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Strategyproof Peer Selection using Randomization, Partitioning, and Apportionment

arXiv.org Artificial Intelligence

Peer review, evaluation, and selection is a fundamental aspect of modern science. Funding bodies the world over employ experts to review and select the best proposals of those submitted for funding. The problem of peer selection, however, is much more general: a professional society may want to give a subset of its members awards based on the opinions of all members; an instructor for a MOOC or online course may want to crowdsource grading; or a marketing company may select ideas from group brainstorming sessions based on peer evaluation. We make three fundamental contributions to the study of procedures or mechanisms for peer selection, a specific type of group decision-making problem, studied in computer science, economics, and political science. First, we propose a novel mechanism that is strategyproof, i.e., agents cannot benefit by reporting insincere valuations. Second, we demonstrate the effectiveness of our mechanism by a comprehensive simulation-based comparison with a suite of mechanisms found in the literature. Finally, our mechanism employs a randomized rounding technique that is of independent interest, as it solves the apportionment problem that arises in various settings where discrete resources such as parliamentary representation slots need to be divided proportionally.


jupyter/jupyter

@machinelearnbot

Recitations from Tel-Aviv University introductory course to computer science, assembled as IPython notebooks by Yoav Ram. Exploratory Computing with Python, a set of 15 Notebooks that cover exploratory computing, data analysis, and visualization. No prior programming knowledge required. Each Notebook includes a number of exercises (with answers) that should take less than 4 hours to complete. Developed by Mark Bakker for undergraduate engineering students at the Delft University of Technology.


The Future of Jobs and Jobs Training

#artificialintelligence

Machines are eating humans' jobs talents. And it's not just about jobs that are repetitive and low-skill. Automation, robotics, algorithms and artificial intelligence (AI) in recent times have shown they can do equal or sometimes even better work than humans who are dermatologists, insurance claims adjusters, lawyers, seismic testers in oil fields, sports journalists and financial reporters, crew members on guided-missile destroyers, hiring managers, psychological testers, retail salespeople, and border patrol agents. Moreover, there is growing anxiety that technology developments on the near horizon will crush the jobs of the millions who drive cars and trucks, analyze medical tests and data, perform middle management chores, dispense medicine, trade stocks and evaluate markets, fight on battlefields, perform government functions, and even replace those who program software – that is, the creators of algorithms. People will create the jobs of the future, not simply train for them, ...


Forecasting The Future And Explaining Silicon Valley's New Religions

#artificialintelligence

Yuval Noah Harari might be Silicon Valley's favorite historian. His last book, Sapiens: A Brief History of Humankind, which detailed the entirety of human history and how Homo Sapiens came to dominate the Earth, was blurbed by President Barack Obama and Bill Gates, and Mark Zuckerberg recommended it for his book club. And more than 100,000 students have taken Harari's online course. In his new book, Homo Deus: A Brief History of Tomorrow, Harari looks forward and hazards a few guesses on what comes next for humanity. These next chapters in our history range from the utopian to the horrific, he says.


The FAA Just Released Its New Drone Rule Book

Popular Science

Transportation of property for compensation or hire allowed provided that The aircraft, including its attached systems, payload and cargo weigh less than 55 pounds total; The flight is conducted within visual line of sight and not from a moving vehicle or aircraft; and The flight occurs wholly within the bounds of a State and does not involve transport between (1) Hawaii and another place in Hawaii through airspace outside Hawaii; (2) the District of Columbia and another place in the District of Columbia; or (3) a territory or possession of the United States and another place in the same territory or possession. If a company or person wants to fly a drone in a way different from these rules, they can do so by applying to the FAA for a Certificate of Waiver, which if granted will give them a legal exception. The rules are a major step towards clarity in the vague world of drone law, though I'm certain there is much still to be decided and discovered in the full body of the rule. Here, if you wish to delve through it, is the full rule.