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Outgoing President Helen V. Milner chaired the plenary titled Globalization and Domestic Political Change. The four participants – Amaney Jamal , Edward Mansfield , Nita Rudra and Lourdes Sola – discussed the changes wrought by globalization in domestic politics (in the Middle East and North Africa, the United States, India and South America) and the impact of increased trade and foreign investment.

Outgoing President Helen V. Milner chaired the plenary titled Globalization and Domestic Political Change. The four participants – Amaney Jamal , Edward Mansfield , Nita Rudra and Lourdes Sola – discussed the changes wrought by globalization in domestic politics (in the Middle East and North Africa, the United States, India and South America) and the impact of increased trade and foreign investment.

Outgoing President Helen V. Milner chaired the plenary titled Globalization and Domestic Political Change. The four participants – Amaney Jamal , Edward Mansfield , Nita Rudra and Lourdes Sola – discussed the changes wrought by globalization in domestic politics (in the Middle East and North Africa, the United States, India and South America) and the impact of increased trade and foreign investment.

Outgoing President Helen V. Milner chaired the plenary titled Globalization and Domestic Political Change. The four participants – Amaney Jamal , Edward Mansfield , Nita Rudra and Lourdes Sola – discussed the changes wrought by globalization in domestic politics (in the Middle East and North Africa, the United States, India and South America) and the impact of increased trade and foreign investment.

This research project delves into a crucial aspect of our modern digital era: understanding how the mere perception of interacting with Artificial Intelligence (AI) influences people's attitudes, particularly regarding complex issues like globalization. At the heart of this study is the question: Does the attitudes that one is conversing with AI, rather than a human, lead to a more significant change in viewpoints? Globalization, a topic of broad and current interest, serves as the perfect backdrop for this investigation. It's an issue that has diverse and strong opinions, making it ideal for examining shifts in perspectives. Our focus is on how participants’ attitudes about their conversational partner (AI or human) can shape the outcomes of their discussions. We aim to uncover whether the perception of interacting with AI leads to more profound changes in attitudes compared to interactions assumed to be with humans. This inquiry is not just about understanding the impact of technology on conversation; it's about grasping the psychological effects of our perceptions of technology. The outcomes of this study have potential implications for policy development, and ethical standards in AI usage, and offer insights into the evolving role of technology in shaping public opinion on significant global matters. The key focus of this study is on a very important part of how people interact with AI: the tendency for people to believe and trust AI more, based on the idea that AI is naturally more trustworthy and knowledgeable than humans. If this turns out to be true, it's something that the whole world needs to pay attention to and talk about. It urges us to critically think about and possibly rethink who should be in control of developing and using AI. In this light, AI isn't just a piece of technology; it's a powerful tool that can change policies and shift what society believes. This makes it essential for governments, businesses, and nonprofit organizations to work together to set ethical rules for making and using AI. This kind of teamwork, involving different groups, makes sure that there's a balanced view, reducing risks while making the most of AI's potential to help society in good ways. Moving AI's management from being mainly about technology to being more about ethics and social responsibility is a big change, but it could be key in dealing with the complex ways AI affects our world. Main hypothesis: H1: Individuals will experience greater attitudes change when they perceive they are interacting with AI, regardless of whether the actual interaction is with AI or a human. Our main hypothesis posits that individuals are more likely to experience attitudes change when they perceive they are interacting with AI, rather than a human. This hypothesis is grounded in the unique characteristics attributed to AI, such as objectivity, neutrality, and the absence of human biases. Research by Sundar (2008) has highlighted the role of source orientation in shaping audience perceptions, suggesting that the perceived non-human nature of AI can make its content more persuasive. Similarly, studies by Nass and Moon (2000) indicate that users often interact with computers socially and ascribe human-like qualities to them, but without the complexity of human-human interaction dynamics. This interaction can lead to an altered processing of information, potentially facilitating more significant attitude changes. Mechanisms Proposed: AI Objectivity Hypothesis (Mediator): H2: Higher trust in AI technology, perceived expertise and objectivity of AI, and less emotional engagement will result in more significant attitude changes in interactions perceived as with AI. Trust in AI: Trust is a pivotal factor in technology acceptance and can influence the persuasiveness of AI (Lee & See, 2004). When people trust AI, they may be more inclined to accept and internalize the information presented. Perceived Expertise: The expertise ascribed to AI significantly affects its persuasiveness. The perception of AI as a knowledgeable entity, capable of processing vast amounts of data, lends it a level of credibility that can sway attitudes (Eagly & Chaiken, 1993). Perceived Objectivity: AI is often viewed as more objective and unbiased compared to humans. This perception of impartiality can make the information provided by AI seem more credible and persuasive (Riedl & Javor, 2012). Emotional Engagement: Emotional engagement can influence persuasion. The potentially lower emotional engagement in AI interactions could lead to a more analytical consideration of information, affecting attitude change (Petty & Cacioppo, 1986). Social Pressure Hypothesis (Moderator): H3: Reduced social co-presence and social anxiety, decreased levels of anthropomorphism, and lower unmitigated communion in perceived AI interactions will lead to greater attitude change. Social Cues and Pressure: The absence of traditional social cues and interpersonal pressure in AI interactions can create an environment more conducive to attitude change (Nass, Steuer, & Tauber, 1994). Anthropomorphism: Lower levels of anthropomorphism in AI interactions might facilitate attitude change, as it reduces the application of social heuristics and biases typical in human-human interactions (Epley, Waytz, & Cacioppo, 2007).

This research project delves into a crucial aspect of our modern digital era: understanding how the mere perception of interacting with Artificial Intelligence (AI) influences people's attitudes, particularly regarding complex issues like globalization. At the heart of this study is the question: Does the attitudes that one is conversing with AI, rather than a human, lead to a more significant change in viewpoints? Globalization, a topic of broad and current interest, serves as the perfect backdrop for this investigation. It's an issue that has diverse and strong opinions, making it ideal for examining shifts in perspectives. Our focus is on how participants’ attitudes about their conversational partner (AI or human) can shape the outcomes of their discussions. We aim to uncover whether the perception of interacting with AI leads to more profound changes in attitudes compared to interactions assumed to be with humans. This inquiry is not just about understanding the impact of technology on conversation; it's about grasping the psychological effects of our perceptions of technology. The outcomes of this study have potential implications for policy development, and ethical standards in AI usage, and offer insights into the evolving role of technology in shaping public opinion on significant global matters. The key focus of this study is on a very important part of how people interact with AI: the tendency for people to believe and trust AI more, based on the idea that AI is naturally more trustworthy and knowledgeable than humans. If this turns out to be true, it's something that the whole world needs to pay attention to and talk about. It urges us to critically think about and possibly rethink who should be in control of developing and using AI. In this light, AI isn't just a piece of technology; it's a powerful tool that can change policies and shift what society believes. This makes it essential for governments, businesses, and nonprofit organizations to work together to set ethical rules for making and using AI. This kind of teamwork, involving different groups, makes sure that there's a balanced view, reducing risks while making the most of AI's potential to help society in good ways. Moving AI's management from being mainly about technology to being more about ethics and social responsibility is a big change, but it could be key in dealing with the complex ways AI affects our world. Main hypothesis: H1: Individuals will experience greater attitudes change when they perceive they are interacting with AI, regardless of whether the actual interaction is with AI or a human. Our main hypothesis posits that individuals are more likely to experience attitudes change when they perceive they are interacting with AI, rather than a human. This hypothesis is grounded in the unique characteristics attributed to AI, such as objectivity, neutrality, and the absence of human biases. Research by Sundar (2008) has highlighted the role of source orientation in shaping audience perceptions, suggesting that the perceived non-human nature of AI can make its content more persuasive. Similarly, studies by Nass and Moon (2000) indicate that users often interact with computers socially and ascribe human-like qualities to them, but without the complexity of human-human interaction dynamics. This interaction can lead to an altered processing of information, potentially facilitating more significant attitude changes. Mechanisms Proposed: AI Objectivity Hypothesis (Mediator): H2: Higher trust in AI technology, perceived expertise and objectivity of AI, and less emotional engagement will result in more significant attitude changes in interactions perceived as with AI. Trust in AI: Trust is a pivotal factor in technology acceptance and can influence the persuasiveness of AI (Lee & See, 2004). When people trust AI, they may be more inclined to accept and internalize the information presented. Perceived Expertise: The expertise ascribed to AI significantly affects its persuasiveness. The perception of AI as a knowledgeable entity, capable of processing vast amounts of data, lends it a level of credibility that can sway attitudes (Eagly & Chaiken, 1993). Perceived Objectivity: AI is often viewed as more objective and unbiased compared to humans. This perception of impartiality can make the information provided by AI seem more credible and persuasive (Riedl & Javor, 2012). Emotional Engagement: Emotional engagement can influence persuasion. The potentially lower emotional engagement in AI interactions could lead to a more analytical consideration of information, affecting attitude change (Petty & Cacioppo, 1986). Social Pressure Hypothesis (Moderator): H3: Reduced social co-presence and social anxiety, decreased levels of anthropomorphism, and lower unmitigated communion in perceived AI interactions will lead to greater attitude change. Social Cues and Pressure: The absence of traditional social cues and interpersonal pressure in AI interactions can create an environment more conducive to attitude change (Nass, Steuer, & Tauber, 1994). Anthropomorphism: Lower levels of anthropomorphism in AI interactions might facilitate attitude change, as it reduces the application of social heuristics and biases typical in human-human interactions (Epley, Waytz, & Cacioppo, 2007).

