Fabian Rogers was none too pleased when the landlord of his rent-stabilized Brooklyn high-rise announced plans to swap out key fobs for a facial recognition system.
He had so many questions: What happened if he didn’t comply? Would he be evicted? And as a young black man, he worried that his biometric data would end up in a police lineup without him ever being arrested. Most of the building’s tenants are people of color, he said, and they already are concerned about over policing in their New York neighborhood.
“There’s a lot of scariness that comes with this,” said Rogers, 24, who along with other tenants is trying to legally block his management company from installing the technology.
“You feel like a guinea pig,” Rogers said. “A test subject for this technology.”
Amid privacy concerns and recent research showing racial disparities in the accuracy of facial recognition technology, some city and state officials are proposing to limit its use.
Law enforcement officials say facial recognition software can be an effective crime-fighting tool, and some landlords say it could enhance security in their buildings. But civil liberties activists worry that vulnerable populations such as residents of public housing or rent-stabilized apartments are at risk for law enforcement overreach.
“This is a very dangerous technology,” said Reema Singh Guliani, senior legislative counsel for the American Civil Liberties Union. “Facial recognition is different from other technologies. You can identify someone from afar. They may never know. And you can do it on a massive scale.
”The earliest forms of facial recognition technology originated in the 1990s, and local law enforcement began using it in 2009. Today, its use has expanded to companies such as Facebook and Apple.
Such software uses biometrics to read the geometry of faces found in a photograph or video and compare the images to a database of other facial images to find a match. It’s used to verify personal identity — the FBI, for example, has access to 412 million facial images.
“Our industry certainly needs to do a better job of helping educate the public how the technology works and how it’s used,” said Jake Parker, senior director of government relations for the Security Industry Association, a trade association based in Silver Spring, Maryland.
“Any technology has the potential to be misused,” Parker said. “But in the United States, we have a number of constitutional protections that limit what the government can do.”
A 2018 study from the Massachusetts Institute of Technology found that the software more often misidentifies darker-skinned people, particularly women of color, raising concerns about bias built into the technology. The study found the software had an error rate of 34.7% for darker-skinned women, compared with 0.8% for lighter-skinned men.
This year several cities — San Francisco; Somerville, Massachusetts; andOakland, California — became the first to ban municipal departments, including police and housing agencies, from using facial recognition technology. And this year, lawmakers in at least 10 states introduced bills to ban or delay the use of the technology by government agencies and businesses.
“We’re concerned about government overreach,” Michigan state Rep. IsaacRobinson, a Democrat who sponsored one of the bills, told Stateline. “And preserving our right to walk freely down the street without having our faces scanned.”
A handful of private apartment complexes in New York have started using the technology. But for now, few public housing complexes seem to be embracing facial recognition software, said Adrianne Todman, CEO of the NationalAssociation of Housing and Redevelopment Officials.
In Detroit, one public housing complex uses live cameras as part of the citywide surveillance system Project Green Light Detroit. Images from those cameras could be loaded into the Detroit Police Department’s facial recognition software.
Agencies rely more on cameras and security personnel to manage safety issues in their communities, Todman said. “They also rely on information they get from residents, who often are the most informed about what’s happening on their floors, in their buildings and in their neighborhoods.”
In May, U.S. Housing and Urban Development Secretary Ben Carson, a Detroit native, was asked about the use of the technology in public housing by U.S.Rep. Rashida Tlaib, a Democrat also from Detroit.
“I oppose the inappropriate use of it,” Carson said. He did not specify what use he considered inappropriate.
HUD spokesman Brian Sullivan said facial recognition technology in public housing was a local issue and that he wouldn’t comment beyond Carson’s testimony at the hearing.
Two weeks ago, Tlaib introduced a bill that would ban facial recognition software from public housing, along with a bill that would ban federal purchases of the technology. A third bill introduced in the House by U.S. Rep.Eliot Engel, a Democrat from New York, would prohibit federal agencies from using facial recognition technology without a court order.
“You can identify someone from afar. They may never know. And you can do it ona massive scale.
