in jeopardy are the ones raising the stakes with AI gambles to even higher levels of magnitude, with an inadequate response from rule makers and enforcers. [SEP] Justify:

Output: The text contrasts the claim by discussing the growing legal uncertainties surrounding AI products, implying that these products, including personal AI assistants, may not be secure. It highlights that many AI products are being rejected by law enforcement or deemed unlawful, which suggests that there are significant risks associated with their use. The mention of 'legal bubbles' and the commodification of personal data indicates that personal AI assistants may be vulnerable to data breaches and hacking rather than being completely secure.


Input: Task: pass the claim using the given text. Claim: Language can serve as a marker of identity and cultural heritage. [SEP] Text: Retrieved from: Газдаг Вільмош (Gazdag Vilmoš), доктор філософії, доцент кафедри угорської філології, Закарпатський угорський інститут ім. Ференца Ракоці ІІ (площа Кошута, 6, м. Берегово, 90202, Україна) gazdagvilmos@gmail. com Gazdag, V. (2019). Szesztra – egy kiveszett szláv jövevényszó regionális újrakölcsönzéséről. Magyar Nyelv, 115(4), 460–467. DOI: 10. 18349/MagyarNyelv. 2019. 4. 460. 2. Gazdag, V. (2018). Másodnyelvi homonimák a kárpátaljai magyar nyelvjárásokban. Magyar Nyelv, 114(3), 347–359. DOI: 10. 18349/MagyarNyelv. 2018. 3. 347. 3. Gazdag, V. (2016). Csernicskó István: Nyelvpolitika a háborús Ukrajnában (Ismerteti). Magyar Nyelvőr, 140(1), 107–110. [SEP] Justify:

Output: The text does not address the claim about language serving as a marker of identity and cultural heritage. Instead, it provides biographical details about an academic and references various scholarly works, which are unrelated to the claim.


Input: Task: corroborate the claim using the given text. Claim: AI is being used to process data from sensors and cameras in autonomous vehicles to navigate streets safely. [SEP] Text: Highway system connecting with the vehicle to ensure safety and provide data from sensorsVehicle does not implement LIDAR sensors that could be useful to increase visibility when doing a 3D mapping to visualize the environmentLogisticsFreightliner6420Long- and short-range RADARs (820 ft and 230 ft), front and back with a 328 ft range and 45-deg 4Highway pilot system supporting data fusion and executing lane stability, collision avoidance, speed control, etc. Sensor information is missing to determine the negative aspects of the technology. This vehicle is currently a prototypeIndustryCompanyCamera countLIDAR countRADAR countUltrasonic countRange of coverageLevel of automationAdvantagesDisadvantagesPersonal vehiclesTesla [9,10]80112Cameras (360-deg FOV), RADAR 160-m of rangeSociety of (SAE) Level 2Lower costs for using ultrasonic sensors to detect objects. By having less autonomous features, safety monitoring is easier for Tesla, and ultrasonic sensors are vulnerable to jamming and spoofing attacksLimitation for ultrasonic sensors can misbehave or not function properly. Limiting possibilities using this hardware will help improve the project to a higher level of automationPersonal vehicles[11,12]12560360-deg FOV and a range of 300 m. Cameras with a range of 500 mSAE Level 4Reduced costs by 90% by using unique LIDARs. Greater flexibility using the with its features such as 95-deg FOV and minimum range of 0 open data set for testing purposes that increases probabilities of innovationLimited testing locations in extreme weather conditions. Smart cities as only target market. Modes of use for are limited to Auto-Taxi service which is restricting advanced testing methodsPersonal vehicles[13,14]5235LIDAR with 360-deg FOV and covering 300 mSAE Level 4Variety of sensors creates diversity and takes advantage of different technologies. for specific scenarios helps reducing costs. Good results according to the data for safety measuresSwitching to low-resolution LIDARs for price reasons can negatively affect performance. have low resolution and a visibility accuracy of 60%. [SEP] Justify:

Output: The text corroborates the claim by discussing various systems and technologies (e.g. RADAR, ultrasonic sensors, LIDAR) that are implemented in autonomous vehicles to enhance navigation and safety. It mentions 'data fusion' and 'collision avoidance', which implies the use of AI to process sensory data for safe navigation. The description of the vehicle's capabilities directly supports the claim regarding AI's role in safe autonomous navigation.


