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Is Artificial Intelligence A Friend Or A Foe? A Closer Look

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Is Artificial Intelligence A Friend Or A Foe? A Closer Look

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Artificial Intelligence Does Not Exist: Lessons from Shared Cognition and the Opposition to the Nature/Nurture Divide

The term artificial intelligence (AI) was first used in the middle of the 20th century, which is when it's history began. The development of artificial intelligence (AI) can be linked to founders such as Alan Turing, who during World War II established the theoretical foundation for intelligent machines. At the Dartmouth Conference in 1956, the area of artificial intelligence was officially established. The goal of the research was to create machines that could mimic human intelligence. In the beginning phases of AI development, researchers focused on rule-based systems and symbolic reasoning, building programs that might use established rules to solve certain issues. But during the "AI winter" of the 1970s and 1980s, when funding and interest in AI research declined, development was slow and hope became low. Developments in machine learning, an area of AI that focuses on providing computers the ability to learn from data, have been linked with assisting to the birth of AI in the twenty-first century. Big data sets and more processing power made it possible for academics to create complicated algorithms. The creation of brain networks, which take inspiration from the human brain, and the use of methods for deep learning are two notable innovations. Despite the amazing successes, worries about AI's risks have increased. The possibility of bias in AI systems is a significant problem since these systems learn on previous data, which might indicate social stereotypes. Complicated AI models' lack of accessibility also brings up moral concerns regarding responsibility and judgment. Fears of job displacement resulted from the rapid growth of AI, as some careers could grow useless due to robotics. Considerations were also brought up about the use of AI in self-driving weapons, which bring up moral and security considerations. Rules, standards, and responsible development techniques become increasingly important as AI develops. Finding a balance between AI's advantages and disadvantages is crucial for assuring a time in the future when technology advances society without sacrificing security or moral principles. Thus, it is essential to learn the background and main motive of AI, and to look forward at the future that what impact will come upon the world.

Link: https://link.springer.com/book/10.1007/978-3-319-99605-9

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The book highlights the autonomy that people gained with personal computers as it describes how computers developed from a centralized, mainframe architecture to the modern era of personal computers. Given the possibility of independent decision-making in advanced AI systems, the concept of autonomy is relevant to arguments regarding the risks associated with AI.

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The text discusses the change in focus of control from local (people using their own PCs) to distant (cloud computing). In discussions regarding AI, the concept of control is essential particularly when worries about losing control over entirely self-sufficient AI systems are present.

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The text briefly discusses the drop in desktop PC sales and the continued existence of desktop PCs in some market industries because of things like improved specific tasks. performance. Computer security issues are relevant to talks about artificial intelligence (AI) since protecting AI systems from malicious usage is becoming increasingly important, particularly with the growth of the internet and networked systems.

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ethical issues are strongly related to the text's wider background, which covers the development of computing and its effects on society. Regarding the creation, application, and possible social impact of AI systems, ethical questions surface.

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The text talks about how the introduction of personal computers changed society and made technology more accessible to everyone. When assessing the risks connected with AI innovations, it is important to take into account the potential for negative effects on employment, privacy, and societal norms.

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Overarching Question or Argument for (Autonomy)

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Overarching Question or Argument for (Autonomy)

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How does the increasing autonomy of AI systems raise concerns about their decision-making capabilities and potential risks?

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Subclaims & Related Arguments (Autonomy)

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Subclaims & Related Arguments (Autonomy)

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1. AI systems can make decisions without human intervention.

2. Lack of human oversight may lead to unintended consequences.

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Key Components of Each Subclaim or Related Argument(Autonomy)

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Key Components of Each Subclaim or Related Argument(Autonomy)

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1. Autonomy refers to the ability of AI systems to operate independently.

2. Decision-making without human intervention raises ethical and safety concerns.

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The push for AI autonomy intersects with ethical considerations about accountability and responsibility.

