Communications of the ACM

A developer discovers what happens when you give AIs something to really care about.

Artificial intelligence (AI) currently acts solo or as a human companion in decisions made in several sensitive domains, such as healthcare, finance, and law. AI systems, even those carefully designed to be fair, have been heavily criticized for delivering misjudged and discriminatory outcomes against individuals and groups of people. The continuous unfair and unjust AI outcomes indicate that the…

Bertrand Meyer considers how disputes over intelligence may boil down to definitions.

Creating opportunities for incarcerated people.

Meet the candidates who introduce their plans—and stands—for the Association.

During Automated Program Repair (APR), it can be challenging to synthesize correct patches for real-world systems in general-purpose programming languages. Recent large language models (LLMs) have been shown to be helpful “copilots” in assisting developers with various coding tasks, and have also been directly applied for patch synthesis. However, most LLMs treat programs as sequences of tokens, …

Finding where the trees are in a city and monitoring any changes are essential for sustainable urban management. Historically, urban forests are mainly inventoried via manual processes often limited to public lands. Leveraging advances in computing, we present a novel generative artificial intelligence (AI) method along with a first-ever national-scale dataset, to automatically localize trees in …

Seeking a hybrid social design approach that blends human and AI relationships in socially responsible ways.

Squaring up the grid.

Reimaging professional and educational practices for an AI-augmented future.

Recognizing reader rejoinders.

Oscar M. Bonastre looks at trends shaping the teaching of programming.

The shiniest tool might cut the deepest.

Considering the unique challenges for learning from past geopolitical tensions.

Throttling access to a leading AI tool for drug discovery has spawned many variants and advances. But there is still some way to go.

Large language models (LLMs) have become integral to numerous applications, raising concerns about bias, fairness, and compliance with emerging regulatory frameworks. This article provides a review of some of the most significant risks associated with biased LLM outputs and their broader societal implications. We discuss how regulatory initiatives such as the European Union’s (EU’s) Artificial In…