“In July, Michigan lawmakers introduced two bills. One would place a five-year moratorium on facial recognition technology while another would ban it outright.
Vermont and Washington state lawmakers introduced bills this year to curb police use of the technology. California lawmakers introduced a bill to require businesses using facial recognition software to alert their customers.
In New York, a package of bills focuses on the use of facial recognition in housing. One bill would ban biometric and facial recognition software from being used in federally funded public housing. Another bill would bar landlords from installing the technology on “any residential premises.”
Project Green Light
Three years ago, Detroit launched Project Green Light Detroit, an $8 million surveillance system that uses live cameras in schools, gas stations, churches, medical centers and liquor stores to deter crime and improve police response times.
The city installed Project Green Light cameras in more than 500 locations with little fanfare. In May, though, a Georgetown University study found the city used facial recognition software, in conjunction with Project Green Light cameras, to make arrests.
“No longer is video surveillance limited to what happens,” the study found,“it may now identify who is going where, doing what, at any point in time.
”The study found live cameras were tracking the movements of tenants in apartment buildings and even patients coming and going from a medical center, which Detroit Police Chief James Craig denied in an interview with Stateline. Craig said his department does not use facial recognition software to track people.
The city started using the cameras in areas with high crime rates, such as gas stations and outside liquor stores. But earlier this year, public housing officials installed Project Green Light cameras in a senior citizens’ community, said Sandra Henriquez, executive director of the Detroit HousingCommission. She said the cameras themselves are not equipped with facial recognition software.
“People seem to conflate the issue,” Henriquez said. “I have video surveillance equipment. I do not have facial recognition software in any ofour properties. I want to make that crystal clear.
”Asked whether she had concerns about the technology, Henriquez said, “I would not say there are concerns. It is a technology, as a landlord, I do not need.I understand, in certain circumstances and applications, there might be a need. But not what happens on my property at this point.”
Henriquez said she has no intention of installing facial recognition software in any of the public housing units and has no plans to install Project GreenLight in other city housing complexes.
The cameras were installed at the behest of tenants, said Craig, the police chief. He said the city has used facial recognition 500 times in the past year to identify suspects. A positive identification was made in about a third of the cases.
“The thing that’s being lost in the conversations, whether it’s cameras or facial recognition, no one talks about the victims,” Craig said. “It’s almost as though the victims don’t count.”
The police take a snapshot from Project Green Light cameras and enter it into the software, which generates photos gleaned from mug books, ranks the photos, and identifies likely matches.
Craig said after the software identifies a possible match, two analysts trained in biometrics by the FBI study the photograph. If they think they’ve made a positive match, they then run it by a supervisor, who turns the photograph over to prosecutors.
A positive match from facial recognition software is not sufficient to charge a suspect with a crime, Craig said.
“Never in my wildest dreams would I have guessed that using facial recognition would have garnered such a vitriolic response,” he said.
Unlocking the Door
Last fall, Nelson Management Group informed tenants of Atlantic Plaza — the rent-stabilized, middle-income complex in Brooklyn where Fabian Rogers lives —it planned to replace key fobs with facial recognition software.
The system would be next to the doors, according to Colleen Dunlap, CEO ofStoneLock, which manufactures the technology. Tenants could be scanned in through an automatic door without touching anything.
But tenants would not be tracked using the StoneLock system, Dunlap said in an emailed statement. “We work hard to protect user privacy.”
Rogers and other tenants objected because surveillance cameras were already on the property, along with security guards and a doorman. They filed a legal action with the state’s Homes and Community Renewal agency, which oversees rent-stabilized housing.
“The sole goal of implementing this technology is to advance that priority and support the safety and security of residents,” Chris Santarelli, a spokesman for the Nelson Management Group, said in an emailed statement.
Rogers, who’s lived in the building for over a decade, remains unconvinced.
“I have no control over where this information goes,” Rogers said.“So we’re going to keep fighting.”