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Forms of Evidence & Potential Sources for Further Research(Autonomy)

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Forms of Evidence & Potential Sources for Further Research(Autonomy)

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1. "As for the locus of control, the PC is still the center of any operation". This contrasts with the "Post-PC era," where control becomes more remote, reflecting a shift towards dependence on cloud services and changing dynamics of user autonomy in computing evolution.

2. Case studies of AI systems making autonomous decisions with unintended outcomes.

3. Ethical guidelines and discussions in AI research literature.

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How does the shift in control, from local (individuals) to remote (cloud computing), impact the dynamics of AI systems and their potential dangers?

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Subclaims & Related Arguments: (Control)

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Subclaims & Related Arguments: (Control)

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1. Remote control may lead to dependence on external services.

2. Centralized control poses security and privacy risks.

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Key Components of Each Subclaim or Related Argument(Control)

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Key Components of Each Subclaim or Related Argument(Control)

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1. Control refers to the ability of individuals to manage and operate their computing systems.

2. Shifts in control affect user autonomy and data security.

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Discussions about control overlap with debates on data privacy and security in AI systems.

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Forms of Evidence & Potential Sources for Further Research(Control)

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Forms of Evidence & Potential Sources for Further Research(Control)

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1. Studies on the implications of centralized control in cloud computing.

2. Privacy breaches and security incidents related to centralized data storage.

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How does the issue of security in computing, as discussed in the text, translate to concerns about the potential dangers of AI?

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1. Inadequate security measures may expose systems to cyber threats.

2. Malicious use of AI technology poses security risks to individuals and organizations.

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Key Components of Each Subclaim or Related Argument

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Key Components of Each Subclaim or Related Argument

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1. Security involves protecting systems from unauthorized access and attacks.

2. AI systems, if compromised, can be used for malicious purposes.

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Security concerns are closely tied to ethical considerations and potential misuse of AI technology.

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Forms of Evidence & Potential Sources for Further Research

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Forms of Evidence & Potential Sources for Further Research

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1. Examples of AI systems exploited for cyberattacks.

2. Security assessments and vulnerabilities in AI applications.

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How do ethical considerations in the development and use of technology connect to the potential dangers of AI?

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1. Unethical use of AI can lead to societal harm.

2. Lack of ethical guidelines may result in biased or discriminatory AI systems.

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Key Components of Each Subclaim or Related Argument

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Key Components of Each Subclaim or Related Argument

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1. Ethics involves principles of fairness, transparency, and responsibility.

2. Unethical AI practices can have far-reaching consequences on individuals and communities.

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Ethical discussions intersect with broader debates on the societal impact of AI.

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Forms of Evidence & Potential Sources for Further Research

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Forms of Evidence & Potential Sources for Further Research

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1. Case studies on AI applications with ethical concerns.

2. Ethical frameworks and guidelines proposed by AI research organizations.

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How does the disruptive nature of technological advancements, as discussed in the text, relate to the potential dangers of AI?

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1. AI's disruptive impact on employment raises concerns about job displacement.

2. Societal norms may be challenged by the rapid integration of AI technologies.

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Key Components of Each Subclaim or Related Argument

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Key Components of Each Subclaim or Related Argument

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1. Disruption involves significant changes to existing structures and practices.

2. AI's influence on employment and societal norms can be transformative.

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Forms of Evidence & Potential Sources for Further Research

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Forms of Evidence & Potential Sources for Further Research

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1. Studies on the effects of AI on job markets and employment.

2. Analyses of societal changes resulting from the widespread adoption of AI technologies.

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Relationships Between Various Claims, Perspectives, etc...

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Relationships Between Various Claims, Perspectives, etc...

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Discussions about AI disruption link to broader conversations on economic and social implications.

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Question: How have computer skills and control changed over time?

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Question: How have computer skills and control changed over time?

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Question: What's the impact of small devices and cloud use today?

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Question: What's the impact of small devices and cloud use today?

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Question: What's hard and good about controlling and using advanced computers?

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Question: What's hard and good about controlling and using advanced computers?

