A promise to remake the web with blockchain

Presented by Meta: How the next wave of technology is upending the global economy and its power structures
Apr 10, 2024 View in browser
 
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By Derek Robertson

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Ethereum cryptocurrency logo is displayed on a mobile phone screen photographed for illustration in Krakow, Poland, on May 12, 2021.

The logo for the Ethereum blockchain. | Beata Zawrzel/NurPhoto via Getty Images

If blockchain evangelists think the technology is poised to transform the world, some are fairly self-aware of the extent to which the average person still doesn’t quite understand what it does.

One of them is Chris Dixon, general partner at Andreessen Horowitz and one of the technology’s biggest boosters. In “Read Write Own: Building the Next Era of the Internet,” published in January by Random House, Dixon explains the blockchain technology behind cryptocurrency and lays out a case that despite some high-profile scandals (ahem, FTX), it can still preserve the best parts of the internet.

But the book isn’t just a sustained defense from one of blockchain’s biggest fans: It’s a case for how the technology could rebuild the economic landscape of Silicon Valley in its image, replacing a digital economy dominated by Big Tech with one that gives users a fairer deal. It also raises some big-picture, unanswered questions: To what end might those users direct the power they wrest away from Silicon Valley megacorporations, and can the ideals of fairness and reciprocity they espouse be written into the blockchain’s very code?

Dixon defends the blockchain with a neat dichotomy, splitting its uses into the “computer,” or the underlying software that enables a decentralized system of digital verification, and the “casino,” the inherent speculative financial capability of tokens. He argues that the unseemly, get-rich-quick qualities attributed to the “casino” (think memecoins) obscure the benefits of the “computer.”

One major benefit of the “computer” in this formulation is how it establishes digital identity and property rights that aren’t controlled by a remote corporation. Dixon compares this to how early internet technology, like the domain name system, works: You permanently own a web domain in a way that you don’t own a Twitter handle or your Facebook account. Therefore, you can publish or conduct whatever business you wish using it, without fear of censorship or “throttling” by large social media platforms.

Blockchains restore that ownership to users’ digital presences by simply eliminating those middleman institutions like Facebook or Google and connecting users to each other directly, via the encrypted code of the blockchain and the apps built on top of it.

But to accomplish all that, you have to convince people to actually use the network. To set rules and incentivize developers, blockchain founders establish a governance structure and capacity for fundraising, creating tokens or cryptocurrency. While the cryptocurrency can be used for speculation (the “casino”), Dixon says setting financial incentives for “computer” developers gives the blockchain business model an advantage over nonprofit development, which lacks the financial firepower to sustain large decentralized networks.

“If you go to a creator and you say ‘Would you like to make $1 million a year or $0 a year,’ that's going to be very compelling,” Dixon said. “Social network revenue last year was $150 billion… if you took 10 percent for the intermediaries instead of 100 percent, that's $130 billion paid out to the network participants.”

It’s a pretty compelling case in a digital media environment where all but the most successful struggle to stay afloat, and are threatened by increasingly sophisticated AI products. Dixon writes that when it comes to governance of these blockchain networks, a fine balance of financial incentives that he calls “tokenomics” can ensure “inscrutable social dynamics” are replaced by “thoughtful design.” (For example, early adoption of the network, developing key tools for it, or simply being a good citizen and following the rules could be rewarded with a financial stake.)

This was the point where, as a reader, my critical radar began to ping furiously. If economic incentives ensure digital property rights and good governance, don’t the “computer” and the “casino” have more in common than either side might like to admit? The notion of designing incentives to drive efficient markets is an old and hotly contested one. Why should it work any differently on a software network than it does in the analog world?

Dixon and other blockchain supporters argue good behavior can be written into the blockchain code: In his formulation, it changes Google’s “don’t be evil” slogan into “can’t be evil.” Dixon says the tech’s altruistic overlay “isn’t to say the computer culture isn’t interested in making money,” but rather that “computer” crypto thinkers take a long view, and “casino” crypto thinkers have a shorter-term approach.

