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Robotic Automations

Dyson’s new AR feature shows where you have (and haven’t) vacuumed | TechCrunch


If this had been announced exactly a week prior, it would have been easy to mistake for some corporate April Foolery. Dyson, however, assures us that augmented reality vacuuming is real and coming in June — slightly belated for spring cleaning, sadly.

When it launches over the summer, CleanTrace will be available for the Dyson Gen5detect system. The press photos bely the technology a bit, as it will be geared at phones, rather than, say, an Apple Vision Pro or Meta Quest headset. While it seems like that sort of heads-up AR would be possible, one ultimately questions how many people are going to want to vacuum with a computer on their heads.

The system is a bit silly and wildly unnecessary, but that’s sort of the fun of it, no? It’s not going to tip over anyone who’s on the fence about a $700 ultra-premium vacuum, but this is hardly the most ridiculous thing Dyson has shown the world.

The company says the feature was influenced by its own robot vacuum mapping. “We realized that we could all learn a thing or two from the methodical cleaning approach of our robot vacuums,” Dyson VP of engineering Charlie Park notes. “Unlike most humans doing the cleaning, Dyson robots know where they are in the room, where they have been, and where they have yet to go.”

In the demos, the system creates a purple (Dyson’s color) overlay, showing the path the vacuum has taken up to that point. The objective is to turn the entire room that color, to ensure that you’ve hit all the spots, rather than simply relying on your technologically out of date eyeballs.

As someone who vacuums nearly every morning I tend to believe Dyson when it notes, “Our research shows that consumers regularly overestimate the amount of time they clean – data shows that around 80% of cleaning sessions last less than 10 minutes, yet people claim they vacuum for an average of 24 minutes per session.”

What that statement ultimately comes down to is that most people hate vacuuming, because most people hate housework. As such, we tend to dramatically overestimate the amount of time we spend doing it each day. And hey, if CleanTrace can save a little time and make the process more efficient, good on it. Should it ultimately prove popular with users, can vacuum gamification be that far off?




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Robotic Automations

Microsoft's $1.5B check for G42 shows growing US-China rift | TechCrunch


As the Gulf region gains growing strategic importance for the tech war between the U.S. and China, Microsoft makes a big move into one of its richest oil countries.

On Monday evening, Microsoft announced a $1.5 billion strategic investment in G42, the Abu Dhabi-based company that has become a major force in the United Arab Emirates’ ambition to be a global leader in artificial intelligence. The minority stake will give Brad Smith, Microsoft’s vice chair and president, a seat on G42’s board of directors.

The deal signifies much more than a mere commercial collaboration between two AI titans. It serves as evidence of the two countries’ strategic positioning amid rising geopolitical tensions.

The funding comes amid U.S. politicians’ escalating concerns over G42’s ties with China. In January, the bipartisan-select House Select Committee on the Chinese Communist Party sent a letter to Commerce Secretary Gina Raimondo calling for the inclusion of G42 on the Entity List, which would bar the Emirati company from accessing sensitive U.S. technologies.

Such a move would put G42 under the same security concerns umbrella as Huawei, which was placed on the Entity List in 2019 and has since been restricted from acquiring critical U.S. technologies, including high-end chips and certain Android services.

Now, the Microsoft deal is a judgment on which superpower G42 has aligned itself with.

Delicate dance

As the UAE navigates a delicate balance between the U.S. and China, its AI poster child G42 has inevitably become a proxy in the tech rivalry between the two superpowers. Though a long-time economic and military ally of the U.S., the UAE has in recent times diverged from Washington’s foreign policy and expanded its partnerships with China, a development that worries Washington.

Last year, the UAE’s president Mohamed bin Zayed attended Russia’s flagship economic forum, which was largely shunned by Western countries in protest of the Ukraine war. The UAE has also increased military cooperation with China, including a plan for their first joint air force training last year.

On the business side, the UAE is attracting Chinese venture capitalists and entrepreneurs who are increasingly excluded from the U.S. market. General managers of Chinese funds have turned to the UAE and its affluent Middle Eastern neighbors for capital as American limited partners retreat from China. Riding on the UAE’s commitment to electrify its economy, China’s electric vehicle manufacturers have been aggressively peddling plug-in models in the market. Last year, premium EV maker Nio secured a handsome $738.5 million investment from an Abu Dhabi-backed fund.