This research project delves into a crucial aspect of our modern digital era: understanding how the mere perception of interacting with Artificial Intelligence (AI) influences people's attitudes, particularly regarding complex issues like globalization. At the heart of this study is the question: Does the attitudes that one is conversing with AI, rather than a human, lead to a more significant change in viewpoints? Globalization, a topic of broad and current interest, serves as the perfect backdrop for this investigation. It's an issue that has diverse and strong opinions, making it ideal for examining shifts in perspectives. Our focus is on how participants’ attitudes about their conversational partner (AI or human) can shape the outcomes of their discussions. We aim to uncover whether the perception of interacting with AI leads to more profound changes in attitudes compared to interactions assumed to be with humans. This inquiry is not just about understanding the impact of technology on conversation; it's about grasping the psychological effects of our perceptions of technology. The outcomes of this study have potential implications for policy development, and ethical standards in AI usage, and offer insights into the evolving role of technology in shaping public opinion on significant global matters. The key focus of this study is on a very important part of how people interact with AI: the tendency for people to believe and trust AI more, based on the idea that AI is naturally more trustworthy and knowledgeable than humans. If this turns out to be true, it's something that the whole world needs to pay attention to and talk about. It urges us to critically think about and possibly rethink who should be in control of developing and using AI. In this light, AI isn't just a piece of technology; it's a powerful tool that can change policies and shift what society believes. This makes it essential for governments, businesses, and nonprofit organizations to work together to set ethical rules for making and using AI. This kind of teamwork, involving different groups, makes sure that there's a balanced view, reducing risks while making the most of AI's potential to help society in good ways. Moving AI's management from being mainly about technology to being more about ethics and social responsibility is a big change, but it could be key in dealing with the complex ways AI affects our world. Main hypothesis: H1: Individuals will experience greater attitudes change when they perceive they are interacting with AI, regardless of whether the actual interaction is with AI or a human. Our main hypothesis posits that individuals are more likely to experience attitudes change when they perceive they are interacting with AI, rather than a human. This hypothesis is grounded in the unique characteristics attributed to AI, such as objectivity, neutrality, and the absence of human biases. Research by Sundar (2008) has highlighted the role of source orientation in shaping audience perceptions, suggesting that the perceived non-human nature of AI can make its content more persuasive. Similarly, studies by Nass and Moon (2000) indicate that users often interact with computers socially and ascribe human-like qualities to them, but without the complexity of human-human interaction dynamics. This interaction can lead to an altered processing of information, potentially facilitating more significant attitude changes. Mechanisms Proposed: AI Objectivity Hypothesis (Mediator): H2: Higher trust in AI technology, perceived expertise and objectivity of AI, and less emotional engagement will result in more significant attitude changes in interactions perceived as with AI. Trust in AI: Trust is a pivotal factor in technology acceptance and can influence the persuasiveness of AI (Lee & See, 2004). When people trust AI, they may be more inclined to accept and internalize the information presented. Perceived Expertise: The expertise ascribed to AI significantly affects its persuasiveness. The perception of AI as a knowledgeable entity, capable of processing vast amounts of data, lends it a level of credibility that can sway attitudes (Eagly & Chaiken, 1993). Perceived Objectivity: AI is often viewed as more objective and unbiased compared to humans. This perception of impartiality can make the information provided by AI seem more credible and persuasive (Riedl & Javor, 2012). Emotional Engagement: Emotional engagement can influence persuasion. The potentially lower emotional engagement in AI interactions could lead to a more analytical consideration of information, affecting attitude change (Petty & Cacioppo, 1986). Social Pressure Hypothesis (Moderator): H3: Reduced social co-presence and social anxiety, decreased levels of anthropomorphism, and lower unmitigated communion in perceived AI interactions will lead to greater attitude change. Social Cues and Pressure: The absence of traditional social cues and interpersonal pressure in AI interactions can create an environment more conducive to attitude change (Nass, Steuer, & Tauber, 1994). Anthropomorphism: Lower levels of anthropomorphism in AI interactions might facilitate attitude change, as it reduces the application of social heuristics and biases typical in human-human interactions (Epley, Waytz, & Cacioppo, 2007).

