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Three things to know about how the US Congress might regulate AI

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Three things to know about how the US Congress might regulate AI


Schumer’s plan is a culmination of many other, smaller policy actions. On June 14, Senators Josh Hawley (a Republican from Missouri) and Richard Blumenthal (a Democrat from Connecticut) introduced a bill that would exclude generative AI from Section 230 (the law that shields online platforms from liability for the content their users create). Last Thursday, the House science committee hosted a handful of AI companies to ask questions about the technology and the various risks and benefits it poses. House Democrats Ted Lieu and Anna Eshoo, with Republican Ken Buck, proposed a National AI Commission to manage AI policy, and a bipartisan group of senators suggested creating a federal office to encourage, among other things, competition with China

Though this flurry of activity is noteworthy, US lawmakers are not actually starting from scratch on AI policy. “You’re seeing a bunch of offices develop individual takes on specific parts of AI policy, mostly that fall within some attachment to their preexisting issues,” says Alex Engler, a fellow at the Brookings Institution. Individual agencies like the FTC,the Department of Commerce, and the US Copyright Office have been quick to respond to the craze of the last six months, issuing policy statements, guidelines, and warnings about generative AI in particular. 

Of course, we never really know whether talk means action when it comes to Congress. However, US lawmakers’ thinking about AI reflects some emerging principles. Here are three key themes in all this chatter that you should know to help you understand where US AI legislation could be going. 

  • The US is home to Silicon Valley and prides itself on protecting innovation. Many of the biggest AI companies are American companies, and Congress isn’t going to let you, or the EU, forget that! Schumer called innovation the “north star” of US AI strategy, meaning regulators will probably be calling on tech CEOs to ask how they’d like to be regulated. It’s going to be interesting watching the tech lobby at work here. Some of this language arose in response to the latest regulations from the European Union, which some tech companies and critics say will stifle innovation
  • Technology, and AI in particular, ought to be aligned with “democratic values.” We’re hearing this from top officials like Schumer and President Biden. The subtext here is the narrative that US AI companies are different from Chinese AI companies. (New guidelines in China mandate that outputs of generative AI must reflect “communist values.”) The US is going to try to package its AI regulation in a way that maintains the existing advantage over the Chinese tech industry, while also ramping up its production and control of the chips that power AI systems and continuing its escalating trade war. 
  • One big question: what happens to Section 230. A giant unanswered question for AI regulation in the US is whether we will or won’t see Section 230 reform. Section 230 is a 1990s internet law in the US that shields tech companies from being sued over the content on their platforms. But should tech companies have that same ‘get out of jail free’ pass for AI-generated content? This is a big question, and it would require that tech companies identify and label AI-made text and images, which is a massive undertaking. Given that the Supreme Court recently declined to rule on Section 230, the debate has likely been pushed back down to Congress. Whenever legislators decide if and how the law should be reformed, it could have a huge impact on the AI landscape. 

So where is this going? Well, nowhere in the short-term, as politicians skip off for their summer break. But starting this fall, Schumer plans to kick off invite-only discussion groups in Congress to look at particular parts of AI. 

In the meantime, Engler says we might hear some discussions about the banning of certain applications of AI, like sentiment analysis or facial recognition, echoing parts of the EU regulation. Lawmakers could also try to revive existing proposals for comprehensive tech legislation—for example, the Algorithmic Accountability Act.

For now, all eyes are on Schumer’s big swing. “The idea is to come up with something so comprehensive and do it so fast. I expect there will be a pretty dramatic amount of attention,” says Engler.

What else I’m reading

  • Everyone is talking about “Bidenomics,” meaning the current president’s specific brand of economic policy. Tech is at the core of Bidenomics, with billions upon billions of dollars being poured into the industry in the US. For a glimpse of what that means on the ground, it’s well worth reading this story from the Atlantic about a new semiconductor factory coming to Syracuse. 
  • AI detection tools try to identify whether text or imagery online was made by AI or by a human. But there’s a problem: they don’t work very well. Journalists at the New York Times messed around with various tools and ranked them according to their performance. What they found makes for sobering reading. 
  • Google’s ad business is having a tough week. New research published by the Wall Street Journal found that around 80% of Google ad placements appear to break their own policies, which Google disputes.

What I learned this week

We may be more likely to believe disinformation generated by AI, according to new research covered by my colleague Rhiannon Williams. Researchers from the University of Zurich found that people were 3% less likely to identify inaccurate tweets created by AI than those written by humans.

It’s only one study, but if it’s backed up by further research, it’s a worrying finding. As Rhiannon writes, “The generative AI boom puts powerful, accessible AI tools in the hands of everyone, including bad actors. Models like GPT-3 can generate incorrect text that appears convincing, which could be used to generate false narratives quickly and cheaply for conspiracy theorists and disinformation campaigns.”

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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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