Considering the Impact of Technology on Society
Moshe Vardi on having the difficult conversation about technology and social responsibility.
Research and Advances
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Toward Practices for Human-Centered Machine Learning
Designing for the social, cultural, and ethical implications of ML are just as important as its technical advances.
AI and Neurotechnology: Learning from AI Ethics to Address an Expanded Ethics Landscape
The merging of machine, body, and psyche is on the horizon due to the technological advancements enabled by neuroscience and AI.
(Re)Use of Research Results (Is Rampant)
Prior pessimism about reuse in software engineering research may have been a result of using the wrong methods to measure the wrong things.
HPC Forecast: Cloudy and Uncertain
An examination of how the technology landscape has changed and possible future directions for HPC operations and innovation.
The Lean Data Scientist: Recent Advances Toward Overcoming the Data Bottleneck
A taxonomy of the methods used to obtain quality datasets enhances existing resources.
Proving Data-Poisoning Robustness in Decision Trees
We present a sound verification technique based on abstract interpretation and implement it in a tool called Antidote, which abstractly trains decision trees for an intractably large space of possible poisoned datasets.
Extracting the Essential Simplicity of the Internet
Looking past inessential complexities to explain the Internet's simple yet daring design.
Technical Perspective: Beautiful Symbolic Abstractions for Safe and Secure Machine Learning
"Proving Data-Poisoning Robustness in Decision Trees," by Samuel Drews et al., addresses the challenge of processing an intractably large set of trained models when enumeration is infeasible in a clean, beautiful, and elegant manner.
Technical Perspective: The Impact of Auditing for Algorithmic Bias
"Actionable Auditing Revisited," by Inioluwa Deborah Raji and Joy Buolamwini, examines how companies producing commercial facial classification software responded to the publication of the groundbreaking 2018 "Gender Shades" study.
A review of network science and complexity theory as they apply to the ability of systems to resist stress and recover from faults.
ACE: Toward Application-Centric, Edge-Cloud, Collaborative Intelligence
Constructing a unified platform for the scalable, reliable, robust, and efficient development and deployment of ECCI applications.
Democratizing Domain-Specific Computing
Creating a programming environment and compilation flow that empowers programmers to create their own DSAs efficiently and affordably on FPGAs.
This paper investigates the commercial impact of Gender Shades, the first algorithmic audit of gender- and skin-type performance disparities in commercial facial analysis models.
A Linearizability-based Hierarchy for Concurrent Specifications
Two linearizability-style correctness conditions that can be used to argue safety properties of progressively more concurrent behaviors of objects.
Technical Perspective: The ‘Art’ of Automatic Benchmark Extraction
"DIAMetrics," by Shaleen Deep et al., describes a versatile framework from Google for automatic extraction of benchmarks and their distributed execution and performance monitoring.
Producing Competent HPC Graduates
Employers seek recruits who can apply the knowledge, skill, and culture they acquire in college to solve problems as soon as they enter the workforce.
Subfield Prestige and Gender Inequality among U.S. Computing Faculty
A study of the intersections of gender, race, socioeconomic status, prestige, and subfield structure in computing.
Seeing Beneath the Skin with Computational Photography
Optical imaging technologies hold powerful potential in healthcare.
DIAMETRICS: Benchmarking Query Engines at Scale
This paper introduces DIAMetrics: a novel framework for end-to-end benchmarking and performance monitoring of query engines.
Finding an Alternate Way Forward with AI
Former Googlers Timnit Gebru and Alex Hanna are thinking about outcomes at their Distributed AI Research Institute.
Shape the Future of Computing
ACM encourages its members to take a direct hand in shaping the future of the association. There are more ways than ever to get involved.
Get InvolvedCommunications of the ACM (CACM) is now a fully Open Access publication.
By opening CACM to the world, we hope to increase engagement among the broader computer science community and encourage non-members to discover the rich resources ACM has to offer.
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