This research project delves into a crucial aspect of our modern digital era: understanding how the mere perception of interacting with Artificial Intelligence (AI) influences people's attitudes, particularly regarding complex issues like globalization. At the heart of this study is the question: Does the attitudes that one is conversing with AI, rather than a human, lead to a more significant change in viewpoints? Globalization, a topic of broad and current interest, serves as the perfect backdrop for this investigation. It's an issue that has diverse and strong opinions, making it ideal for examining shifts in perspectives. Our focus is on how participants’ attitudes about their conversational partner (AI or human) can shape the outcomes of their discussions. We aim to uncover whether the perception of interacting with AI leads to more profound changes in attitudes compared to interactions assumed to be with humans. This inquiry is not just about understanding the impact of technology on conversation; it's about grasping the psychological effects of our perceptions of technology. The outcomes of this study have potential implications for policy development, and ethical standards in AI usage, and offer insights into the evolving role of technology in shaping public opinion on significant global matters. The key focus of this study is on a very important part of how people interact with AI: the tendency for people to believe and trust AI more, based on the idea that AI is naturally more trustworthy and knowledgeable than humans. If this turns out to be true, it's something that the whole world needs to pay attention to and talk about. It urges us to critically think about and possibly rethink who should be in control of developing and using AI. In this light, AI isn't just a piece of technology; it's a powerful tool that can change policies and shift what society believes. This makes it essential for governments, businesses, and nonprofit organizations to work together to set ethical rules for making and using AI. This kind of teamwork, involving different groups, makes sure that there's a balanced view, reducing risks while making the most of AI's potential to help society in good ways. Moving AI's management from being mainly about technology to being more about ethics and social responsibility is a big change, but it could be key in dealing with the complex ways AI affects our world. Main hypothesis: H1: Individuals will experience greater attitudes change when they perceive they are interacting with AI, regardless of whether the actual interaction is with AI or a human. Our main hypothesis posits that individuals are more likely to experience attitudes change when they perceive they are interacting with AI, rather than a human. This hypothesis is grounded in the unique characteristics attributed to AI, such as objectivity, neutrality, and the absence of human biases. Research by Sundar (2008) has highlighted the role of source orientation in shaping audience perceptions, suggesting that the perceived non-human nature of AI can make its content more persuasive. Similarly, studies by Nass and Moon (2000) indicate that users often interact with computers socially and ascribe human-like qualities to them, but without the complexity of human-human interaction dynamics. This interaction can lead to an altered processing of information, potentially facilitating more significant attitude changes. Mechanisms Proposed: AI Objectivity Hypothesis (Mediator): H2: Higher trust in AI technology, perceived expertise and objectivity of AI, and less emotional engagement will result in more significant attitude changes in interactions perceived as with AI. Trust in AI: Trust is a pivotal factor in technology acceptance and can influence the persuasiveness of AI (Lee & See, 2004). When people trust AI, they may be more inclined to accept and internalize the information presented. Perceived Expertise: The expertise ascribed to AI significantly affects its persuasiveness. The perception of AI as a knowledgeable entity, capable of processing vast amounts of data, lends it a level of credibility that can sway attitudes (Eagly & Chaiken, 1993). Perceived Objectivity: AI is often viewed as more objective and unbiased compared to humans. This perception of impartiality can make the information provided by AI seem more credible and persuasive (Riedl & Javor, 2012). Emotional Engagement: Emotional engagement can influence persuasion. The potentially lower emotional engagement in AI interactions could lead to a more analytical consideration of information, affecting attitude change (Petty & Cacioppo, 1986). Social Pressure Hypothesis (Moderator): H3: Reduced social co-presence and social anxiety, decreased levels of anthropomorphism, and lower unmitigated communion in perceived AI interactions will lead to greater attitude change. Social Cues and Pressure: The absence of traditional social cues and interpersonal pressure in AI interactions can create an environment more conducive to attitude change (Nass, Steuer, & Tauber, 1994). Anthropomorphism: Lower levels of anthropomorphism in AI interactions might facilitate attitude change, as it reduces the application of social heuristics and biases typical in human-human interactions (Epley, Waytz, & Cacioppo, 2007).

This research project delves into a crucial aspect of our modern digital era: understanding how the mere perception of interacting with Artificial Intelligence (AI) influences people's attitudes, particularly regarding complex issues like globalization. At the heart of this study is the question: Does the attitudes that one is conversing with AI, rather than a human, lead to a more significant change in viewpoints? Globalization, a topic of broad and current interest, serves as the perfect backdrop for this investigation. It's an issue that has diverse and strong opinions, making it ideal for examining shifts in perspectives. Our focus is on how participants’ attitudes about their conversational partner (AI or human) can shape the outcomes of their discussions. We aim to uncover whether the perception of interacting with AI leads to more profound changes in attitudes compared to interactions assumed to be with humans. This inquiry is not just about understanding the impact of technology on conversation; it's about grasping the psychological effects of our perceptions of technology. The outcomes of this study have potential implications for policy development, and ethical standards in AI usage, and offer insights into the evolving role of technology in shaping public opinion on significant global matters. The key focus of this study is on a very important part of how people interact with AI: the tendency for people to believe and trust AI more, based on the idea that AI is naturally more trustworthy and knowledgeable than humans. If this turns out to be true, it's something that the whole world needs to pay attention to and talk about. It urges us to critically think about and possibly rethink who should be in control of developing and using AI. In this light, AI isn't just a piece of technology; it's a powerful tool that can change policies and shift what society believes. This makes it essential for governments, businesses, and nonprofit organizations to work together to set ethical rules for making and using AI. This kind of teamwork, involving different groups, makes sure that there's a balanced view, reducing risks while making the most of AI's potential to help society in good ways. Moving AI's management from being mainly about technology to being more about ethics and social responsibility is a big change, but it could be key in dealing with the complex ways AI affects our world. Main hypothesis: H1: Individuals will experience greater attitudes change when they perceive they are interacting with AI, regardless of whether the actual interaction is with AI or a human. Our main hypothesis posits that individuals are more likely to experience attitudes change when they perceive they are interacting with AI, rather than a human. This hypothesis is grounded in the unique characteristics attributed to AI, such as objectivity, neutrality, and the absence of human biases. Research by Sundar (2008) has highlighted the role of source orientation in shaping audience perceptions, suggesting that the perceived non-human nature of AI can make its content more persuasive. Similarly, studies by Nass and Moon (2000) indicate that users often interact with computers socially and ascribe human-like qualities to them, but without the complexity of human-human interaction dynamics. This interaction can lead to an altered processing of information, potentially facilitating more significant attitude changes. Mechanisms Proposed: AI Objectivity Hypothesis (Mediator): H2: Higher trust in AI technology, perceived expertise and objectivity of AI, and less emotional engagement will result in more significant attitude changes in interactions perceived as with AI. Trust in AI: Trust is a pivotal factor in technology acceptance and can influence the persuasiveness of AI (Lee & See, 2004). When people trust AI, they may be more inclined to accept and internalize the information presented. Perceived Expertise: The expertise ascribed to AI significantly affects its persuasiveness. The perception of AI as a knowledgeable entity, capable of processing vast amounts of data, lends it a level of credibility that can sway attitudes (Eagly & Chaiken, 1993). Perceived Objectivity: AI is often viewed as more objective and unbiased compared to humans. This perception of impartiality can make the information provided by AI seem more credible and persuasive (Riedl & Javor, 2012). Emotional Engagement: Emotional engagement can influence persuasion. The potentially lower emotional engagement in AI interactions could lead to a more analytical consideration of information, affecting attitude change (Petty & Cacioppo, 1986). Social Pressure Hypothesis (Moderator): H3: Reduced social co-presence and social anxiety, decreased levels of anthropomorphism, and lower unmitigated communion in perceived AI interactions will lead to greater attitude change. Social Cues and Pressure: The absence of traditional social cues and interpersonal pressure in AI interactions can create an environment more conducive to attitude change (Nass, Steuer, & Tauber, 1994). Anthropomorphism: Lower levels of anthropomorphism in AI interactions might facilitate attitude change, as it reduces the application of social heuristics and biases typical in human-human interactions (Epley, Waytz, & Cacioppo, 2007).

