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AI inventors may find it hard to patent tech under US law • The Register

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Comment Future AI could be a challenge for US Patent and Trademark Office (USPTO) officials, who need to wrap their heads around complex technology that’s perhaps not quite compatible with today’s laws.

Under the Department of Commerce, the USPTO’s core mission is to protect intellectual property, or IP. Creators file patent applications in hope of keeping competitors from copying their inventions without permission, and patents are supposed to allow businesses to thrive with their own novel designs while not stifling wider innovation.

Fast evolving technologies, such as deep learning, are pushing the limits of today’s IP policies and rules. Clerks are trying to apply traditional patent approval rules to non-trivial machine-learning inventions, and bad decisions could result in a stranglehold on competition among public and private AI creators. We all know how overly broad patents on software and other technology can make it past USPTO, causing headaches for years to come.

“AI is already impacting most industries and many aspects of our society,” Kathi Vidal, the agency’s director and a former engineer, said during the inaugural meeting of the AI and Emerging Technologies (ET) Partnership Series held virtually last month.

“AI and emerging technologies have the potential to dramatically improve our day-to-day lives. They will provide countless and unpredictable benefits to our social well-being not just here in the United States, but around the world. But the bottom line is, we need to get this right.

“We need to make sure we’re setting laws, policies and practices that benefit the US and the world.”

Publishing patents disseminates valuable knowledge, giving engineers and scientists ideas on how to advance technologies or invent new ones. Inventors have to meet a list of criteria in order for their applications to be considered. Not only do they have to demonstrate their invention is novel, non-obvious, and useful, they have to describe their work in a way that someone skilled in the same field can understand and reproduce it.

And here’s the rub.

Neural networks aren’t easily explainable. The number-crunching process that seemingly magically transforms input data into an output is often opaque and not interpretable. Experts often don’t know why a model behaves the way it does, making it difficult for patent examiners to assess the nitty-gritty details of an application.

Furthermore, reproducibility is notoriously difficult in machine learning. Developers need access to a model’s training data, parameters, and/or weights to recreate it. Providing this information in a patent application may satisfy examiners, but it may not be in the interests of the inventors or the wider public.

Medical data taken from real patients to train an algorithm that can detect tumors, for example, is sensitive and opens up all sorts of risks if it is handed over for government agency workers to process, publish, and store. Full disclosure of the system may also reveal proprietary information. It may be easier in some cases to not patent the technology at all.

The USPTO previously hit a stumbling block when it came to applying patent law to AI inventions. Mary Critharis, USPTO’s chief policy officer and director for international affairs, noted the acceptance rate for AI patents dropped in comparison to non-AI inventions in 2014 following the US Supreme’s Court decision [PDF] in the Alice Corp vs CLS Bank International case. Justices ruled CLS could not have infringed Alice’s financial computer software patent, because it was too abstract.

Like laws of nature and natural phenomena, abstract ideas can’t ordinarily be patented. The Supreme Court ruling may therefore have had a chilling effect on AI patent applications and acceptance, as they too may have been assumed to be too abstract, at least until further guidance was issued to patent examiners on how to deal with abstract designs.

“[The data] provides some suggestive evidence that the Alice decision impacted AI technologies,” said Critharis.

“The allowance rate stayed below the non-AI application rate until about 2019. The reason for this was that in 2019, the USPTO had issued revised subject matter eligibility guidance,” she continued, referring to the advice discussed here [PDF].

“I think this is the reason why we’re seeing an increase in allowance rates, but there was definitely an impact of the Alice decision on AI related applications.”

As machine learning evolves, and more patents are applied for and picked apart in court, we could see another dip in allowance rates.

Last year, a group of US senators said there is “a lack of consistency and clarity in patent eligibility laws,” and asked the USPTO to clarify what inventions are patentable and why. “The lack of clarity has not only discouraged investment in critical emerging technologies, but also led the courts to foreclose protection entirely for certain important inventions in the diagnostics, biopharmaceutical, and life sciences industries,” they wrote in a letter. 

Clear guidance from the USPTO is helpful in encouraging inventors to file patents more successfully. But advice only goes so far. US courts, ultimately, have the final say in these matters.

And, separately, it’s not clear if and how AI-generated technologies can be patented. Who owns the IP rights of art, music, or writing created using generative models? These creations riff off existing content and can mimic certain styles. Do they violate copyright?

Can these models be listed as inventors if they create content? Current US laws, at least, only recognize IP produced by “natural persons” much to the chagrin of one man. Stephen Thaler sued Andrei Iancu, the former director of the patent office, when his application listing a neural network system named DABUS as an inventor was rejected.

There hasn’t been a significant commercial application of these technologies in a way that will precipitate what will be the next patent war in the sense that there was the sewing machine patent war

It could get interesting if, as some legal experts believe, people start filing patents for inventions devised and optimized by automated machine-learning algorithms. These inventions may not be entirely novel but the way in which they were produced was; will these be accepted, or is it an obvious rejection?

