04 The Ethics of AI (Computer Science).pptx

The ethics of Artificial Intelligence

1. The Ethics of Artificial Intelligence Understanding the Implications of AI

2. Introduction to AI Artificial Intelligence (AI) is a broad field that encompasses various technologies and methodologies aimed at enabling machines to perform tasks that typically require human intelligence. Here’s a comprehensive definition that includes the aspect of learning: Artificial Intelligence (AI) is the simulation of human intelligence processes by machines, particularly computer systems. These processes include: Learning : The ability of AI systems to improve their performance over time through experience. This can involve: Supervised Learning : Learning from labelled data to make predictions or decisions. Unsupervised Learning : Identifying patterns in data without pre-existing labels. Reinforcement Learning : Learning through trial and error, receiving feedback from actions taken. Comprehension : Understanding and processing information, which allows AI to interpret data and make sense of it in a human-like manner. Problem Solving : The capability to analyse complex problems and devise solutions, often using algorithms and computational models. Reasoning : The ability to draw conclusions from available information, enabling AI to make informed decisions. In summary, AI is not just about mimicking human thought but also about learning from data and experiences to enhance its capabilities and adapt to new situations.

3. Examples of AI in everyday life. Chatbots Robot vacuums Autonomous cars Smart Assistants Media Recommendations Traffic Information Smart Speakers Virtual Reality Gaming Smartphones Search Engines Email Spam Filters Antivirus Software

4. Importance of Ethics in AI. Why does ethics matter in AI? As AI becomes more integrated into society, ethical considerations ensure technology benefits everyone. Fairness and Non-discrimination: AI systems should be designed and trained to avoid perpetuating existing societal biases, ensuring equitable outcomes for all individuals regardless of race, gender, religion, or other protected characteristics. Privacy and Data Security: Robust safeguards must be in place to protect personal data used to train and operate AI systems, preventing misuse and upholding individual privacy rights. Transparency and Explainability: AI decision-making processes should be transparent and understandable, allowing individuals to comprehend how AI systems arrive at their conclusions and challenge potentially unfair or inaccurate results. Accountability and Responsibility: Clear lines of accountability should be established for the actions and outcomes of AI systems, determining who is responsible when AI causes harm or makes incorrect decisions. Human Oversight and Control: Maintaining meaningful human oversight and control over AI systems is crucial to prevent unintended consequences and ensure that AI remains a tool that serves humanity's best interests.

5. Key Ethical Issues.

6. Job Displacement. Definition:  The loss of jobs due to automation. Impact:  Changes in the job market and the need for new skills. Customer Service Representative : AI chatbots and virtual assistants can handle customer inquiries and complaints, providing instant responses and reducing the need for human agents. Data Entry Clerk : Automated systems can now input, process, and manage data more efficiently than humans, minimizing errors and speeding up workflows. Warehouse Worker : Robotics and AI-driven systems are used for sorting, packing, and transporting goods, streamlining operations and reducing the reliance on human labour. Paralegal : AI tools can analyse legal documents, conduct research, and even draft contracts, allowing law firms to operate with fewer paralegals. Market Research Analyst : AI algorithms can analyse vast amounts of data to identify trends and consumer behaviour, providing insights faster and more accurately than traditional methods. These changes highlight how AI is transforming the job landscape, often enhancing efficiency but also leading to job displacement in certain sectors.

7. Autonomous Weapons. Definition:  Weapons systems that operate without human intervention. Ethical concerns – who is accountable for these systems? Determining Responsibility:  It's difficult to assign blame when an autonomous weapon malfunctions or makes an incorrect decision, leading to civilian casualties or other harm. Lack of Human Oversight:  The absence of human control raises concerns about potential misuse or unintended escalation of conflict. Bias and Discrimination:  AI systems trained on biased data may exhibit discriminatory behaviour, leading to disproportionate targeting of certain groups.

8. Corporate Manslaughter & Autonomous Weapons. What is Corporate Manslaughter? A crime where companies can be held responsible for deaths caused by their negligence. Example: If a company's safety procedures are bad and someone dies as a result, the company can be charged. How Does This Relate to Autonomous Weapons? Autonomous Weapons:  Robots that can choose and attack targets without human control. The Problem:  If an autonomous weapon kills someone due to a design flaw or malfunction, who is responsible? Potential for Corporate Manslaughter:  The company that made the weapon could be charged if their negligence led to the death.