This research project delves into a crucial aspect of our modern digital era: understanding how the mere perception of interacting with Artificial Intelligence (AI) influences people's attitudes, particularly regarding complex issues like globalization. At the heart of this study is the question: Does the attitudes that one is conversing with AI, rather than a human, lead to a more significant change in viewpoints? Globalization, a topic of broad and current interest, serves as the perfect backdrop for this investigation. It's an issue that has diverse and strong opinions, making it ideal for examining shifts in perspectives. Our focus is on how participants’ attitudes about their conversational partner (AI or human) can shape the outcomes of their discussions. We aim to uncover whether the perception of interacting with AI leads to more profound changes in attitudes compared to interactions assumed to be with humans. This inquiry is not just about understanding the impact of technology on conversation; it's about grasping the psychological effects of our perceptions of technology. The outcomes of this study have potential implications for policy development, and ethical standards in AI usage, and offer insights into the evolving role of technology in shaping public opinion on significant global matters. The key focus of this study is on a very important part of how people interact with AI: the tendency for people to believe and trust AI more, based on the idea that AI is naturally more trustworthy and knowledgeable than humans. If this turns out to be true, it's something that the whole world needs to pay attention to and talk about. It urges us to critically think about and possibly rethink who should be in control of developing and using AI. In this light, AI isn't just a piece of technology; it's a powerful tool that can change policies and shift what society believes. This makes it essential for governments, businesses, and nonprofit organizations to work together to set ethical rules for making and using AI. This kind of teamwork, involving different groups, makes sure that there's a balanced view, reducing risks while making the most of AI's potential to help society in good ways. Moving AI's management from being mainly about technology to being more about ethics and social responsibility is a big change, but it could be key in dealing with the complex ways AI affects our world. Main hypothesis: H1: Individuals will experience greater attitudes change when they perceive they are interacting with AI, regardless of whether the actual interaction is with AI or a human. Our main hypothesis posits that individuals are more likely to experience attitudes change when they perceive they are interacting with AI, rather than a human. This hypothesis is grounded in the unique characteristics attributed to AI, such as objectivity, neutrality, and the absence of human biases. Research by Sundar (2008) has highlighted the role of source orientation in shaping audience perceptions, suggesting that the perceived non-human nature of AI can make its content more persuasive. Similarly, studies by Nass and Moon (2000) indicate that users often interact with computers socially and ascribe human-like qualities to them, but without the complexity of human-human interaction dynamics. This interaction can lead to an altered processing of information, potentially facilitating more significant attitude changes. Mechanisms Proposed: AI Objectivity Hypothesis (Mediator): H2: Higher trust in AI technology, perceived expertise and objectivity of AI, and less emotional engagement will result in more significant attitude changes in interactions perceived as with AI. Trust in AI: Trust is a pivotal factor in technology acceptance and can influence the persuasiveness of AI (Lee & See, 2004). When people trust AI, they may be more inclined to accept and internalize the information presented. Perceived Expertise: The expertise ascribed to AI significantly affects its persuasiveness. The perception of AI as a knowledgeable entity, capable of processing vast amounts of data, lends it a level of credibility that can sway attitudes (Eagly & Chaiken, 1993). Perceived Objectivity: AI is often viewed as more objective and unbiased compared to humans. This perception of impartiality can make the information provided by AI seem more credible and persuasive (Riedl & Javor, 2012). Emotional Engagement: Emotional engagement can influence persuasion. The potentially lower emotional engagement in AI interactions could lead to a more analytical consideration of information, affecting attitude change (Petty & Cacioppo, 1986). Social Pressure Hypothesis (Moderator): H3: Reduced social co-presence and social anxiety, decreased levels of anthropomorphism, and lower unmitigated communion in perceived AI interactions will lead to greater attitude change. Social Cues and Pressure: The absence of traditional social cues and interpersonal pressure in AI interactions can create an environment more conducive to attitude change (Nass, Steuer, & Tauber, 1994). Anthropomorphism: Lower levels of anthropomorphism in AI interactions might facilitate attitude change, as it reduces the application of social heuristics and biases typical in human-human interactions (Epley, Waytz, & Cacioppo, 2007).

This research project delves into a crucial aspect of our modern digital era: understanding how the mere perception of interacting with Artificial Intelligence (AI) influences people's attitudes, particularly regarding complex issues like globalization. At the heart of this study is the question: Does the attitudes that one is conversing with AI, rather than a human, lead to a more significant change in viewpoints? Globalization, a topic of broad and current interest, serves as the perfect backdrop for this investigation. It's an issue that has diverse and strong opinions, making it ideal for examining shifts in perspectives. Our focus is on how participants’ attitudes about their conversational partner (AI or human) can shape the outcomes of their discussions. We aim to uncover whether the perception of interacting with AI leads to more profound changes in attitudes compared to interactions assumed to be with humans. This inquiry is not just about understanding the impact of technology on conversation; it's about grasping the psychological effects of our perceptions of technology. The outcomes of this study have potential implications for policy development, and ethical standards in AI usage, and offer insights into the evolving role of technology in shaping public opinion on significant global matters. The key focus of this study is on a very important part of how people interact with AI: the tendency for people to believe and trust AI more, based on the idea that AI is naturally more trustworthy and knowledgeable than humans. If this turns out to be true, it's something that the whole world needs to pay attention to and talk about. It urges us to critically think about and possibly rethink who should be in control of developing and using AI. In this light, AI isn't just a piece of technology; it's a powerful tool that can change policies and shift what society believes. This makes it essential for governments, businesses, and nonprofit organizations to work together to set ethical rules for making and using AI. This kind of teamwork, involving different groups, makes sure that there's a balanced view, reducing risks while making the most of AI's potential to help society in good ways. Moving AI's management from being mainly about technology to being more about ethics and social responsibility is a big change, but it could be key in dealing with the complex ways AI affects our world. Main hypothesis: H1: Individuals will experience greater attitudes change when they perceive they are interacting with AI, regardless of whether the actual interaction is with AI or a human. Our main hypothesis posits that individuals are more likely to experience attitudes change when they perceive they are interacting with AI, rather than a human. This hypothesis is grounded in the unique characteristics attributed to AI, such as objectivity, neutrality, and the absence of human biases. Research by Sundar (2008) has highlighted the role of source orientation in shaping audience perceptions, suggesting that the perceived non-human nature of AI can make its content more persuasive. Similarly, studies by Nass and Moon (2000) indicate that users often interact with computers socially and ascribe human-like qualities to them, but without the complexity of human-human interaction dynamics. This interaction can lead to an altered processing of information, potentially facilitating more significant attitude changes. Mechanisms Proposed: AI Objectivity Hypothesis (Mediator): H2: Higher trust in AI technology, perceived expertise and objectivity of AI, and less emotional engagement will result in more significant attitude changes in interactions perceived as with AI. Trust in AI: Trust is a pivotal factor in technology acceptance and can influence the persuasiveness of AI (Lee & See, 2004). When people trust AI, they may be more inclined to accept and internalize the information presented. Perceived Expertise: The expertise ascribed to AI significantly affects its persuasiveness. The perception of AI as a knowledgeable entity, capable of processing vast amounts of data, lends it a level of credibility that can sway attitudes (Eagly & Chaiken, 1993). Perceived Objectivity: AI is often viewed as more objective and unbiased compared to humans. This perception of impartiality can make the information provided by AI seem more credible and persuasive (Riedl & Javor, 2012). Emotional Engagement: Emotional engagement can influence persuasion. The potentially lower emotional engagement in AI interactions could lead to a more analytical consideration of information, affecting attitude change (Petty & Cacioppo, 1986). Social Pressure Hypothesis (Moderator): H3: Reduced social co-presence and social anxiety, decreased levels of anthropomorphism, and lower unmitigated communion in perceived AI interactions will lead to greater attitude change. Social Cues and Pressure: The absence of traditional social cues and interpersonal pressure in AI interactions can create an environment more conducive to attitude change (Nass, Steuer, & Tauber, 1994). Anthropomorphism: Lower levels of anthropomorphism in AI interactions might facilitate attitude change, as it reduces the application of social heuristics and biases typical in human-human interactions (Epley, Waytz, & Cacioppo, 2007).

