Our ability to answer questions currently separates us from machines in the world of artificial intelligence . But researchers are working on algorithms to give computers this skill too . Now , scientists at Facebook have come up with questions that they say artificially intelligent machines must answer , if they can ever match human brainpower – but some of them are a bit tricky , meaning some people may fail them too . Scientists at Facebook ( logo shown ) have come up with questions that they say artificially intelligent machines must answer if they can ever match human brainpower – but some of them are a bit tricky , meaning some people may fail them too . The team from the social media firm ’ s AI lab in New York have come up with a list of 20 questions to separate humans from robots , because they say ‘ many existing learning systems can currently not solve them. ’ They test different types of reasoning and the ability to process language . 1 ) The first question of the 20 listed in the research paper was the simplest for a computer to answer . It is : . John is in the playground . Bob is in the office . Where is John ? 2 ) A harder example for a computer to answer is a question that requires it to differentiate three separate arguments , such as : . Mary gave the cake to Fred . Fred gave the cake to Bill . Jeff was given the milk by Fred . Who gave the cake to Fred ? Who did Fred give the cake to ? What did Jeff receive ? Who gave the milk ? 3 ) Another task tested a machine 's ability to perform simple counting operations by asking about the number of objects . For example : . Daniel picked up the football . Daniel dropped the football . Daniel got the milk . Daniel took the apple . How many objects is Daniel holding ? 4 ) Basic deduction skills were tested by questions such as : . Sheep are afraid of wolves . Cats are afraid of dogs . Mice are afraid of cats . Gertrude is a sheep . What is Gertrude afraid of ? 5 ) And reasoning about size was tested by this question : . The football fits in the suitcase . The suitcase fits in the cupboard . The box of chocolates is smaller than the football . Will the box of chocolates sit in the suitcase ? The intelligent computers were tested on 20 questions in total , but none of them got a perfect score . The answers to the five examples listed , are shown above . The sometimes tricky questions test different types of reasoning and the ability to process language . A stock image of a perplexed person is shown . Some of the questions require machines to recall facts , while others need reasoning , or to count the number of objects , expressed in a written passage . The researchers say that humans should be able to score full marks . While you may have got one answer wrong , none of the seven computer learning programmes that Facebook tested got all 20 questions right . The experiment was designed to test whether a machine can answer questions ‘ via chaining facts , simple induction , deduction and many more , ’ the study published on arXiv says . Scientists are keen to create this ability so that humans can talk fluently with machines , which could lead to robots looking after the elderly and more intelligent websites , for example . The paper says : ‘ One long-term goal of machine learning research is to produce methods that are applicable to reasoning and natural language , in particular building an intelligent dialogue agent. ’ The experts aim to ‘ classify these tasks into skill sets , so that researchers can identify ( and then rectify ) the failings of their systems. ’ The results of the test show that humans are still ahead of the game when it comes to interpreting the world ’ s subtleties and language . The questions are written in very clear and simple terms so there is still a way to go before computers catch us up .
Test was developed by experts at Facebook to test machines with AI . It 's comprised of 20 questions testing reasoning and language skills . Humans are expected to get a full score , with careful consideration . None of the AI algorithms managed this showing more research is needed .