Essays in the Category "AI and Large Language Models"
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Should You Use AI for a Task? Here’s a Simple Way to Decide
Sometimes, what matters isn’t your output but what you put into the process. Think of it like work vs. the gym
I teach public policy at the Harvard Kennedy School and the Munk School at the University of Toronto. And it will come as no surprise to you that my students regularly use AI to complete their writing assignments. Doing so is a waste of their tuition money. But if their entire career is going to include AI writing assistants, why shouldn’t they embrace their future?
The best way I’ve found to explain the dilemma comes from the AI researcher Daniel Meissler: it’s the difference between work and the gym.
At work, if your job is to move a bunch of heavy things from one side of the room to another, you should use whatever assistive tech you have on hand: a wagon, a forklift … even an AI-powered robot. But at the gym, it makes no sense for that robot to lift weights for you. The point of weightlifting isn’t to move heavy things across the room; it’s to actually lift those heavy things…
Why AI Needs a “Genie Coefficient”
Proposing a new metric for whether AI does what you actually want
Major benchmarks measure what AI can do. None measure whether it does what you mean: the distance between what you ask an AI to do and the unspoken assumptions about how you want the AI to do it. We propose a new metric: the Genie coefficient.
There’s often a gap between one person’s request and another’s understanding. Most of the time, we bridge it using general knowledge. For example, if you ask a friend to get you coffee, they’ll pour a cup from the pot or buy one from a coffee shop. They won’t bring you a bag of raw beans or snatch a cup from a stranger and hand it to you. You never specified any of this. You never had to…
The Fight Against AI Data Centers Is Important—but It’s Just a Starting Point
AI companies want to capture the value created by entire industries. That concentration of wealth and power is society’s greatest risk
Opposition to AI data centers has emerged as a primary theme in US politics, one that—surprisingly—doesn’t fall along party lines. We applaud people coming together for constructive debate on any issue, and agree that communities need to evaluate whether any economic benefits these data centers bring is worth their costs. Still, we worry that a focus on data centers obscures the larger impacts of AI on people’s lives: the concentration of power of AI companies, and their widespread political and financial influence.
Local data center opposition is grounded in legitimate concerns about misallocation of land resources when housing is at a premium, …
AI Surveillance Is Being Supercharged—and It Will Chill Social Progress
These systems will soon be able to track our public and private lives. But we can make the policy choices to reject it
In the near future, AI-powered surveillance systems will be able to track everything we do in public, and much of what we do in private. And if we do something wrong—shoplift, litter, jaywalk, you name it—the system will notice, retain it, tie it to your official government record, communicate that fact to you, and provide real-time alerts to any relevant authorities… and maybe also to the general public.
Think of these systems as automated speed cameras, but on steroids. Only they’ll enforce not just speed limits, but any other rule you can imagine. And you won’t receive a ticket weeks later by mail; you’ll be informed about and fined for your violation immediately…
Once, Cyberattacks Required Great Skill. AI Is Changing That
Modern AI systems are, in effect, a universal adviser to help people do harmful things. We’ll need to harness AI for defense, too
Last week, national security agencies from the Five Eyes—that’s the rich, English-language-speaking countries club—jointly released a statement warning of the increasing cyber risks of AI models: in particular, their ability to autonomously hack into systems and networks. The statement was more measured than some of the breathless headlines about it, and the advice they gave is pretty much the standard advice everyone gives—albeit with newfound urgency.
Internet risks are nothing new, and cyberattacks—both large and small—have been a significant issue since long before the current crop of generative AI models…
If an AI Chatbot Misleads You, Who Is to Blame?
A court in Germany found that Google was responsible for what its chatbots say in search summaries. This is the accountability we need
Earlier this month, a German court ruled that Google is liable for its AI search summaries. Rejecting defenses like “users can check for themselves,” and that they generally know “that information generated with AI should not be blindly trusted,” the court held that the AI’s summaries are reflections of the company and “above all an expression of Google’s business activities.”
This is the latest skirmish in a decades-old battle over internet publishing. Historically, there were two different types of information distributors: carriers and publishers. A phone company is a carrier. It’ll transmit whatever you say, even discussions about committing a crime. Words are words, and the phone company does not know—nor is it liable for—the words you choose to speak. A newspaper, on the other hand, is a publisher. It decides the words it publishes, and what quotes to include in its articles. If those words or quotes are defamatory or otherwise illegal, it’s liable…
The Anthropic “Fable” Saga Proves: We Have Opened the AI Pandora’s Box. What Now?
We have opened the AI Pandora’s box. Now we have to make the best of it
On June 9th, Anthropic released its Fable generative AI model. Three days later, the US government classified it as a dangerous munition, and used its export-control authority to prohibit any foreign nationals from accessing it. Unable to differentiate between Americans and foreigners, the company shut off access for everyone.
The government’s actions won’t help. The problem isn’t any one particular model; it’s the general trend of increasing AI capabilities. And any real solution requires the sort of collective action that just isn’t possible right now…
AI Use by the US Government Is Ballooning. And the Lack of Transparency Is Troubling
The list of government AI use cases has ballooned by 70% since Biden left office and includes many plans to hand over sensitive governmental functions to AI
On 14 April, the Trump administration quietly acknowledged the widespread use of AI to automate government processes. The office of management and budget (OMB) disclosed a staggering 3,611 active or planned use cases for AI across the federal government. The list has ballooned by 70% from the one published in the final year of the Biden administration, and includes many disturbing-seeming plans to hand over sensitive governmental functions to AI.
Scanning this list, many readers may find many causes for alarm. It represents a transfer of decision processes from human to machine on a massive scale over matters of individual freedom, public health and well-being, nuclear reactor safety and more…
Bernie Sanders’ AI Sovereign Wealth Fund Plan Is Good. But We Think This Is Better
While we do not outright oppose the taking of AI company stock, or of a US sovereign wealth fund, there are better ways to achieve the senator’s goals
Let no one accuse Bernie Sanders of ducking the big questions. Writing in the New York Times last week, the senator asked: “Will the future of humanity be determined by a handful of billionaires who have promoted and developed AI, with virtually no democratic input, who stand to become even richer and more powerful than they are today?”
We agree entirely that this is one of the most potent questions facing global democracy today. Our book, Rewiring Democracy, surveys the emerging uses for and impacts of AI in democracy around the world and reaches the same conclusion: that the most urgent risk posed by AI is the …
Rewiring Democracy: AI & the Struggle for Open Knowledge in Brazil
Rewiring Democracy Series, Part 3
This is the third in a multi-part series by Sanders and Schneier going into depth on real-world examples of democratic technologies from their book, Rewiring Democracy: How AI Will Transform Our Politics, Government, and Citizenship. Their first piece was about the Japanese digital democracy party “Team Mirai” and their second was about the Swiss Public AI model “Apertus.”
It’s not an easy time for those trying to do good in the world, especially for those in the Global South. Financial pressures from the collapse of foreign aid, surging energy costs, and inflation combine with rising authoritarianism and a …
Sidebar photo of Bruce Schneier by Joe MacInnis.