  We analyze a bilateral trade model in which the buyer's value for the product
and the seller's costs are uncertain, the seller chooses the product price, and
the product is recommended by an algorithm based on its value and price. We
characterize an algorithm that maximizes the buyer's expected payoff and show
that the optimal algorithm underrecommends the product at high prices and
overrecommends at low prices. Higher algorithm precision increases the maximal
equilibrium price and may increase prices across all of the seller's costs,
whereas informing the seller about the buyer's value results in a
mean-preserving spread of equilibrium prices and a mean-preserving contraction
of the buyer's payoff.