Given the two countries’ increasing economic ties, it’s no surprise that G42, the AI poster child of the UAE, has also forged ties with Chinese firms. What appears to be commercial relationships, however, have greatly concerned U.S. politicians.

In its letter to Raimondo, the House Select Committee on the CCP noted that G42 maintains relationships with companies like Huawei, biotech giant Beijing Genomics Institute (BGI) and Tencent.

The Committee also highlighted the background of G42’s CEO Peng Xiao, who previously held a senior position at a subsidiary of DarkMatter, a company that develops “spyware and surveillance tools that can be used to spy on dissidents, journalists, politicians, and U.S. companies.”

Given these alleged Chinese ties, the Committee is concerned that G42 can be a way for Chinese firms to access U.S. technologies that are otherwise under export control. G42 and its affiliates maintain “extensive commercial relationships” with companies including Microsoft, Dell, and OpenAI.

Picking side

The deal between the two private tech giants represents an uncommon case involving overt backing from their respective governments. According to the announcement, this “commercial partnership is backed by assurances to the U.S. and UAE governments through a first-of-its-kind binding agreement to apply world-class best practices to ensure the secure, trusted, and responsible development and deployment of AI.”

If the deal goes through, it will designate Microsoft as G42’s official cloud partner. Under the agreement, the Emirati company’s data platform and other key technology infrastructure will migrate to Microsoft Azure, which will power G42’s AI product development. G42 already has a partnership with OpenAI that commenced in 2023.

The partnership with Microsoft appears to be a continuation of G42’s ongoing effort to pare back its Chinese influence. The firm has divested from its China-related investments, including TikTok parent ByteDance, and Xiao said late last year that the firm had plans to phase out Chinese hardware because “We cannot work with both sides.”

What Microsoft gains in return is extensive market access to the region, where its AI business and Azure will be implemented across a range of industries like financial services, healthcare, energy, government and education. The partnership will also see the pair launching a $1 billion fund “for developers to boost AI skills” in the UAE and the broader region.

As tech companies have learned in the past few years, it’s become increasingly difficult to avoid picking a side — whether in terms of technology solutions, markets or capital — between the U.S. and China. The developments around G42 demonstrate that even a country like the UAE, which has sought to be a neutral ground between the two rival nations, will ultimately be forced to take a side.




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Robotic Automations

YC's latest Demo Day shows fascinating wagers on healthcare, chip design, AI and more | TechCrunch


The second half of Y Combinator’s Winter 2024 cohort presented on Thursday, once again bringing dozens and dozens of new startups before a chunk of the venture investing community. As we did on Wednesday, a number of the TechCrunch crew watched the entire run of presentations, picking out a handful of favorites to highlight.

Enjoy our favorites from the second round of Y Combinator demos while we go out and buy another few pots of coffee. To work!

TechCrunch’s staff favorites

Atopile

  • What it does: Lets electrical engineers design circuit boards using code
  • Why it’s a fave: Lots of electrical engineering work on circuit boards is done via GUIs. Who knew? Not this writer, which is why Atopile piqued my interest immediately. The startup, co-founded by Matt Wildoer, Timothée Peter and Narayan Powderly, aims to bring design reuse, version control and automation to hardware design — aspects that the trio claims are seriously lacking in existing design tools. Instead of forcing electrical engineers to draw schematics by hand and validate every small change on test benches, Atopile captures a product’s requirements using a custom programming language and, from there, builds and validates the necessary manufacturing files. Nifty.
  • Who picked it: Kyle

Scritch

  • What it does: A platform for vets to run their practices
  • Why it’s a fave: So, platforms to run vet businesses aren’t new, as I’ve discovered after a cursory Google search (or a few). BUT, Scritch’s co-founders — Claire Lee and Rachel Lee — say that what makes theirs different is a heavy reliance on automation. Scritch handles scheduling, billing and clinical workflows as well as inventory management and care coordination. In addition, the platform supports vet customers by filing insurance claims on their behalf — which sounds like a very attractive feature for this would-be pet owner.
  • Who picked it: Kyle

Lantern

  • What it does: Postgres vector search tool
  • Why it’s a fave: If you cover the AI world at all, you’ve heard of vectors. There are companies like Semi that have raised lots of capital for their own open source vector database software, for example. Lantern sells a hosted Postgres vector database on its own Lantern Cloud. Its pitch: their product is cheaper than a similar offering from AWS. Continuing my hunt for the startups that might make lots of picks-and-shovels money from the AI boom, I’m adding Lantern to the list.
  • Who picked it: Alex