The USPTO cannot definitively answer all these questions; some of these issues will have to be tried and tested in court.

“There haven’t been a lot of court cases on AI yet,” said Adam Mossoff, Professor of Law at the Antonin Scalia Law School at George Mason University, during a panel discussion.

“There hasn’t been a significant commercial application of these technologies in a way that will precipitate what will be the next patent war in the sense that there was the sewing machine patent war, and there was the patent war over fiber optics, and there was the patent war over disposable diapers and everything else. And when that happens, I think we’re going to see a real concern here.”

The UPTSO has asked the public to comment on current policies that describe what inventions can or cannot be patented.

Some people thought the agency was effective at issuing patents and helping protect inventors against patent trolls, while others disagreed and said the agency’s framework stifles innovation for small businesses and startups.

A recent report [PDF] from the agency concluded that everyone did agree on one thing: “The standard for determining whether an invention is patenting should be clear, predictable, and consistently applied.” ®

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Linux 6.0 debuts, missing some Rusty bits • The Register

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Emperor Penguin Linus Torvalds has released the first release candidate for Linux 6.0, but doesn’t mind what you call it.

“After I had already decided to call this kernel 6.0, a few Chinese developers piped up and pointed out that ‘5.20’ is a more wholesome version of the Western ‘4.20’ internet-famous number,” he wrote in his announcement that Linux 6.0 rc1 has been released.

“4.20” is a reference to a day on which some celebrate marijuana, while “5.20” does likewise for magic mushrooms.

“So if you want to call this ‘Linux 5.20’, go right ahead,” Torvalds wrote.

“Because the kernel version numbers really are entirely made up and have no intrinsic meaning.”

That this week’s release has the 6.0 label is still nice to know, as discussion on the Linux kernel mailing list in recent weeks used 5.20 and 6.0 interchangeably.

As The Register has already reported, the release does not make major changes to the kernel but does include many useful updates – such as more RISC-V support, code to drive Intel’s Gaudi accelerators, and improved ACPI handling.

Torvalds lamented some Rust-enabling code didn’t make it into the release.

“I actually was hoping that we’d get some of the first rust infrastructure, and the multi-gen LRU VM, but neither of them happened this time around,” he mused, before observing “There’s always more releases.”

“This is one of those releases where you should not look at the diffstat too closely, because more than half of it is yet another AMD GPU register dump,” he added, noting that Intel’s Gaudi2 Ai processors are also likely to produce plenty of similar kernel additions.

“The CPU people also show up in the JSON files that describe the perf events, but they look absolutely tiny compared to the ‘asic_reg’ auto-generated GPU and AI hardware definitions,” he added.

The release includes 13,099 changed files, 1,280,295 insertions and 341,210 deletions. Torvalds calculated those numbers “just because I was curious and looked.”

He wants you to be curious too – or at least curious enough to test the kernel, because that’s what release candidates are for and this one contains at least one active bug. ®

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Tinder is the most hated app in Ireland

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Ireland is one of 19 countries worldwide that strongly dislikes Tinder. One in five Tweets by Irish people about all apps are negative.

According to Electronics Hub’s analysis of the most hated apps in the world, Tinder is the most loathed app in Ireland.

Irish people are not alone in their hatred for the dating app. Tinder was the most hated app in 19 countries in total, with Canadians, Americans, Nigerians, Kenyans and our neighbours in the UK also singling it out as their least favourite.

Electronics Hub determined the most hated apps in each country by analysing Twitter data. It processed more than 3m geotagged tweets related to 87 social media, dating, mobile games, entertainment, cryptocurrency and money transfer apps.

Researchers calculated the percentage of tweets about each app that were negative using a sentiment analysis tool which identifies whether a tweet has positive, negative or neutral sentiment.

Infographic of the most hated apps in the world by country.

Click to enlarge and see the most hated apps in the world by country. Infographic: Electronics Hub

Ireland was found to be one of the most negative countries when it came to attitudes towards apps. One in five Tweets posted by Irish people about apps were negative, Electronics Hub found.

Despite Irish people’s professed loathing for Tinder, the dating platform tried to play a role in keeping daters safe in the pandemic. It hooked up with the HSE to promote vaccines by adding badges to users’ profiles.

Tinder was only the second-most hated app in the world, with Roblox taking first place. More than 20 countries said the child-targeted gaming app was their most hated app. Other unpopular apps include Snapchat, Disney and Reddit.

Neighbouring countries tend to dislike similar apps, with the Scandinavians professing a dislike for Reddit and South Americans hating e-commerce apps.

Dating apps, meanwhile, are disliked the world over. In Iraq, 71.4pc of all tweets about Tinder are negative, which is the highest out of any country. A state-by-state breakdown of the most hated apps in North America also found Tinder took the top spot in 21 states.

