(Very good article to discuss. I hope you enjoy, please. Juan Antonio)
Artificial Intelligence Leaves the Research Lab
"Progress in ML in the last decade has been extraordinary and has rekindled the notion that AI systems could eventually reach human levels of performance, which was abandoned for several decades. Even if we are still currently far from this achievement, technological progress in ML has passed a threshold that enables it to have a huge economic impact, estimated to be close to 16 trillion US dollars by 2030 . This contrasts with the first few decades of ML progress, when researchers had the luxury of focusing purely on the fundamental aspects of their work, not worrying too much about its potential societal impacts — an object recognition algorithm could be tested on a common dataset like MNIST  or ImageNet , and an objective performance metric would be obtained in order to measure progress, without having to think about the messiness and complexity of deployment and social impact. Something crucial has changed in recent years, as algorithms initially developed in the lab are increasingly being improved and deployed in society in real-world applications such as healthcare, transportation, and industrial production with real-life consequences, and we are likely seeing just the tip of the iceberg in terms of social impact".
"As researchers and engineers become more conscious of the social impacts of machine learning, we have the opportunity and duty to make our voices heard."
By Alexandra Luccioni on May 7th, 2020 in Commentary, Ethics, Human Impacts, Magazine Articles, Social Implications of Technology, Societal Impact