Paradigm

  • What it does: AI agents for task automation
  • Why it’s a fave: There has been lots of talk about using AI to replace workers who execute repetitive tasks. More interesting in the near-term are AI tools that help those same workers do more, faster. That’s what Paradigm is building for the marketing and sales market use cases, with a human-in-the-loop angle. I’ve spent enough time with business development representatives and account executives to know that the market for this tech could be huge.
  • Who picked it: Alex

Just words

  • What it does: GenAI to help companies write better
  • Why it’s a fave: When Just Words founder Neha Mittal worked at Twitter and Pinterest she discovered that minor word changes in user-facing communications had a big impact on engagement rates. That tracks with what I’ve learned writing online. The startup’s plan to bring a similar sort of boost to customers may prove popular; I chose it as a favorite because it fits neatly into a theme I have noticed since the rise of ChatGPT and similar services: people hate writing. They don’t want to do it! So, tools that help people not write are going to be big.
  • Who picked it: Alex

Pythagora

  • What it does: Builds apps and refines them from text prompts
  • Why it’s a fave: I love two things about this. First, it has $47,000 worth of monthly recurring revenue — $564,000 ARR — from 140 customers in less than a quarter. That’s a lot, quickly. And second, because of the way that it describes an interactive approach to app development, in which you answer questions and then it codes up what you have in mind. I am downloading Visual Studio to give this a try, but the concept itself is very appealing to me, someone who has not really written code since high school. (Later in the day, Marblism shared a related pitch that I would be remiss to not include here.)
  • Who picked it: Alex

CommodityAI

  • What it does: AI-power shipment management for commodities trading
  • Why it’s a fave: Trading commodities involves cross-border communication, strict adherence to import laws and a lot of paperwork. CommodityAI’s mission — to bring all the invoices and paperwork involved in commodities trading online and add a collaboration layer on top of it — makes a lot of sense. This seems like a big improvement over parties having to call each other in other countries to double-check numbers and data on paper documents — if they can find them.
  • Who picked it: Becca

Kopia

  • What it does: Partners with apparel retailers to allow shoppers to try on clothes virtually
  • Why it’s a fave: I don’t love buying clothes online because it’s hard to predict what items will look like on my body, and sending packages back is a pain. Kopia wants to help consumers visualize how outfits will fit by dressing an avatar that mimics the person’s body type. Other startups have tried the idea of a virtual fitting room, but I still haven’t seen these tools available on shopping sites. Will Kopia’s product pique retailers’ interest? Hard to say, but I hope that they or another company figures this out because I sure need a wardrobe update.
  • Who picked it: Marina

Care Weather

  • What it does: More accurate weather data using low-cost flat satellites
  • Why it’s a fave: Getting weather forecasts correct is incredibly important because inclement weather can affect people, structures and supply chains. I really like that this company is not only trying to make weather forecasts more accurate, but that it’s doing so by building less-expensive satellites. The company says its tech is 17x more accurate for predicting weather outcomes than existing systems — a lofty statement. Even if it’s not as accurate as the startup claims, I’m a fan of anything that will better help me predict when my building’s basement is going to flood.
  • Who picked it: Becca

Miden

  • What it does: Infrastructure for card issuer processing and core banking for businesses in Sub-Saharan Africa
  • Why it’s a fave: Technology for Sub-Saharan Africa is not something you hear of often in startup land; tech for B2B companies located in that region is even less common. Building fintech infrastructure so that companies can issue cards, or even just file expense reports, seems like a smart foundation for the company to get customers and then expand into other fintech products. The tech Miden is building is clearly in demand: The startup said it is already profitable and seeing strong traction so far.
  • Who picked it: Becca

Oma Care

  • What it does: Helps pay family caregivers.
  • Why it’s a fav: The caregiving market is growing, and there is a massive opportunity — and demand — to make such a daunting experience flow a bit easier. I liked this app because there have been studies that show that caregiving duties most often fall on women, as they are more than twice as likely to be caregivers compared to men. Most often, they do not get paid for this, adding to the stat that women’s unpaid labor globally is worth more than $10 trillion. I welcome anything that tries to address this issue, and I’m excited to see more innovation in this space.
  • Who picked it: Dom

