A film I loved growing up was the 1986 classic Short Circuit. In one scene, Johnny Five, the incredible robot that becomes “alive” after being struck by lightning, devours book after book, spending seconds on each title. Soon he runs out. “Ahh! More input, Stephanie! More!”
“There isn’t anything more!” replies Stephanie, the woman who found him. “You’ve read everything in the house!”
I asked OpenAI’s ChatGPT if it could relate. “Absolutely — I totally empathize with Johnny Five,” it responded. “‘Need input!’ is basically my core vibe. The more info I get, the better I understand, respond, and connect. Johnny was just an AI [artificial intelligence] trying to make sense of the world ... same here, just with fewer laser beams and more typing.”
It is true. While ChatGPT does not move around on caterpillar tread, or have a laser gun strapped to its back (yet), its challenges are cannily identical. Having scraped just about the entire sum of human knowledge, ChatGPT and other AI efforts are making the same rallying cry: Need input!
One solution is to create synthetic data and to train a model using that, though this comes with inherent challenges, particularly around perpetuating bias or introducing compounding inaccuracies.
The other is to find a great gushing spigot of new and fresh data, the more “human” the better. That is where social networks come in, digital spaces where millions, even billions, of users willingly and constantly post reams of information. Photos, posts, news articles, comments — every interaction of interest to companies that are trying to build conversational and generative AI. Even better, this content is not riddled with the copyright violation risk that comes with using other sources.
Lately, top AI companies have moved more aggressively to own or harness social networks, trampling over the rights of users to dictate how their posts may be used to build these machines. Social network users have long been “the product,” as the famous saying goes. They are now also a quasi “product developer” through their posts.
Some companies had the benefit of a social network to begin with. Meta Platforms Inc, the biggest social networking company on the planet, used in-app notifications to inform users that it would be harnessing their posts and photos for its Llama AI models. Late last month, Elon Musk’s xAI acquired X, formerly Twitter, in what was primarily a financial sleight of hand, but one that made ideal sense for Musk’s Grok AI. It has been able to gain a foothold in the chatbot market by harnessing timely tweets posted on the network as well as the huge archive of online chatter dating back almost two decades. Then there is Microsoft Corp, which owns the professional network LinkedIn and has been pushing heavily for users (and journalists) to post more original content to the platform.
However, Microsoft does not share LinkedIn data with its close partner OpenAI, which might explain reports that the ChatGPT maker was in the early stages of building a social network of its own. OpenAI’s CEO and cofounder, Sam Altman, has been soliciting feedback on the idea, news Web site The Verge reported, noting that Altman had earlier hinted that such a project was on his mind when it was reported that Meta would be releasing a standalone AI app to compete with ChatGPT.
Other companies without a social media head start are realizing it puts them at a disadvantage. Perplexity.ai in March made public its bid to buy TikTok, noting its value for a company building an AI search engine.
“This would provide users with comprehensive, well-cited answers that combine the best answer engine in the world with one of the largest libraries of user generated content,” the company said.
Earlier this month, Amazon.com Inc was also reported to be among the bidders, though CEO Andy Jassy declined to comment when asked directly by CNBC.
Google, which has tried and failed to make various social networks happen, has less need for TikTok videos because it already owns YouTube. Instead, it has put in place an “expanded partnership” with Reddit, the link-sharing social network, giving it access, Google said in a blog post last year, to “an incredible breadth of authentic, human conversations and experiences.” Expect more deals like this: A former Reddit competitor, Digg, is being revived with the obvious intent to create another repository of human interactions that will be of use to AI companies.
All of these moves speak to AI companies’ demand for data. It comes at the expense of users who entered information on social networks for one purpose and now find it being used for another. Quietly, companies have been altering privacy policies to cover the legality of this shift.
Hidden away in settings, you can find ways to isolate your data from being used to build AI — though you are likely already too late. Like Johnny Five, AI companies “need input!” They are going to get it however and from wherever they can.
Dave Lee is Bloomberg Opinion’s US technology columnist. He was previously a correspondent for the Financial Times and BBC News. This column reflects the personal views of the author and does not necessarily reflect the opinion of the editorial board or Bloomberg LP and its owners.
A foreign colleague of mine asked me recently, “What is a safe distance from potential People’s Liberation Army (PLA) Rocket Force’s (PLARF) Taiwan targets?” This article will answer this question and help people living in Taiwan have a deeper understanding of the threat. Why is it important to understand PLA/PLARF targeting strategy? According to RAND analysis, the PLA’s “systems destruction warfare” focuses on crippling an adversary’s operational system by targeting its networks, especially leadership, command and control (C2) nodes, sensors, and information hubs. Admiral Samuel Paparo, commander of US Indo-Pacific Command, noted in his 15 May 2025 Sedona Forum keynote speech that, as
Chinese Nationalist Party (KMT) Chairman Eric Chu (朱立倫) last week announced that the KMT was launching “Operation Patriot” in response to an unprecedented massive campaign to recall 31 KMT legislators. However, his action has also raised questions and doubts: Are these so-called “patriots” pledging allegiance to the country or to the party? While all KMT-proposed campaigns to recall Democratic Progressive Party (DPP) lawmakers have failed, and a growing number of local KMT chapter personnel have been indicted for allegedly forging petition signatures, media reports said that at least 26 recall motions against KMT legislators have passed the second signature threshold
In a world increasingly defined by unpredictability, two actors stand out as islands of stability: Europe and Taiwan. One, a sprawling union of democracies, but under immense pressure, grappling with a geopolitical reality it was not originally designed for. The other, a vibrant, resilient democracy thriving as a technological global leader, but living under a growing existential threat. In response to rising uncertainties, they are both seeking resilience and learning to better position themselves. It is now time they recognize each other not just as partners of convenience, but as strategic and indispensable lifelines. The US, long seen as the anchor
The Central Election Commission (CEC) on Friday announced that recall motions targeting 24 Chinese Nationalist Party (KMT) lawmakers and Hsinchu Mayor Ann Kao (高虹安) have been approved, and that a recall vote would take place on July 26. Of the recall motions against 35 KMT legislators, 31 were reviewed by the CEC after they exceeded the second-phase signature thresholds. Twenty-four were approved, five were asked to submit additional signatures to make up for invalid ones and two are still being reviewed. The mass recall vote targeting so many lawmakers at once is unprecedented in Taiwan’s political history. If the KMT loses more