Artificial intelligence can tell Scotch whisky from American whiskey and identify its strongest constituent aromas more reliably than human experts – by using data rather than tasting the drinks. Andreas Grasskamp at the Fraunhofer Institute for Process Engineering and Packaging IVV in Germany and his colleagues trained an AI molecular odour prediction algorithm called OWSum on descriptions of different whiskies. Then, in a study involving 16 samples – nine types of Scotch whisky and seven types of American bourbon or whiskey – they tasked OWSum with telling drinks from the two nations apart based on keyword descriptions of their flavours, such as flowery, fruity, woody or smoky. Using these alone, the AI could tell which country a drink came from with almost 94 per cent accuracy. Because the complex aroma of these spirits is determined by the absence or presence of many chemical compounds, the researchers also fed the AI a reference dataset of 390 molecules commonly found in whiskies.

They arguably have one of the best occupations in the world. But whisky sommeliers may soon have some competition for their jobs – from AI. Scientists have devised machine learning algorithms that can determine whether a whisky is of American or Scotch origin and identify its strongest aromas. And they even outperform human experts, the results show. A whisky's aroma is determined by a complex mixture of odorous compounds, which makes it highly challenging to assess. Panels of human experts are often used to identify the strongest notes of a whisky but these require a significant investment in time, money and training – and agreement between experts is often rare.

Researchers based at the STFC Hartree Centre worked with the Scotch Whisky Research Institute (SWRI) using data analytics to tackle counterfeiting across the sector. Without efficient data processing techniques, the time cost prevents such techniques ever becoming part of a routine authentication provision within the Scotch Whisky sector. The SWRI carries out pre-competitive fundamental research on behalf of its members, representing approximately 90% of the production capacity of the sector. SWRI offers analytical services, using traditional techniques such as GC-FID (Gas Chromatography – Flame Ionisation Detector) or GC-MS (Gas chromatography–Mass Spectrometry) to detect counterfeits. Using these methods to distinguish between different samples can be challenging given the complexity resulting from the number of different compounds present in the vapour above a whisky sample.