Risk of 'Industrial Capture' Looms Over AI Revolution
An anonymous reader shares a report: There's a colossal shift going on in artificial intelligence -- but it's not the one some may think. While advanced language-generating systems and chatbots have dominated news headlines, private AI companies have quietly entrenched their power. Recent developments mean that a handful of individuals and corporations now control much of the resources and knowledge in the sector -- and will ultimately shape its impact on our collective future. The phenomenon, which AI experts refer to as "industrial capture," was quantified in a paper published by researchers from the Massachusetts Institute of Technology in the journal Science earlier this month, calling on policymakers to pay closer attention. Its data is increasingly crucial. [...] The MIT research found that almost 70 per cent of AI PhDs went to work for companies in 2020, compared to 21 per cent in 2004. Similarly, there was an eightfold increase in faculty being hired into AI companies since 2006, far faster than the overall increase in computer science research faculty. "Many of the researchers we spoke to had abandoned certain research trajectories because they feel they cannot compete with industry -- they simply don't have the compute or the engineering talent," said Nur Ahmed, author of the Science paper. In particular, he said that academics were unable to build large language models like GPT-4, a type of AI software that generates plausible and detailed text by predicting the next word in a sentence with high accuracy. The technique requires enormous amounts of data and computing power that primarily only large technology companies like Google, Microsoft and Amazon have access to. Ahmed found that companies' share of the biggest AI models has gone from 11 per cent in 2010 to 96 per cent in 2021. A lack of access means researchers cannot replicate the models built in corporate labs, and can therefore neither probe nor audit them for potential harms and biases very easily. The paper's data also showed a significant disparity between public and private investment into AI technology.
Read more of this story at Slashdot.