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These ten enterprise M&A deals totaled over $40B in 2019
It would be hard to top the 2018 enterprise M&A total of a whopping $87 billion, and predictably this year didn’t come close. In fact, the top 10 enterprise M&A deals in 2019 were less than half last year’s, totaling $40.6 billion. This year’s biggest purchase was Salesforce buying Tableau for $15.7 billion, which would…
It would be hard to top the 2018 enterprise M&A total of a whopping $87 billion, and predictably this year didn’t come close. In fact, the top 10 enterprise M&A deals in 2019 were less than half last year’s, totaling $40.6 billion.
This year’s biggest purchase was Salesforce buying Tableau for $15.7 billion, which would have been good for third place last year behind IBM’s mega deal plucking Red Hat for $34 billion and Broadcom grabbing CA Technologies for $18.8 billion.
Contributing to this year’s quieter activity was the fact that several typically acquisitive companies — Adobe, Oracle and IBM — stayed mostly on the sidelines after big investments last year. It’s not unusual for companies to take a go-slow approach after a big expenditure year. Adobe and Oracle bought just two companies each with neither revealing the prices. IBM didn’t buy any.
Microsoft didn’t show up on this year’s list either, but still managed to pick up eight new companies. It was just that none was large enough to make the list (or even for them to publicly reveal the prices). When a publicly traded company doesn’t reveal the price, it usually means that it didn’t reach the threshold of being material to the company’s results.
As always, just because you buy it doesn’t mean it’s always going to integrate smoothly or well, and we won’t know about the success or failure of these transactions for some years to come. For now, we can only look at the deals themselves.
Jumia, DHL, and Alibaba will face off in African ecommerce 2.0
The business of selling consumer goods and services online is a relatively young endeavor across Africa, but ecommerce is set to boom. Over the last eight years, the sector has seen its first phase of big VC fundings, startup duels and attrition. To date, scaling e-commerce in Africa has straddled the line of challenge and…
The business of selling consumer goods and services online is a relatively young endeavor across Africa, but ecommerce is set to boom.
Over the last eight years, the sector has seen its first phase of big VC fundings, startup duels and attrition.
To date, scaling e-commerce in Africa has straddled the line of challenge and opportunity, perhaps more than any other market in the world. Across major African economies, many of the requisites for online retail — internet access, digital payment adoption, and 3PL delivery options — have been severely lacking.
Still, startups jumped into this market for the chance to digitize a share of Africa’s fast growing consumer spending, expected to top $2 billion by 2025.
African e-commerce 2.0 will include some old and new players, play out across more countries, place more priority on internet services, and see the entry of China.
But before highlighting several things to look out for in the future of digital-retail on the continent, a look back is beneficial.
Jumia vs. Konga
The early years for development of African online shopping largely played out in Nigeria (and to some extent South Africa). Anyone who visited Nigeria from 2012 to 2016 likely saw evidence of one of the continent’s early e-commerce showdowns. Nigeria had its own Coke vs. Pepsi-like duel — a race between ventures Konga and Jumia to out-advertise and out-discount each other in a quest to scale online shopping in Africa’s largest economy and most populous nation.
Traveling in Lagos traffic, large billboards for each startup faced off across the skyline, as their delivery motorcycles buzzed between stopped cars.
Covering each company early on, it appeared a battle of VC attrition. The challenge: who could continue to raise enough capital to absorb the losses of simultaneously capturing and creating an e-commerce market in notoriously difficult conditions.
In addition to the aforementioned challenges, Nigeria also had (and continues to have) shoddy electricity.
Both Konga — founded by Nigerian Sim Shagaya — and Jumia — originally founded by two Nigerians and two Frenchman — were forced to burn capital building fulfillment operations most e-commerce startups source to third parties.
That included their own delivery and payment services (KongaPay and JumiaPay). In addition to sales of goods from mobile-phones to diapers, both startups also began experimenting with verticals for internet based services, such as food-delivery and classifieds.
While Jumia and Konga were competing in Nigeria, there was another VC driven race for e-commerce playing out in South Africa — the continent’s second largest and most advanced economy.
E-tailers Takealot and Kalahari had been jockeying for market share since 2011 after raising capital in the hundreds of millions of dollars from investors Naspers and U.S. fund Tiger Global Management.
