Inherent Limitations of AI Fairness
AI fairness should not be considered a panacea: It may have the potential to make society more fair than ever, but it needs critical thought and outside help to make it happen.
Research and Advances
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Shortcut Learning of Large Language Models in Natural Language Understanding
Shortcuts often hinder the robustness of large language models.
On Specifying for Trustworthiness
As autonomous systems increasingly become part of our lives, it is crucial to foster trust between humans and these systems, to ensure positive outcomes and mitigate harmful ones.
What Should We Do when Our Ideas of Fairness Conflict?
Standards for fair decision making could help us develop algorithms that comport with our consensus views; however, algorithmic fairness has its limits.
10 Things Software Developers Should Learn about Learning
Understanding how human memory and learning works, the differences between beginners and experts, and practical steps developers can take to improve their learning, training, and recruitment.
Understanding and handling interference across multiple active cameras.
Theoretical Analysis of Edit Distance Algorithms
To what extent have the techniques for theoretical analysis of edit distance algorithms achieved their goals?
Data Analytics Anywhere and Everywhere
Mobile, ubiquitous, and immersive computing appear poised to transform visualization, data science, and data-driven decision making.
Informatics Higher Education in Europe: A Data Portal and Case Study
A discussion on the need for coordinated, governed, data-driven computing education initiatives of the future.
Scrambled Features for Breakfast: Concepts of Agile Language Development
Describing a framework to support simpler development of languages best suited to express the problems and solutions of each particular domain.
Low-code has the potential to empower more people to automate tasks by creating computer programs.
Show It or Tell It? Text, Visualization, and Their Combination
When communicating information, language should be considered as co-equal with visualization.
A conceptual framework and research agenda for neural rendering of realistic digital faces.
An effort to bring artificial intelligence into better alignment with our moral aims and finally realize the vision of superior decision making through AI.
Developing tools that better complement natural human capabilities to support a more human-centered vision.
How Many Ways Can You Teach a Robot?
ACM Prize recipient Pieter Abbeel is working to help robots learn, and learn to improve.
A Computational Inflection for Scientific Discovery
Enabling researchers to leverage systems to overcome the limits of human cognitive capacity.
A Tale of Two Markets: Investigating the Ransomware Payments Economy
A data-driven, follow-the-money approach to characterize the ransomware ecosystem uncovers two parallel ransomware criminal markets: commodity ransomware and Ransomware as a Service (RaaS).
The Principles of Data-Centric AI
Uniting data-centric perspectives and concepts to trace the foundations of DCAI.
Data Science–A Systematic Treatment
While the success of early data-science applications is evident, the full impact of data science has yet to be realized.
Theoretical Analysis of Sequencing Bioinformatics Algorithms and Beyond
A case study reveals the theoretical analysis of algorithms is not always as helpful as standard dogma might suggest.
Fusing Creativity and Innovation in Asia’s Manufacturing Industry
The Kawahara Universal Information Network Project explores the technologies needed for the next generation of the Internet of Things and HCI.
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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