AI Ethics

Responsible AI considers safety, fairness, privacy, transparency, and the possible effects on people. Its purpose is to reduce harm and promote trustworthy use, not merely to entertain, create sound, or decorate an object. Therefore safe and fair use is the option that best represents responsible AI practice.

An AI model learns patterns from its training data. If that data is wrong, incomplete, unrepresentative, or biased, the model may learn an unreliable pattern and produce incorrect results. Accurate data and a clear question generally improve performance, while electricity is necessary for operation but is not itself the stated cause of wrong results.

Using AI to create or spread false information is inappropriate because it can mislead people, damage reputations, create panic, and cause harmful decisions. Learning support, disease-detection assistance, and automation of repetitive work can be beneficial when accuracy, privacy, human oversight, and safety are considered. Thus A is the only clearly inappropriate use.

AI applications may handle names, contact details, locations, images, voices, or other information linked to individuals. Privacy protects this information from unnecessary collection, unauthorised access, misuse, or sharing. Making a machine attractive, reducing paper, or increasing sound volume may be useful elsewhere, but none is the main purpose of privacy.

Creating and spreading false or misleading information can deceive people, damage reputations, create fear, and influence decisions unfairly. It is therefore an unethical use. Health-check assistance, translation, and routine automation may provide benefits when accuracy, consent, privacy, human review, and safety are properly considered.

Fairness is important because an AI system may influence opportunities, services, or decisions affecting different people. Fair design and review aim to reduce unjustified bias and provide people with equal and respectful treatment. Option A expresses this purpose. The other choices describe selfish benefit, hiding errors, or violating privacy, none of which is fairness.

AI outputs are generated from data and programmed methods, so they can be inaccurate, incomplete, or biased. Human checking can compare an output with evidence, notice unreasonable conclusions, and correct or reject it when necessary. Option A states this benefit. Accepting everything without verification can produce unreliable decisions rather than improve quality.

Personal information such as an image, voice, location, or contact detail should be handled lawfully and respectfully. In ordinary responsible use, the person should be informed about the purpose and give appropriate consent before the data is used. Option A supports privacy and control. Sharing data widely, using it secretly, or treating silence as consent is unsafe.

AI ethics examines how technology affects people and whether it is designed and used responsibly. Important concerns include fairness, privacy, safety, transparency, accountability, and preventing harm. Option A captures these concerns. Processing speed, storage efficiency, and screen settings may be technical matters, but they do not by themselves answer ethical questions.

A chatbot may produce a plausible answer that is inaccurate, incomplete, outdated, or unsupported. The student should compare the historical claim with reliable books, educational resources, archives, or official sources and cite the sources appropriately. C is correct. Blind acceptance is unsafe, while rejecting every AI answer is unnecessary if the claim is carefully checked.

AI may produce an incorrect, incomplete, or biased output, even when it sounds confident. Sharing such an output without checking can spread misinformation and cause harm. Therefore, A is the action to avoid. Setting a clear purpose, protecting privacy, and keeping human oversight are all responsible practices that reduce risk and improve accountability.

AI chatbots generate responses from training data and learned patterns; they do not possess a guarantee of truth. They may misunderstand a prompt, repeat an error, or present biased or outdated information confidently. Reliable sources and teachers should therefore be used for checking. Speed does not prove accuracy, and AI does not replace all human guidance.

Good digital citizenship means using AI honestly, safely, and responsibly while respecting other people’s privacy, dignity, and rights. It includes checking information before sharing, protecting personal data, and considering possible harm. Option A expresses these behaviours. Sharing unverified information or collecting private data without permission undermines trust and responsible citizenship.

Privacy is at risk when information that can identify a person, such as a name, location, contact detail, or photograph, is collected or shared without proper permission. Thus, option C is correct. Secure storage and informed consent reduce privacy risks, while checking accuracy mainly concerns reliability.

Good digital citizenship means using technology safely, ethically, and respectfully, while protecting privacy and checking information before sharing it. Option C states this broad responsibility. Stealing data, sharing unverified AI content, or distributing someone’s image without permission can cause harm and violate privacy or trust.

If an AI model learns from data that unfairly represents groups or contains historical bias, its predictions may disadvantage some people. This can produce discriminatory or unfair outcomes, making option B a genuine risk. Saving time, personalised practice, and assistance with disease signs are potential benefits, though they still require responsible use.

Spreading misleading information is not responsible because AI-generated or AI-amplified false claims can confuse people, damage reputations, and influence decisions unfairly. Translation, image recognition, and personalised recommendations can be responsible applications when they are used lawfully, explained appropriately, and checked for accuracy, privacy, and bias. A recommendation should not be treated as an unquestionable fact, but the application itself is not automatically irresponsible. Therefore, B is the clear answer.

A sound privacy practice is to protect personal information, limit access, and share it only with appropriate permission and purpose. Passwords should never be posted publicly, and sensitive account details should not be entered carelessly on an unsecured network. Sharing without consent or exposing credentials can lead to misuse, identity theft, or unauthorised access.

AI-generated misinformation can look convincing even when it is false. People may trust it and make harmful decisions about health, money, safety, or social issues. AI does not automatically verify every claim before sharing, so users must check evidence and reliable sources rather than assuming that generated content is factual.

AI ethics concerns how systems are designed and used so that they are safe, fair, responsible, and respectful of people. It includes privacy, consent, accountability, transparency, and reducing harmful bias. A machine’s physical size or the colour of a laboratory wall is not the central ethical issue in AI.

A responsible user treats AI output as assistance rather than unquestionable truth. The user should understand the result, check important facts, consider possible bias, protect private information, and use the output appropriately. Accepting every answer, inserting misleading data, or sharing private details violates responsible use.

In AI, bias means a systematic and unfair tendency in a system’s decisions or predictions that disadvantages, or sometimes unfairly favours, a person or group. It may arise from unbalanced training data, biased labels, model design, or the way the system is used. Therefore, option A correctly describes bias. Fast operation concerns speed, internet connection concerns networking, and image recognition concerns an AI capability, not fairness.

When designed and used responsibly, AI can assist healthcare workers, help identify useful information, and adapt learning material to a student’s needs. These benefits still require safety checks and human judgment. Misinformation, theft of personal information, and increased algorithmic bias are harmful social effects, not positive impacts.

AI systems learn from data, so inaccurate, incomplete, or biased training data can produce unreliable or unfair decisions. This is an important risk, especially when decisions affect people. Personalised practice, time savings, and translation can be useful applications, although they too should be checked and used responsibly.

A chatbot may give information that is outdated, incomplete, or incorrect, even when the answer sounds confident. An examination date is important, so the student should compare it with the school’s official timetable or notice. Forwarding an unchecked answer could spread an error to other students.