It’s not surprising that patent filings related to AI are increasing. In 2012, neural networks suddenly became a hot topic of interest from tech companies, after they enabled big improvements in speech and image recognition. But the moves to lock up technology contrast with the emphasis on openness in companies’ public discussion of their AI strategies.

The patent-filing surge recalls the fierce battles over intellectual property in the last big tech revolution, around smartphones. Apple and Samsung have fought at least 50 lawsuits over technology and designs for smartphones, according to the NBER paper; Apple and Google tussled in about 20.

More patents filed in a particular area make lawsuits more likely, says Richard Abramson, a Stanford lecturer who previously was general counsel at independent research institute SRI. “If you give everybody a gun you can pretty much bet the incidence of shooting is going to rise,” he says.

Litigation over AI could harm the open progress tech giants say they want. Twenty-five years ago, patent suits were mostly disputes between companies fighting to use specific technology in their products, Abramson says. Today many are brought by companies, often dubbed “trolls,” holding patents they don’t plan to use for anything but extracting compensation. “Now companies are freaked out by patent troll activity, and a lot of them stockpile patents in order to have something to shoot back,” he says.

There’s no indication yet that any of the leading AI companies are working to leverage their AI patents. Spokespeople for Google and DeepMind both said that their companies hold patents defensively, not with the intent to start fights with others. Google’s spokesperson also noted that the company accounts for a small minority of recent AI-related filings. A Facebook spokesperson said its filings shouldn’t be read to indicate current or future plans. IBM’s chief patent counsel, Manny Schecter, said the company’s patent horde reflects its investment in fundamental research.

Those statements leave room for future changes in policy. Given the recent history of fights over tech patents, some researchers still worry the AI patents piling up could be used in ways that could stifle progress. Assessing the value and scope of patents is complex, and even expert interpretations can vary. But some of the applications filed by Google and others appear to describe fundamental techniques with broad applications in research, says Miles Brundage, who researches trends in AI development at the University of Oxford. “It’s not had an impact yet, but this might be a ticking time bomb,” he says.

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DeepMind, the Alphabet unit behind the AlphaGo software that defeated a world champion at Go, has filed applications including on DQN, an extension to a learning algorithm originating in the 1980s that helped DeepMind software master Atari games. Since DeepMind published academic work on DQN, researchers elsewhere have explored and extended its insights.

Google has a patent pending on dropout, a now-standard technique used to help neural networks generalize to new data they were not trained on. One Facebook application covers an approach to designing neural networks dubbed memory networks, which enhance a conventional machine-learning system for processing text with a kind of short-term memory.

Mark Riedl, a professor at Georgia Institute of Technology currently on leave to work at Salesforce’s AI research group in Palo Alto, says patents on algorithms and other fundamental machine-learning techniques make him uneasy. The patents filed so far haven't yet caused problems for researchers, but assigning legal ownership of relatively abstract ideas doesn’t fit with the open progress that has lately made machine learning so exciting, he says.

Not all the patents recently filed on AI ideas and techniques will be awarded. Patents on software have become harder to get since a 2014 Supreme Court ruling that merely implementing an idea on a computer isn’t enough to make it patentable. And last year, USPTO significantly expanded the number of examiners dedicated to scrutinizing AI patents, something expected to screen out more applications.