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WTA’s egg freezing policy is a win for women

Sloane Stephens supports the move. Credit: Getty

Sloane Stephens supports the move. Credit: Getty

June 13 2025 - 2:45pm

The Women’s Tennis Association (WTA) this week announced a landmark policy that will allow female tennis players to take time off to freeze their eggs or embryos without jeopardizing their professional rankings. Women ranked in the top 750 who miss over 10 weeks of competition can now use a special protected ranking to enter up to three tournaments within 10 weeks of returning. Former US Open champion Sloane Stephens, who froze her eggs in the off-season, said the move was “the best thing possible”.

This policy is part of a broader and necessary conversation about the importance of fertility planning for women in general, and especially for those pursuing ambitious or so-called “greedy careers”, amid declining birthrates. For many, their 30s are critical for professional advancement but also a time when fertility declines sharply. Egg freezing offers a solution by allowing women to separate reproductive timing from biological aging, giving them more flexibility and control over their lives and careers.

The underlying premise of egg freezing is that the primary issue that causes a decline in female fertility with age is the egg aging and not aging of the broader female reproductive system itself (e.g. uterus). This is clear in data which indicates that women using younger donor eggs have birth success rates similar to younger women using their own eggs as measured by the percentage of transferred embryos resulting in a live birth. By contrast, women over 35 using their own eggs see a decline in success, with a dramatic decline in one’s 40s.

Despite this, public perception of egg freezing is mixed. Some view it as a false promise, encouraging women to delay childbirth without guaranteeing results. This skepticism stems from outdated technology and poor media coverage. Early freezing techniques used slow-freeze methods that often damaged eggs. But the introduction of vitrification in the mid 2000s marked a turning point. The American Society for Reproductive Medicine (ASRM) has since removed the “experimental” label from egg freezing in 2012.

Yet misleading headlines persist. A 2024 Vox article titled “The Failed Promise of Egg Freezing” cites a 39% success rate, based on a retrospective study conducted over 15 years on 543 women at NYU Langone. However, deeper analysis reveals that the study’s participants were not freezing their eggs at an optimal age, with the median age of egg freezing being 38. When stratified by age and egg number, the story changes: women who were under 38 at the time of freezing and froze 20 or more eggs had a 70% success rate, comparable to IVF using fresh eggs collected at the same age. It is reasonable to speculate that these success rates would be even higher for women freezing eggs at lower ages, but this is not yet confirmed and high quality studies shedding light on this question would be very informative.

Although improving the underlying technology behind IVF is certainly desirable, the bigger barriers to successful egg freezing at the moment are informational and financial. Many women remain unaware of the optimal time to freeze eggs: biologically speaking, between ages 25 and 32. Yet most freeze eggs much later, with the median age across studies being 35.538 (meaning half freeze eggs after this point). What’s more, an egg freezing cycle costs between $5,000 to $8,000 in the US, including medication. Simply put: women can least afford to freeze their eggs when it would be optimal for them to do it.

Unfortunately, freezing eggs later not only reduces the chances of success due to a decline in egg quality, but also increases the cost, as older women need more cycles to retrieve enough viable eggs. Another problem is that not all clinics are the same. Survival rates for thawed (defrosted) eggs range from 71% to 94%, depending on the clinic, but data is not consistently reported and some clinics do not show survival success rates at all. It is highly likely many clinics have survival rates way below 71% that they simply do not report.

There are several paths forward. On the scientific front, improving IVF outcomes so fewer eggs are needed could make the entire process more efficient and dramatically reduce costs, as fewer eggs and consequently less retrieval cycles would be needed in the first place.

From a cultural and policy perspective, women may benefit from better education about how important it is to freeze eggs early. This is separate from the moral question about whether we ought to be recommending this for young women in the first place rather than encouraging people to have kids at a younger age. Yet, for women who feel that starting a family would truly hamper their career — as in physically demanding professional sport — policies like the WTA’s offer another route amid a global birth rate crisis.


