Karen Hao
technologyreview.com
Originally published 27 Dec 19Here is an excerpt:
Meanwhile, the need for greater ethical responsibility has only grown more urgent. The same advancements made in GANs in 2018 have led to the proliferation of hyper-realistic deepfakes, which are now being used to target women and erode people’s belief in documentation and evidence. New findings have shed light on the massive climate impact of deep learning, but organizations have continued to train ever larger and more energy-guzzling models. Scholars and journalists have also revealed just how many humans are behind the algorithmic curtain. The AI industry is creating an entirely new class of hidden laborers—content moderators, data labelers, transcribers—who toil away in often brutal conditions.
But not all is dark and gloomy: 2019 was the year of the greatest grassroots pushback against harmful AI from community groups, policymakers, and tech employees themselves. Several cities—including San Francisco and Oakland, California, and Somerville, Massachusetts—banned public use of face recognition, and proposed federal legislation could soon ban it from US public housing as well. Employees of tech giants like Microsoft, Google, and Salesforce also grew increasingly vocal against their companies’ use of AI for tracking migrants and for drone surveillance.
Within the AI community, researchers also doubled down on mitigating AI bias and reexamined the incentives that lead to the field’s runaway energy consumption. Companies invested more resources in protecting user privacy and combating deepfakes and disinformation. Experts and policymakers worked in tandem to propose thoughtful new legislation meant to rein in unintended consequences without dampening innovation.
The info is here.
