Facebook’s management obstructed the architect of its recommendation algorithms from mitigating their negative social impact. The social network focused on reining in algorithmic bias against particular groups of users at the expense of efforts to reduce disinformation.

Having dismissed two key researchers, Google restructured its efforts in AI ethics. Marian Croak, an accomplished software engineer and vice president of engineering at Google, will lead a new center of expertise in responsible AI, the company announced.

Datasets for training face recognition models have ballooned in size — while slipping in quality and respect for privacy. In a survey of 130 datasets compiled over the last four decades, researchers traced how the need for increasing quantities of data led researchers to relax their standards.

A panel of AI experts appointed by the U.S. government came out against a ban on autonomous weapons. A draft report from the National Security Commission on Artificial Intelligence recommends against a proposed international global prohibition of AI-enabled autonomous weapon systems.

Amazon is monitoring its delivery drivers with in-vehicle cameras that alert supervisors to dangerous behavior. The online retail giant rolled out a ceiling-mounted surveillance system that flags drivers who, say, read texts, fail to use seatbelts, exceed the speed limit, or ignore a stop sign.

Western governments and institutions struggling to formulate principles of algorithmic fairness tend to focus on issues like race and gender. A new study of AI in India found a different set of key issues.

An algorithm is helping cities locate pipes that could release highly toxic lead into drinking water. BlueConduit, a startup that focuses on water safety, is working with dozens of North American municipal governments to locate lead water lines so they can be replaced.

Computer vision is alerting authorities the moment someone draws a gun. Several companies offer deep learning systems that enable surveillance cameras to spot firearms and quickly notify security guards or police.

An AI-powered collar may help protect wild elephants from poachers, hunters, and other hostile humans. Ten ElephantEdge wireless tracking collars will be fitted onto African elephants next year, TechCrunch reported.

The past year was the first in which general-purpose models became economically useful. GPT-3, in particular, demonstrated that large language models have surprising linguistic competence and the ability to perform a wide variety of useful tasks.

As AI engineers, we have tools to design and build any technology-based solution we can dream of. But many AI developers don’t consider it their responsibility to address potential negative consequences as a part of this work.

The worldwide pandemic and a contentious U.S. election whipped up a storm of automated disinformation, and some big AI companies reaped the whirlwind.

A new database tracks failures of automated systems including machine learning models. The Partnership on AI, a nonprofit consortium of businesses and institutions, launched the AI Incident Database, a searchable collection of reports on the technology’s missteps.

In Argentina, a municipal face recognition system could misidentify children as suspected lawbreakers. Authorities in Buenos Aires are scanning subway riders’ faces to find offenders in a database of suspects but the system mixes criminal records with personal information about minors.

Will AI that discriminates based on race, gender, or economic status undermine the public’s confidence in the technology? Seduced by the promise of cost savings and data-driven decision making, organizations will deploy biased systems that end up doing real-world damage.