Kediska Qiimaynta Saamaynta Algorithmic

Jawaabaha iyo sharraxaadaha waxay soo baxayaan markaad qaadanayso kediska.

1. Waa maxay ujeedada ugu weyn ee qiimaynta saamaynta algorithm?
   • To measure how fast a model runs in production
   • To identify who a system could affect, possible harms and safeguards before and during deployment
   • To certify that a model has no errors
   • To calculate the licensing cost of AI software
2. Qiimaynta noocee ah ayaa dhiirigelisay habka AIA?
   • Environmental and privacy impact assessments
   • Credit ratings and stock valuations
   • Medical board exams
   • Software speed benchmarks
3. Kanada AIA, maxay buundada su'aalaha go'aaminaysaa?
   • The salary of the project lead
   • Whether the system may use cloud computing
   • One of four impact levels that trigger specific requirements
   • The number of users allowed
4. Halkee laga helay AIA-yada Kanada ee la dhammaystiray?
   • They are kept secret by law
   • Only in internal audit files
   • On the government's open data portal
   • Only to the vendor who built the system
5. Marka loo eego sharciga EU AI, qodobkee qeexaya qiimaynta saamaynta xuquuqda aasaasiga ah?
   • Qodobka 5aad
   • Article 27
   • Qodobka 35aad
   • Article 99
6. Which deployer would clearly be expected to carry out a FRIA under the AI Act?
   • A gamer using a chatbot for fun
   • A startup training a spam filter for its own inbox
   • A bank deploying a high-risk credit scoring system
   • A student using an AI writing assistant
7. How does the FRIA relate to a GDPR data protection impact assessment?
   • It replaces the DPIA entirely
   • It complements the DPIA rather than replacing it
   • It is identical to the DPIA
   • It only applies when no personal data is used
8. According to the guide, what is a common misconception about AIAs?
   • That they involve affected groups
   • That they cover data sources
   • That they consider harms before deployment
   • That they are a one-time compliance form