Input: Task: contrast the claim using the given text. Claim: All personal AI assistants are completely secure from data breaches and hacking. [SEP] Text: If history is any guide, the recent anomalous economic inaction in the face of legal dynamism portends legal instability ‘on steroids’ for the AI-based industry. Footnote 12 In this 2021. Antitrust authority in its famous 2016 Facebook case, Inc. and others v. Bundeskartellamt, held that personal data are not commodities and Gesetz gegen Wettbewerbsbeschränkungen [GWB] [Act], Jun. 26, 2013, Bundesgesetzblatt (Gazette) at 1, 1750, 3245. cannot be sold for a price and this decision was affirmed by the CJEU in 2023. Footnote 36 The industry perceived the fact that the Courts did not immediately reject the “commodification consensus,” as a green light. Footnote 37 Soon, and most technological companies released innovations pointing to the commodification of these previously unexploited resources, investing in them as if their commodification bets could not fail and as if everything was legally permitted. Footnote 38 Over the years, we have witnessed a growing industry upon these commodification bets, juiced up by the initial success in managing some leeway from courts and some specialized agencies—if not temporary support. Footnote 39 The pouring of investments in the multi-billion industry and a policy consensus that personal data are an irreplaceable resource for the future have long fed the expectations that the commodification bid was successful. A sort of normalization of surveillance has appeared to change the social norm. Footnote 40 In the industry’s legal viewpoint, the priority was often given to economically profiting from personal data, assuming proper procedures and risk assessments were in place. In this context, the tech industry considered the legal costs of using personal data quite low, similar to handling a commonly traded asset like currency. Footnote 41 Similarly, possible fines or compensation for unlawful processing were perceived as the mere cost of doing business. Footnote 42 It is no surprise that personal data have long been used and circulated as freely as a commodity to feed data driven business models devised “without much concern about social, economic, or legal consequences […] As the saying goes, it was better to ask for forgiveness than permission. [SEP] Justify:

Output: The text contrasts the claim by highlighting the commodification of personal data and indicating that personal data have long been used and circulated freely, suggesting a normalization of surveillance and lowering of legal costs for using personal data. This implies that there are significant risks associated with the security of personal data, which contradicts the assertion that all personal AI assistants are completely secure from data breaches and hacking.


Input: Task: pass the claim using the given text. Claim: Language can serve as a marker of identity and cultural heritage. [SEP] Text: Retrieved from: Даниленко Андрій (Danylenko Andriy), професор, доктор філософії, Університет Пейс, Коледж мистецтв і наук ім. Дайсона, Сучасні мови та культури, США (41 Park Row, 2nd Floor, New York, NY 10038, United States) adanylenko@pace. edu Danylenko, A. , Naienko, H. (2019). Linguistic russification in Russian Ukraine: languages, imperial models, and policies. Russian Linguistics, 43(1), 19–39. DOI: 10. 1007/s11185-018-09207-1 2. Danylenko, A. (2018). The correlation of linguistic patterning and societal structures insystemic typology. Cracoviensis, 135(1), 81–96. DOI: 10. 4467/20834624SL. 18. 007. 8167. 3. Danylenko, A. (2018), Complexity development and simplification in systemic typology: types of changes in the internal determinant. Cracoviensis, 135(2), 113–129. DOI: 10. 4467/20834624SL. 18. 010. 8469 4. Danylenko, A. (2017). A missing chain? Оn the sociolinguistics of the of Lithuania 1. Acta Baltico-Slavica, 41, 31–57. DOI: 10. 11649/abs. 2017. [SEP] Justify:

Output: The text does not address the claim about language being a marker of identity and cultural heritage. It lists various works by the author Andriy Danylenko, along with their citations, without discussing or providing evidence related to the claim.