Ruxandra Teslo is a fellow at Renaissance Philanthropy and co-founder of the Clinical Trial Abundance project. She writes about the intersection of science, culture, and policy at her Substack. She holds a PhD in Genomics from Cambridge University.


China is threatening America in the AI race

Reports sugget Zhipu AI  has released a new model that can rival leading US systems. Credit: Getty

Reports sugget Zhipu AI has released a new model that can rival leading US systems. Credit: Getty

July 1 2026 - 10:18am

China is trying to catch up with America on artificial intelligence. The Wall Street Journal has reported that Zhipu AI — one of China’s six “AI tiger” LLMs — has released a new model that can rival leading US systems, including Anthropic’s Mythos, in cybersecurity tasks such as pinpointing security bugs. While this marks a milestone in China’s drive to catch up with Western AI capabilities, strong performance on a single benchmark does not mean it has taken the lead. Chinese models still lag behind their Western counterparts in broader capabilities, such as autonomous operation. Skepticism is therefore warranted before resorting to hysterical conclusions, but complacency about the geopolitical implications of China’s AI advances would be an even greater mistake.

On the infrastructure side, Chinese AI is still constrained by access to advanced chips, with American labs way ahead in computing capacity as well as investment. Analysis from earlier this year suggests that Chinese models are likely to be at least a few months behind those in the US. But they are still continuing to make progress, or that the geopolitical importance of AI will be decided only by whose LLM has ventured deeper into the technological frontier. The practical applications of AI, countries’ to capture foreign markets, and the application of AI into the real economy will matter just as much.

Here, China may hold an advantage. As with its dominance across many critical supply chains, Beijing may not need to produce the most advanced AI systems — only those that are affordable and widely deployable. In doing so, it could consolidate global influence by supplying functional, low-cost AI at scale.

Beijing seems to be pursuing exactly that path, developing an AI “open-source” strategy that offers affordable, widely available AI models for companies and individuals to use and modify as they wish. The production of the DeepSeek AI model, which matched the performance of Silicon Valley tools such as ChatGPT at a fraction of the cost for users, created goodwill among Chinese models with developers.

The four most popular models on OpenRouter, an AI hardware platform for developers, are now all Chinese. The goal for China is not only to win the frontier-model race, but to make its systems the default layer of AI adoption across industries and global markets. For most economies, the choice is increasingly between an affordable tool they can deploy now and a more robust one that may be out of reach.

And while the countries adopting Chinese models may be exposed to political pressure and cyber threats from Beijing, safer and more capable alternatives matter little if they are unaffordable. American AI companies are already under pressure to monetize products whose operating costs are rising. If Chinese open-source models become the cheap default for startups, universities, governments and businesses across the developing world, then America’s AI lead will be eroded from below.

Perhaps more concerning for America in the long run is how AI can give Chinese manufacturing even more strength, through the ongoing integration of AI as a general-purpose technology. China’s new Five-Year Plan mentioned AI more than 50 times and includes an “AI+” action plan aimed at spreading AI across the economy.

Beijing has been pioneering automation of its critical infrastructure for years, with promising recent results in increasing warplane production capacity. In that regard, China’s open-model strategy and manufacturing dominance will reinforce each other. Cheap, adaptable models accelerate deployment across the real economy while those deployments generate real-world data and use cases that can feed back into further model improvement.

The United States should not dismiss the importance of its lead in the AI race. That lead worries Beijing, not least because a more automated Chinese economy would also become more vulnerable to AI-generated cyber threats. But nor should Washington assume that China cannot catch up with American capabilities over time.

This AI competition represents part of a broader struggle over tech supply chains and geopolitical influence. Decisions over whether to adopt US or Chinese models could produce a more fragmented global reality, with different regions relying on different cloud providers, chips and security structures. The result will likely be a global economy which is divided into competing spheres, rather than one which produces a single winner.


Miquel Vila is a political and geopolitical risk consultant focusing on industrial strategy, critical infrastructure and global supply chains.

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