This research project delves into a crucial aspect of our modern digital era: understanding how the mere perception of interacting with Artificial Intelligence (AI) influences people's attitudes, particularly regarding complex issues like globalization. At the heart of this study is the question: Does the attitudes that one is conversing with AI, rather than a human, lead to a more significant change in viewpoints? Globalization, a topic of broad and current interest, serves as the perfect backdrop for this investigation. It's an issue that has diverse and strong opinions, making it ideal for examining shifts in perspectives. Our focus is on how participants’ attitudes about their conversational partner (AI or human) can shape the outcomes of their discussions. We aim to uncover whether the perception of interacting with AI leads to more profound changes in attitudes compared to interactions assumed to be with humans. This inquiry is not just about understanding the impact of technology on conversation; it's about grasping the psychological effects of our perceptions of technology. The outcomes of this study have potential implications for policy development, and ethical standards in AI usage, and offer insights into the evolving role of technology in shaping public opinion on significant global matters. The key focus of this study is on a very important part of how people interact with AI: the tendency for people to believe and trust AI more, based on the idea that AI is naturally more trustworthy and knowledgeable than humans. If this turns out to be true, it's something that the whole world needs to pay attention to and talk about. It urges us to critically think about and possibly rethink who should be in control of developing and using AI. In this light, AI isn't just a piece of technology; it's a powerful tool that can change policies and shift what society believes. This makes it essential for governments, businesses, and nonprofit organizations to work together to set ethical rules for making and using AI. This kind of teamwork, involving different groups, makes sure that there's a balanced view, reducing risks while making the most of AI's potential to help society in good ways. Moving AI's management from being mainly about technology to being more about ethics and social responsibility is a big change, but it could be key in dealing with the complex ways AI affects our world. Main hypothesis: H1: Individuals will experience greater attitudes change when they perceive they are interacting with AI, regardless of whether the actual interaction is with AI or a human. Our main hypothesis posits that individuals are more likely to experience attitudes change when they perceive they are interacting with AI, rather than a human. This hypothesis is grounded in the unique characteristics attributed to AI, such as objectivity, neutrality, and the absence of human biases. Research by Sundar (2008) has highlighted the role of source orientation in shaping audience perceptions, suggesting that the perceived non-human nature of AI can make its content more persuasive. Similarly, studies by Nass and Moon (2000) indicate that users often interact with computers socially and ascribe human-like qualities to them, but without the complexity of human-human interaction dynamics. This interaction can lead to an altered processing of information, potentially facilitating more significant attitude changes. Mechanisms Proposed: AI Objectivity Hypothesis (Mediator): H2: Higher trust in AI technology, perceived expertise and objectivity of AI, and less emotional engagement will result in more significant attitude changes in interactions perceived as with AI. Trust in AI: Trust is a pivotal factor in technology acceptance and can influence the persuasiveness of AI (Lee & See, 2004). When people trust AI, they may be more inclined to accept and internalize the information presented. Perceived Expertise: The expertise ascribed to AI significantly affects its persuasiveness. The perception of AI as a knowledgeable entity, capable of processing vast amounts of data, lends it a level of credibility that can sway attitudes (Eagly & Chaiken, 1993). Perceived Objectivity: AI is often viewed as more objective and unbiased compared to humans. This perception of impartiality can make the information provided by AI seem more credible and persuasive (Riedl & Javor, 2012). Emotional Engagement: Emotional engagement can influence persuasion. The potentially lower emotional engagement in AI interactions could lead to a more analytical consideration of information, affecting attitude change (Petty & Cacioppo, 1986). Social Pressure Hypothesis (Moderator): H3: Reduced social co-presence and social anxiety, decreased levels of anthropomorphism, and lower unmitigated communion in perceived AI interactions will lead to greater attitude change. Social Cues and Pressure: The absence of traditional social cues and interpersonal pressure in AI interactions can create an environment more conducive to attitude change (Nass, Steuer, & Tauber, 1994). Anthropomorphism: Lower levels of anthropomorphism in AI interactions might facilitate attitude change, as it reduces the application of social heuristics and biases typical in human-human interactions (Epley, Waytz, & Cacioppo, 2007).

This research project delves into a crucial aspect of our modern digital era: understanding how the mere perception of interacting with Artificial Intelligence (AI) influences people's attitudes, particularly regarding complex issues like globalization. At the heart of this study is the question: Does the attitudes that one is conversing with AI, rather than a human, lead to a more significant change in viewpoints? Globalization, a topic of broad and current interest, serves as the perfect backdrop for this investigation. It's an issue that has diverse and strong opinions, making it ideal for examining shifts in perspectives. Our focus is on how participants’ attitudes about their conversational partner (AI or human) can shape the outcomes of their discussions. We aim to uncover whether the perception of interacting with AI leads to more profound changes in attitudes compared to interactions assumed to be with humans. This inquiry is not just about understanding the impact of technology on conversation; it's about grasping the psychological effects of our perceptions of technology. The outcomes of this study have potential implications for policy development, and ethical standards in AI usage, and offer insights into the evolving role of technology in shaping public opinion on significant global matters. The key focus of this study is on a very important part of how people interact with AI: the tendency for people to believe and trust AI more, based on the idea that AI is naturally more trustworthy and knowledgeable than humans. If this turns out to be true, it's something that the whole world needs to pay attention to and talk about. It urges us to critically think about and possibly rethink who should be in control of developing and using AI. In this light, AI isn't just a piece of technology; it's a powerful tool that can change policies and shift what society believes. This makes it essential for governments, businesses, and nonprofit organizations to work together to set ethical rules for making and using AI. This kind of teamwork, involving different groups, makes sure that there's a balanced view, reducing risks while making the most of AI's potential to help society in good ways. Moving AI's management from being mainly about technology to being more about ethics and social responsibility is a big change, but it could be key in dealing with the complex ways AI affects our world. Main hypothesis: H1: Individuals will experience greater attitudes change when they perceive they are interacting with AI, regardless of whether the actual interaction is with AI or a human. Our main hypothesis posits that individuals are more likely to experience attitudes change when they perceive they are interacting with AI, rather than a human. This hypothesis is grounded in the unique characteristics attributed to AI, such as objectivity, neutrality, and the absence of human biases. Research by Sundar (2008) has highlighted the role of source orientation in shaping audience perceptions, suggesting that the perceived non-human nature of AI can make its content more persuasive. Similarly, studies by Nass and Moon (2000) indicate that users often interact with computers socially and ascribe human-like qualities to them, but without the complexity of human-human interaction dynamics. This interaction can lead to an altered processing of information, potentially facilitating more significant attitude changes. Mechanisms Proposed: AI Objectivity Hypothesis (Mediator): H2: Higher trust in AI technology, perceived expertise and objectivity of AI, and less emotional engagement will result in more significant attitude changes in interactions perceived as with AI. Trust in AI: Trust is a pivotal factor in technology acceptance and can influence the persuasiveness of AI (Lee & See, 2004). When people trust AI, they may be more inclined to accept and internalize the information presented. Perceived Expertise: The expertise ascribed to AI significantly affects its persuasiveness. The perception of AI as a knowledgeable entity, capable of processing vast amounts of data, lends it a level of credibility that can sway attitudes (Eagly & Chaiken, 1993). Perceived Objectivity: AI is often viewed as more objective and unbiased compared to humans. This perception of impartiality can make the information provided by AI seem more credible and persuasive (Riedl & Javor, 2012). Emotional Engagement: Emotional engagement can influence persuasion. The potentially lower emotional engagement in AI interactions could lead to a more analytical consideration of information, affecting attitude change (Petty & Cacioppo, 1986). Social Pressure Hypothesis (Moderator): H3: Reduced social co-presence and social anxiety, decreased levels of anthropomorphism, and lower unmitigated communion in perceived AI interactions will lead to greater attitude change. Social Cues and Pressure: The absence of traditional social cues and interpersonal pressure in AI interactions can create an environment more conducive to attitude change (Nass, Steuer, & Tauber, 1994). Anthropomorphism: Lower levels of anthropomorphism in AI interactions might facilitate attitude change, as it reduces the application of social heuristics and biases typical in human-human interactions (Epley, Waytz, & Cacioppo, 2007).

