The author of "The Eleventh Hour" looks back on a few works--by Mikhail Bulgakov, Franz Kafka, Voltaire, and E. M. Forster--that have helped him craft his own. Salman Rushdie prefers not to immerse himself in other people's writing when he is working on his own. "When I'm writing fiction, I tend not to read fiction. I actually don't want other people's voices to sneak into my head," Rushdie said recently. That's not to say that other writers' books aren't an important part of his process--posing questions, providing instruction, and offering models of characters.

We develop synthetic notions of oracle computability and Turing reducibility in the Calculus of Inductive Constructions (CIC), the constructive type theory underlying the Coq proof assistant. As usual in synthetic approaches, we employ a definition of oracle computations based on meta-level functions rather than object-level models of computation, relying on the fact that in constructive systems such as CIC all definable functions are computable by construction. Such an approach lends itself well to machine-checked proofs, which we carry out in Coq. There is a tension in finding a good synthetic rendering of the higher-order notion of oracle computability. On the one hand, it has to be informative enough to prove central results, ensuring that all notions are faithfully captured. On the other hand, it has to be restricted enough to benefit from axioms for synthetic computability, which usually concern first-order objects. Drawing inspiration from a definition by Andrej Bauer based on continuous functions in the effective topos, we use a notion of sequential continuity to characterise valid oracle computations. As main technical results, we show that Turing reducibility forms an upper semilattice, transports decidability, and is strictly more expressive than truth-table reducibility, and prove that whenever both a predicate $p$ and its complement are semi-decidable relative to an oracle $q$, then $p$ Turing-reduces to $q$.

Automated vehicles (AVs) are social robots that can potentially benefit our society. According to the existing literature, AV explanations can promote passengers' trust by reducing the uncertainty associated with the AV's reasoning and actions. However, the literature on AV explanations and trust has failed to consider how the type of trust - cognitive versus affective - might alter this relationship. Yet, the existing literature has shown that the implications associated with trust vary widely depending on whether it is cognitive or affective. To address this shortcoming and better understand the impacts of explanations on trust in AVs, we designed a study to investigate the effectiveness of explanations on both cognitive and affective trust. We expect these results to be of great significance in designing AV explanations to promote AV trust.

On January 17 1803, a young man named George Forster was hanged for murder at Newgate prison in London. After his execution, as often happened, his body was carried ceremoniously across the city to the Royal College of Surgeons, where it would be publicly dissected. What actually happened was rather more shocking than simple dissection though - Forster was going to be electrified. Giovanni Aldini's experiments with a human corpse - one of the first, and most controversial, to attempt to reanimate a human using electricity Luigi Galvani was an Italian physician who demonstrated what we now understand to be the electrical basis of nerve impulses, when he made frog muscles twitch by jolting them with a spark from an electrostatic machine. Galvani one day observed his assistant using a scalpel on a nerve in a frog's leg; when a nearby electric generator created a spark, the frog's leg twitched, prompting Galvani to develop his famous experiment.

The influence of Artificial Intelligence (AI) and Artificial Life (ALife) technologies upon society, and their potential to fundamentally shape the future evolution of humankind, are topics very much at the forefront of current scientific, governmental and public debate. While these might seem like very modern concerns, they have a long history that is often disregarded in contemporary discourse. Insofar as current debates do acknowledge the history of these ideas, they rarely look back further than the origin of the modern digital computer age in the 1940s-50s. In this paper we explore the earlier history of these concepts. We focus in particular on the idea of self-reproducing and evolving machines, and potential implications for our own species. We show that discussion of these topics arose in the 1860s, within a decade of the publication of Darwin's The Origin of Species, and attracted increasing interest from scientists, novelists and the general public in the early 1900s. After introducing the relevant work from this period, we categorise the various visions presented by these authors of the future implications of evolving machines for humanity. We suggest that current debates on the co-evolution of society and technology can be enriched by a proper appreciation of the long history of the ideas involved.

The reconstruction and analyzation of high energy particle physics data is just as important as the analyzation of the structure in real world networks. In a previous study it was explored how hierarchical clustering algorithms can be combined with kt cluster algorithms to provide a more generic clusterization method. Building on that, this paper explores the possibilities to involve deep learning in the process of cluster computation, by applying reinforcement learning techniques. The result is a model, that by learning on a modest dataset of 10; 000 nodes during 70 epochs can reach 83; 77% precision in predicting the appropriate clusters.

Forster's cat, Timothy, is pretty cute, but Forster is tired of him bringing in dead or dying birds and mice and dropping them on the carpet. Eight years ago, an image-recognition software company solved the same problem with its company cat, Flo. Quantum Picture developed a cat door that let Flo in, but locked her out if it saw she was carrying something in her mouth. At the time, the door connected to a desktop computer that ran the program that snapped pictures of Flo and analyzed them as she approached the door. Now, Forster is determined to build Flo's door for Timothy on weekends, in between his usual consulting work in Simi Valley, Calif.

When the writer Rebecca Forster first heard how Google was using her work, it felt like she was trapped in a science fiction novel. "Is this any different than someone using one of my books to start a fire? I have no idea," she says. "I have no idea what their objective is. Certainly it is not to bring me readers."

When the writer Rebecca Forster first heard how Google was using her work, it felt like she was trapped in a science fiction novel. "Is this any different than someone using one of my books to start a fire? I have no idea," she says. "I have no idea what their objective is. Certainly it is not to bring me readers."

A key front for ethical questions in artificial intelligence, and computer science more generally, is teaching students how to engage with the questions they will face in their professional careers based on the tools and technologies we teach them.  In past work (and current teaching) we have advocated for the use of science fiction as an appropriate tool which enables AI researchers to engage students and the public on the current state and potential impacts of AI. We present teaching suggestions for E.M. Forster's 1909 story, "The Machine Stops," to teach topics in computer ethics.  In particular, we use the story to examine ethical issues related to being constantly available for remote contact, physically isolated, and dependent on a machine --- all without mentioning computer games or other media to which students have strong emotional associations. We give a high-level view of common ethical theories and indicate how they inform the questions raised by the story and afford a structure for thinking about how to address them.