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So, Amazon’s ‘AI-powered’ cashier-free shops use a lot of … humans. Here’s why that shouldn’t surprise you

Published

1 month ago

April 11, 2024

so,-amazon’s-‘ai-powered’-cashier-free-shops-use-a-lot-of-…-humans.-here’s-why-that-shouldn’t-surprise-you

This is how these bosses get rich: by hiding underpaid, unrecognised human work behind the trappings of technology
In 2021, when Amazon launched its first “just walk out” grocery store in the UK in Ealing, west London, this newspaper reported on the cutting-edge technologies that Amazon said made it all possible: facial-recognition cameras, sensors on the shelves and, of course, “artificial intelligence”. The first customers queued outside, excited to experience the future. “I am an early adopter,” one of them said. “I can’t wait to see how this new technology works and I think it is going to be everywhere shortly.”
The promise of the “just walk out” stores was that customers would not need to queue for a cashier, scan their own items or even pause on the way out. They could simply take what they needed, walk out the door and the benevolent all-seeing eye of technology would seamlessly price their goods, charge their account and send them a receipt.
The reality was that people were watching Amazon’s customers shop. More than a thousand of them, as reported by The Information, watching the cameras and labelling footage of shoppers. An employee who worked on the technology said that actual humans – albeit distant and invisible ones, based in India – reviewed about 70% of sales made in the “cashier-less” shops as of mid-2022 (Amazon responded that “the characterisation of the role and number of human reviewers is not accurate”). Now, Amazon is reportedly moving away from “just walk out” and rolling out “smart shopping carts” instead (AKA a scanner in your trolley – big whoop).
I can’t stress enough how little of a surprise this should be. First, the fake robot shtick is very, very old. It goes back at least to 1770, and the original “Mechanical Turk”, a chess-playing robot that wowed the courts of Europe for decades until being revealed that it was, in fact, a series of grandmasters hiding in a box. Recent updates include Facebook’s “smart assistant”, M, which claimed to be AI but referred any complex queries to people; and Cruise, the self-driving car company whose operations required remote workers to intervene every two-and-a-half to five miles.
All of these are, separately, quite funny stories. But collectively they paint a picture of a society, and a culture, utterly unequipped to register the violence that is being done to it, merely because historical process is draped in the ribbons of “technology”. This violence is enacted simultaneously on the high street and the global stage. What makes me angry about how often we keep falling for it is not merely that we should know better, but what the costs of doing so actually are.
The national minimum wage in the UK is £11.44. A small grocery store like the Amazon Fresh shops might have half a dozen staff. Assuming all of them were on full wage (unlikely) and all of them were on the lowest wage (ie not managers), the average individual salary would be about £20k and the annual wage bill would be about £130k. When this work is outsourced via video cameras, it is passed to data labellers. Amazon’s remote data labellers might be paid one or two pounds an hour, if they are lucky. If you can replace half a dozen UK staff with half a dozen data labellers in India, Kenya or the Philippines, then the difference in the annual staff bill alone could be almost £100,000 a year.
Jeff Bezos is the second-wealthiest person in the world, worth about $205bn (£163bn). That money doesn’t come out of nowhere. It doesn’t drop out of a pier-end slot machine called, “I learned to code at Princeton and that’s why I’m better than you”. It is the result of deliberately hiding actual work – designing, making, sorting, packing, cooking, farming, delivering – behind little icons on your smartphone screen, in order to devalue it. It is the systematic use of the fake robot trick to lower the value of labour, until people are reportedly sleeping in tents at the factory gates, then banking the difference.
The size of Bezos’s rocket is very precisely determined by the difference in costs between paying a worker in Britain and a worker in India – including all the historically determined racist and colonialist inequality that calculation involves. But make no mistake – Bezos and his ilk will pay a robot even less, as soon as that’s possible. The only lesson of Amazon Fresh is that we are not – quite – there yet.
The fake robot shtick has another purpose too: it’s a distraction. In 2021, Amazon and Google jointly signed a $1.2 billion contract to provide the Israeli state, including the military, with cloud computing and AI systems. While there’s no evidence that Google or Amazon’s technology has been used in killings of civilians, this continuing deal displays a willingness to engage with a military that has killed 30,000 people, and whose use of “AI”-powered targeting allows it to say: “The machine did it.”
“Just walk out” might have had its day, but the elision of consumer comfort and plausible deniability is alive and well on the high street. Tesco opened its first GetGo store in 2021, promising the same kind of checkout-free convenience as “just walk out” – they now operate stores in London, Birmingham and Welwyn Garden City. Tesco boasts that instead of using facial recognition, GetGo creates “skeleton outlines” of you. The underlying technology for the service is provided by Trigo, an Israeli company that boasts that almost all of its engineers were “cherry-picked from elite military units” including Unit 8200, the IDF’s military surveillance agency, and Unit 9900, its specialist surveillance and mapping division. Point-to-point tracking of unknown bodies through built-up space, based on algorithmic analysis of gait and posture? I wonder where they learned to do that.
Source: theguardian.com
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Sainsbury’s aims to be an ‘AI-enabled grocer’ with Microsoft AI technology