This research project delves into a crucial aspect of our modern digital era: understanding how the mere perception of interacting with Artificial Intelligence (AI) influences people's attitudes, particularly regarding complex issues like globalization. At the heart of this study is the question: Does the attitudes that one is conversing with AI, rather than a human, lead to a more significant change in viewpoints? Globalization, a topic of broad and current interest, serves as the perfect backdrop for this investigation. It's an issue that has diverse and strong opinions, making it ideal for examining shifts in perspectives. Our focus is on how participants’ attitudes about their conversational partner (AI or human) can shape the outcomes of their discussions. We aim to uncover whether the perception of interacting with AI leads to more profound changes in attitudes compared to interactions assumed to be with humans. This inquiry is not just about understanding the impact of technology on conversation; it's about grasping the psychological effects of our perceptions of technology. The outcomes of this study have potential implications for policy development, and ethical standards in AI usage, and offer insights into the evolving role of technology in shaping public opinion on significant global matters. The key focus of this study is on a very important part of how people interact with AI: the tendency for people to believe and trust AI more, based on the idea that AI is naturally more trustworthy and knowledgeable than humans. If this turns out to be true, it's something that the whole world needs to pay attention to and talk about. It urges us to critically think about and possibly rethink who should be in control of developing and using AI. In this light, AI isn't just a piece of technology; it's a powerful tool that can change policies and shift what society believes. This makes it essential for governments, businesses, and nonprofit organizations to work together to set ethical rules for making and using AI. This kind of teamwork, involving different groups, makes sure that there's a balanced view, reducing risks while making the most of AI's potential to help society in good ways. Moving AI's management from being mainly about technology to being more about ethics and social responsibility is a big change, but it could be key in dealing with the complex ways AI affects our world. Main hypothesis: H1: Individuals will experience greater attitudes change when they perceive they are interacting with AI, regardless of whether the actual interaction is with AI or a human. Our main hypothesis posits that individuals are more likely to experience attitudes change when they perceive they are interacting with AI, rather than a human. This hypothesis is grounded in the unique characteristics attributed to AI, such as objectivity, neutrality, and the absence of human biases. Research by Sundar (2008) has highlighted the role of source orientation in shaping audience perceptions, suggesting that the perceived non-human nature of AI can make its content more persuasive. Similarly, studies by Nass and Moon (2000) indicate that users often interact with computers socially and ascribe human-like qualities to them, but without the complexity of human-human interaction dynamics. This interaction can lead to an altered processing of information, potentially facilitating more significant attitude changes. Mechanisms Proposed: AI Objectivity Hypothesis (Mediator): H2: Higher trust in AI technology, perceived expertise and objectivity of AI, and less emotional engagement will result in more significant attitude changes in interactions perceived as with AI. Trust in AI: Trust is a pivotal factor in technology acceptance and can influence the persuasiveness of AI (Lee & See, 2004). When people trust AI, they may be more inclined to accept and internalize the information presented. Perceived Expertise: The expertise ascribed to AI significantly affects its persuasiveness. The perception of AI as a knowledgeable entity, capable of processing vast amounts of data, lends it a level of credibility that can sway attitudes (Eagly & Chaiken, 1993). Perceived Objectivity: AI is often viewed as more objective and unbiased compared to humans. This perception of impartiality can make the information provided by AI seem more credible and persuasive (Riedl & Javor, 2012). Emotional Engagement: Emotional engagement can influence persuasion. The potentially lower emotional engagement in AI interactions could lead to a more analytical consideration of information, affecting attitude change (Petty & Cacioppo, 1986). Social Pressure Hypothesis (Moderator): H3: Reduced social co-presence and social anxiety, decreased levels of anthropomorphism, and lower unmitigated communion in perceived AI interactions will lead to greater attitude change. Social Cues and Pressure: The absence of traditional social cues and interpersonal pressure in AI interactions can create an environment more conducive to attitude change (Nass, Steuer, & Tauber, 1994). Anthropomorphism: Lower levels of anthropomorphism in AI interactions might facilitate attitude change, as it reduces the application of social heuristics and biases typical in human-human interactions (Epley, Waytz, & Cacioppo, 2007).

This research project delves into a crucial aspect of our modern digital era: understanding how the mere perception of interacting with Artificial Intelligence (AI) influences people's attitudes, particularly regarding complex issues like globalization. At the heart of this study is the question: Does the attitudes that one is conversing with AI, rather than a human, lead to a more significant change in viewpoints? Globalization, a topic of broad and current interest, serves as the perfect backdrop for this investigation. It's an issue that has diverse and strong opinions, making it ideal for examining shifts in perspectives. Our focus is on how participants’ attitudes about their conversational partner (AI or human) can shape the outcomes of their discussions. We aim to uncover whether the perception of interacting with AI leads to more profound changes in attitudes compared to interactions assumed to be with humans. This inquiry is not just about understanding the impact of technology on conversation; it's about grasping the psychological effects of our perceptions of technology. The outcomes of this study have potential implications for policy development, and ethical standards in AI usage, and offer insights into the evolving role of technology in shaping public opinion on significant global matters. The key focus of this study is on a very important part of how people interact with AI: the tendency for people to believe and trust AI more, based on the idea that AI is naturally more trustworthy and knowledgeable than humans. If this turns out to be true, it's something that the whole world needs to pay attention to and talk about. It urges us to critically think about and possibly rethink who should be in control of developing and using AI. In this light, AI isn't just a piece of technology; it's a powerful tool that can change policies and shift what society believes. This makes it essential for governments, businesses, and nonprofit organizations to work together to set ethical rules for making and using AI. This kind of teamwork, involving different groups, makes sure that there's a balanced view, reducing risks while making the most of AI's potential to help society in good ways. Moving AI's management from being mainly about technology to being more about ethics and social responsibility is a big change, but it could be key in dealing with the complex ways AI affects our world. Main hypothesis: H1: Individuals will experience greater attitudes change when they perceive they are interacting with AI, regardless of whether the actual interaction is with AI or a human. Our main hypothesis posits that individuals are more likely to experience attitudes change when they perceive they are interacting with AI, rather than a human. This hypothesis is grounded in the unique characteristics attributed to AI, such as objectivity, neutrality, and the absence of human biases. Research by Sundar (2008) has highlighted the role of source orientation in shaping audience perceptions, suggesting that the perceived non-human nature of AI can make its content more persuasive. Similarly, studies by Nass and Moon (2000) indicate that users often interact with computers socially and ascribe human-like qualities to them, but without the complexity of human-human interaction dynamics. This interaction can lead to an altered processing of information, potentially facilitating more significant attitude changes. Mechanisms Proposed: AI Objectivity Hypothesis (Mediator): H2: Higher trust in AI technology, perceived expertise and objectivity of AI, and less emotional engagement will result in more significant attitude changes in interactions perceived as with AI. Trust in AI: Trust is a pivotal factor in technology acceptance and can influence the persuasiveness of AI (Lee & See, 2004). When people trust AI, they may be more inclined to accept and internalize the information presented. Perceived Expertise: The expertise ascribed to AI significantly affects its persuasiveness. The perception of AI as a knowledgeable entity, capable of processing vast amounts of data, lends it a level of credibility that can sway attitudes (Eagly & Chaiken, 1993). Perceived Objectivity: AI is often viewed as more objective and unbiased compared to humans. This perception of impartiality can make the information provided by AI seem more credible and persuasive (Riedl & Javor, 2012). Emotional Engagement: Emotional engagement can influence persuasion. The potentially lower emotional engagement in AI interactions could lead to a more analytical consideration of information, affecting attitude change (Petty & Cacioppo, 1986). Social Pressure Hypothesis (Moderator): H3: Reduced social co-presence and social anxiety, decreased levels of anthropomorphism, and lower unmitigated communion in perceived AI interactions will lead to greater attitude change. Social Cues and Pressure: The absence of traditional social cues and interpersonal pressure in AI interactions can create an environment more conducive to attitude change (Nass, Steuer, & Tauber, 1994). Anthropomorphism: Lower levels of anthropomorphism in AI interactions might facilitate attitude change, as it reduces the application of social heuristics and biases typical in human-human interactions (Epley, Waytz, & Cacioppo, 2007).

Trends and shocks subjects continue to receive a lot of attention. In October 2007, Al Gore and the Intergovernmental Panel on Climate Change (IPCC) received the Nobel Prize for their work on climate change. On Nov. 17, 2007, the IPCC released its latest report conclusively documenting climate change. In the last issue of Defense AT and L, I presented a variety of cyberspace, energy, and resources trends and shocks that will impact the acquisition community. In this article, I address further future impacts to acquisition arising from trends and shocks emanating from changes in climate, demographics, technology, and globalization. History is replete with examples of unexpected events that startled and surprised people and countries and that drove change throughout time. Our goals are to keep from being surprised and to take note of todays trends in order to avoid or mitigate any adverse impacts to acquisition.