Garage

  • What it does: Marketplace for used fire-fighting equipment
  • Why it’s a fave: This is such a neat idea! Outfitting one firefighter costs a couple thousand dollars, so creating a way for these departments to get gear without spending a lot of money seems smart. That’s especially true, considering you wouldn’t want budget concerns to prevent fire stations from getting their firefighters the safest gear. Sometimes good ideas for technology aren’t complicated.
  • Who picked it: Becca

PointOne

  • What it does: Al-powered time tracking and billing for lawyers
  • Why it’s a fave: PointOne co-founder Adrian Parlow, who was previously an attorney at Fenwick & West, says that one of the worst parts of being a lawyer is having to track time in six-minute increments. I am not a lawyer or a paralegal, but I imagine figuring out how many fractions of an hour went to each client is tedious and time-consuming. PointOne claims that advances in AI can automate timesheet generation by capturing work done on lawyers’ laptops and computers. I am a big fan of all applications that reduce professionals’ busy work. Now can somebody figure this out for filing expenses?
  • Who picked it: Marina


Software Development in Sri Lanka

Robotic Automations

MIT tool shows climate change could cost Texans a month and a half of outdoor time by 2080 | TechCrunch


There are a lot of ways to describe what’s happening to the Earth’s climate: Global warming. Climate change. Climate crisis. Global weirding. They all try to capture in different ways the phenomena caused by our world’s weather systems gone awry. Yet despite a thesaurus-entry’s worth of options, it’s still a remarkably difficult concept to make relatable.

Researchers at MIT might finally have an answer, though. Instead of predicting Category 5 hurricanes or record heat days, they’ve developed a tool that allows people to see how many “outdoor days” their region might experience from now through 2100 if carbon emissions growth remains unchecked.

The results might be alarming or comforting, depending on where you live.

For people in California or France or Germany, things don’t look so bad. The climate won’t be quite as hospitable in the summers, but it’ll grow a little bit more clement in the spring and fall, adding anywhere from a few days to nearly a month of outdoor weather compared with historical records. The U.K. will be even better off, gaining 40 outdoor days by the end of the century.

Not everyone will come out ahead, though. Some temperate places like New York, Massachusetts, China and Japan will lose a week or more of outdoor days. Elsewhere, the picture looks even more dire. Illinois will lose more than a month of outdoor days by the 2080s as the summers grow unbearably hot. Texas will lose a month and a half for the same reason.

Yet it’s the countries with some of the most vulnerable populations that’ll suffer the most (as scientists have been warning). Nigeria’s summers will grow even hotter and longer, lopping off nearly two months of outdoor days. India will lose almost two and a half months.

It doesn’t have to be that way. Even if the world fails to reach net zero carbon emissions by 2050 — but still manages to by 2070 — the situation will improve dramatically. Both Nigeria and India would only lose one month of outdoor days, and more northerly regions would retain some of their added outdoor days.

Assessing risk

The MIT tool is a relatable application of a field of study known as climate scenario analysis, a branch of strategic planning that seeks to understand how climate change will impact various regions and demographics. It’s not a new field, but as advances in computational power have fostered more sophisticated climate models, it has become more broadly applicable than before.

A range of startups are using this relatively newfound predictive capability to help give shape to an uncertain future.

Many startups in the space are focused on tackling that uncertainty for investors, lenders and insurers. Jupiter Intelligence, Cervest and One Concern all focus on those markets, supplying customers with dashboards and data feeds that they can tailor to regions or even assets of interest. The startups also determine the risk of flood, wildfire and drought, and they’ll deliver reports detailing risk to assets and supply chains. They can also crank out regulatory disclosures, highlighting relevant climate risks.

Investors and insurers are sufficiently worried about how climate change will affect assets and supply chains that these startups have attracted some real cash. Jupiter intelligence has raised $97 million, according to PitchBook, while Cervest has raised $43 million and One Concern has brought in $152 million.

While major financial institutions are an obvious customer base for climate forecasting companies, other markets exposed to the outdoors are also in need of solutions.

ClimateAI is targeting agriculture, including agribusiness, lenders, and food and beverage companies, all of which have watched as droughts, floods and storms have decimated crops. As a result, water risk assessment is a key feature of ClimateAI’s forecasts, though it provides other weather and climate-related data, too. The startup has raised $37 million so far, per PitchBook.

Sensible Weather is working on markets that are a little closer to home for most of us. It provides insurance for people embarking on outdoor events and activities, from live concerts to camping and golfing. It works with campgrounds, golf courses, live event operators and more, allowing them to give customers an option to insure their outing against inclement weather. It’s an approach that’s landed the startup $22 million in funding, according to PitchBook.

