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The new lawsuit that shows facial recognition is officially a civil rights issue

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The new lawsuit that shows facial recognition is officially a civil rights issue


Williams’s wrongful arrest, which was first reported by the New York Times in August 2020,  was based on a bad match from the Detroit Police Department’s facial recognition system. Two more instances of false arrests have since been made public. Both are also Black men, and both have taken legal action. 

Now Williams is following in their path and going further—not only by suing the department for his wrongful arrest, but by trying to get the technology banned. 

On Tuesday, the ACLU and the University of Michigan Law School’s Civil Rights Litigation Initiative filed a lawsuit on behalf of Williams, alleging that the arrest violated his Fourth Amendment rights and was in defiance of Michigan’s civil rights law.

The suit requests compensation, greater transparency about the use of facial recognition, and an end to the Detroit Police Department’s use of facial recognition technology, whether direct or indirect.

What the lawsuit says

The documents filed on Tuesday lay out the case. In March 2019, the DPD had run a grainy photo of a Black man with a red cap from Shinola’s surveillance video through its facial recognition system, made by a company called DataWorks Plus. The system returned a match with an old driver’s license photo of Williams. Investigating officers then included William’s license photo as part of a photo line-up, and a Shinola security contractor (who wasn’t actually present at the time of the theft) identified Williams as the thief. The officers obtained a warrant, which requires multiple sign-offs from department leadership, and Williams was arrested.

The complaint argues that the false arrest of Williams was a direct result of the facial recognition system, and that  “this wrongful arrest and imprisonment case exemplifies the grave harm caused by the misuse of, and reliance upon, facial recognition technology.” 

The case contains four counts, three of which focus on the lack of probable cause for the arrest while one focuses on the racial disparities in the impact of facial recognition. “By employing technology that is empirically proven to misidentify Black people at rates far higher than other groups of people,” it states, ”the DPD denied Mr. Williams the full and equal enjoyment of the Detroit Police Department’s services, privileges, and advantages because of his race or color.”

Facial recognition technology’s difficulties in identifying darker-skinned people are well documented. After the killing of George Floyd in Minneapolis in 2020, some cities and states announced bans and moratoriums on the police use of facial recognition. But many others, including Detroit, continued to use it despite growing concerns. 

“Relying on subpar images”

When MIT Technology review spoke with Williams’s ACLU lawyer, Phil Mayor, last year, he stressed that problems of racism within American law enforcement made the use of facial recognition even more concerning. 

“This isn’t a one-bad-actor situation,” Mayor said. “This is a situation in which we have a criminal legal system that is extremely quick to charge, and extremely slow to protect people’s rights, especially when we’re talking about people of color.”

Eric Williams, a senior staff attorney at the Economic Equity Practice in Detroit, says cameras have many technological limitations, not least that they are hard-coded with color ranges for recognizing skin tone and often simply cannot process darker skin.

“I think every Black person in the country has had the experience of being in a photo and the picture turns up either way lighter or way darker.”

“I think every Black person in the country has had the experience of being in a photo and the picture turns up either way lighter or way darker,” says Williams, who is a member of the ACLU of Michigan’s lawyers committee but is not working on the Robert Williams case. “Lighting is one of the primary factors when it comes to the quality of an image. So the fact that law enforcement is relying, to some degree … on really subpar images is problematic.” 

There have been cases that challenged biased algorithms and artificial-intelligence technologies on the basis of race. Facebook, for example, underwent a massive civil rights audit after its targeted advertising algorithms were found to serve ads on the basis of race, gender, and religion. YouTube was sued in a class action lawsuit by Black creators who alleged that its AI systems profile users and censor or discriminate against content on the basis of race. YouTube was also sued by LGBTQ+ creators who said that content moderation systems flagged the words “gay” and “lesbian.” 

Some experts say it was only a matter of time until the use of biased technology by a major institution like the police was met with legal challenges. 

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The hunter-gatherer groups at the heart of a microbiome gold rush

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The hunter-gatherer groups at the heart of a microbiome gold rush


The first step to finding out is to catalogue what microbes we might have lost. To get as close to ancient microbiomes as possible, microbiologists have begun studying multiple Indigenous groups. Two have received the most attention: the Yanomami of the Amazon rainforest and the Hadza, in northern Tanzania. 

Researchers have made some startling discoveries already. A study by Sonnenburg and his colleagues, published in July, found that the gut microbiomes of the Hadza appear to include bugs that aren’t seen elsewhere—around 20% of the microbe genomes identified had not been recorded in a global catalogue of over 200,000 such genomes. The researchers found 8.4 million protein families in the guts of the 167 Hadza people they studied. Over half of them had not previously been identified in the human gut.

Plenty of other studies published in the last decade or so have helped build a picture of how the diets and lifestyles of hunter-gatherer societies influence the microbiome, and scientists have speculated on what this means for those living in more industrialized societies. But these revelations have come at a price.

A changing way of life

The Hadza people hunt wild animals and forage for fruit and honey. “We still live the ancient way of life, with arrows and old knives,” says Mangola, who works with the Olanakwe Community Fund to support education and economic projects for the Hadza. Hunters seek out food in the bush, which might include baboons, vervet monkeys, guinea fowl, kudu, porcupines, or dik-dik. Gatherers collect fruits, vegetables, and honey.

Mangola, who has met with multiple scientists over the years and participated in many research projects, has witnessed firsthand the impact of such research on his community. Much of it has been positive. But not all researchers act thoughtfully and ethically, he says, and some have exploited or harmed the community.

