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| Section | Objectives |
|---|---|
| Prompt Structure and Clarity | - Writing clear and specific prompts
|
| Iterative Refinement Techniques | - Improving prompt performance
|
| Prompt Engineering for Domain-Specific Tasks | - Applying prompts in practical domains
|
| Chain-of-Thought and Multi-Step Prompting | - Reasoning-oriented prompting
|
| Ethical Considerations and Responsible Use | - Responsible AI usage
|
| Handling Edge Cases and Ambiguity | - Managing unreliable outputs
|
| Context and Role Definition | - Establishing AI context
|
| Performance Metrics and Evaluation | - Evaluating prompt effectiveness
|
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問題 #13
A person is preparing for an upcoming speech and wants to use generative AI to help prepare for the speech.
What should the person do before writing a prompt?
答案：B
解題說明：
The most critical step in the "pre-prompting" phase is the clear identification of the objective. Before interacting with a generative AI, the user must identify the goal of the speech. This foundational step dictates every other element of the prompt, including the persona, tone, and specific constraints. For example, a speech intended to persuade a group of investors requires a radically different linguistic approach than a speech intended to toast a friend at a wedding.
By identifying the goal first, the user can construct a prompt that provides the AI with a clear "definition of success." In practical applications, this is often referred to as the "Intent" phase. If a user skips this and goes straight to writing a draft or providing samples, the AI may generate content that is stylistically correct but fundamentally misses the mark regarding the intended outcome. Clear goals allow the user to evaluate the AI's output critically-checking if the generated text actually serves the purpose of informing, persuading, entertaining, or inspiring. Without a defined goal, prompt engineering becomes a trial-and-error process rather than a strategic exercise.
問題 #14
What is the principle of ethics that is ensured by explaining AI system decision-making to stakeholders and users?
答案：B
解題說明：
Transparencyin AI ethics refers to the degree to which an AI system's internal logic, data sources, and decision-making processes are visible and understandable to humans. It is the direct antidote to the "Black Box" problem. When an AI system provides a recommendation, the principle of transparency ensures that stakeholders (such as regulators, developers, and end-users) can understand the "why" behind the output. This is often achieved through "Explainable AI" (XAI) techniques.
In practical prompt engineering, transparency is optimized by instructing the model to provide its reasoning.
For example, using "Chain of Thought" prompting forces the AI to list the steps it took to arrive at a conclusion. This makes the interaction transparent because the user can see if the AI relied on faulty logic or biased data. Transparency builds trust; if a user understands how an AI reached a conclusion, they are more likely to adopt the technology. Furthermore, transparency is a prerequisite for other ethical principles like Fairness and Accountability, as you cannot fix a bias or hold a system accountable if you cannot see how it functions internally.
問題 #15
Which major challenge has been an issue for AI systems?
答案：C
解題說明：
One of the most significant and persistent challenges in the field of Artificial Intelligence is the lack of inherent ethical reasoning. AI models operate based on mathematical probabilities and patterns found within their training data; they do not possess a moral compass, a sense of justice, or an understanding of social nuances unless specifically programmed or constrained by human-defined rules. This often leads to issues where an AI might generate biased, harmful, or socially insensitive outputs because it is simply reflecting the biases present in its training set without any ethical filter.
While AI is actually quite proficient at analyzing vast amounts of data and is increasingly capable of processing unstructured data and generating video, the "black box" nature of its decision-making makes ethical alignment difficult. Ensuring that an AI respects privacy, avoids discrimination, and adheres to human values requires significant external intervention, such as Reinforcement Learning from Human Feedback (RLHF). The challenge lies in the fact that ethics are often subjective and context-dependent, making it nearly impossible to encode a universal moral code into a machine. This lack of ethical reasoning is why human oversight remains a critical component of AI deployment, especially in high-stakes fields like law, healthcare, and autonomous systems.
問題 #16
There have been complaints that deepfake videos on a social media platform are being circulated that show public figures making false statements. Which area of ethical concern does this situation demonstrate?
答案：B
解題說明：
The rise of deepfakes-AI-generated synthetic media that convincingly depicts people saying or doing things they never did-falls squarely under the ethical concern ofMisinformation and manipulation. This represents a significant challenge to the "Information Integrity" of digital platforms. By creating realistic but false content, generative AI can be used to influence elections, damage reputations, or incite social unrest.
This ethical concern highlights the "dual-use" nature of AI. While the same technology can be used for harmless entertainment or high-end film production, in the hands of bad actors, it becomes a tool for
"cognitive hacking." Prompt engineering optimization in this context involves developing guardrails within AI models to prevent the generation of content involving public figures or non-consensual imagery. It also involves the use of AI todetectdeepfakes by identifying microscopic inconsistencies in pixels or heart-rate signatures that are invisible to the human eye. Addressing misinformation requires a combination of technical watermarking, robust platform policies, and user education to ensure that the boundary between reality and AI- generated fiction remains clear.
問題 #17
A company released a new sports watch, and an advertiser wants to use generative AI to help produce a text- based advertisement for the watch that explains the features of the watch. Which prompt engineering solution is most likely to achieve this goal?
答案：C
解題說明：
To achieve a high-quality, accurate advertisement, the most effective solution is togive a list of features that should be highlighted. In prompt engineering, this is known as providing "input data" or "grounding." Without a specific list of features, the AI will likely "hallucinate" capabilities for the sports watch-such as a
100-day battery life or a built-in laser-that the product does not actually possess.
By providing a concrete list (e.g., "GPS tracking, heart rate monitor, 50m water resistance, and sapphire glass"), the user provides the AI with the raw materials needed to construct the ad. This shifts the AI's role from "fictional writer" to "creative editor." The model can then focus on persuasive language and structural formatting rather than inventing technical specifications. This is the standard professional approach for marketing teams: use the prompt to establish the "facts" and let the AI handle the "flair." It ensures the resulting text is both creative and factually grounded, which is the primary requirement for any commercial advertisement.
問題 #18
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