Y10W09WR Artificial Intelligence and Its Risks

Part 1

How to Write

Explanatory – Explanatory piece

An explanatory text makes a concept, process or system understandable to a reader who is encountering it for the first time. It is written for someone who wants to genuinely understand how or why something works. The tone should be clear and patient — building understanding step by step without assuming prior knowledge.

  • Ideas & content: Select the most important information needed to understand the topic. Focus on how and why — explanation is about building genuine understanding, not just describing what exists.
  • Structure & cohesion: Move from the general to the specific. Introduce the concept, explain how or why it works, then give examples or consequences. Use cause-and-effect connectives to show relationships between ideas.
  • Voice & audience: Write as a knowledgeable guide. Define terms as you introduce them. Avoid jargon without explanation. Your reader should feel guided through the topic, not overwhelmed by it.
  • Language choices: Use precise vocabulary and define technical terms clearly. Write in the present tense for ongoing processes. Vary sentence length — shorter sentences help when ideas are complex.
  • Conventions: Spell technical vocabulary accurately. Use commas, colons and semicolons to manage complex explanations. Keep sentences clear even when the ideas are demanding.

Common pitfalls: Describing what something is without explaining how or why it works — readers need to understand the mechanism, not just the label. Including too many facts without connecting them into a clear explanation that builds understanding progressively.

Part 2

Your Task Plan for Today

The brief

Question: Write a three-paragraph explanatory piece explaining what artificial intelligence is, how machine learning works and what the main concerns about AI’s growing role in society are. Select the most relevant material from the notes, organise it clearly and write entirely in your own words. You will need to decide what to leave out.

Stimulus: Read the following notes carefully. They contain more information than you can use.

Artificial intelligence refers to computer systems designed to perform tasks that would typically require human intelligence. Machine learning is the dominant approach in modern AI. Rather than being explicitly programmed with rules, machine learning systems learn patterns from large amounts of data. A machine learning model is trained by exposing it to many examples and adjusting its internal parameters to minimise errors in its predictions or outputs. Deep learning uses neural networks — mathematical structures loosely inspired by the brain — with many layers that allow the model to learn increasingly abstract representations of data. Large language models, which underlie AI systems like those used in chatbots, are trained on vast quantities of text and learn to predict what words or tokens are likely to follow others. This produces outputs that appear coherent and knowledgeable but are generated by pattern-matching rather than genuine understanding. AI systems can exhibit bias when the data used to train them contains or reflects existing human biases. Facial recognition systems have been shown to perform less accurately on darker-skinned faces, reflecting imbalances in training data. AI is increasingly used in consequential decisions including credit assessment, hiring screening, medical diagnosis assistance and criminal sentencing tools. Explainability is a significant challenge — in many deep learning systems, it is not possible to give a clear account of why the system produced a particular output, which creates accountability difficulties. Generative AI systems can produce text, images, audio and video that is difficult to distinguish from human-made content. Concerns about AI include job displacement, misuse for surveillance, generation of misinformation and concentration of AI capability in a small number of large companies. There is ongoing debate about how AI should be regulated and whether existing legal frameworks are adequate.

Task Analysis: This task asks you to explain a concept or system clearly and completely. You must select relevant material, organise it logically and write for a reader with no specialist knowledge. A strong response helps readers understand not just how something works, but why it matters.

Quick Plan

Plan your explanation:

  • Your main concept — what are you explaining and why does it matter?
  • Key parts or steps — what are the main elements?
  • Why it works this way — what’s the logic or reason?
  • Real examples — what concrete examples clarify the concept?
  • Why readers should care — what real-world significance does this have?

Define the key concept

Begin by explaining your core concept clearly. Avoid jargon without explanation. Help readers understand exactly what you’re about to discuss.

Background/context

Help readers understand why this topic matters. What real-world problems or questions does it involve? What makes this worth knowing about?

Causes/effects

Show how things work and what their consequences are. Trace cause-and-effect relationships explicitly. This helps readers understand not just what happens but why.

Examples that teach

Use specific, concrete examples that illuminate the concept. Real scenarios and applications make abstract ideas tangible and memorable.

Limits/nuance

Acknowledge what’s complex, uncertain or contested about this topic. What don’t experts fully understand yet? This intellectual honesty builds credibility and prevents oversimplification.

Check before you submit: Have you explained the concept clearly without jargon? Have you included relevant examples? Have you answered why this matters? Is your explanation accessible?