By focusing on the economic opportunities and economic data, fears about AI investment can turn into smart business decisions. There are many paths AI evolution could take. On one end of the spectrum, AI is dismissed as a marginal fad, another bubble fueled by notoriety and misallocated capital. On the other end, it's cast as a dystopian force, destined to eliminate jobs on a large scale and destabilize economies. Markets oscillate between skepticism and the fear of missing out, while the technology itself evolves quickly and investment dollars flow at a rate not seen in decades. All the while, many of today's financial and economic thought leaders hold to the consensus that the financial landscape will stay the same as it has been for the last several years.

Bonus: If you're an subscriber, you can join David and Richard, alongside's editor in chief, Mat Honan, for an exclusive conversation live on Tuesday, December 9 at 1pm ET about this topic. Sign up to be a part here . Any far-reaching new technology is always uneven in its adoption, but few have been more uneven than generative AI. That makes it hard to assess its likely impact on individual businesses, let alone on productivity across the economy as a whole. At one extreme, AI coding assistants have revolutionized the work of software developers. Mark Zuckerberg recently predicted that half of Meta's code would be written by AI within a year.

If AI takes over many jobs, how will people make a living? If AI takes over many jobs, how will people make a living? Once the AI bubble pops, we'll all suffer. Could that be better than letting it grow unabated? The Guardian's journalism is independent.

Forget the glorious successes of past breakthroughs--the real justification for research investment is what we get for our money. MIT Technology Review You can read more from the series here. Given the draconian cuts to US federal funding for science, including the administration's proposal to reduce the 2026 budgets of the National Institutes of Health by 40% and the National Science Foundation by 57%, it's worth asking some hard-nosed money questions: How much we be spending on R&D? How much value do we get out of such investments, anyway? To answer that, it's important to look at both successful returns and investments that went nowhere. How Trump's policies are affecting early-career scientists--in their own words Every year, we recognize extraordinary young researchers on our Innovators Under 35 list. Recent honorees told us how they're faring under the new administration.

Artificial Intelligence (AI) is reframed as a cognitive engine driving a novel productivity revolution distinct from the Industrial Revolution's physical thrust. This paper develops a theoretical framing of AI as a cognitive revolution akin to written language - a transformative augmentation of human intellect rather than another mechanized tool. We compare AI's emergence to historical leaps in information technology to show how it amplifies knowledge work. Examples from various domains demonstrate AI's impact as a driver of productivity in cognitive tasks. We adopt a multidisciplinary perspective combining computer science advances with economic insights and sociological perspectives on how AI reshapes work and society. Through conceptual frameworks, we visualize the shift from manual to cognitive productivity. Our central argument is that AI functions as an engine of cognition - comparable to how human language revolutionized knowledge - heralding a new productivity paradigm. We discuss how this revolution demands rethinking of skills, organizations, and policies. This paper, balancing academic rigor with clarity, concludes that AI's promise lies in complementing human cognitive abilities, marking a new chapter in productivity evolution.

In the early hours of April 12, 1812, a crowd of men approached Rawfolds Mill, a four-story stone building on the banks of the River Spen, in West Yorkshire. This was Brontë country--a landscape of bleak moors, steep valleys, and small towns nestled in the hollows. The men, who'd assembled on the moors hours earlier, were armed with muskets, sticks, hatchets, and heavy blacksmith's hammers. When they reached the mill, those at the front broke windows to gain entry, and some fired shots into the darkened factory. But the mill's owner, William Cartwright, had been preparing for trouble.

Any effect on the current statistics, he says, will likely still be quite small and won't be "world-changing," so he's not surprised that signs of AI's impact haven't been detected yet. But he's watching closely, with the hope that over the next few years AI could help reverse a two-decade slump in productivity growth that is undermining much of the economy. If that does happen, Syverson says, "then it is world changing." The newest versions of generative AI are bedazzling, with lifelike videos, seemingly expert-sounding prose, and other all too humanlike behaviors. Business leaders are fretting over how to reinvent their companies as billions flow into startups, and the big AI companies are creating ever more powerful models.

I described a 1999 result by Koutsoupias and Papadimitriou, regarding multi-agent systems. They studied systems in which non-cooperative agents share a common resource and proposed the ratio between the worst possible Nash equilibrium and the social optimum as a measure of the effectiveness of the system. This ratio has become known as the "Price of Anarchy," as it measures how far from optimal such non-cooperative systems can be. They showed that the price of anarchy could be arbitrarily high, depending on the complexity of the system. The Price-of-Anarchy concept has later been extended to other types of equilibria--for example, Pareto-Optimal Equilibria.b

There's no shortage of concern about the speed with which some of the world's top artificial intelligence research labs are rolling out new AI tools that could change the way we live and work. The release of generative AI tools like ChatGPT to the public has prompted consternation about privacy and the spread of misinformation and bias. Not long after Microsoft released an AI-powered version of its search tool, Bing, to a select group of users in February, Bing threatened a philosophy professor with blackmail. A month later, some of the biggest names in tech signed an open letter urging the world's leading artificial intelligence labs to pause training their super-powerful computer systems for six months, arguing that recent advances in AI present "profound risks to society and humanity." In an op-ed in TIME the same day, Eliezer Yudkowsky, a decision theorist who leads the nonprofit Machine Intelligence Research Institute, urged the labs to shut down their research entirely.

The integration of NLP tools into businesses has already shown significant benefits. For example, NLP-powered chatbots can provide customers with instant assistance and support.