AS Level Computer Science (9618) Study Notes

Chapter 7.1: Ethics and Ownership

Hello! Welcome to one of the most interesting and relevant parts of your course. Computer Science isn't just about writing perfect code; it’s also about understanding the huge impact technology has on society, and how we must act responsibly.
This chapter gives you the essential framework—the moral rules and legal protections—that govern how software is used and how technology professionals should behave. Don't worry if the licensing types seem tricky at first; we will break them down clearly!

1. Ethics and the Computing Professional

Ethics refers to the moral principles that govern a person's or group's behavior. In computing, these principles help guide professionals when faced with difficult choices concerning data, privacy, security, and the public good.

1.1 The Need for Ethical Conduct

As a computing professional, you are often dealing with sensitive information and powerful tools. Therefore, you need to act ethically to:

  • Maintain public trust in technology (e.g., ensuring systems are secure).
  • Protect individual rights and privacy.
  • Ensure the safety and integrity of systems you build.
The Impact of Acting Ethically or Unethically

A single choice can have massive consequences:

  • Ethical Action: A developer discovers a severe security vulnerability in their company’s software and immediately works to patch it before it can be exploited.
  • Unethical Action: An employee secretly sells their company's customer data (names, addresses) to a marketing firm for personal profit, violating customer privacy and company trust. The impact is financial loss and severe reputational damage.

1.2 Professional Ethical Bodies

Many professionals join bodies to uphold high standards and get guidance. The syllabus highlights two key examples:

1. BCS (British Computer Society) – The Chartered Institute for IT

  • Purpose: To set professional standards, certify IT competence, and promote the wider social and economic impact of IT.

2. IEEE (Institute of Electrical and Electronic Engineers)

  • Purpose: A global organization focused on advancing technological innovation and excellence, often publishing extensive ethical codes related to software engineering and AI development.

Key Takeaway: Joining an ethical body demonstrates commitment to professional conduct, helping guide difficult decisions and maintaining the integrity of the profession.

2. Intellectual Property: Copyright Legislation

When someone writes a program, draws a graphic, or composes a piece of music, that work is their intellectual property.

2.1 The Need for Copyright

Copyright legislation is the legal framework designed to protect the rights of the creators (authors) of original works.

  • It ensures that only the creator (or those they permit) can copy, modify, or distribute the work.
  • Purpose: To encourage creativity and innovation by guaranteeing that creators can benefit financially from their efforts, rather than having their work instantly stolen and copied.
  • Example: If you write a complex accounting program, copyright prevents a rival company from simply copying your entire source code and selling it as their own product.

Common Mistake Alert: Students sometimes confuse copyright with patents. Copyright protects the *expression* of an idea (the code itself); patents protect the *idea* or *invention* (how the algorithm works).

3. Software Licensing and Justification

A license defines exactly *how* a user is legally allowed to use a piece of software. Since virtually all software is protected by copyright, the license is the mechanism by which the copyright holder grants specific permissions to others.

3.1 Types of Software Licencing

We need to understand four main types of software licenses: Commercial, Shareware, Free Software Foundation (FSF), and Open Source Initiative (OSI).

1. Commercial Software
  • Definition: Software developed and sold for profit. The user typically purchases a copy or subscription.
  • Key Characteristics: The source code is usually closed source (kept secret). Usage is strictly defined (e.g., install on only one machine).
  • Example: Microsoft Windows, Adobe Photoshop, most proprietary games.
2. Shareware
  • Definition: Software distributed free of charge, but only for a limited period or with limited functionality ("try before you buy").
  • Key Characteristics: After the trial period, the user must purchase a license to continue full use. The source code is usually closed.
  • Example: A game that lets you play the first few levels for free, but requires purchase for the rest.
3. Free Software Foundation (FSF) / Free Software

Don't be fooled by the word "Free"! This refers to "freedom," not necessarily price. FSF software guarantees the user the "Four Essential Freedoms":

  1. The freedom to run the program for any purpose.
  2. The freedom to study how the program works, and change it. (Requires access to source code).
  3. The freedom to redistribute copies.
  4. The freedom to improve the program and release the improvements to the public.

(Memory Aid: Think R.S.R.I. – Run, Study, Redistribute, Improve!)

4. Open Source Initiative (OSI) / Open Source Software
  • Definition: Software where the source code is made publicly available for viewing, modification, and enhancement.
  • Key Characteristics: While similar to FSF, Open Source focuses more on collaboration and technical advantages, rather than strict moral freedom. It must comply with the 10 points of the OSI definition.
  • Example: Linux Operating System, Python programming language, Apache web server.

3.2 Justifying the Use of a Licence

When should a company choose one over the other?

  • Use Commercial/Shareware if: You need maximum profit, highly controlled distribution, dedicated customer support, and protection of intellectual property (closed source).
  • Use FSF/Open Source if: Collaboration and community improvements are key, customisation is essential, and cost needs to be minimized. Many large companies use Open Source because they can modify it to exactly fit their internal needs.

Quick Review: Licensing

  • Commercial: Pay, proprietary, closed.
  • Shareware: Trial period, then pay, closed.
  • FSF: Free (freedom) to modify and share code.
  • Open Source: Source code available, emphasis on collaboration.

4. Artificial Intelligence (AI)

Artificial Intelligence (AI) is the area of Computer Science dedicated to creating systems that can perform tasks that typically require human intelligence, such as learning, problem-solving, decision-making, and language comprehension.

4.1 Applications of AI

AI is now central to many modern systems. Key applications include:

  1. Expert Systems: Systems designed to mimic the decision-making ability of a human expert (e.g., medical diagnosis systems).
  2. Speech Recognition: Converting spoken language into text (e.g., Siri or Alexa).
  3. Image Processing: Used in facial recognition, quality control in manufacturing, and automated surveillance.
  4. Autonomous Systems: Self-driving vehicles and robots that navigate and make decisions without constant human input.
  5. Fraud Detection: Analyzing transaction patterns in real-time to flag unusual or suspicious activity.

4.2 The Impact of AI

Understanding AI’s impact is vital for AS Level, covering social, economic, and environmental aspects.

Social Issues
  • Bias and Discrimination: If AI training data reflects existing societal biases (e.g., racial or gender bias), the resulting AI system may perpetuate or amplify that unfairness in its decisions (e.g., loan applications, hiring).
  • Privacy and Surveillance: Widespread use of facial recognition and data tracking raises significant concerns about continuous monitoring and the erosion of personal privacy.
  • Decision-making Transparency: It can be hard to understand *why* an AI made a certain decision ("the black box problem"), which reduces public trust, especially in high-stakes fields like law or medicine.
Economic Issues
  • Job Displacement: AI-driven automation (like robotics or advanced algorithms) can perform repetitive or analytical tasks faster and cheaper than humans, leading to unemployment in certain sectors.
  • New Job Creation: Conversely, AI creates new roles in data science, AI maintenance, and ethical oversight.
  • Increased Productivity: Businesses using AI can dramatically reduce costs and increase efficiency, leading to higher profits and economic growth.
Environmental Issues
  • High Energy Consumption: Training large, complex AI models (like large language models) requires massive amounts of electrical power, contributing significantly to carbon emissions.
  • Optimisation: AI can be used positively to manage resources, such as optimising global supply chains, managing smart energy grids, or developing more energy-efficient materials.

Did you know? The training process for some of the world's largest language models can use the same amount of electricity as several homes use in a year! This is a major area of environmental concern for computer scientists.

Key Takeaway: AI offers huge advantages in application and efficiency, but professionals must ethically manage the risks associated with bias, privacy invasion, and energy usage.