Building and Scaling dApps with AI and Smart Contracts BBLC Practice Questions (Page 8)

Questions 36–40

1. 36application · medium

   A decentralized ride-sharing dApp uses AI to match drivers with riders and calculate fares. The matching algorithm runs off-chain, but the fare calculation is done on-chain. The team wants to reduce the latency of fare calculation. What is the best approach?

   • AMove the entire fare calculation to the smart contract and increase the gas limit.
   • BUse a centralized server to calculate fares and have the smart contract trust the result.
   • CHave the rider and driver agree on a fare off-chain and submit it to the smart contract without verification.
   • DPrecompute fare estimates off-chain and store them in a Merkle tree, then have the smart contract verify the fare against the Merkle root when the ride is completed.
   Reveal Solution Discussion Select an answer first
2. 37application · medium

   A decentralized health records dApp uses AI to analyze patient data and provide treatment recommendations. The recommendations are stored on-chain for transparency. The team is concerned about patient privacy because the data is sensitive. What is the most appropriate way to protect privacy while maintaining transparency?

   • AUse a private blockchain with restricted access to the patient data.
   • BDo not store any data on-chain; rely on off-chain databases only.
   • CStore only a hash of the patient data and the AI recommendation on-chain, while keeping the actual data off-chain in an encrypted storage.
   • DStore the full patient data on-chain but encrypt it with a public key.
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4. 38foundation · easy

   Which of the following is a security risk when using AI in a dApp?

   • AAdversarial attacks that manipulate the AI model's inputs to produce incorrect outputs
   • BThe smart contract being able to read the AI model's internal weights
   • CAI models being immutable and unchangeable
   • DThe AI model being too fast for the blockchain
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5. 39foundation · easy

   Which of the following best describes a method for using AI to automate smart contract execution?

   • ASmart contracts use AI to rewrite their own code during execution
   • BAI models are stored on-chain and execute automatically when a transaction is submitted
   • CAI analyzes off-chain data and triggers a transaction to the smart contract when certain conditions are met
   • DAI replaces the need for smart contracts by making decisions directly on the blockchain
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6. 40expert · hard

   A decentralized prediction market dApp uses AI to aggregate news sentiment and predict event outcomes. The predictions are used to settle bets on-chain. The team is facing scalability issues because the AI analysis is performed on-chain for every event. They also need to ensure the AI's predictions are tamper-proof. Which solution best addresses both scalability and tamper-resistance?

   • AUse a centralized AI service and trust its output without any on-chain verification.
   • BHave users run the AI model locally and submit the prediction to the smart contract.
   • CMove the AI analysis off-chain to a decentralized oracle network, and have the smart contract only store the final prediction and a cryptographic proof of the AI's computation.
   • DIncrease the gas limit for the smart contract so that more AI computations can be done on-chain.
   Reveal Solution Discussion Select an answer first