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A woman who was walking her dog in Milton Keynes, England, saw a delivery robot plunge "straight into the canal." Starship Technologies has urged residents not to worry if they see one of its robots in distress. The company noted, however, that people should report any sightings of their machines "swimming or in any other odd situation." ESPECIALLY BALL HANDLING: A man, shooting hoops in the nude at a park in Longwood, Fla., at 7:30 on a Sunday night, told arresting officers that he thought playing naked would help improve his basketball skills. A 23-year-old man kicked several people out of his family's home in Glassboro, N.J., stole a neighbor's pickup truck and got into an accident involving two other vehicles.

This has led to the development of a plethora of domain-dependent and context-specific methods for dealing with the interpretation of machine learning (ML) models and the formation of explanations for humans. Unfortunately, this trend is far from being over, with an abundance of knowledge in the field which is scattered and needs organisation. The goal of this article is to systematically review research works in the field of XAI and to try to define some boundaries in the field. From several hundreds of research articles focused on the concept of explainability, about 350 have been considered for review by using the following search methodology. In a first phase, Google Scholar was queried to find papers related to "explainable artificial intelligence", "explainable machine learning" and "interpretable machine learning". Subsequently, the bibliographic section of these articles was thoroughly examined to retrieve further relevant scientific studies. The first noticeable thing, as shown in figure 2 (a), is the distribution of the publication dates of selected research articles: sporadic in the 70s and 80s, receiving preliminary attention in the 90s, showing raising interest in 2000 and becoming a recognised body of knowledge after 2010. The first research concerned the development of an explanation-based system and its integration in a computer program designed to help doctors make diagnoses [3]. Some of the more recent papers focus on work devoted to the clustering of methods for explainability, motivating the need for organising the XAI literature [4, 5, 6].

Instead of talking about rocket trips to Mars or self-driving cars, Tesla Motors CEO Elon Musk turned his attention Friday night to a more mundane topic. He came to talk about roofs. But like all things Musk, there was nothing normal about the roofs he came to discuss. On Wisteria Lane, the backlot set of what used to be the Desperate Housewives TV series at Universal Studios Hollywood, Musk showed off a new kind of solar roof that will be offered starting next year through SolarCity, the home solar installation company that he is seeking to merge into Tesla. Instead of a massive, unattractive array of solar panels typically seen in suburbia, SolarCity had installed roof tiles that are solar collector themselves on several of the houses that are part of the film set.

At dawn on 17 March the inhabitants of Los Angeles were woken by a mild tremor. Less than three minutes later the Los Angeles Times website published an initial piece on the subject, at first sight a wire drafted in haste by a press agency: "A shallow magnitude 4.7 earthquake was reported Monday morning five miles [8km] from Westwood, California, according to the US Geological Survey. The temblor occurred at 6.25am Pacific time at a depth of 5.0 miles. According to the USGS, the epicentre was six miles from Beverly Hills, California, seven miles from Universal City, California, seven miles from Santa Monica, California, and 348 miles from Sacramento, California. In the past 10 days, there have been no earthquakes magnitude 3.0 and greater centred nearby. This information comes from the USGS Earthquake Notification Service and this post was created by an algorithm written by the author."