AI Ethics

Useful AI begins with a clearly defined purpose and depends on relevant, reliable, and sufficiently representative data. Poor, incomplete, or biased data can produce poor results even when the system is technically advanced. Machine colour, room size, and loudness normally do not determine whether an AI solution is appropriate or trustworthy.

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.

AI systems may collect or process names, locations, photographs, voices, and other personal information. Privacy ensures that such information is collected, stored, used, and shared only for appropriate purposes and with proper permission. Therefore, option A is correct; the other options describe unrelated physical or technical activities.

Ethical rules guide the responsible design and use of AI. They help protect people’s rights, privacy, safety, dignity, and equal treatment. They also encourage checking data and results before important decisions are made. Thus option A is correct; changing colours or ignoring data accuracy is unrelated or unsafe.

An AI output may be incorrect, incomplete, biased, or unsuitable for the particular situation, even when it appears confident. Checking it against evidence, rules, or a reliable source helps detect errors before action is taken. Therefore A is correct; speed, storage, and automatic input changes are different issues.

AI may produce errors, unfair patterns, or results that do not fit the real context. Human supervision allows a person to review important outputs, question them, correct mistakes, and stop harmful actions. Therefore A is correct. Unchecked automation and removal of accountability are unsafe, while supervision does not primarily increase computer speed.

Fairness means that an AI system should not unjustly favour or disadvantage people, especially because of irrelevant personal characteristics. It requires attention to equal opportunity, appropriate treatment, and possible bias in data or outcomes. Helping only one person, hiding errors, or blocking someone without a valid reason is not fair decision-making.

Responsible AI use includes protecting personal information, limiting access, checking outputs, and avoiding harm. Option A reflects privacy protection. Option B violates consent and privacy, option C ignores the possibility of error, and option D deliberately causes harm. Therefore only A represents safe and responsible behaviour.

Safety in AI means designing, testing, and using a system so that foreseeable risks and harmful effects on people, property, or the environment are reduced. It also includes suitable safeguards and human review. Accepting unchecked decisions, exposing personal data, or spreading misinformation increases risk rather than providing safety.

A chatbot can produce useful answers, but it may also generate inaccurate, incomplete, outdated, or misunderstood information. Comparing its response with a textbook, reliable source, or teacher helps confirm correctness before use. Speed is not evidence of truth, and submitting copied AI text in an examination is not responsible learning.

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 can create a poster quickly, but it may insert an incorrect date, time, venue, spelling, image, or other detail. The student should review the complete poster, compare facts with the event information, correct errors, and then seek approval if needed. Sharing an unchecked poster can confuse participants and spread misinformation.

AI-generated career information may contain factual errors, outdated details, unsupported claims, or unnecessary personal data. The student should verify important facts with reliable sources, remove private information, and review the wording before publication. Options A and B ignore verification, while D exposes classmates’ data without a legitimate need or permission.

Responsible AI considers whether a system can cause harm, treat people unfairly, or misuse personal information. Therefore safety, fairness, and privacy are important principles, along with accountability and appropriate human oversight. Speed and cost may matter for design, but they alone cannot show that an AI system is responsible or ethical.

AI can make mistakes, reflect bias in its data, or give an answer that does not fit the real situation. Human supervision allows people to review outputs, ask for evidence, correct errors, and stop harmful actions. Keeping a machine off, ignoring outputs, or surrendering every decision does not provide responsible oversight or accountability.

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.