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In December, our small but mighty AI reporting team was asked by our editors to make a prediction: What’s coming next for AI?
In 2024, AI contributed both to Nobel Prize–winning chemistry breakthroughs and a mountain of cheaply made content that few people asked for but that nonetheless flooded the internet. Take AI-generated Shrimp Jesus images, among other examples. There was also a spike in greenhouse-gas emissions last year that can be attributed partly to the surge in energy-intensive AI. Our team got to thinking about how all of this will shake out in the year to come.
As we look ahead, certain things are a given. We know that agents—AI models that do more than just converse with you and can actually go off and complete tasks for you—are the focus of many AI companies right now. Building them will raise lots of privacy questions about how much of our data and preferences we’re willing to give up in exchange for tools that will (allegedly) save us time. Similarly, the need to make AI faster and more energy efficient is putting so-called small language models in the spotlight.
We instead wanted to focus on less obvious predictions. Mine were about how AI companies that previously shunned work in defense and national security might be tempted this year by contracts from the Pentagon, and how Donald Trump’s attitudes toward China could escalate the global race for the best semiconductors. Read the full list.
What’s not evident in that story is that the other predictions were not so clear-cut. Arguments ensued about whether or not 2025 will be the year of intimate relationships with chatbots, AI throuples, or traumatic AI breakups. To witness the fallout from our team’s lively debates (and hear more about what didn’t make the list), you can join our upcoming LinkedIn Live this Thursday, January 16. I’ll be talking it all over with Will Douglas Heaven, our senior editor for AI, and our news editor, Charlotte Jee.
There are a couple other things I’ll be watching closely in 2025. One is how little the major AI players—namely OpenAI, Microsoft, and Google—are disclosing about the environmental burden of their models. Lots of evidence suggests that asking an AI model like ChatGPT about knowable facts, like the capital of Mexico, consumes much more energy (and releases far more emissions) than simply asking a search engine. Nonetheless, OpenAI’s Sam Altman in recent interviews has spoken positively about the idea of ChatGPT replacing the googling that we’ve all learned to do in the past two decades. It’s already happening, in fact.
The environmental cost of all this will be top of mind for me in 2025, as will the possible cultural cost. We will go from searching for information by clicking links and (hopefully) evaluating sources to simply reading the responses that AI search engines serve up for us. As our editor in chief, Mat Honan, said in his piece on the subject, “Who wants to have to learn when you can just know?”
Now read the rest of The Algorithm
Deeper Learning
What’s next for our privacy?
The US Federal Trade Commission has taken a number of enforcement actions against data brokers, some of which have tracked and sold geolocation data from users at sensitive locations like churches, hospitals, and military installations without explicit consent. Though limited in nature, these actions may offer some new and improved protections for Americans’ personal information.
Why it matters: A consensus is growing that Americans need better privacy protections—and that the best way to deliver them would be for Congress to pass comprehensive federal privacy legislation. Unfortunately, that’s not going to happen anytime soon. Enforcement actions from agencies like the FTC might be the next best thing in the meantime. Read more in Eileen Guo’s excellent story here.
Bits and Bytes
Meta trained its AI on a notorious piracy database
New court records, Wired reports, reveal that Meta used “a notorious so-called shadow library of pirated books that originated in Russia” to train its generative AI models. (Wired)
OpenAI’s top reasoning model struggles with the NYT Connections game
The game requires players to identify how groups of words are related. OpenAI’s o1 reasoning model had a hard time. (Mind Matters)
Anthropic’s chief scientist on 5 ways agents will be even better in 2025
The AI company Anthropic is now worth $60 billion. The company’s cofounder and chief scientist, Jared Kaplan, shared how AI agents will develop in the coming year. (MIT Technology Review)
A New York legislator attempts to regulate AI with a new bill
This year, a high-profile bill in California to regulate the AI industry was vetoed by Governor Gavin Newsom. Now, a legislator in New York is trying to revive the effort in his own state. (MIT Technology Review)
