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The Download: China’s social credit law, and robot dog navigation

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This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology.

Here’s why China’s new social credit law matters

It’s easier to talk about what China’s social credit system isn’t than what it is. Ever since 2014, when China announced plans to build it, it has been one of the most misunderstood things about China in Western discourse. Now, with new documents released in mid-November, there’s an opportunity to correct the record.

Most people outside China assume it’ll act as a Black Mirror-esque system powered by technologies to automatically score every Chinese citizen based on what they did right and wrong. Instead, it’s a mix of attempts to regulate the financial credit industry, to enable government agencies to share data with each other, and to promote state-sanctioned moral values—however vague that may sound.

Although the system itself will still take a long time to materialize, by releasing a draft law last week, China is now closer than ever to defining what it will look like—and how it will affect the lives of millions of citizens. Read the full story.

—Zeyi Yang

Watch this robot dog scramble over tricky terrain just by using its camera

The news: When Ananye Agarwal took his dog out for a walk up and down the steps in the local park near Carnegie Mellon University, other dogs stopped in their tracks. That’s because Agarwal’s dog was a robot—and a special one at that. Unlike other robots, which tend to rely heavily on an internal map to get around, his robot uses a built-in camera and uses computer vision and reinforcement learning to walk on tricky terrain.

Why it matters: While other attempts to use cues from cameras to guide robot movement have been limited to flat terrain, Agarwal and his fellow researchers managed to get their robot to walk up stairs, climb on stones, and hop over gaps. They’re hoping their work will help make it easier for robots to be deployed in the real world, and vastly improve their mobility in the process. Read the full story.

—Melissa Heikkilä

Trust large language models at your own peril

When Meta launched Galactica, an open-source large language model, the company was hoping for a big PR win. Instead, all it got was flak on Twitter and a spicy blog post from one of its most vocal critics, ending with its embarrassing decision to take the public demo of the model down after only three days. 

Galactica was intended to help scientists by summarizing academic papers, and solving math problems, among other tasks. But outsiders swiftly prompted the model to provide “scientific research” on the benefits of homophobia, anti-Semitism, suicide, eating glass, being white, or being a man—demonstrating not only how its botched launch was premature, but just how insufficient AI researchers’ efforts to make large language models safer have been. Read the full story.

This story is from The Algorithm, our weekly newsletter giving you the inside track on all things AI. Sign up to receive it in your inbox every Monday.

The must-reads

I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.

1 Verified anti-vax Twitter accounts are spreading health misinformation
And perfectly demonstrating the problem with charging for verification in the process. (The Guardian
+ Maybe Twitter wasn’t helping your career as much as you thought it was. (Bloomberg $)
+ A deepfake of FTX’s founder has been circulating on Twitter. (Motherboard)
+ Some of Twitter’s liberal users are refusing to leave. (The Atlantic $)
+ Twitter’s layoff bloodbath is over, apparently. (The Verge)
+ Twitter’s potential collapse could wipe out vast records of recent human history. (MIT Technology Review)

2 NASA’s Orion spacecraft has completed its lunar flyby
Paving the way to humans returning to the moon. (Vox)

3 Amazon’s warehouse-watching algorithms are trained by humans 
Poorly-paid workers in India and Costa Rica are reviewing thousands of hours of mind-numbing footage. (The Verge)
+ The AI data labeling industry is deeply exploitative. (MIT Technology Review)

4 How to make sense of climate change
Accepting the hard facts is the first step towards avoiding the grimmest ending for the planet. (New Yorker $)
+ The world’s richest nations have agreed to pay for global warming. (The Atlantic $)
+ These three charts show who is most to blame for climate change. (MIT Technology Review)

5 Apple uncovered a cybersecurity startup’s dodgy dealings  
It compiled a document that illustrates the extent of Corellium’s relationships, including with the notorious NSO Group. (Wired $)
+ The hacking industry faces the end of an era. (MIT Technology Review)

6 The crypto industry is still feeling skittish
Shares in its largest exchange have dropped to an all-time low. (Bloomberg $)
+ The UK wants to crack down on gamified trading apps. (FT $)

7 The criminal justice system is failing neurodivergent people
Mimicking an online troll led to an autistic man being sentenced to five and a half years in jail. (Economist $)

8 Your workplace could be planning to scan your brain 🧠
All in the name of making you a more efficient employee. (IEEE Spectrum)

9 Facebook doesn’t care if your account is hacked
A series of new solutions to rescue accounts doesn’t seem to have had much effect. (WP $)
+ Parent company Meta is being sued in the UK over data collection. (Bloomberg $)
+ Independent artists are building the metaverse their way. (Motherboard)

10 Why training image-generating AIs on generated images is a bad idea
The ‘contaminated’ images will only confuse them. (New Scientist $)
+ Facial recognition software used by the US government reportedly didn’t work. (Motherboard)
+ The dark secret behind those cute AI-generated animal images. (MIT Technology Review)

Quote of the day

“It feels like they used to care more.”

—Ken Higgins, an Amazon Prime member, is losing faith in the company after a series of frustrating delivery experiences, he tells the Wall Street Journal.

The big story

What if you could diagnose diseases with a tampon?

February 2019

On an unremarkable side street in Oakland, California, Ridhi Tariyal and Stephen Gire are trying to change how women monitor their health.

Their plan is to use blood from used tampons as a diagnostic tool. In that menstrual blood, they hope to find early markers of endometriosis and, ultimately, a variety of other disorders. The simplicity and ease of this method, should it work, will represent a big improvement over the present-day standard of care. Read the full story.

—Dayna Evans

We can still have nice things

A place for comfort, fun and distraction in these weird times. (Got any ideas? Drop me a line or tweet ’em at me.)

+ Happy Thanksgiving—in your nightmares!
+ Why Keith Haring’s legacy is more visible than ever, 32 years after his death.
+ Even the gentrified world of dinosaur skeleton assembly isn’t immune to scandals.
+ Pumpkins are a Thanksgiving staple—but it wasn’t always that way.
+ If I lived in a frozen wasteland, I’m pretty sure I’d be the world’s grumpiest cat too.



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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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