This new dataset shows that AI still lacks commonsense reasoning

Abductive reasoning, frequently misidentified as deductive reasoning, is the process of making a plausible prediction when faced with incomplete information. For example, given a photo showing a toppled truck and a police cruiser on a snowy freeway, abductive reasoning may lead someone to infer that dangerous road conditions caused an accident. Humans can quickly consider this sort of context to arrive at a hypothesis. But AI struggles, despite recent technical advances. Motivated to explore the challenge, researchers at the Allen Institute for Artificial Intelligence, the University of California, Berkeley, and the MIT-IBM Watson AI lab created a dataset called Sherlock, a collection of over 100,000 images of scenes paired with clues a viewer could use to answer questions about the scenes.