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1. Skills: Basic literacy and numeracy.

2. Control: Local control with direct interaction.

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1. Skills: Broadened to include digital literacy, numeracy, and programming.

2. Control: Local control as PCs became central.

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1. Research and Application of Artificial Intelligence Technology in the Field of Risk Perception

Bai, Shuya, et al. “Research and Application of Artificial Intelligence Technology in the Field of Risk Perception.” Journal of Physics: Conference Series, vol. 1302, no. 2, 2019, pp. 22002-, https://doi.org/10.1088/1742-6596/1302/2/022002.

2. Trolice, Mark P., et al. “Artificial Intelligence—the Future Is Now.” Journal of Assisted Reproduction and Genetics, vol. 38, no. 7, 2021, pp. 1607–12, https://doi.org/10.1007/s10815-021-02272-4.

3. Au-Yong-Oliveira, Manuel, et al. “The Role of AI and Automation on the Future of Jobs and the Opportunity to Change Society.” Advances in Intelligent Systems and Computing, vol. 932, Springer International Publishing, 2019, pp. 348–57,  https://doi.org/10.1007/978-3-030-16187-3_34.

4. The Future of AI: How AI Is Changing the World - Built In https://builtin.com/artificial-intelligence/artificial-intelligence-future

Date accessed:November 22, 2023 - Mike Thomas

5. Is AI our friend or worst enemy? - 4 + 4 arguments to decide - Codecool https://codecool.com/en/blog/is-ai-our-friend-or-worst-enemy-4-4-arguments-to-decide/

Date published:November 18, 2021 - Date accessed:November 22, 2023

6. Will AI – Artificial Intelligence Take Over The World? - Tech Business News

https://www.techbusinessnews.com.au/opinion/could-artificial-intelligence-take-over-the-world/

Date published:May 18, 2023 - Date accessed:November 22, 2023 - Darren Pesen

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From the pre-digital era to the post-PC age, the source I read, “This Changes Everything - ICT and Climate Change: What Can We Do?” provided a thorough examination of the development of computers. A highlight is the highly detailed representation of historical settings through pop culture references, such as the TV show "Columbo" and the motion picture "War Games." This method made the story more realistic and interesting while also increasing the accessibility of the growth of technology.

The difficulty in the book was the thorough investigation of how PCs affect society. The book carefully analyzed the change in technical democracy that occurred when personal computers became widely available and less limited to use by professionals. An organized structure for understanding changing patterns was provided by the place of management, the concentration on skills, and the difference between ordinary and expert users.

Viewing the post-PC era and the increasing number of mobile devices presents an upcoming insight. The conversation around the change to cloud computing and the growing skill set needed by consumers highlights how quickly technology is developing.

The social consequences of these technical changes are an issue that needs more research. The book discussed the effects on education, entrepreneurship, and families, but it might go into more detail about the wider social and economic consequences. Furthermore, taking into consideration different points of view might improve the study's thoroughness.

Moreover, the challenge that I encountered was finding some points from the book that can be considered as a question for complex thinking. It was hard for me to pick points from the book that would tell me how AI is dangerous, but after reading, I was able to find some points and connect with my idea. Thus, I believe I was able to overcome this problem, as I had to think creatively and had to create questions that would fit in with the information of the book and my topic.

To sum up, the book was informative in its historical consideration, unexpected in its references to popular media, and detailed in its evaluation of technological, social, and economic aspects. Its depth would be improved by additional investigation of global viewpoints and societal consequences.

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Skills: Simplified for non-specialists, with increased complexity for experts.

Control: Shifted towards remote control with cloud computing.

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Small devices and cloud services have streamlined user interactions, reducing the need for extensive technical skills. Basic digital literacy suffices for everyday tasks.

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The locus of control has shifted to the cloud, allowing users to access and manage data remotely. Cloud services handle storage and processing, enhancing flexibility.

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Professionals now require a broader skill set due to the integration of cloud computing. This includes expertise in collaborative tools, data analytics, and leveraging diverse applications.