Input: Task: corroborate the claim using the given text. Claim: AI is being used to process data from sensors and cameras in autonomous vehicles to navigate streets safely. [SEP] Text: precision is needed because RADARs are not capable of detecting non-metallic objects in dangerous weather conditions5 [15,16]2454N/ASAE Level 3Implementation of solid-state LIDARs that are cheaper and more effective than mechanical LIDARs. Precise 3D mapping and point cloud up to 250 m. Great sensor fusion between 12 sensorsTesting limitations for the prototype and adaptation to real-life. Gab between information available and the current state of the project. Limited mapping after reaching 250 mPersonal vehiclesArgo AI, Cruise9220LIDARs with a 360-deg FOV and a range up to 400 mN/ASpecific sensor information is not publicly available. Main limitation for the research and the main reason why there are not clear advantagesN/APublic transports (buses)Volvo [19,20]6322LIDAR with 160-deg FOV and a range of 200 mSAE Level 2Different types of sensors are tested and implemented to gather the maximum information possible. For an autonomous vehicle with this size it is necessary to increase the number of sensorsPrototype has not been tested in different weather conditions that could have influence over the performance of the busPublic transports (shuttles)Navya [21,22]21000with a 360- and 180-deg 4Technology employed can be scaled to develop bigger projects. Sensor fusion is accurate and effective with enhanced safety systems and obstacle detection methodsThe space of the vehicle is very limited (up to 15 passengers). Testing areas are limited and controlled (campuses, airports, smart cities). The technology has not been tested in bigger-scale vehicles. This could create a limitation when building a project with a bigger passenger capacity(Shuttles)EasyMile [23]3210LIDAR with 360-deg FOV and 250-m range. Front and lateral cameras with a range up to 300 mSAE Level 4A great variety of modes for its use (Metro mode, bus mode, on-demand mode). EZ10 project is implementing RADAR sensors for data fusion and safetySimilar disadvantages compared with Navya. The shuttle is functional, but the capabilities are limited. Not really an autonomous solution to a big scale project of public transportation(Trains)SNCF [24,25]2442LIDARs with 360-deg with a range of 140 mGoA 4Increased safety. [SEP] Justify:

Output: The text corroborates the claim by mentioning the use of various sensors, including LIDAR and cameras, that are essential for enhancing safety systems and obstacle detection methods in autonomous vehicles. It describes how these technologies are implemented to gather maximum information, which aligns with the claim that AI is utilized in processing data from sensors and cameras to ensure safe navigation.


Input: Task: contrast the claim using the given text. Claim: All personal AI assistants are completely secure from data breaches and hacking. [SEP] Text: ”Footnote 43 After an initial period in which the support of the courts and the acceptance of the techno-optimist narratives and ethics promulgated by enthusiastic academics in favor of the commodification of personal data seemed to be secured, there has been a widening gap between the legal practices within the economy and the rules upheld in the courts. The ECJ played a major role in this shift, given that it has tended to favor the protection of fundamental rights and freedoms—rather than economic claims. Footnote 44 The big question about the viability and stability of personal data as the currency of the Internet is closely related to the fate of these systemic commodification bets placed by primary economic actors and elements of governmental bodies. If the bet fails for good, the legal basis of the market would disappear, and liabilities and bankruptcies could eventually follow. II. Inadaptations as a Denial of the Legal-Recent developments have complicated the general agreement on data commodification, especially due to various cases being considered or already decided by the Court of Justice of the (CJEU). A major issue arising from these cases is determining the legal grounds for processing behavioral data on social media, which is proving to be a complex legal challenge. Social media could choose among different lawful grounds under the GDPR, for example, consent (40. For example, the EU Commission and Council continue to support the ’commodification consensus’, rejecting the EU Parliament’s proposal for a fundamental rights impact assessment or relying on standardization bodies,Footnote 69 which combined with widespread risk-based approaches, may ultimately allow the deployment of authoritarian technologies such as the emotion recognition or remote biometric control systems that seriously threaten individual freedoms and dignity. Footnote 70 In particular, the AIA proposal’s structural reliance on a supposedly “clearly” defined risk-based approach to the design of market boundaries for new AI-based solutions feeds the myth that the vagueness of the legal rules it lays down can be supplemented by the rigorous application of “risk management science. ” Footnote 71 A science which, when applied to the specific cases of protection of fundamental rights, simply does not exist. Footnote 72 There are instead mere risk focusing subjective and discretionary forecasting techniques, which might help [S]ystemize decision making and render what is tacit explicit, but what it cannot in itself do, is provide a plan for what agencies should do. [SEP] Justify:

Output: The text contrasts the claim by discussing the complexities and legal challenges surrounding data protection and commodification, particularly in relation to personal data usage in AI and social media. It highlights potential risks and vulnerabilities inherent in the commodification of personal data and suggests that widespread risk-based approaches may lead to the deployment of technologies that threaten individual freedoms, indicating that personal AI assistants cannot be considered completely secure from data breaches and hacking.


Input: Task: pass the claim using the given text. Claim: Language can serve as a marker of identity and cultural heritage. [SEP] Text: 002 Золтан Андраш (Zoltán András), професор, доктор філологічних наук, Будапештський університет імені Лоранда Етвеша, Угорщина (H-1053 Budapest, Egyetem tér 1-3) zoltandr@gmail. com Zoltán, A. (2018). Ранний славяноболгарский вклад в венгерский язык. Hungaricae, 63, 171–180. DOI: 10. 1556/060. 2018. 63. 1. 19 2. Zoltán, A. (2017). Mely szláv nyelvből jött zabrál szavunk? Magyar Nyelv, 113(2), 225–227. DOI: 10. 18349/MagyarNyelv. 2017. 2. 225 3. Zoltán, A. (2017). Szláv jövevényszavaink néhány időrendi és nyelvföldrajzi kérdése. Magyar Nyelv. 113. 2017. P. 1−9. DOI: 10. 18349/MagyarNyelv. 2017. 1. 1 4. Zoltán, A. (2017). Az ómagyar szerencs ’útonálló’ nyoma a régi kárpátukránban. Magyar Nyelv. 113. 2017. P. 206−210. DOI: 10. 18349/MagyarNyelv. 2017. 2. [SEP] Justify:

Output: The text is irrelevant to the claim as it does not provide any information regarding language as a marker of identity and cultural heritage. Instead, the text appears to focus on academic references and contributions of a specific professor related to Slavic languages and their linguistic influences in Hungarian, which does not directly address the claim.


Input: Task: corroborate the claim using the given text. Claim: AI is being used to process data from sensors and cameras in autonomous vehicles to navigate streets safely. [SEP] Text: This vehicle is currently a prototype Table 2Recommended sensor configurations based on vehicle type and functionality Type of vehicleSensors recommendedSensor configuration propertiesAdditional commentsPersonal VehiclesUltrasonic sensors, more than 5 cameras, GPS, and GNSSWith this sensor configuration, the vehicle should be able to detect the entire surroundings. Due to the functionality of personal vehicles, there should be a 360-deg range of coverage for LIDARs, ultrasonic sensors, and camerasDepending on the level of automation for a specific vehicle, the produce could choose between an ultrasonic sensor or a LIDAR. Least autonomous vehicles could benefit from ultrasonic sensors due to their low cost. However, a more autonomous car should implement LIDARs to benefit from 3D mapping and precisionShuttles/Buses/cameras with a large and GNSSThis configuration is similar to the one chosen for personal vehicles. In this case, cameras should have a large field of view due to the size increment of the vehicle. In addition, more sensors are required to ensure a proper sensor fusion in bigger vehiclesBuses and shuttles could consider implementing ultrasonic vehicle to reduce costs. These could fusion also with LIDARs for better results regarding object detection considering that most of these types of vehicles will have a basic level of automationwith at least 120 m of range, LIDARs, cameras, and ultrasonic sensorsFor trains, the sensor configuration can fluctuate. Trains will benefit with this configuration from advanced sensing technology with RADARs and LIDARs. These sensors should have a minimum amount of range of 120 m to increase response time in case of accidents. GPS and GNSS are encouraged but no necessary due to the control and monitoring of railroadsN/cameras with a large barometersThis specific configuration for drones will give the vehicle the ability to monitor its surroundings with cameras and LIDARs. GNSS and GPS sensors will help the drone with orientation. IMUs and barometers are crucial to register weather changesBasic object detection is needed for drones since they avoid close contact with the ground, there is no need of LIDARs for that purpose. [SEP] Justify:

Output: The text corroborates the claim by outlining recommended sensor configurations for various types of vehicles, which indicates the use of multiple sensors and cameras for environmental detection. It explains how personal vehicles should utilize more than five cameras, ultrasonic sensors, and LIDARs for 360-degree coverage and object detection, implying that these devices aid in navigation and safety, which aligns with the claim about AI processing data from these sensors for safe navigation.


Input: Task: contrast the claim using the given text. Claim: All personal AI assistants are completely secure from data breaches and hacking. [SEP] Text: It does not determine how to construct discrete ‘risks’ or suggest how risk creators are to be dealt with in order to increase compliance or the furthering of statutory objectives. Footnote 73 These heuristics alone do not provide any objective, predictable and enforceable criteria as to which activities are lawful or unlawful, let alone what the legal consequences of the use of the technologies under discussion are. This means that “risk calculations” and formal procedures do not lead to normative, predictable guidance on how AI products can be used and deployed without undermining the protection of fundamental rights. Footnote 74 Such a convention, which exaggerates the ability of risk management techniques to generate a “degree of certainty based on probabilistic logic,” risks becoming ideological or wishful thinking. Footnote 75 For the rhetorical move to label what is “uncertain” as “risky” makes it possible to play down the problem of knowledge about the actual impact of new products on constitutionally protected interests and the ensuing questions of democratic public order. The move is also instrumental to justify a de facto transfer of regulatory power to the EU Commission for example, 1. 4, Centre for -identification code: CN00000022, CUP: D13C22001330005. 3. weforum. org/docs/WEF_ITTC_PersonalDataNewAsset_Report_2011. pdf. ; Paul M. Schwartz, Property, Privacy, and Personal Data, 117 Harv. L. Rev. 2056, 2057 (2004); & Jana Korunovska, Towards a for Personal Data, 32 J. of Info. Tech. 62, 62 (2017). 25 25 & Malgieri, supra note 111, at 6; Ian C. Ballon, Camp: at the Intersection of Law and Business’, in E-Commerce and Internet Law: A with Forms 345 (Ian C. Ballon, 2nd ed. 2016). 26 26 See e. g. , Daniel Cole, Rights’ as ‘Stilts’: A comment on Hodgson, 11 J. Inst. Econ. 725, 729 (2015); Pistor, supra note 19. 27 27 See e. g. & Byers, Big Data: Frontier for Innovation, Competition, and Productivity, McInstitute 1, 11 (2011); Anupam Chander, Future-Proofing Law, 51 U. [SEP] Justify:

Output: The text contrasts the claim by highlighting the complexities and uncertainties surrounding the use of AI technologies, specifically noting that current risk management techniques do not provide predictable or enforceable criteria for the lawful use of these technologies. This implies that AI assistants may not be completely secure, as the text suggests a lack of certainty about the actual impacts of such technologies on privacy and fundamental rights, thus undermining the claim of total security.


Input: Task: pass the claim using the given text. Claim: Language can serve as a marker of identity and cultural heritage. [SEP] Text: 206 Литвин Микола, доктор історичних наук, професор, завідувач відділу «Центр дослідження українсько-польських відносин», Інститут українознавства ім. І. Крип’якевича НАН України (вул. Козельницька, 4, Львів, 79026, Україна) ukrpol. centr@gmail. com Lytvyn, M. , Khakhula, L. (2019). How and why do politicians use history? Review: Georgiy Kasianov. Past Continuous: historical politics of the 1980s – 2000s: Ukraine and its neighbors. Kyiv, Laurus, Antropos-Logos-Film. 430 s. Східноєвропейський історичний вісник, 10, 196–199. DOI: 10. 24919/2519-058x. 10. 159177 2. Lytvyn, M. , Khakhula, L. (2019). była osamotniona w dobie nowożytnej? Michał Klimecki, Zbigniew Karpus, Czas samotności. Ukraina i Ukraińcy w latach 1914–2018 Warszawa, Bellona, 2018, 336 s. [SEP] Justify:

Output: The text provided contains bibliographic information about a publication and does not address the claim regarding language as a marker of identity and cultural heritage. It does not provide any information or arguments related to the relationship between language and cultural identity, thus making it irrelevant to the claim.