“I meet with policymakers and they ask me ‘Isn't this all self-interested?’ and I say ‘Sure it is, because we're a venture capital firm and we want to see a lot of startups,’” Dixon said. “We're dependent on startups, and having an internet that is controlled by five companies and kind of calcified is bad for our business… but I make the case that it's also probably good societally to also have a dynamic internet, startup creation and new companies.”

Dixon’s book is a very strong explainer of a series of technological concepts whose abstraction can chafe at the limits of human attention. But even more so, it’s a crystal-clear demonstration of the market-driven ethos underpinning even the most altruistic blockchain projects.

If Dixon’s dream comes true, a great deal of power will certainly shift from the behemoth tech platforms to users. Those users will then try to maximize the internet’s “value” in their own right, meeting each other on the digital plane to barter for maximal utility. To avoid the blunders, bloodthirsty competition, monopoly and roll-up that followed a previous generation of web utopians’ ascent, it’s going to take the most supremely intelligent on-chain code that Dixon and his fellow believers can muster.

 

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advice for congress on ai

AI entrepreneur-critic Gary Marcus has some urgent advice for Congress as it ponders AI legislation.

Writing in POLITICO Magazine (and speaking yesterday to the POLITICO Tech podcast), Marcus hammered a few key areas where he says lawmakers must take action on AI, including but not limited to:

Data rights: “Training data should require consent, compensation and licensing. Nobody should be allowed to use your data for free, without your consent,” Marcus writes. “Privacy rights might sound boring, wonky and very 2010. But the U.S. government has never seriously locked them down, and with AI snarfing up everything you ever did, the need is more urgent than ever.”

Transparency: “The least we should insist on, given how much AI models can influence our lives,” Marcus writes, is openness about training data, transparency around what safety testing has been done, and enforced labeling of AI-generated content.

Liability: Marcus writes that AI companies shouldn’t be able to hide behind the shield of Section 230, and should be held liable for harms from their content.

“Layered oversight”: Including independent scientists monitoring the technology, a federal agency charged with “convening outside scientists and ethicists, setting up processes for licensing and auditing and so on” and an international “treaty in which the U.S. has a firm hand.”

ai persuasion

A study from a leading AI company claims the more powerful language models get, the more persuasive they become.

In a blog post published yesterday, engineers from Anthropic write that each of their LLMs has been more persuasive than the one that came before it. To measure this, they presented respondents with a claim and asked the extent of their agreement with it, then gave them an argument backing that claim (composed by their Claude LLMs), and then asked again how much they agree with the original claim.

Not only did the engineers find that the more powerful the model, the more persuasive, but they also observed the current model Claude 3 Opus is roughly as persuasive as a human. They sound a note of caution, however, writing that “persuasion is difficult to study in a lab setting” and the “results may not transfer to the real world.”

Still, measuring persuasion is only the first step toward figuring out the impact of these models, they write: “It will be important to investigate real-world impacts beyond people's stated opinions — do persuasive AI arguments actually influence people's decisions and actions?” They say further research and deployment will be needed to mitigate the risks of large language models as they improve.

 

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an ai tower of babel

Europe is rushing to action to keep English-language chatbots from smothering the global market.

POLITICO’s Gian Volpicelli reported on efforts across Europe to create fluent European-language chatbots, with France’s Economy Minister Bruno Le Maire arguing that “Mark Twain should not erase Stendhal.” In the past year, 13 European countries have begun to develop models focused on their local languages.

Gian writes that most of these products are open source, hoping to draw in a wider community of volunteers that might compete with U.S. AI giants’ overwhelming financial advantage.

“Having models in the local language is also about encouraging more people in your country to code and develop more AI products,” Carlos Romero Duplá, a consultant and former Spanish diplomat who negotiated the EU AI Act, told Gian. “It fosters a whole tech ecosystem.”

 

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