Trends and shocks subjects continue to receive a lot of attention. In October 2007, Al Gore and the Intergovernmental Panel on Climate Change (IPCC) received the Nobel Prize for their work on climate change. On Nov. 17, 2007, the IPCC released its latest report conclusively documenting climate change. In the last issue of Defense AT and L, I presented a variety of cyberspace, energy, and resources trends and shocks that will impact the acquisition community. In this article, I address further future impacts to acquisition arising from trends and shocks emanating from changes in climate, demographics, technology, and globalization. History is replete with examples of unexpected events that startled and surprised people and countries and that drove change throughout time. Our goals are to keep from being surprised and to take note of todays trends in order to avoid or mitigate any adverse impacts to acquisition.

Trends and shocks subjects continue to receive a lot of attention. In October 2007, Al Gore and the Intergovernmental Panel on Climate Change (IPCC) received the Nobel Prize for their work on climate change. On Nov. 17, 2007, the IPCC released its latest report conclusively documenting climate change. In the last issue of Defense AT and L, I presented a variety of cyberspace, energy, and resources trends and shocks that will impact the acquisition community. In this article, I address further future impacts to acquisition arising from trends and shocks emanating from changes in climate, demographics, technology, and globalization. History is replete with examples of unexpected events that startled and surprised people and countries and that drove change throughout time. Our goals are to keep from being surprised and to take note of todays trends in order to avoid or mitigate any adverse impacts to acquisition.

Trends and shocks subjects continue to receive a lot of attention. In October 2007, Al Gore and the Intergovernmental Panel on Climate Change (IPCC) received the Nobel Prize for their work on climate change. On Nov. 17, 2007, the IPCC released its latest report conclusively documenting climate change. In the last issue of Defense AT and L, I presented a variety of cyberspace, energy, and resources trends and shocks that will impact the acquisition community. In this article, I address further future impacts to acquisition arising from trends and shocks emanating from changes in climate, demographics, technology, and globalization. History is replete with examples of unexpected events that startled and surprised people and countries and that drove change throughout time. Our goals are to keep from being surprised and to take note of todays trends in order to avoid or mitigate any adverse impacts to acquisition.

Trends and shocks subjects continue to receive a lot of attention. In October 2007, Al Gore and the Intergovernmental Panel on Climate Change (IPCC) received the Nobel Prize for their work on climate change. On Nov. 17, 2007, the IPCC released its latest report conclusively documenting climate change. In the last issue of Defense AT and L, I presented a variety of cyberspace, energy, and resources trends and shocks that will impact the acquisition community. In this article, I address further future impacts to acquisition arising from trends and shocks emanating from changes in climate, demographics, technology, and globalization. History is replete with examples of unexpected events that startled and surprised people and countries and that drove change throughout time. Our goals are to keep from being surprised and to take note of todays trends in order to avoid or mitigate any adverse impacts to acquisition.

Trends and shocks subjects continue to receive a lot of attention. In October 2007, Al Gore and the Intergovernmental Panel on Climate Change (IPCC) received the Nobel Prize for their work on climate change. On Nov. 17, 2007, the IPCC released its latest report conclusively documenting climate change. In the last issue of Defense AT and L, I presented a variety of cyberspace, energy, and resources trends and shocks that will impact the acquisition community. In this article, I address further future impacts to acquisition arising from trends and shocks emanating from changes in climate, demographics, technology, and globalization. History is replete with examples of unexpected events that startled and surprised people and countries and that drove change throughout time. Our goals are to keep from being surprised and to take note of todays trends in order to avoid or mitigate any adverse impacts to acquisition.

Globalization, automation, and rapid technological change have been a net positive for the world, but not for everyone. We need to invest in communities and workers who have been left behind. #Tech #artificialintelligence #CNNTownHall #SXSW #CNNSXSW #Delaney2020 https://t.co/Ad9PLjKXe5 Source: https://twitter.com/JohnDelaney/status/1104887328567422978 Uploader: John Delaney

Globalization, automation, and rapid technological change have been a net positive for the world, but not for everyone. We need to invest in communities and workers who have been left behind. #Tech #artificialintelligence #CNNTownHall #SXSW #CNNSXSW #Delaney2020 https://t.co/Ad9PLjKXe5 Source: https://twitter.com/JohnDelaney/status/1104887328567422978 Uploader: John Delaney

Background: Excess body weight and metabolic comorbidities represent a risk for the emergence of chronic diseases and premature deaths, a growing phenomenon observed in riverside communities in the Amazon. Methods: The study developed was a descriptive and analytical cohort of the risk factors predisposing to excess body weight in communities of the Tapajós valley region exposed to mercurial contamination. The sample population includes 130 adult individuals from Barreiras and 80 from São Luiz do Tapajós, of both sexes, who agreed to participate in this study. A semi-structured questionnaire was applied to obtain epidemiological and nutritional information, and validated conventional methods were used to evaluate the anthropometric parameters. Results: Total mercury in hair was measured using the atomic absorption spectrometry technique. In both communities, the prevalence of overweight was 60%, and abdominal adiposity among these individuals was higher than in those without overweight. The consumption of fish in the overweight and eutrophic groups in the inhabitants of the community of São Luiz do Tapajós differed, as well as and the average levels of mercury in the hair were higher in those who were overweight. However, this association was not observed in the community of Barreiras, where about approximately 61% of individuals, regardless of body weight, consumed little fish and in turn had low average levels of mercury in their hair. Conclusions: The evidence indicates changes in the eating habits of the studied communities, determining a nutritional imbalance through an increasing body weight gain among individuals, high BMI, and consequently the measurement of abdominal adiposity, which are factors for non-transmissible chronic diseases. Moreover, not only the excessive caloric intake and sedentary lifestyle, but also it is note, that mercurial toxicity must have contributed to affect affecting endocrine homeostasis and the physiology of metabolism; and, therefore, it is essential to seek appropriate interventions to combat public health diseases in communities exposed to mercurial contamination.

Background: Excess body weight and metabolic comorbidities represent a risk for the emergence of chronic diseases and premature deaths, a growing phenomenon observed in riverside communities in the Amazon. Methods: The study developed was a descriptive and analytical cohort of the risk factors predisposing to excess body weight in communities of the Tapajós valley region exposed to mercurial contamination. The sample population includes 130 adult individuals from Barreiras and 80 from São Luiz do Tapajós, of both sexes, who agreed to participate in this study. A semi-structured questionnaire was applied to obtain epidemiological and nutritional information, and validated conventional methods were used to evaluate the anthropometric parameters. Results: Total mercury in hair was measured using the atomic absorption spectrometry technique. In both communities, the prevalence of overweight was 60%, and abdominal adiposity among these individuals was higher than in those without overweight. The consumption of fish in the overweight and eutrophic groups in the inhabitants of the community of São Luiz do Tapajós differed, as well as and the average levels of mercury in the hair were higher in those who were overweight. However, this association was not observed in the community of Barreiras, where about approximately 61% of individuals, regardless of body weight, consumed little fish and in turn had low average levels of mercury in their hair. Conclusions: The evidence indicates changes in the eating habits of the studied communities, determining a nutritional imbalance through an increasing body weight gain among individuals, high BMI, and consequently the measurement of abdominal adiposity, which are factors for non-transmissible chronic diseases. Moreover, not only the excessive caloric intake and sedentary lifestyle, but also it is note, that mercurial toxicity must have contributed to affect affecting endocrine homeostasis and the physiology of metabolism; and, therefore, it is essential to seek appropriate interventions to combat public health diseases in communities exposed to mercurial contamination.