Input: Task: corroborate the claim using the given text. Claim: AI is being used to process data from sensors and cameras in autonomous vehicles to navigate streets safely. [SEP] Text: In specific areas such as farming, attachments can be added to give the drone extra functions and increase its utilityhigh-definition cameras, IMUsRobots are used in controlled spaces; this configuration will give the robot the ability to autonomously accomplish tasks with accuracyMost robots will need around 2–4 cameras since there is no need to have complete control of the surrounding area 5 conclude this paper, autonomous vehicles are getting developed and used more than ever. Companies are investing in this new technology to provide new products and incorporate these vehicles into their production system to increase productivity. It is important to acknowledge that not every sensor configuration will work for every type of usage or implementation. Asking this question would be the initial motivation for this study to be conducted. Along with this paper, there was a detailed analysis of case studies of current autonomous vehicles available on the market and prototypes under development. Divided by industry, the study gathered data about sensors from several companies among four industries (and Logistics). A comparison was done in order to choose the best sensors based on vehicle type and functionality. Based on the advantages and disadvantages of each sensor configuration, this paper pretends to recommend general sensor configurations that will adapt properly to the properties of the vehicle and the usage when integrating them into the production process or to deploy them as products on the market. 6 The future of autonomous vehicles is promising, research and development are intensifying each day, and computer scientists are eager to discover new ways to introduce this technology into people’s lifestyles. The topic presented for this research paper is incredibly extensive. Regarding the findings of this study, many technologies of autonomous vehicles have been deployed in the past months or years. However, many others are still in the development stage. This is limiting the research because there are no sensor data or information to analyze. Future researchers should specifically address the new trends in autonomous vehicles and keep updating the information when a new vehicle is deployed. Moreover, sensor technology has few options in the market for RADARs and LIDARs. Velodyne, for example, is one of the most famous manufacturers of LIDARs for autonomous vehicles. Conflict of are no conflicts of interest. 1. Varghese, J. Z. , Boone, R. G. , 2015, “Overview of Sensors and Systems,” on and. 10–11, 191. 2. Campbell, S. , O’Mahony, N. [SEP] Justify:

Output: The text corroborates the claim by discussing the development and use of autonomous vehicles, highlighting how companies are investing in technology that includes data gathering from various sensors. It mentions the role of cameras and sensor configurations in enabling autonomous vehicles to operate accurately and safely, supporting the idea that AI is integral in processing this data for navigation.


Input: Task: contrast the claim using the given text. Claim: All personal AI assistants are completely secure from data breaches and hacking. [SEP] Text: C. Davis L. Rev. 1, 19 (2017) (discussing the idea of the constitutive function of the law for digital activities. ) 28 28 Purtova, of as No One’s Property, 7 L. , Innovation, & Tech 83, 83 (2015). 29 29 Zuboff, supra note 3 at Part I, 97. 30 30 See e. g. , Urbano Reviglio, of in Surveillance Capitalism: A Transnational and Interdisciplinary Overview, 11 Internet Pol’y Rev. 1, 2 (2022) (describing the role of data brokers in trading the predictive promise of “behavioral insights” inferred through profiling). 31 31 Demsetz, Toward a theory of property rights 62 Am. Econ. Rev. 347 (1967); Jhon R. Umbeck, A Theory of with Application to the Rush (1981); (detailing how, in the tradition of Harold Demsetz, argued many decades ago, when analyzing the “golden race” in California, that the propertization of publicly available valuable goods that lack a proper default legal allocation, for example, public goods whose owners are not identified by law, like the gold in Californian mines when California was annexed to the United States, depends on the practical capability of some entities to collect those goods and exclude others from the use of those goods). See also Nadezhda Purtova, in Personal Data: Learning from the American Discourse, 25 Comp. L & Sec. Rev. 507 (2009) (describing how Purtova applied Umbeck’s theory to personal data, suggesting that the ambiguity about the ownership of personal data across the different legal systems would rapidly create the basis for an incredible market power asymmetry to the advantage of the few entities —Big Tech— capable of monetizing personal data). 32 32 Morelli. & Oreste Pollicino, Metaphors, in Cyberspace, 63 Am. J Comp. L. 616, 616 (2020). 33 33 Kuchař, Entrepreneurship and Institutional Change, 26 J. of Evolutionary Econs. 349, 350 (2016); Nora McDonald & Andrea Forte, Norms in Discourse, 5 association for computing mach. [SEP] Justify:

Output: The text contrasts the claim by discussing the complexities of personal data ownership and the vulnerabilities related to personal data management. It highlights that ambiguity in personal data ownership contributes to market power imbalances, particularly benefitting large tech entities that profit from personal data, indicating that these systems may not be completely secure.


Input: Task: pass the claim using the given text. Claim: Language can serve as a marker of identity and cultural heritage. [SEP] Text: Pamięc i Sprawiedliwość, 33, 547–553. Retrieved from: 3. Литвин, М. , Хахула, Л. (2019). Рецензія на книгу Литвина Сергія “Симон Петлюра у боротьбі за самостійну державу”. of Culture and Arts Herald, 1, 442–444. DOI: 10. 32461/2226-3209. 1. 2019. 167196 4. Lytvyn, M. , Khakhula, L. (2019). The ukrainian memory community in Poland (the second half of the XX – beginning of the XXI centuries). Східноєвропейський історичний вісник, 12, 178–191. DOI: 10. 24919/2519-058x. 12. [SEP] Justify:

Output: The text does not address the claim about language as a marker of identity and cultural heritage. It discusses various academic articles and publications without providing any relevant information on the role of language in identity or cultural heritage.


Input: Task: corroborate the claim using the given text. Claim: Autonomous vehicle technology is advancing rapidly, with companies testing fully driverless cars in certain areas. [SEP] Text: is Open Access? is an initiative that aims to make scientific research freely available to all. To date our community has made over 100 million downloads. It’s based on principles of collaboration, unobstructed discovery, and, most importantly, scientific progression. As PhD students, we found it difficult to access the research we needed, so we decided to create a new publisher that levels the playing field for scientists across the world. How? By making research easy to access, and puts the academic needs of the researchers before the business interests of publishers. are a community of more than 103,000 authors and editors from 3,291 institutions spanning 160 countries, including winners and some of the world’s most-cited researchers. Publishing on IntechOpen allows authors to earn 10. 5772/intechopen. 89917 this 1. Choose citation style Select style to clipboard Get citation 2. Choose citation style Select format Bibtex RIS Download citation IntechVehicle and Edited by From the Edited by and purchase hard copies of this book, please contact the representative in India: CBS Publishers & Distributors Pvt. Ltd. www. cbspd. com | customercare@cbspd. com 1. Choose citation style Select style to clipboard Get citation 2. Choose citation style Select format Bibtex RIS Download citation Impact of this 1. IntroductionAn autonomous car is a vehicle that can guide itself without human command and control. It is also known as a driverless car, self-driving car, unmanned vehicle or a robot car. Autonomous vehicles are able to perceive their surroundings (obstacles and track) and commute to destination with the help of a combination of sensors, cameras and radars. Advanced control systems can interpret the information provided by sensors to detect obstacles and choose the most suitable navigation path for the vehicle. Enormous research has been carried out to bring the idea of autonomous car to life. Now a days, such vehicles have become a concrete reality and they have been created and extensively tested on roads, although they are not yet commercially available on a large scale. In autonomous vehicles, one of the most important features is the correct and accurate detection of obstacles as well as the track of the vehicle. The vehicle or car should be able to detect the presence of an obstacle precisely and well in time so that it can stop itself at a safe distance in order to avoid the collision. [SEP] Justify:

Output: The text corroborates the claim by discussing advancements in autonomous vehicle technology, describing them as vehicles that can guide themselves without human command, and mentioning that enormous research has been carried out to make autonomous cars a reality. It states that these vehicles have been created and extensively tested on roads, which aligns with the assertion that companies are testing fully driverless cars.