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‘A sweatshop in the UK’: how the cost of living crisis triggered walkouts at Amazon | Industrial action

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Amazon workers say they are working in a “sweatshop” as safety concerns and worries about the cost of living crisis have triggered walkouts at warehouses around the country.

The Observer has spoken to four staff involved in the walkouts, who work at three Amazon warehouses, including Tilbury in Essex, where protests began on 4 August. All say they will struggle to survive this winter with pay rise offers between 35p and 50p an hour – far less than the rate of inflation, which is currently at 9.4%.

The workers, who spoke anonymously for fear of reprisals from Amazon, said they were speaking out to highlight how the firm’s ultra-cheap, ultra-convenient, super-fast delivery model works.

Amazon employs more than 70,000 people in the UK, adding 25,000 staff in 2021 alone. Many work at the company’s 21 fulfilment centres, where some workers say they are asked to carry out long, physical shifts, with difficult targets, for low pay.

Starting pay in Amazon warehouses will shortly be increasing to between £10.50 and £11.45 per hour, depending on location. An Amazon spokesperson said this was a 29% increase in the minimum hourly wage paid to staff since 2018. They said it is also augmented by a comprehensive benefits package worth thousands of pounds a year, and a company pension plan.

But staff say it is too low for the type of work being done and given the current economic crisis, especially at a company that just posted $121bn (£100bn) in revenues in the second quarter of 2022 alone.

“When we heard the news, it was shocking,” said one worker at Amazon’s warehouse in Tilbury. “It’s ridiculous. Inflation is [forecast to reach] 13%, and our salary increases barely 3%.” The worker rents a house with her husband for £1,350 a month without bills. “My salary is £1,600. … I’m lucky I’m married, otherwise I’d be homeless.”

Some staff are seeking a pay rise of £2 an hour from the tech giant.

Hundreds of Amazon employees stop working over disputed pay rise – video

Another worker at Amazon’s warehouse in Tilbury said they were “petrified” about how they would survive this winter. “We had a scenario recently where someone was living in [an] Amazon [warehouse],” he said. “If I’m honest, I can probably see that happening again.

“I can see people staying in the canteen all the time because they can’t afford to go home.”

The worker is protesting against the poor pay offer, as well as conditions that lock staff in cages for entire shifts at the warehouses, from where they pick items to be delivered to customers. (Amazon says the workstations are to protect workers from moving robotics.)

“It’s a Chinese sweatshop in the UK,” said the second worker at Tilbury. “It’s how they set up their model.”

The worker has struggled with his mental health while working for the company. “I’ve realised how bad Amazon is for my mental health,” he said. “The anxiety of going into work, knowing you’ve got to do the same stuff day in, day out, is horrible.”

That concern is echoed by a worker at an Amazon facility near Bristol, who has worked there with his wife for three years. “It was good initially,” the worker said. “There was a lot of safety consciousness, and the targets were pretty reasonable. But now they’re just pushing it higher and higher, and exploiting people.”

Around 100 Amazon staff at Bristol staged a sit-in at the company canteen on 10 August – action for which they say they were docked pay by management at the site. “The vast majority of people went back to work at that point, because at the end of the day, as much as they want to fight for it, they have to think about themselves financially.”

The Bristol warehouse worker says that managers used to stop employees from lifting heavy items from bins on high shelves in the warehouse without a ladder. “If you overstretched yourself for 10 hours, you’d end up with a bad neck and a bad back,” he said.

That has subsequently changed as staff said they felt pressured to meet ever-escalating demand. Staff pushing carts around the warehouse used to be limited to using one cart at a time for safety reasons; now it is claimed managers turn a blind eye to staff pulling two carts at once. “They don’t say nothing because all they care about is getting the work done as fast as possible,” he said. “Safety just goes out the window.”

He says he has personally lifted items weighing up to 25kg by himself, despite rules saying anything heavier than 15kg should be lifted by two people.

A worker at an Amazon facility in the north-west of England said that managers at his warehouse similarly ignored rules around not running on site and lifting down heavy items from high areas in an attempt to meet targets, which at his site require two items to be picked every minute.

Amazon declined to respond to specific claims.

Martha Dark, director at Foxglove, a non-profit organisation working to highlight issues within tech companies that supports Amazon workers, said: “None of the workers we’re supporting wanted to protest.

“They’re desperate and can’t survive on these wages. Meanwhile, Amazon threatens to dock pay and send workers to HR for revealing the truth about life in the warehouse.”

She added: “Amazon needs to respect workers’ rights to organise, stop penalising people who are fighting to survive and provide a real pay rise now.”

Two workers said they plan to leave the company because of the conditions and pay. However, some hope to stay put – to change things.

“If a lot of us who are experienced leave Amazon at this point they’ll get a new group of people in who they can mould into this depressing way of work,” said the Bristol worker. “That’s the problem.”

This article was amended on 14 August 2022. Inflation is at 9.4%, not 13% as stated in an earlier version; the latter is a forecast rate.

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