Includes bibliographical references and index

Includes bibliographical references and index

Includes bibliographical references and index

Includes bibliographical references and index

Includes bibliographical references and index

Includes bibliographical references and index

Rapid change has faced, information technology and communications world in the last two decades of the new type of illiteracy, failure to comply with the growth of the doctrine of technology on the one hand and lack of attention to retraining and learning. Traditional methods, educational structures, policies and governing policies and implementations objectives governing this issue as a cultural phenomenon, no longer massive volume of demand for education is not responsive and necessary than of the government is faced with this problem, how can the different sectors of society with the transformation of the educational need. It is important that policies that literacy is part of the culture of each country have formulated policies, which uses different parts of culture and cultural diversity of the lands is written and the synergies necessary for the growth of literacy in society and move towards balanced development to occur and cultural of diseases caused by the global growth of literacy and lack of coordination with different cultures prevent these teachings. This paper, based on the policy objectives of literacy, the dynamics of education, culture and politics and its effects, globalization, education and cultural policies of governments, review modeling literacy policy based on cultural diversity and change and increased participation of all society.

Rapid change has faced, information technology and communications world in the last two decades of the new type of illiteracy, failure to comply with the growth of the doctrine of technology on the one hand and lack of attention to retraining and learning. Traditional methods, educational structures, policies and governing policies and implementations objectives governing this issue as a cultural phenomenon, no longer massive volume of demand for education is not responsive and necessary than of the government is faced with this problem, how can the different sectors of society with the transformation of the educational need. It is important that policies that literacy is part of the culture of each country have formulated policies, which uses different parts of culture and cultural diversity of the lands is written and the synergies necessary for the growth of literacy in society and move towards balanced development to occur and cultural of diseases caused by the global growth of literacy and lack of coordination with different cultures prevent these teachings. This paper, based on the policy objectives of literacy, the dynamics of education, culture and politics and its effects, globalization, education and cultural policies of governments, review modeling literacy policy based on cultural diversity and change and increased participation of all society.

Rapid change has faced, information technology and communications world in the last two decades of the new type of illiteracy, failure to comply with the growth of the doctrine of technology on the one hand and lack of attention to retraining and learning. Traditional methods, educational structures, policies and governing policies and implementations objectives governing this issue as a cultural phenomenon, no longer massive volume of demand for education is not responsive and necessary than of the government is faced with this problem, how can the different sectors of society with the transformation of the educational need. It is important that policies that literacy is part of the culture of each country have formulated policies, which uses different parts of culture and cultural diversity of the lands is written and the synergies necessary for the growth of literacy in society and move towards balanced development to occur and cultural of diseases caused by the global growth of literacy and lack of coordination with different cultures prevent these teachings. This paper, based on the policy objectives of literacy, the dynamics of education, culture and politics and its effects, globalization, education and cultural policies of governments, review modeling literacy policy based on cultural diversity and change and increased participation of all society.

Rapid change has faced, information technology and communications world in the last two decades of the new type of illiteracy, failure to comply with the growth of the doctrine of technology on the one hand and lack of attention to retraining and learning. Traditional methods, educational structures, policies and governing policies and implementations objectives governing this issue as a cultural phenomenon, no longer massive volume of demand for education is not responsive and necessary than of the government is faced with this problem, how can the different sectors of society with the transformation of the educational need. It is important that policies that literacy is part of the culture of each country have formulated policies, which uses different parts of culture and cultural diversity of the lands is written and the synergies necessary for the growth of literacy in society and move towards balanced development to occur and cultural of diseases caused by the global growth of literacy and lack of coordination with different cultures prevent these teachings. This paper, based on the policy objectives of literacy, the dynamics of education, culture and politics and its effects, globalization, education and cultural policies of governments, review modeling literacy policy based on cultural diversity and change and increased participation of all society.

Rapid change has faced, information technology and communications world in the last two decades of the new type of illiteracy, failure to comply with the growth of the doctrine of technology on the one hand and lack of attention to retraining and learning. Traditional methods, educational structures, policies and governing policies and implementations objectives governing this issue as a cultural phenomenon, no longer massive volume of demand for education is not responsive and necessary than of the government is faced with this problem, how can the different sectors of society with the transformation of the educational need. It is important that policies that literacy is part of the culture of each country have formulated policies, which uses different parts of culture and cultural diversity of the lands is written and the synergies necessary for the growth of literacy in society and move towards balanced development to occur and cultural of diseases caused by the global growth of literacy and lack of coordination with different cultures prevent these teachings. This paper, based on the policy objectives of literacy, the dynamics of education, culture and politics and its effects, globalization, education and cultural policies of governments, review modeling literacy policy based on cultural diversity and change and increased participation of all society.

Rapid change has faced, information technology and communications world in the last two decades of the new type of illiteracy, failure to comply with the growth of the doctrine of technology on the one hand and lack of attention to retraining and learning. Traditional methods, educational structures, policies and governing policies and implementations objectives governing this issue as a cultural phenomenon, no longer massive volume of demand for education is not responsive and necessary than of the government is faced with this problem, how can the different sectors of society with the transformation of the educational need. It is important that policies that literacy is part of the culture of each country have formulated policies, which uses different parts of culture and cultural diversity of the lands is written and the synergies necessary for the growth of literacy in society and move towards balanced development to occur and cultural of diseases caused by the global growth of literacy and lack of coordination with different cultures prevent these teachings. This paper, based on the policy objectives of literacy, the dynamics of education, culture and politics and its effects, globalization, education and cultural policies of governments, review modeling literacy policy based on cultural diversity and change and increased participation of all society.

2019-04-02 Geo-Economics and Geo-Politics Drive Successive Eras of Predatory Globalization and Social Engineering - Historical emergence of climate change gender equity and anti-racism as State doctrines __ Reader View

2019-04-02 Geo-Economics and Geo-Politics Drive Successive Eras of Predatory Globalization and Social Engineering - Historical emergence of climate change gender equity and anti-racism as State doctrines __ Reader View

2019-04-02 Geo-Economics and Geo-Politics Drive Successive Eras of Predatory Globalization and Social Engineering - Historical emergence of climate change gender equity and anti-racism as State doctrines __ Reader View

2019-04-02 Geo-Economics and Geo-Politics Drive Successive Eras of Predatory Globalization and Social Engineering - Historical emergence of climate change gender equity and anti-racism as State doctrines __ Reader View

2019-04-02 Geo-Economics and Geo-Politics Drive Successive Eras of Predatory Globalization and Social Engineering - Historical emergence of climate change gender equity and anti-racism as State doctrines __ Reader View

2019-04-02 Geo-Economics and Geo-Politics Drive Successive Eras of Predatory Globalization and Social Engineering - Historical emergence of climate change gender equity and anti-racism as State doctrines __ Reader View

Mixtec Evangelicals: Globalization, Migration, and Religious Change in a Oaxacan Indigenous Group https://openresearchlibrary.org/content/168e72c9-4f95-4dcd-8179-b3dac28b0e53

Mixtec Evangelicals: Globalization, Migration, and Religious Change in a Oaxacan Indigenous Group https://openresearchlibrary.org/content/168e72c9-4f95-4dcd-8179-b3dac28b0e53

Mixtec Evangelicals: Globalization, Migration, and Religious Change in a Oaxacan Indigenous Group https://openresearchlibrary.org/content/168e72c9-4f95-4dcd-8179-b3dac28b0e53

Mixtec Evangelicals: Globalization, Migration, and Religious Change in a Oaxacan Indigenous Group https://openresearchlibrary.org/content/168e72c9-4f95-4dcd-8179-b3dac28b0e53

Mixtec Evangelicals: Globalization, Migration, and Religious Change in a Oaxacan Indigenous Group https://openresearchlibrary.org/content/168e72c9-4f95-4dcd-8179-b3dac28b0e53