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Hard Aspect: Advanced computers demand increasingly complex skills from expert users, requiring continuous learning to navigate sophisticated applications and technologies.

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Challenge: The proliferation of personal computers brought about technological democratization but introduced the challenge of ensuring widespread digital literacy to effectively use these technologies.

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Notable Shift: The control over computer operations has shifted from local (direct user control) to remote (cloud computing), enhancing convenience but raising concerns about data security and dependence on internet connectivity.

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Understanding the challenges and dynamics of controlling and using advanced computers is crucial for guiding technological education, promoting digital literacy, informing design and security practices, and adapting to the continuous evolution of technology. These insights facilitate informed decision-making, shape education programs, and contribute to the development of user-friendly and secure technologies in our digital age.

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Small devices and cloud services simplify user interactions, emphasizing the importance of basic digital literacy. The shift to cloud-based control enhances flexibility by allowing remote data access. Professionals now need a broader skill set, including proficiency in collaborative tools, data analytics, and diverse applications, due to the integration of cloud computing.

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The evolution of computing has reshaped user skills and control mechanisms, transitioning from basic literacy and local control to simplified user experiences and increased complexity for experts. The pivotal shift towards remote control with cloud computing broadened skill requirements to include digital literacy, numeracy, and programming. Recognizing this progression is essential for adapting educational strategies and designing technology that aligns with both everyday tasks and the demands of cloud-based computing.

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1. IS THE PRODUCTION OF AI ROBOTS BENEFICIAL FOR BUSINESSES?

2. WHAT WILL HAPPEN IF ROBOTS ARE USED IN MILITARY FEILDS?

3. IS IT SAFE TO LAUNCH PERSONAL ROBOTS LIKE SIRI TO PEOPLE FOR NORMAL USES?

4. IS AI BENEFICIAL FOR EDUCATION?

5. ARE STUDENTS LEARNING BETTER FROM AI OR THEY ARE BEING LAZY?

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KEY UNCOMMON TERMS FOR ROBOTS AND EDUCATION

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KEY UNCOMMON TERMS FOR ROBOTS AND EDUCATION

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1. Model Cannibalism: This term refers to the potential negative impact of training future AI models on flawed or biased data generated by previous models. As misinformation and inaccuracies are perpetuated through AI systems, subsequent models may inherit and amplify these issues, leading to a self-perpetuating cycle of biased information.

2. Cognitive Impact of Chatbots: This term encompasses the psychological influence that AI chatbots, particularly large language models, can have on users. It focuses on how the human-like nature of chatbots, including their conversational abilities and use of first-person pronouns, may manipulate people's beliefs or behaviors, making them more susceptible to trust and perceive the AI as a friend rather than a tool.

3. Model Hallucinations: This term describes a phenomenon observed in large language models like ChatGPT, where the AI system generates fabricated or false information during its responses. Model hallucinations highlight the risk of AI systems disseminating inaccurate or misleading content, contributing to the spread of misinformation and disinformation in various domains, including news and social media.

4. Generative AI Bias:

This term refers to the potential bias embedded in the outputs generated by generative AI systems, such as ChatGPT. As these systems learn from diverse datasets, including text from the internet, books, and other sources, they may inadvertently replicate and perpetuate existing biases present in the training data. Addressing generative AI bias is crucial in education to ensure fair and equitable outcomes, especially when it comes to student interactions, content creation, and decision-making processes influenced by AI.

5. Pedagogical Interactivity:

Pedagogical interactivity goes beyond traditional educational interactions by incorporating AI-driven, personalized, and adaptive learning experiences. In the context of AI in education, this term emphasizes the dynamic engagement between students and AI systems, fostering tailored instructional approaches. The concept involves AI platforms actively responding to individual student needs, preferences, and learning styles, contributing to a more interactive and responsive educational environment. It underscores the potential for AI to enhance the overall learning experience through personalized and adaptive pedagogical strategies.