Published

2 days ago

May 17, 2024

Peter Tolan

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Sainsbury’s, a prominent UK supermarket chain, is set to leverage Microsoft’s artificial intelligence and machine learning tools to elevate its store operations and provide customers with a more engaging and convenient shopping experience.
As part of its strategic initiative, the ‘Next Level Sainsbury’s strategy’, the supermarket will integrate generative AI, powered by Microsoft Azure, to enhance its online shopping platform and optimize customers’ search experience. By harnessing AI capabilities, Sainsbury’s aims to offer a more interactive and personalized online shopping journey for its millions of customers across the UK.
In addition to enhancing the online shopping experience, Sainsbury’s plans to equip its store colleagues with real-time data and insights to streamline in-store processes such as shelf replenishment. Leveraging multiple data inputs, including shelf-edge cameras, AI technology will guide colleagues on prioritizing restocking activities, thereby improving efficiency and productivity.
Over the next five years, Sainsbury’s will deploy Microsoft Azure to implement these initiatives, integrating data assets with Microsoft 365 collaboration tools to drive innovation and operational excellence.
Clodagh Moriarty, Chief Retail and Technology Officer at Sainsbury’s, expressed confidence in the collaboration with Microsoft, emphasizing its role in accelerating the supermarket’s ambition to become the UK’s leading AI-enabled grocer. Moriarty highlighted the strategic investment in transformative capabilities, aimed at enhancing efficiency, productivity, and customer service while delivering value to shareholders.
Clare Barclay, CEO of Microsoft UK, commended Sainsbury’s visionary approach, noting its commitment to placing AI at the forefront of its business strategy. Barclay expressed enthusiasm for the collaboration, emphasizing its potential to revolutionize the retail experience for both customers and store colleagues.
The partnership between Sainsbury’s and Microsoft signifies a significant step towards ushering in the next generation of retail, powered by innovative AI-driven solutions.
Source: technologyrecord.com
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Researchers build AI-driven sarcasm detector

Published

2 days ago

May 17, 2024

Peter Tolan

Artificial intelligence has made remarkable strides, from passing bar exams to reading bedtime stories with emotion. Yet, despite these feats, it still falls short of matching the intricate nuances of human communication—particularly, the art of sarcasm.
However, researchers in the Netherlands are determined to change that narrative. They have developed an AI-driven sarcasm detector that can discern when sarcasm is being used, a feat previously thought to be exclusive to human cognition.
Matt Coler, from the University of Groningen’s speech technology lab, expresses excitement about the project’s progress. He emphasizes the importance of understanding sarcasm, a pervasive aspect of human discourse, to facilitate seamless communication between humans and machines.
Recognizing sarcasm poses challenges due to its subtlety, especially in text-based interactions where cues like tone and facial expressions are absent. To overcome this, researchers trained their AI using a combination of text, audio, and emotional content from popular sitcoms like Friends and The Big Bang Theory.
The AI, trained on annotated data from these shows, demonstrated an impressive ability to detect sarcasm in unlabelled exchanges from the sitcoms, achieving an accuracy rate of nearly 75%. Further enhancements are underway, including incorporating visual cues like eyebrow movements and smirks, to improve accuracy even more.
Beyond enhancing interactions with AI assistants, this technology holds potential for detecting negative language and identifying instances of abuse or hate speech. However, as AI becomes more adept at understanding sarcasm, questions arise about its potential to wield sarcasm itself.
Coler muses about the implications of machines responding with sarcasm, raising concerns about clarity in communication. Nonetheless, advancements in AI-driven sarcasm detection offer promising prospects for improving human-machine interactions and bridging the gap between artificial and human intelligence.
Source: theguardian.com

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AI, bias and experiments: how Women in News is tackling tech’s inbuilt stereotypes

Published

2 days ago

May 17, 2024

Peter Tolan

Issues surrounding bias in AI are deeply rooted in the accuracy, trustworthiness, and quality of data, which, if overlooked, can significantly skew outcomes. Lyndsey Jones, an AI author and transformation coach, delves into these concerns, offering valuable insights for newsrooms on monitoring and reviewing data.
Madhumita Murgia, an AI journalist and the first artificial intelligence editor of the Financial Times, sheds light on how women, migrants, precarious workers, and minority groups are disproportionately affected by the technical limitations of Generative AI. Murgia emphasizes the lack of representation of these groups in the development process of AI technologies, highlighting the need for inclusive participation.
WAN-IFRA Women In News workshops on the Age of AI in the newsroom have brought bias effects to the forefront. Through the Digital ABCs training program, media professionals are equipped with skills to navigate the digital landscape and drive organizational change.
A newly launched module focuses on AI, with over 100 participants in eastern Europe taking part, now extended to journalists in parts of Africa, the Middle East, and Southeast Asia. Instances of bias surfaced during the training, such as generating offensive avatars and misinterpretation of accents in AI tools.
Google CEO Sundar Pichai’s acknowledgment of biased AI tools reflects ongoing concerns in the industry. Timnet Gebru’s dismissal from Google for highlighting biases further underscores the need for vigilance in addressing these issues.
Diverse teams in WIN’s Age of AI program are experimenting with various tools like fact-checking and enhancing staff skill sets in AI usage. Projects under consideration for further EU funding include a video lab for content amplification and an AI avatar for journalist safety.
Media companies must ensure diverse staff collaboration when testing AI tools. Quotas for women in AI research and cross-border partnerships may be necessary for smaller media groups to compete effectively.
Journalists can take steps to improve content quality by examining storytelling practices and ensuring diversity in sources and representation. Consistency of data collection across departments and assessing biases in data sets are crucial for ethical AI usage in journalism. Ultimately, AI tools should be used to enhance journalism’s quality and integrity, rather than generating clickbait or misinformation.
Source: wan-ifra.org

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