Facility location games provide an abstract model of mechanism design. In such games, a mechanism takes a profile of $n$ single-peaked preferences over an interval as an input and determines the location of a facility on the interval. In this paper, we restrict our attention to distance-based single-peaked preferences and focus on a well-known class of parameterized mechanisms called ordered weighted average methods, which is proposed by Yager in 1988 and contains several practical implementations such as the standard average and the Olympic average. We comprehensively analyze their performance in terms of both incentives and fairness. More specifically, we provide necessary and sufficient conditions on their parameters to achieve strategy-proofness, non-obvious manipulability, individual fair share, and proportional fairness, respectively.

Consider a large piece of land that is to be split in a fair manner among several farmers, who all have an equal entitlement to a share of this land. They all have different plans for their allotted pieces – growing a variety of crops, using the land as a pasture, or putting up a solar farm – so each of them has their own preferences over the land, depending on the type of soil, incline, access to water, etc. There may also be constraints on the shape of each individual piece: e.g., it is probably a bad idea to partition the land into pieces that are 800m long and 2m wide, even if such a partition is perfectly fair. The problem of allocating the land in a fair manner under these constraints has been considered in prior work (Segal-Halevi et al., Fair and square: Cake-cutting in two dimensions, Journal of Mathematical Economics 2017; Segal-Halevi et al., Envy-free division of land, Mathematics of Operations Research 2020), for two classic notions of fairness, namely, proportionality (if there are N agents, each of them should value their piece at least as highly as V/N, where V is the value they assign to the entire piece of land) and envy-freeness (no agent considers another agent's piece to be more valuable than their own). In our work, we consider a variant of this problem where, in addition to geometric constraints on the shapes of the individual pieces, we require the pieces to be separated: there is a separation parameter s such that any two pieces belonging to two different agents have to be at distance at least s from each other. Such a constraint is motivated by practical considerations, e.g., providing access or avoiding cross-pollination; if the "land" to be divided is, say, an exhibition hall or a market square, the separation requirement can be used to capture social distancing constraints.

As thousands of workers commence working from home due to Coronavirus, the Internet is awash with memes about the tempting distractions of YouTube. The artificial intelligence used by YouTube to continually serve relevant distractions is a modern shoulder devil for the home worker. Baby Shark has nearly 4.8 billion views on YouTube. In 2011 Google revealed that streaming 1-minute of video on YouTube consumes 0.0002 KwH of energy. That means that so far, people watching the 136-second-long Baby Shark video have collectively consumed about 2,112,000 KwH of energy. To give that context, in 2019 the average UK home consumed 3,100 KwH of electricity.

For the past few months, Huawei has been making headlines for all the wrong reasons -- the US government warned against buying the company's phones, which led to the breakdown of near-final deals with AT&T and Verizon. Then Best Buy, one of its few US retail partners, backed away too. We're not sure if the concerns hold any weight, but one thing is clear: It sucks to be Huawei right now. And in the midst of that turmoil, Huawei revealed its new P20 Pro, a remarkably well-built device with a triple camera system and loads of style. I doubt that would ever win over a Sinophobic bureaucrat though, so there's a strong chance no one in the US will ever be able to walk into a store and buy one.

Sophia, the worlds most advanced humanoid released to date was granted an honorary citizenship a few months ago by Saudi Arabia. In a move that set the net flooding with awe and dismay, this act probably triggered the first step towards recognising artificial intelligence being in the room and not at door step. The UN joined to recognise Sophia as the world's first UN Innovation Champion by UNDP. While these moves were music to many, artificial intelligence is raising a lot of divided opinions across the best of brains in science and technology. A quote widely in circulation on the social media on Einstein's premonition of a world having a generation of idiots may have its fair share of laughs. Einstein had indeed written a letter to his friend, psychiatrist Otto Juliusburger, in 1948 where he believed that the abominable deterioration of ethical standards stemmed primarily from the mechanisation and depersonalisation of our lives, a disastrous byproduct of science and technology.

Rapid advances in artificial intelligence technology are raising ethical questions, as pointed out by Dr Jason Millar ("The momentous advance in artificial intelligence demands a new set of ethics", Comment). He asks whether it is desirable to develop autonomous systems that operate beyond human control. Other ethical dilemmas may arise sooner than we think. While many have poured scorn on the idea that robots could possess consciousness, if consciousness can be interpreted as an algorithm – a series of logical cause-and-effect statements – then, because the output of an algorithm is platform-independent, there is no reason in principle why that algorithm should not operate in a robot. There is a debate as to whether brain activity is algorithmic, but other forms of biological information processing are and there is no convincing evidence to the contrary.