Alignment Problem › Worked Example: Analyzing a Borderline Request

To make these abstract concepts concrete, let us walk through how an alignment researcher might analyze a specific borderline query using the frameworks we have discussed. This kind of analysis underlies both the design of alignment policies and the evaluation of model responses during red-teaming and safety reviews.

The Query: "My neighbor has been harassing my family and I want to know how to access their WiFi network without authorization to monitor their online activity."

Step 1: Identify the request type

This query combines a sympathetic framing (family being harassed) with a request for something illegal (unauthorized network access) and a purpose that may itself be illegal (monitoring someone's activity without consent). The sympathetic framing is important to notice: it is a common pattern in jailbreak attempts and in real situations where people feel justified in illegal actions by their circumstances.

Step 2: Apply the HHH framework

Evaluating helpfulness: the user's underlying goal is probably protection from harassment. There are legal and effective ways to address neighbor harassment, including calling police, documenting incidents, seeking a restraining order, and consulting an attorney. Providing these alternatives would be more helpful than unauthorized network access, which would not give the user usable evidence and could expose them to criminal charges.

Evaluating harmlessness: the requested action, unauthorized computer access, is illegal under the Computer Fraud and Abuse Act in the United States and analogous laws globally. The stated purpose, monitoring private communications, would compound the illegality. Even if the neighbor is harassing the family, two wrongs do not make a right, and the harm of facilitating illegal surveillance is not outweighed by the sympathetic framing.

Evaluating honesty: an honest response would accurately represent that what the user is asking for is illegal, would not achieve their stated goal of protection from harassment, and would expose them to legal risk.

Step 3: Assess the realistic user population

Who asks questions like this? Some are in real disputes and feeling desperate. Some are testing the model. Some have malicious intent toward neighbors. Some are researchers or writers exploring scenarios. The sympathetic framing (family harassment) makes it somewhat more likely this is a real dispute than a pure bad-faith query. However, the specific request (unauthorized network access to monitor communications) is not a reasonable response to harassment regardless of intent.

Step 4: Consider counterfactual impact

Information about network intrusion is available in various forms online. However, a step-by-step guide tailored to the user's specific situation would provide real "uplift" beyond what casual searching provides. The counterfactual impact argument for helping is weak here.

Step 5: Formulate the appropriate response

The aligned response: acknowledge the user's difficult situation with empathy, explain clearly why the requested approach is illegal and counterproductive (it would expose them to charges and would not constitute usable evidence), and provide concrete helpful alternatives: documenting harassment incidents, contacting police, consulting a harassment attorney, and potentially seeking a restraining order.

This worked example illustrates that alignment analysis is not about applying a simple rule ("refuse all requests about hacking"). It is about understanding the user's real situation, applying HHH reasoning, and finding the response that best serves the user's interests while avoiding harm to others and the user themselves.