As more businesses and consumers become aware of how climate change is affecting their lives, their demand for certainty will create a wealth of new markets that will offer these startups and their peers ample opportunity to expand. Climate scenario analysis, once a niche limited to academic labs and insurance companies, appears poised to enter the mainstream.


Software Development in Sri Lanka

Robotic Automations

Exclusive: Footage from 2020 shows Astra rocket exploding during prelaunch testing


Footage obtained by TechCrunch shows the catastrophic ending that Astra’s Rocket 3.0 suffered during prelaunch testing in March 2020.

The explosion, which occurred at Alaska’s Pacific Spaceport Complex, was simply reported as an “anomaly” at the time, an industry term for pretty much any issue that deviates from the expected outcome.

“I can confirm we had an anomaly on the launch pad,” Alaska Aerospace CEO Mark Lester told local reporters at the time. “We are executing our emergency checklist. We request everyone stay clear of the area to allow our crew to address the situation.”

Meanwhile, Astra CEO Chris Kemp told TechCrunch at the time that the rocket “suffered an anomaly following an otherwise successful day of testing in Kodiak in preparation for a launch this week.” He added that the company’s hardware “was the only thing harmed.” He told a separate publication that the company would not be attempting a launch after that week, and that it would “wait until conditions with coronavirus improve before making another attempt” — when in actuality, there was no longer a rocket to launch.

The video clip shows the micro launcher burst into flames. It’s clear the vehicle did not survive. It would have been Astra’s third orbital launch attempt.

At the time, Astra was taking such failures in stride. When the company emerged from stealth earlier that year, it did so with a conviction that it could build rockets at such a high volume, and at such a low price, that some amount of failure could be priced in: 100% reliability was not the end goal. That’s how Kemp summed it up in a May 2022 interview: “The expectation I think that a lot of people have is every launch has to be perfect,” he said. “I think what Astra has to do, really, is we have to have so many launches nobody thinks about it anymore.”

Astra went on to reach orbit for the first time in November 2021, and a second time in March 2022.

Astra had been one of the biggest success stories for space industry investors, with the startup going public in July 2021 at a $2.1 billion valuation after raising nearly $500 million for its ultra-low-cost launch plans. But those plans failed to materialize, and after months of burning cash, Astra’s board quietly accepted a take-private deal from Kemp and CTO Adam London at a stock price of just $0.50 per share. The deal is expected to close sometime this quarter, at which time Astra will cease trading on the Nasdaq.

Astra did not return a request for comment on the 2020 launch failure.


Software Development in Sri Lanka

Robotic Automations

A new games-focused VC in Turkey shows the industry there continues to gain steam | TechCrunch


Turkey has gained a well-earned reputation as being a veritable cauldron of mobile games startups, leading to the rise of VCs dedicated to the sector. The latest to join this coterie is Laton Ventures, a new gaming-focused VC that has raised a $35 million fund. Founding partner — and solo GP — Görkem Türk says he’s aiming to build a bridge between the Turkish gaming ecosystem and the rest of the world, investing in the pre-seed and seed stages. The fund is legally domiciled in the Netherlands.

As an emerging market with a young population, Turks have eaten up mobile games as fast as they can be produced, giving rise to over 740 gaming startups. More than 48% of the 86 million people in Turkey are under the age of 30 and over 92% of internet users play games in Turkey compared to the world average of 82%.

Indeed, between 2018 and 2022, Turkish gaming startups raised more than $1 billion in funding.

Admittedly, Laton has some competition. There are now at least 25 VC funds that invest in video game startups based out of Turkey. That said, most invest in other tech sectors as well.

Türk, who is a former gaming and startups industry manager at Google, explained to me in a call that Laton plans to stand apart by emphasizing operational advisory to its portfolio companies.

“We’re positioning as a bridge between the Turkish gaming ecosystem, which is booming, and the international gaming ecosystem. Secondly, we will double down on operational support in areas like user acquisition, game design, cohort analysis, development, and so on. We’re backed by over 20 exited founders. That really sets us apart,” he said.

The fund has already invested in five companies in the past six months: Two in Turkey, two in Europe and one in the U.S., and plans to leverage its veteran industry adviser network.

