AI Uncertainty and Fertility Tech: Key Questions Answered

Technology is advancing at a breathtaking pace, but not everyone feels excited about it. In recent essays and reports, experts have highlighted a growing sense of unease—dubbed AI malaise—as artificial intelligence becomes ubiquitous, yet its long-term effects remain murky. Meanwhile, innovations in fertility technology are reshaping how families are created, with robots and AI stepping into IVF labs. And beyond the clinic, law enforcement agencies are exploring smart glasses for real-time identification. This Q&A covers the most pressing questions from today's tech landscape.

What is the era of AI malaise?

Coined by MIT Technology Review's editor-in-chief Mat Honan, AI malaise describes the strange, unsettled feeling many people share as AI spreads into every corner of life. We know the technology isn't going away, but we're uncertain what it will ultimately do. Will it improve society or undermine it? Could it steal jobs or crash the economy? Apps are being injected with AI features whether users want them or not, and it's increasingly difficult to gauge whether we're relying on AI too heavily—or not enough. This mood of confusion and anxiety is captured in an essay accompanying the publication's list of 10 Things That Matter in AI Right Now, which highlights key trends shaping the field.

How is technology reshaping babymaking?

Fertility technology has undergone a profound transformation. Clinicians now use improved hormonal treatments, embryologists can culture embryos longer in the lab, and IVF clinics offer multiple genetic tests for embryos. These advances have not only boosted success rates but also allowed for changes in family structure, giving would-be parents more reproductive choices. Looking ahead, AI and robots are poised to usher in another new era for IVF. Automated systems can analyze embryo quality more consistently, while machine learning helps predict implantation success. The social impact is equally significant, with technology enabling single parents, same-sex couples, and older individuals to have biological children.

How are robots learning to operate in the real world?

For decades, researchers dreamed of robots that could move through human environments, adapt, and interact naturally. But actual progress was slow because programming every scenario proved impossible. Now, advances in AI have sparked a revolution. Instead of following rigid rules, robots learn through trial and error, running simulations, and processing vast amounts of real-world data. This approach lets them handle the messiness of everyday life—opening doors, navigating crowds, or picking up unfamiliar objects. The shift has rekindled big ambitions in Silicon Valley, with roboticists believing that general-purpose helper robots might finally be within reach. The full story, published in MIT Technology Review's print magazine, details the milestones that led to this transformation.

What new developments are happening with smart glasses and law enforcement?

Immigration and Customs Enforcement (ICE) is reportedly planning to develop its own smart glasses, dubbed ICE Glasses, capable of identifying people in real time using biometric data. This follows existing practices: ICE already uses an app with facial recognition to track citizens. However, these plans have sparked privacy concerns and legal challenges. A new lawsuit aims to stop ICE from using DNA to track individuals without proper oversight. The move highlights the growing tension between surveillance technology and civil liberties, especially when deployed by agencies with broad enforcement powers. These stories, selected from today's must-reads, underscore the ongoing debate over how much monitoring is acceptable in a democratic society.

Why is it so hard to know if we're using AI too much or too little?

The core of AI malaise lies in a fundamental uncertainty. On one hand, AI promises efficiency, innovation, and solutions to complex problems. On the other, its rapid integration feels forced and opaque. Users don't always have a choice—AI features appear in operating systems, search engines, and productivity tools whether asked for or not. Economists debate whether automation will create new jobs or render millions obsolete. There's no clear consensus on how much AI is optimal. This ambiguity leaves both individuals and policymakers guessing, leading to the uncomfortable feeling described in Mat Honan's essay. Until we have better metrics for measuring AI's societal impact, the malaise is likely to persist.

What social impacts have fertility technologies had on families?

Fertility technologies have dramatically expanded the definition of family. In vitro fertilization (IVF) and genetic testing allow people to have children later in life, while same-sex couples and single individuals can now become biological parents with the help of egg or sperm donors. Surrogacy and embryo adoption further broaden options. However, these advances also raise ethical questions about genetic selection, the commercialization of reproduction, and access inequalities. The technology has enabled family structures that were once impossible, but it also requires careful regulation to ensure equitable access and informed consent. As AI and robots enter IVF labs, these social implications will only grow more complex.