9. History. Asimov’s 3 Laws of Robotics (1940) A robot may not injure a human being or, through inaction, allow a human being to come to harm. A robot must obey the orders given to it by human being beings, except where such orders would conflict with the First Law. A robot must protect its own existence, as long as such protection does not conflict with the First or Second Law.

10. The Three Laws. Isaac Asimov's Three Laws of Robotics have sparked considerable debate regarding their relevance in today's discussions about artificial intelligence and robotics. Here’s a breakdown of the perspectives on their relevance: Influence on Ethics : Asimov's laws have significantly influenced both science fiction and real-world discussions on AI ethics. They provide a foundational framework for thinking about the responsibilities of robots and AI systems towards humans. Limitations in Complexity : Critics argue that the laws assume a simplistic view of robots as equals to humans, which doesn't align with the complexities of modern AI and robotics. The real-world applications of AI often involve nuanced decision-making that these laws do not adequately address. Practical Challenges : The laws raise practical questions about accountability and responsibility. For instance, if an autonomous system causes harm, determining who is responsible—developers, users, or the AI itself—remains a significant challenge.

11. Ethics of AI in Education. Absolutely! The integration of AI in education brings about several ethical considerations that are crucial to address. Here are the main ethical considerations, categorized for clarity: 1. Equity and Accessibility Bias and Fairness: Inclusive Learning: 2. Data Privacy and Security Student Data Protection: Informed Consent: 3. Teacher-Student Relationship Human Interaction: Role of Educators: 4. Transparency and Accountability Explainability of AI Decisions: Accountability for Outcomes: 5. Misinformation and Reliability Quality of Information: Loss of Critical Thinking Skills: 6. Ethical Use of AI Tools Responsible Implementation:. Continuous Monitoring:

12. The Ethics of AI in education. Assignment: AI in Education: A Two-Sided Perspective Artificial Intelligence (AI) is increasingly making its way into the classroom, promising to revolutionize education. However, this integration raises numerous questions about its impact on both educators and students. This assignment requires you to explore the use of AI in education from two distinct perspectives: the educator and the student. Task: You will write a comprehensive essay that addresses the following: Part 1: The Educator's Perspective (50%) Imagine you are a high school teacher in a subject of your choice. Identify and discuss three specific ways AI could be used to enhance teaching and learning in your chosen subject. For each example, provide a detailed explanation of how the AI tool would work, its potential benefits, and its potential drawbacks. Consider the ethical implications of using AI in this context, including issues like bias, privacy, and the potential for replacing human teachers. Finally, propose strategies for mitigating the potential drawbacks and ensuring ethical and responsible use of AI in your classroom. Part 2: The Student's Perspective (50%) Now imagine you are a student in the same high school class. Describe how the use of AI in your chosen subject would impact your learning experience. Focus on both the positive and negative aspects of AI-assisted learning, considering factors like personalized learning, accessibility, workload, and the potential for cheating. Discuss how AI could affect your relationship with your teacher and your overall learning process. Conclude by reflecting on the role of AI in education and its potential to shape the future of learning. Word Count: Your essay should be approximately 1000 words in length, with roughly 500 words dedicated to each perspective.

13. The Ethics of AI in education. Marking Guide for Students: Content (70%): Depth of analysis:  Clearly and comprehensively analyses the use of AI in education from both the educator and student perspectives. Specific examples:  Provides three specific examples of AI tools and their potential applications in the chosen subject. Exploration of benefits and drawbacks:  Identifies and discusses both the positive and negative aspects of AI in education. Ethical considerations:  Explores ethical implications of AI use, including bias, privacy, and potential for replacing human teachers. Strategies for mitigation:  Proposes strategies for mitigating potential drawbacks and ensuring ethical use of AI. Structure and Organization (20%): Logical flow:  Presents information in a clear and coherent manner. Paragraphing and transitions:  Uses effective paragraphing and transitions to guide the reader. Introduction and conclusion:  Provides a strong introduction and conclusion that summarises the key points. Writing Style (10%): Clarity and conciseness:  Expresses ideas clearly and concisely. Grammar and spelling:  Uses correct grammar and spelling. (Use spell check) Academic tone:  Maintains an appropriate academic tone.