Ethics in artificial intelligence (AI): Analyse the ethics in AI, including autonomous vehicles and autonomous weapon systems.

Lesson 48/59 | Study Time: Min


The realm of artificial intelligence (AI) is one that has grown tremendously over the past decade, and with this rapid growth, a multitude of ethical questions arise. Whether it's autonomous vehicles navigating our roads or drones hovering above, the ethical implications are vast and complex.

Unravelling the Ethics of AI 🧩

The ethical considerations in AI are often underestimated until we dive deeper into its implications. Take for example, autonomous vehicles. These vehicles are designed to operate without human intervention, taking decisions on the road based on complex algorithms. However, what happens when an autonomous vehicle encounters an unavoidable accident? Who does the vehicle choose to protect - the passenger or the pedestrian?

These are not just hypothetical questions. In 2018, a self-driving car from Uber struck and killed a pedestrian in Arizona, USA, in what is believed to be the first pedestrian fatality involving an autonomous vehicle. This incident spurred widespread debate about the ethical programming of these vehicles and who should be held accountable for such accidents.

Navigating the Skies: Autonomous Drones 🚁

Similarly, autonomous drones - unmanned aerial vehicles - are becoming increasingly common for a plethora of tasks from delivering packages to conducting military operations. But how much autonomy should a drone have? Should it have the ability to conduct a potentially lethal operation without human approval?

A chilling example is the case of a Turkish drone reportedly hunting down and killing a human target autonomously in Libya's civil war. This incident raises serious ethical dilemmas around the use of AI in warfare and combat situations.

Balancing the Equation: Risks and Benefits ⚖️

AI systems undoubtedly bring numerous benefits, from increased efficiency and accuracy to the potential for truly revolutionary breakthroughs. However, these benefits must be weighed against the serious ethical concerns they raise. Issues of safety, privacy, and accountability are paramount.

In the realm of privacy, AI's capacity to process vast amounts of data is both a boon and a bane. On one hand, it enables us to tailor services and products to individual needs. On the other hand, it raises serious privacy concerns. A stark reminder of this was the Cambridge Analytica scandal, where the personal data of millions of people's Facebook profiles were harvested without their consent for political advertising purposes.

For AI systems to be ethically sound, they must be transparent, accountable, and respect privacy. Legal frameworks must be established to govern their use and to ensure accountability. The future of AI isn't just about technological advancements but also about carefully navigating these ethical, social, and legal challenges. It's about understanding the potential implications of the decisions we are programming into these systems and striving for a future where technology serves humanity in a way that aligns with our shared values and ethical norms.



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1- Introduction 2- Models of data communication and computer networks: Analyse the models used in data communication and computer networks. 3- Hierarchical computer networks: Analyse the different layers in hierarchical computer networks. 4- IP addressing in computer networks: Set up IP addressing in a computer network. 5- Static and dynamic routing: Set up static and dynamic routing in a computer network. 6- Network traffic management and control: Manage and control network traffic in a computer network. 7- Network troubleshooting: Diagnose and fix network problems. 8- Introduction 9- Concepts and sources of big data. 10- Recommendation systems, sentiment analysis, and computational advertising. 11- Big data types: streaming data, unstructured data, large textual data. 12- Techniques in data analytics. 13- Problems associated with large data sets used in applied analytical models. 14- Approaches to visualize the output from an enforced analytical model. 15- Big data processing platforms and tools. 16- Performing simple data processing tasks on a big data set using tools 17- Introduction 18- Relational Database Management Systems: Analyze the concepts and architecture of a relational database management system. 19- Entity Relationship Model: Analyze the components of an entity relationship model. 20- Relational Model: Analyze relation, record, field, and keys in a relational model. 21- ER to Relational Model Conversion: Perform a conversion from an ER model to the relational model. 22- Functional Dependency: Analyze the concepts of closure sets, closure operation, trivial, non-trivial, and semi-trivial functional dependencies. 23- Normal Forms: Analyze the concepts of lossless, attribute-preserving, and functional-dependency-preserving decomposition, and first normal form. 24- Installation of Programming Languages and Databases: Install MySQL and phpMyAdmin and install Java and Python programming languages. 25- CRUD Operations: Perform create, read, update, delete (CRUD) operations in MySQL. 26- MySQL Operations: Perform MySQL operations using CONCAT, SUBSTRING, REPLACE, REVERSE, CHAR LENGTH, UPPER, and LOWER commands. 27- Aggregate Functions: Perform MySQL operations using count, group by, min, max, sum, and average functions. 28- Conditional Statements and Operators: Perform MySQL operations using not equal, not like, greater than, less than, logical AND, logical OR. 29- Join Operations: Perform MySQL operation. 30- Introduction 31- Historical development of databases: Analyze the evolution of technological infrastructures in relation to the development of databases. 32- Impact of the internet, the world-wide web, cloud computing, and e-commerce: Analyze the impact of these technologies on modern organizations. 33- Strategic management information system (MIS): Analyze the characteristics and impact of a strategic MIS. 34- Information systems for value-added change: Analyze how information systems can support value-added change in organizations. 35- Functionality of information communication technology: Analyze the functionality offered by information communication technology and its implications. 36- International, ethical, and social problems of managing information systems: Define the international, ethical, and social problems associated. 37- Security and legislative issues in building management information systems: Define the security and legislative issues related to building MIS. 38- Security and legislative issues in implementing management information systems: Define the security and legislative issues related to implementing MIS. 39- Security and legislative issues in maintenance. 40- Introduction 41- Ethical concepts in computing: Analyse common ethical concepts and theories in computing. 42- Laws and social issues in information technology: Analyse laws and social issues in areas including privacy, encryption, and freedom of speech. 43- Intellectual property and computer crime: Analyse the laws relating to trade secrets, patents, copyright, fair use and restrictions, peer-to-peer. 44- Data privacy: Define data privacy and analyse the types of data included in data privacy. 45- Ethical theories and the U.S. legal system: Analyse philosophical perspectives such as utilitarianism versus deontological ethics and the basics. 46- Ethical dilemmas in information technology: Apply ethical concepts and an analytical process to common dilemmas found in the information technology. 47- Impacts of intellectual property theft and computer crime: Analyse the impacts of intellectual property theft and computer crime. 48- Ethics in artificial intelligence (AI): Analyse the ethics in AI, including autonomous vehicles and autonomous weapon systems. 49- Ethics in robotics: Analyse the ethics in robotics, including robots in healthcare. 50- Introduction 51- Technologies involved in building a secure e-commerce site. 52- Common problems faced by e-commerce sites. 53- Requirements analysis and specification for an e-commerce project. 54- Writing a project proposal and creating a presentation. 55- Front-end development tools, frameworks, and languages. 56- Back-end development languages, frameworks, and databases. 57- Application of software development methodologies. 58- Creating a project report and user documentation. 59- Delivering structured presentations on the software solution.
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