We study the impact of algorithmic trading in the foreign exchange market using a high-frequency dataset representing a majority of global interdealer trading in three major currency pairs, euro-dollar, dollar-yen, and euro-yen, from 2003 through 2007. We find that human-initiated trades account for a larger share of the variance in exchange rate returns than computer-initiated trades: humans are still the informed traders. There is some evidence, however, that algorithmic trading contributes to a more efficient price discovery process via the elimination of triangular arbitrage opportunities and the faster incorporation of macroeconomic news surprises into the price. We also show that algorithmic trades tend to be correlated, indicating that computer-driven strategies are not as diverse as those used by human traders. Despite this correlation, we find no evidence that algorithmic trading causes excess volatility. Furthermore, the amount of algorithmic activity in the market has a small, but positive, impact on market liquidity.