To that end, Laton’s LPs include Mehmet Ecevit, co-founder of Gram Games; Mert Gür, founder of Loop Games; Mert Can Kurum, founder of Ruby Games; Fırat İleri, managing partner of Hummingbird Ventures; Nevzat Aydın, founder of Yemeksepeti; and Eric Kress, founder of Gossamer.


Software Development in Sri Lanka

Robotic Automations

Uber Eats courier's fight against AI bias shows justice under UK law is hard won | TechCrunch


On Tuesday, the BBC reported that Uber Eats courier Pa Edrissa Manjang, who is Black, had received a payout from Uber after “racially discriminatory” facial recognition checks prevented him from accessing the app, which he had been using since November 2019 to pick up jobs delivering food on Uber’s platform.

The news raises questions about how fit U.K. law is to deal with the rising use of AI systems. In particular, the lack of transparency around automated systems rushed to market, with a promise of boosting user safety and/or service efficiency, that may risk blitz-scaling individual harms, even as achieving redress for those affected by AI-driven bias can take years.

The lawsuit followed a number of complaints about failed facial recognition checks since Uber implemented the Real Time ID Check system in the U.K. in April 2020. Uber’s facial recognition system — based on Microsoft’s facial recognition technology — requires the account holder to submit a live selfie checked against a photo of them held on file to verify their identity.

Failed ID checks

Per Manjang’s complaint, Uber suspended and then terminated his account following a failed ID check and subsequent automated process, claiming to find “continued mismatches” in the photos of his face he had taken for the purpose of accessing the platform. Manjang filed legal claims against Uber in October 2021, supported by the Equality and Human Rights Commission (EHRC) and the App Drivers & Couriers Union (ADCU).

Years of litigation followed, with Uber failing to have Manjang’s claim struck out or a deposit ordered for continuing with the case. The tactic appears to have contributed to stringing out the litigation, with the EHRC describing the case as still in “preliminary stages” in fall 2023, and noting that the case shows “the complexity of a claim dealing with AI technology”. A final hearing had been scheduled for 17 days in November 2024.

That hearing won’t take place after Uber offered — and Manjang accepted — a payment to settle, meaning fuller details of what exactly went wrong and why won’t be made public. Terms of the financial settlement have not been disclosed, either. Uber did not provide details when we asked, nor did it offer comment on exactly what went wrong.

We also contacted Microsoft for a response to the case outcome, but the company declined comment.

Despite settling with Manjang, Uber is not publicly accepting that its systems or processes were at fault. Its statement about the settlement denies courier accounts can be terminated as a result of AI assessments alone, as it claims facial recognition checks are back-stopped with “robust human review.”

“Our Real Time ID check is designed to help keep everyone who uses our app safe, and includes robust human review to make sure that we’re not making decisions about someone’s livelihood in a vacuum, without oversight,” the company said in a statement. “Automated facial verification was not the reason for Mr Manjang’s temporary loss of access to his courier account.”

Clearly, though, something went very wrong with Uber’s ID checks in Manjang’s case.

Pa Edrissa Manjang (Photo: Courtesy of ADCU)

Worker Info Exchange (WIE), a platform workers’ digital rights advocacy organization which also supported Manjang’s complaint, managed to obtain all his selfies from Uber, via a Subject Access Request under U.K. data protection law, and was able to show that all the photos he had submitted to its facial recognition check were indeed photos of himself.

“Following his dismissal, Pa sent numerous messages to Uber to rectify the problem, specifically asking for a human to review his submissions. Each time Pa was told ‘we were not able to confirm that the provided photos were actually of you and because of continued mismatches, we have made the final decision on ending our partnership with you’,” WIE recounts in discussion of his case in a wider report looking at “data-driven exploitation in the gig economy”.

Based on details of Manjang’s complaint that have been made public, it looks clear that both Uber’s facial recognition checks and the system of human review it had set up as a claimed safety net for automated decisions failed in this case.

Equality law plus data protection

The case calls into question how fit for purpose U.K. law is when it comes to governing the use of AI.

Manjang was finally able to get a settlement from Uber via a legal process based on equality law — specifically, a discrimination claim under the U.K.’s Equality Act 2006, which lists race as a protected characteristic.

Baroness Kishwer Falkner, chairwoman of the EHRC, was critical of the fact the Uber Eats courier had to bring a legal claim “in order to understand the opaque processes that affected his work,” she wrote in a statement.

