रियल एस्टेट क्विज़ में एआई

जैसे ही आप प्रश्नोत्तरी लेते हैं उत्तर और स्पष्टीकरण दिखाई देते हैं।

1. A model estimates a property’s value for internal planning. What should not be assumed?
   • That the estimate is a neutral appraisal or appropriate for every decision
   • That it has a date
   • That it used property data
   • That it needs documentation
2. Why define the property, market, and date before evaluating an estimate?
   • Every property uses the same reference market
   • Value depends on market context and the decision being made
   • A date changes only the display format
   • The model always predicts sale price
3. A model uses postal code because it predicts historical price well. What should reviewers consider?
   • Whether the code has five digits
   • Only whether it improves average error
   • Whether it proxies for protected characteristics or historical segregation
   • Whether the model is explainable by name
4. Why evaluate errors across neighborhoods and property types?
   • It eliminates interest-rate changes
   • All groups have identical data quality
   • The average guarantees fairness
   • A citywide average can hide systematic differences
5. What should be monitored after deployment?
   • Only the vendor’s marketing page
   • Listings, interest rates, and data coverage changes
   • The model’s logo
   • A single citywide score
6. What data does the real-estate guide say to protect?
   • Only the model’s weights
   • Only public house styles
   • Applicant, tenant, owner, and location information
   • The office phone number
7. A property recommendation may steer or exclude applicants. What does the guide recommend?
   • Provide oversight and a route to correct inaccurate data
   • Let the score silently decide
   • Remove the correction path
   • Use the same threshold without review
8. Before relying on an automated housing outcome, what should a practitioner do?
   • Skip privacy review
   • Trust a high score alone
   • Assume the same rules apply everywhere
   • Document the model, data, vendor, threshold, and human action and consult qualified experts