One enduring problem, says Mangola, is that scientists have tended to come and study the Hadza without properly explaining their research or their results. They arrive from Europe or the US, accompanied by guides, and collect feces, blood, hair, and other biological samples. Often, the people giving up these samples don’t know what they will be used for, says Mangola. Scientists get their results and publish them without returning to share them. “You tell the world [what you’ve discovered]—why can’t you come back to Tanzania to tell the Hadza?” asks Mangola. “It would bring meaning and excitement to the community,” he says.

Some scientists have talked about the Hadza as if they were living fossils, says Alyssa Crittenden, a nutritional anthropologist and biologist at the University of Nevada in Las Vegas, who has been studying and working with the Hadza for the last two decades.

The Hadza have been described as being “locked in time,” she adds, but characterizations like that don’t reflect reality. She has made many trips to Tanzania and seen for herself how life has changed. Tourists flock to the region. Roads have been built. Charities have helped the Hadza secure land rights. Mangola went abroad for his education: he has a law degree and a master’s from the Indigenous Peoples Law and Policy program at the University of Arizona.

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The Download: a microbiome gold rush, and Eric Schmidt’s election misinformation plan

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The Download: a microbiome gold rush, and Eric Schmidt’s election misinformation plan


Over the last couple of decades, scientists have come to realize just how important the microbes that crawl all over us are to our health. But some believe our microbiomes are in crisis—casualties of an increasingly sanitized way of life. Disturbances in the collections of microbes we host have been associated with a whole host of diseases, ranging from arthritis to Alzheimer’s.

Some might not be completely gone, though. Scientists believe many might still be hiding inside the intestines of people who don’t live in the polluted, processed environment that most of the rest of us share. They’ve been studying the feces of people like the Yanomami, an Indigenous group in the Amazon, who appear to still have some of the microbes that other people have lost. 

But there is a major catch: we don’t know whether those in hunter-gatherer societies really do have “healthier” microbiomes—and if they do, whether the benefits could be shared with others. At the same time, members of the communities being studied are concerned about the risk of what’s called biopiracy—taking natural resources from poorer countries for the benefit of wealthier ones. Read the full story.

—Jessica Hamzelou

Eric Schmidt has a 6-point plan for fighting election misinformation

—by Eric Schmidt, formerly the CEO of Google, and current cofounder of philanthropic initiative Schmidt Futures

The coming year will be one of seismic political shifts. Over 4 billion people will head to the polls in countries including the United States, Taiwan, India, and Indonesia, making 2024 the biggest election year in history.

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Navigating a shifting customer-engagement landscape with generative AI

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Navigating a shifting customer-engagement landscape with generative AI


A strategic imperative

Generative AI’s ability to harness customer data in a highly sophisticated manner means enterprises are accelerating plans to invest in and leverage the technology’s capabilities. In a study titled “The Future of Enterprise Data & AI,” Corinium Intelligence and WNS Triange surveyed 100 global C-suite leaders and decision-makers specializing in AI, analytics, and data. Seventy-six percent of the respondents said that their organizations are already using or planning to use generative AI.

According to McKinsey, while generative AI will affect most business functions, “four of them will likely account for 75% of the total annual value it can deliver.” Among these are marketing and sales and customer operations. Yet, despite the technology’s benefits, many leaders are unsure about the right approach to take and mindful of the risks associated with large investments.

Mapping out a generative AI pathway

One of the first challenges organizations need to overcome is senior leadership alignment. “You need the necessary strategy; you need the ability to have the necessary buy-in of people,” says Ayer. “You need to make sure that you’ve got the right use case and business case for each one of them.” In other words, a clearly defined roadmap and precise business objectives are as crucial as understanding whether a process is amenable to the use of generative AI.

The implementation of a generative AI strategy can take time. According to Ayer, business leaders should maintain a realistic perspective on the duration required for formulating a strategy, conduct necessary training across various teams and functions, and identify the areas of value addition. And for any generative AI deployment to work seamlessly, the right data ecosystems must be in place.

Ayer cites WNS Triange’s collaboration with an insurer to create a claims process by leveraging generative AI. Thanks to the new technology, the insurer can immediately assess the severity of a vehicle’s damage from an accident and make a claims recommendation based on the unstructured data provided by the client. “Because this can be immediately assessed by a surveyor and they can reach a recommendation quickly, this instantly improves the insurer’s ability to satisfy their policyholders and reduce the claims processing time,” Ayer explains.

All that, however, would not be possible without data on past claims history, repair costs, transaction data, and other necessary data sets to extract clear value from generative AI analysis. “Be very clear about data sufficiency. Don’t jump into a program where eventually you realize you don’t have the necessary data,” Ayer says.

The benefits of third-party experience

Enterprises are increasingly aware that they must embrace generative AI, but knowing where to begin is another thing. “You start off wanting to make sure you don’t repeat mistakes other people have made,” says Ayer. An external provider can help organizations avoid those mistakes and leverage best practices and frameworks for testing and defining explainability and benchmarks for return on investment (ROI).

Using pre-built solutions by external partners can expedite time to market and increase a generative AI program’s value. These solutions can harness pre-built industry-specific generative AI platforms to accelerate deployment. “Generative AI programs can be extremely complicated,” Ayer points out. “There are a lot of infrastructure requirements, touch points with customers, and internal regulations. Organizations will also have to consider using pre-built solutions to accelerate speed to value. Third-party service providers bring the expertise of having an integrated approach to all these elements.”

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