Moral and ethical Issues — OCR A-Level Computer Science

Moral and ethical issues in Computer Science explore the profound impact of technology on individuals, society, and the environment. This topic, part of the OCR A-Level specification, examines how computing professionals must consider the consequences of their work, from data privacy and algorithmic bias to environmental sustainability and intellectual property. Understanding these issues is crucial for developing responsible technology that aligns with human values and legal frameworks.

The study of moral and ethical issues is not just theoretical; it directly influences real-world decisions in software development, data handling, and system design. Students will analyse ethical theories such as utilitarianism and deontology, and apply them to contemporary dilemmas like the use of AI in surveillance, the ethics of autonomous vehicles, and the digital divide. This topic also ties into legal considerations, including the Data Protection Act 2018 and the Computer Misuse Act 1990, providing a holistic view of professional responsibility.

Mastering this topic prepares students for the 'Ethical, legal, cultural and environmental concerns' section of the OCR exam, where they must evaluate scenarios and justify their reasoning. It also fosters critical thinking and empathy, essential skills for any computing professional. By engaging with these issues, students learn to balance innovation with accountability, ensuring technology serves the greater good.

• →Ethical frameworks: Utilitarianism (greatest good for the greatest number) and deontology (duty-based rules) are key for analysing dilemmas.
• →Data protection and privacy: The Data Protection Act 2018 (GDPR) governs how personal data is collected, stored, and used, with principles like consent and purpose limitation.
• →Algorithmic bias: When algorithms reflect or amplify human prejudices, leading to unfair outcomes in areas like hiring or policing.
• →Environmental impact: The energy consumption of data centres and e-waste from discarded devices raise sustainability concerns.
• →Intellectual property: Copyright, patents, and open-source licensing affect how software and digital content are created and shared.

• Ability to articulate individual, social, ethical, and cultural opportunities and risks of digital technology
• Understanding of key computing-related legislation including the Data Protection Act 1998, Computer Misuse Act 1990, Copyright Design and Patents Act 1988, and Regulation of Investigatory Powers Act 2000
• Evaluation of the impact of computers in the workforce and automated decision-making
• Discussion of artificial intelligence, environmental effects, and internet censorship
• Analysis of monitoring behaviour and personal information usage
• Understanding of piracy and offensive communications
• Awareness of layout, colour paradigms, and character sets in a global context

• 💡Use specific examples of technology to support your arguments
• 💡Ensure you can distinguish between the different acts of legislation and their primary purposes
• 💡Practice evaluating both sides of an ethical argument (e.g., the benefits vs. risks of AI)
• 💡Refer to the command words in the question to determine the required depth of your response
• 💡When evaluating ethical dilemmas, always reference a specific ethical framework (e.g., 'From a utilitarian perspective, this is acceptable because...') to show deeper understanding.
• 💡Use real-world examples to support your arguments, such as the Cambridge Analytica scandal for data misuse or the Volkswagen emissions scandal for environmental ethics.
• 💡In 9-mark questions, structure your answer with clear paragraphs: one for each ethical, legal, and environmental point, and always include a justified conclusion.

• Failing to link ethical issues to specific, real-world examples
• Confusing the specific remits of different pieces of legislation
• Providing generic answers that lack depth or critical evaluation
• Ignoring the 'cultural' aspect of the topic in favour of only moral or ethical points
• Misconception: 'If something is legal, it is automatically ethical.' Correction: Legality and ethics are distinct; for example, collecting data with consent may be legal but could still be unethical if users are manipulated.
• Misconception: 'Ethical issues only apply to big companies like Facebook or Google.' Correction: Every developer, even when creating a small app, must consider privacy, accessibility, and potential misuse of their software.
• Misconception: 'Algorithmic bias is only about race or gender.' Correction: Bias can also relate to age, location, socioeconomic status, or any other characteristic present in training data.