AI researchers urge tech to go beyond scale to address systemic social issues

The definition of success for startups and Big Tech companies alike has long been summed up by three words: hockey stick growth. The paper argues that scale thinking is not just a way to grow a business, but a method that impacts all parts of that business, actively inhibits participation in tech and society, and “forces particular types of participation to operate as extractive or exploitative labor.”

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Artificial intelligence and the antitrust case against Google

Following the launch of investigations last year, the U.S. Department of Justice (DOJ) together with attorney generals from 11 U.S. states filed a lawsuit against Google on Tuesday alleging that the company maintains monopolies in online search and advertising, and violates laws prohibiting anticompetitive business practices.

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Syte raises $40 million to bring visual search to online retailers

Visual search is now a core part of countless mobile apps, from Google Lens and Bing to Pinterest and eBay. But building the underlying AI infrastructure to let people search databases and catalogs using images rather than words is a resource-intensive endeavor requiring a lot of time and technical expertise, which is where Syte comes into play.

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Zest raises $15 million to reduce loan algorithm bias

Zest AI, a company developing AI-powered loan decisioning products, today closed a $15 million funding round led by Insight Partners. A spokesperson says the capital will be used to accelerate Zest’s go-to-market efforts and product R&D.
About 1 out of every 9 loan applications (10.8%) for home buying — and more than 1 in 4 applications (26.4%) for refinancing — were denied in 2017, according to a nationwide analysis of lender data conducted by the U.S. Bureau of Consumer Financial Protection. Minorities were disproportionately rejected, with the overall denial rate for mortgage applications from Black Americans reaching 18.4% in 2018. (Hispanic and Asian applicants were rejected 13.5% and 10.6% of the time, respectively, compared with 8.8% for non-Hispanic white applicants.)

Zest, which was cofounded in 2009 by former Google CIO Douglas Merrill and ex-Sears VP Shawn Budde, claims its mission is to create “more rigorous” standards around debiasing algorithmic lending. To this end, the company helps banks, credit unions, and specialty lenders identify borrowers by taking into account more than credit scores. Zest claims institutions that lend using its models — including Discover, Akbank, and VyStar — have seen a 20% increase in approval rates on average and an up to 50% reduction in chargeoffs, or declarations that an amount of debt is unlikely to be collected.
Zest provides over 30 customers with resources to prep, build, iterate, and document machine-learning decisioning models for cards, auto loans, personal loans, mortgages, and student loans. Complementary tools help teams evaluate and validate the models for safety, stability, business impact, and compliance. Customers can deploy and monitor algorithms in production, or they can engage Zest’s team of service and machine learning experts for assistance with development and validation steps.
Zest claims to use a technique called adversarial debiasing to minimize potential model prejudice. The technique pits two machine learning models against each other, with one attempting to predict creditworthiness while the other second-guesses the race, gender, and other attributes of the applicant scored by the first model. Competition drives both to improve their methods until the predictor can no longer distinguish the race or gender outputs of the first model, resulting in a model that is ostensibly more accurate and fair.
Zest recently introduced ZAML Fair, which the company claims can reduce bias in loan portfolios with “little or no” impact on profitability. ZAML Fair leverages the transparency tools built into Zest’s solutions suite to rank a system’s variables by how much they lead to biased outcomes. It then attempts to mitigate the influence of those signals to produce a superior model.
Based on the mortgage lenders who tested ZAML Fair, Zest says the tool would eliminate 70% of the nation’s gap in approval rates between Hispanic and white mortgage applicants and cut the even larger gap between Black and white borrowers by more than 40%. In a blog post, Zest cited a survey conducted by the Harris Poll that found a majority of Americans would give up more personal data if it resulted in a fairer credit decision. With that in mind, Zest believes it can reduce bias by using “better math and more data to assess borrowers.”
Of course, it’s difficult — if not impossible — to completely rid algorithms of bias. Facial recognition models fail to recognize Black, Middle Eastern, and Latinx people more often than those with lighter skin. AI researchers from MIT, Intel, and Canadian AI initiative CIFAR have found high levels of bias from some of the most popular pretrained models. And algorithms developed by Facebook have proven to be 50% more likely to disable the accounts of Black users compared with white users.
But Zest claims the data proves its efforts are making a difference. Using Zest’s underwriting software platform, one lender says it was able to shrink the disparity in approval rates between white applicants and applicants of color by 30% on average, with no increase in portfolio risk. Separately, an auto lender was able to approve “thousands” more borrowers.
“The COVID-19 shock led many financial institutions to update and improve their systems for resilience and durability, which caused a significant increase in demand for our business,” CEO Mike de Vere told VentureBeat via email. “A big part of that included building new and improved underwriting systems with the latest math and software technology. This resulted in Zest’s best Q2 on record, with an eye on finishing the year with triple-digit growth.”
Los Angeles-based Zest has raised over $87 million in venture capital to date.
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AiFi raises $15 million to accelerate cashierless retail