So how did things turn out in West and Southern Africa? In 2014, the lead investor of a flailing Kalahari — Naspers — facilitated a merger with Takealot (that was more of an acquisition). They nixed the Kalahari brand in 2016 and bought out Takelot’s largest investor, Tiger Global, in 2018. Takealot is now South Africa’s leading e-commerce site by market share, but only operates in one country.
In Nigeria, by 2016 Jumia had outpaced its rival Konga in Alexa ratings (6 vs 14), while out-raising Konga (with backing of Goldman Sachs) to become Africa’s first VC backed, startup unicorn. By early 2018, Konga was purchased in a distressed acquisition and faded away as a competitor to Jumia.
Jumia went on to expand online goods and services verticals into 14 Africa countries (though it recently exited a few) and in April 2019 raised over $200 million in an NYSE IPO — the first on a major exchange for a VC-backed startup operating in Africa.
Jumia’s had bumpy road since going public — losing significant share-value after a short-sell attack earlier in 2019 — but the continent’s leading e-commerce company still has heap of capital and generates $100 million in revenues (even with losses).
Airbnb’s New Year’s Eve guest volume shows its falling growth rate
Hello and welcome back to our regular morning look at private companies, public markets and the gray space in between. It’s finally 2020, the year that should bring us a direct listing from home-sharing giant Airbnb, a technology company valued at tens of billions of dollars. The company’s flotation will be a key event in…
Hello and welcome back to our regular morning look at private companies, public markets and the gray space in between.
It’s finally 2020, the year that should bring us a direct listing from home-sharing giant Airbnb, a technology company valued at tens of billions of dollars. The company’s flotation will be a key event in this coming year’s technology exit market. Expect the NYSE and Nasdaq to compete for the listing, bankers to queue to take part, and endless media coverage.
Given that that’s ahead, we’re going to take periodic looks at Airbnb as we tick closer to its eventual public market debut. And that means that this morning we’re looking back through time to see how fast the company has grown by using a quirky data point.
Airbnb releases a regular tally of its expected “guest stays” for New Year’s Eve each year, including 2019. We can therefore look back in time, tracking how quickly (or not) Airbnb’s New Year Eve guest tally has risen. This exercise will provide a loose, but fun proxy for the company’s growth as a whole.
Before we look into the figures themselves, keep in mind that we are looking at a guest figure which is at best a proxy for revenue. We don’t know the revenue mix of the guest stays, for example, meaning that Airbnb could have seen a 10% drop in per-guest revenue this New Year’s Eve — even with more guest stays — and we’d have no idea.
So, the cliche about grains of salt and taking, please.
But as more guests tends to mean more rentals which points towards more revenue, the New Year’s Eve figures are useful as we work to understand how quickly Airbnb is growing now compared to how fast it grew in the past. The faster the company is expanding today, the more it’s worth. And given recent news that the company has ditched profitability in favor of boosting its sales and marketing spend (leading to sharp, regular deficits in its quarterly results), how fast Airbnb can grow through higher spend is a key question for the highly-backed, San Francisco-based private company.
- 2009: 1,400
- 2010: 6,000 (+329%)
- 2011: 3,1000 (+417%)
- 2012: 108,000 (248%)
- 2013: 250,000 (+131%)
- 2014: 540,000 (+116%)
- 2015: 1,100,000 (+104%)
- 2016: 2,000,000 (+82%)
- 2017: 3,000,000 (+50%)
- 2018: 3,700,000 (+23%)
- 2019: 4,500,000 (+22%)
In chart form, that looks like this:
Let’s talk about a few things that stand out. First is that the company’s growth rate managed to stay over 100% for as long as it did. In case you’re a SaaS fan, what Airbnb pulled off in its early years (again, using this fun proxy for revenue growth) was far better than a triple-triple-double-double-double.
Next, the company’s growth rate in percentage terms has slowed dramatically, including in 2019. At the same time the firm managed to re-accelerate its gross guest growth in 2019. In numerical terms, Airbnb added 1,000,000 New Year’s Eve guest stays in 2017, 700,000 in 2018, and 800,000 in 2019. So 2019’s gross adds was not a record, but it was a better result than its year-ago tally.
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