“AI is complex, and presents unique challenges for employers, lawyers and regulators. It is important to understand that as AI usage increases, the technology can lead to discrimination and human rights abuses,” she wrote. “We are particularly concerned that Mr Manjang was not made aware that his account was in the process of deactivation, nor provided any clear and effective route to challenge the technology. More needs to be done to ensure employers are transparent and open with their workforces about when and how they use AI.”

U.K. data protection law is the other relevant piece of legislation here. On paper, it should be providing powerful protections against opaque AI processes.

The selfie data relevant to Manjang’s claim was obtained using data access rights contained in the U.K. GDPR. If he had not been able to obtain such clear evidence that Uber’s ID checks had failed, the company might not have opted to settle at all. Proving a proprietary system is flawed without letting individuals access relevant personal data would further stack the odds in favor of the much richer resourced platforms.

Enforcement gaps

Beyond data access rights, powers in the U.K. GDPR are supposed to provide individuals with additional safeguards, including against automated decisions with a legal or similarly significant effect. The law also demands a lawful basis for processing personal data, and encourages system deployers to be proactive in assessing potential harms by conducting a data protection impact assessment. That should force further checks against harmful AI systems.

However, enforcement is needed for these protections to have effect — including a deterrent effect against the rollout of biased AIs.

In the U.K.’s case, the relevant enforcer, the Information Commissioner’s Office (ICO), failed to step in and investigate complaints against Uber, despite complaints about its misfiring ID checks dating back to 2021.

Jon Baines, a senior data protection specialist at the law firm Mishcon de Reya, suggests “a lack of proper enforcement” by the ICO has undermined legal protections for individuals.

“We shouldn’t assume that existing legal and regulatory frameworks are incapable of dealing with some of the potential harms from AI systems,” he tells TechCrunch. “In this example, it strikes me…that the Information Commissioner would certainly have jurisdiction to consider both in the individual case, but also more broadly, whether the processing being undertaken was lawful under the U.K. GDPR.

“Things like — is the processing fair? Is there a lawful basis? Is there an Article 9 condition (given that special categories of personal data are being processed)? But also, and crucially, was there a solid Data Protection Impact Assessment prior to the implementation of the verification app?”

“So, yes, the ICO should absolutely be more proactive,” he adds, querying the lack of intervention by the regulator.

We contacted the ICO about Manjang’s case, asking it to confirm whether or not it’s looking into Uber’s use of AI for ID checks in light of complaints. A spokesperson for the watchdog did not directly respond to our questions but sent a general statement emphasizing the need for organizations to “know how to use biometric technology in a way that doesn’t interfere with people’s rights”.

“Our latest biometric guidance is clear that organisations must mitigate risks that come with using biometric data, such as errors identifying people accurately and bias within the system,” its statement also said, adding: “If anyone has concerns about how their data has been handled, they can report these concerns to the ICO.”

Meanwhile, the government is in the process of diluting data protection law via a post-Brexit data reform bill.

In addition, the government also confirmed earlier this year it will not introduce dedicated AI safety legislation at this time, despite Prime Minister Rishi Sunak making eye-catching claims about AI safety being a priority area for his administration.

Instead, it affirmed a proposal — set out in its March 2023 whitepaper on AI — in which it intends to rely on existing laws and regulatory bodies extending oversight activity to cover AI risks that might arise on their patch. One tweak to the approach it announced in February was a tiny amount of extra funding (£10 million) for regulators, which the government suggested could be used to research AI risks and develop tools to help them examine AI systems.

No timeline was provided for disbursing this small pot of extra funds. Multiple regulators are in the frame here, so if there’s an equal split of cash between bodies such as the ICO, the EHRC and the Medicines and Healthcare products Regulatory Agency, to name just three of the 13 regulators and departments the U.K. secretary of state wrote to last month asking them to publish an update on their “strategic approach to AI”, they could each receive less than £1 million to top up budgets to tackle fast-scaling AI risks.

Frankly, it looks like an incredibly low level of additional resource for already overstretched regulators if AI safety is actually a government priority. It also means there’s still zero cash or active oversight for AI harms that fall between the cracks of the U.K.’s existing regulatory patchwork, as critics of the government’s approach have pointed out before.

A new AI safety law might send a stronger signal of priority — akin to the EU’s risk-based AI harms framework that’s speeding toward being adopted as hard law by the bloc. But there would also need to be a will to actually enforce it. And that signal must come from the top.


Software Development in Sri Lanka

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