AiFi, a Santa Clara-based cashierless retail startup that emerged from stealth in February 2019, today secured an investment from Qualcomm and existing backers. A company spokesperson didn’t disclose the exact amount, but she said it doubles AiFi’s total raised to $30 million.

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Recognizing data points that signal trends for the future of business post-pandemic

Planning for a post-COVID-19 future and creating a robust enterprise strategy require both strategic scenario planning and the ability to recognize what scenario planners call “news from the future” — data points that tell you whether the world is trending in the direction of one or another of your imagined scenarios.

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When AI hurts people, who is held responsible?

Following a Maricopa County Grand Jury decision, the woman behind the wheel of a semi-autonomous Uber vehicle was charged last month with negligent homicide in the 2018 death of Elaine Herzberg. The lawsuit against the backup driver in the first known autonomous vehicle fatality promises to be a landmark case with the power to shape the future of artificial intelligence in the U.S.

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The secrets of small data: How Machine Learning finally reached the enterprise

Over the past decade, “big data” has become Silicon Valley’s biggest buzzword. When they’re trained on mind-numbingly large data sets, machine learning (ML) models can develop a deep understanding of a given domain, leading to breakthroughs for top tech companies.

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U.S. Congress calls for antitrust reforms to limit powers of Amazon, Apple, Facebook, and Google

Members of Congress investigating the activity of Amazon, Apple, Facebook, and Google say antitrust law reform is needed to safeguard democracy and “ensure that our economy remains vibrant and open in the digital age.”

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Via acquires delivery logistics startup Fleetonomy to bolster fulfillment with AI

In a move to expand its business into the logistics and delivery segment, ride-hailing startup Via today announced that it acquired Fleetonomy for an undisclosed sum.

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Amazon went wide with Alexa; now it’s going deep

Amazon’s naked ambition to become part of everyone’s daily lives was on full display this week at its annual hardware event. It announced a slew of new Alexa-powered devices, including a home surveillance drone, a suite of Ring-branded car alarm systems, and miscellany like an adorable little kids’ Echo device. But it’s clear Amazon’s strategy has shifted, even if only for a product cycle, from going wide to going deep.

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Wilson Logistics will put Locomation’s autonomous driving tech in 1,000 trucks

Autonomous trucking company Locomation today announced that Wilson Logistics has agreed to equip 1,120 of its trucks with Locomation’s platooning technology, with the first units to be delivered in 2022.

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WhyLabs raises $4 million to grow AI and data monitoring platform

WhyLabs is launching out of stealth today with $4 million to grow its platform for data scientists who need help monitoring and troubleshooting problems they encounter with datasets or AI models. The goal is to help teams managing machine learning models save time and catch problems before they make trouble for businesses or customers.

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How U.S. tech policy could change if Democrats win back the Senate

Election Day in the U.S. is now only weeks away, and the variables and stakes are rapidly mounting. If Democrats succeed in taking control of the legislative and executive branches of government, the shift could end a long-standing policy gridlock. To get an idea of how Democratic control of Congress could influence tech policy…

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AI researchers devise failure detection method for safety-critical machine learning

Researchers from MIT, Stanford University, and the University of Pennsylvania have devised a method for predicting failure rates of safety-critical machine learning systems and efficiently determining their rate of occurrence.

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How AI is impacting customer experience in Fintech

Companies like MasterCard are implementing AI strategies that transform how customer experience is done. Join MasterCard Lab’s VP of Artificial Intelligence & Machine Learning and others for insights on why AI is essential for Fintech companies now, and developing an AI strategy going forward. 

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