An Ethical Crisis in Computing
Moshe Y. Vardi,
Rice University –
Computer scientists think often of “Ender’s Game” these days. In
this award-winning 1985 science-fiction novel by Orson Scott Card,
Ender is being trained at Battle School, an institution designed
to make young children into military commanders against an
unspecified enemy. Ender’s team engages in a series of
computer-simulated battles, eventually destroying the enemy’s
planet, only to learn then that the battles were very real and a
real planet has been destroyed.
Many of us got involved in computing because programming was fun.
The benefits of computing seemed intuitive to us. We truly believe
that computing yields tremendous societal benefits; for example,
the life-saving potential of driverless cars is enormous! Like
Ender, however, we realized recently that computing is not a
game–it is real–and it brings with it not only societal benefits,
but also significant societal costs, such as labor polarization,
disinformation, and smart-phone addiction.
The common reaction to this crisis is to label it as an “ethical
crisis” and the proposed response is to add courses in ethics to
the academic computing curriculum. I will argue that the ethical
lense is too narrow. The real issue is how to deal with
technology’s impact on society.
Technology is driving the future, but who is doing the steering?
Moshe Y. Vardi is University Professor and the George
Distinguished Service Professor in Computational Engineering at
Rice University. He is the recipient of several awards, including
the ACM SIGACT Goedel Prize, the ACM Kanellakis Award, the ACM
SIGMOD Codd Award, the Blaise Pascal Medal, the IEEE Computer
Society Goode Award, and the EATCS Distinguished Achievements Award.
He is the author and co-author of over 650 papers, as well as two
books. He is a fellow of several societies, and a member of
several academies, including the US National Academy of
Engineering and National Academy of Science. He holds seven
honorary doctorates. He is a Senior Editor of the Communications
of the ACM, the premier publication in computing.
Joaquim Armando Pires Jorge
11th Lisbon Machine Learning Summer School
LxMLS 2021 will take place July 7th to July 15th in online format (via zoom and slack). It is organized jointly by Instituto Superior Técnico (IST), a leading Engineering and Science school in Portugal, the Instituto de Telecomunicações, the Instituto de Engenharia de Sistemas e Computadores, Investigação e Desenvolvimento em Lisboa (INESC-ID), Unbabel and Cleverly.
Click here for information about past editions (LxMLS 2011, LxMLS 2012, LxMLS 2013, LxMLS 2014, LxMLS 2015, LxMLS 2016, LxMLS 2017, LxMLS 2018, LxMLS 2019, LxMLS 2020) and to watch the videos of the lectures (2016, 2017, 2018, 2020).
Call for Participation
* Application Deadline: May 15, 2021
* Decision: June 1, 2021
* Early Registration: June 15 – July 1, 2021
* Summer School: July 7 – 15, 2021
Topics and Intended Audience
The school will cover a range of Machine Learning (ML) topics, from theory to practice, that are important in solving Natural Language Processing (NLP) problems that arise in the analysis and use of Web data.
Our target audience is:
- Researchers and graduate students in the fields of NLP and Computational Linguistics;
- Computer scientists who have interests in statistics and machine learning;
- Industry practitioners who desire a more in depth understanding of these subjects.
Features of LxMLS:
- No deep previous knowledge of ML or NLP is required, but the attendants are assumed to have some basic background on mathematics and programming
- Lecturers are leading researchers in machine learning and natural language processing (see speakers)
- Days are divided into morning lectures and afternoon lab sessions and practical talks (see schedule)
- The Labs guide will be provided one month in advance. Last year’s guide can be found here
- A day zero is scheduled to review basic concepts and introduce the necessary tools for implementation exercises
- Both basic (e.g linear classifiers) and advanced topics (e.g. deep learning, reinforcement learning) will be covered
Due to the current COVID-19 pandemic, the 11th Lisbon Machine Learning School will be held online (via zoom and slack). Similar to last year, we are excited for the opportunity to create a virtual school, where you will be able to attend all the lectures, and participate in the Q&As and labs remotely. We will also provide the tools for students to engage with each other remotely. The lectures will also be streamed to YouTube, and will become freely available later in our YouTube channel. The Q&A, labs and social activities will remain restricted to the accepted students only.
List of Confirmed Speakers
LUIS PEDRO COELHO Fudan University | China
MÁRIO FIGUEIREDO Instituto de Telecomunicações & Instituto Superior Técnico | Portugal
ANDRE MARTINS Instituto de Telecomunicações & Unbabel | Portugal
IRYNA GULEYVICH Technical University Darmstat | Germany
NOAH SMITH University of Washington & Allen Institute for Artificial Intelligence | USA
SLAV PETROV Google Inc. | USA
XAVIER CARRERAS dMetrics | USA
GRAHAM NEUBIG Carnegie Mellon University | USA
BHIKSHA RAJ Carnegie Mellon University | USA
CHRIS DYER Google Deep Mind | UK
ELIAS BARENBOIM Columbia University | USA
ADELE RIBEIRO Columbia University | USA
STEFAN RIEZLER Institut für Computerlinguistik, Universität Heidelberg | Germany
BARBARA PLANK IT University of Copenhagen | Denmark
SASHA RUSH Cornell Tech | USA
Please visit the webpage for up to date information: http://lxmls.it.pt/2021
To apply, please fill the form in https://lisbonmls.wufoo.com/forms/application-form-lxmls-2021/
Any questions should be directed to: email@example.com.
International European Conference on Parallel and Distributed Computing
The 27th International European Conference on Parallel and Distributed Computing (Euro-Par 2021) will take from August 30 to September 3 2021 in Lisbon.
Euro-Par is the prime European conference covering all aspects of parallel and distributed processing, ranging from theory to practice, from small to the largest parallel and distributed systems and infrastructures, from fundamental computational problems to full-fledged applications, from architecture, compiler, language and interface design and implementation, to tools, support infrastructures, and application performance aspects.
The 2021 edition of Euro-Par will be organized as a collaboration between INESC-ID and Instituto Superior Técnico (IST).
– Abstract Submission: February 5, 2021
– Paper Submission Deadline: February 12, 2021
– Author Notification: April 30, 2021
– Camera-Ready Papers: June 6, 2021
More information is available here.