Input: Task: contrast the claim using the given text. Claim: All personal AI assistants are completely secure from data breaches and hacking. [SEP] Text: 218, 218 (2015); Philippe Jougleux, Facebook and the (EU) Law, in 48 Law, Governance and (2022). 40 40 Hartzog, & Johanna Gunawan, Privacy Nicks: How the Surveillance, 101 Wash. U. L. Rev. 717 (2023). See also & Marco Giraudo, in : A View, 67 Eur. J. Pol. Econ. 101967 (2021). 41 41 Janeček & Malgieri, supra note 15, at 940. 42 42 Ballon, supra note 25, at 418. 43 43 Manyika et al. , supra note 27, at 12–13. 44 44 & Lee A. Bygrave, Demystifying the Regime: Cross- Scholarship, 16 Regul. and Governance 137, 150 (2022); Hielke Hijmans, Union as Guardian of Internet Privacy: of Art. 16 TFEU, in 31 Law, Governance and 202 ff (2016). 45 45 Meta Case, supra note 36. 46 46 Board (EDPB) 1/2023 on the dispute submitted by the Irish SA on data transfers by for its Facebook service (Art. 65 GDPR) (2023) 47 47 Datatilsynet [Protection Authority], Decision n. 21/03530-16 (July 14, 2023) (citing 1. 3 Is a Surveillance Capitalism, Wired (May 22, 2023) 50 50 In particular, economic agents have already “visualized” the economic implications and costs associated with legal issues arising from “accidents” with personal data in case of malicious cyber-attacks or data breaches. See e. g. , in to Cyber-Attacks, (July 27, 2023) Only recently some companies seem willing to consider partially adjusting their personal data harvesting practices to the emerging legal landscape, at least in the EU. See e. g. , Sam Schechner, to for Ads in Europe, Journal (Aug. 1, 2023) In practical terms, the ongoing shift may amount to a massive drying up of the “data pipelines. ” Behavioral advertising might be the first area of the industry whose legal foundations may eventually collapse due to unanticipated legal shifts, as the recent EDBP and CJEU decisions seem to confirm. [SEP] Justify:

Output: The text contrasts the claim by discussing the vulnerabilities associated with personal data, particularly in the context of cyber-attacks and data breaches. It mentions that economic agents are already assessing the implications of legal issues arising from 'accidents' involving personal data, indicating that there are significant risks to the security of personal AI assistants.


Input: Task: pass the claim using the given text. Claim: Language can serve as a marker of identity and cultural heritage. [SEP] Text: 177553 Мозер Міхаель (Moser Michael), доктор габілітований, професор, Інститут славістики Віденського університету, Австрія (Universitätsring 1, Vienna, Austria 1010), Український Вільний Університет, Німеччина (Barellistraße 9A, München, Germany 80638), Католицький університет ім. Петера Пазманя, Угорщина (Szentkirályi utca, 28, Budapest, Hungary 1088). michael. moser@univie. ac. at Moser, M. (2017). Zur jüngsten Sprachensituation in der Ukraine (2012–2016). Hungaricae, 62/1, 171–196. DOI: 10. 1556/060. 2017. 62. 1. 14 2. Moser, M. (2015). Il ruolo di Ševčenko nella codificazione della lingua letteraria ucraina moderna. Studi Slavistici, 13, 265–278. DOI: 10. 13128/Studi-Slavis-17981 3. Moser, M. (2014). Behavior of during the Interwar Period. Russian Linguistics, 38, 315–339. DOI: 10. [SEP] Justify:

Output: The text provides biographical and publication information about an academic without any direct mention of how language functions as a marker of identity and cultural heritage. Therefore, it does not address the claim at all.