Kathy Griffin admits vanity behind third facelift and describes graphic details of painful recovery
The comedian opens up about her latest cosmetic surgery, crediting Beverly Hills surgeon Dr Ben Talei and revealing unfiltered truths about the aftermath.
Kathy Griffin opens up about third facelift and painful healing process
Pooja Pillai is an entertainment journalist with Asian Media Group, where she covers cinema, pop culture, internet trends, and the politics of representation. Her work spans interviews, cultural features, and social commentary across digital platforms.
She began her reporting career as a news anchor, scripting and presenting stories for a regional newsroom. With a background in journalism and media studies, she has since built a body of work exploring how entertainment intersects with social and cultural shifts, particularly through a South Indian lens.
She brings both newsroom rigour and narrative curiosity to her work, and believes the best stories don’t just inform — they reveal what we didn’t know we needed to hear.
Comedian Kathy Griffin admits to having her third facelift along with eyelid and chin surgery.
The Emmy-winning star credits Beverly Hills surgeon Dr Ben Talei, who has also worked with singer Sia.
Griffin shared the recovery was “painful” and detailed the difficult first days post-surgery.
The My Life on the D-List star has a long history with cosmetic procedures dating back to her 20s.
Kathy Griffin is once again making headlines, not for her comedy, but for her latest cosmetic transformation. The 64-year-old comedian was photographed in Malibu this week looking noticeably more youthful after confirming she had undergone her third facelift, along with additional work on her eyelids and chin.
Griffin, known for her sharp wit and unapologetic honesty, was seen leaving a Pilates class wearing an orange T-shirt reading “Adopt, Don’t Shop,” navy leggings, black flats, and oversized orange sunglasses. Her signature red hair was tied back in a high ponytail as she carried a patterned tote bag in the bright California sun.
The stand-up comic confirmed the surgery on her Talk Your Head Off podcast, telling listeners, “Yes, it’s my third. I know that’s so vain! No one has ever gone to a Kathy Griffin show to see her beautiful, youthful face. You come to hear my jokes.”
Kathy Griffin describes tough recovery after undergoing faceliftGetty Images
Who performed Kathy Griffin’s facelift?
Griffin named Beverly Hills-based Dr Ben Talei as the surgeon behind her latest procedures. Talei is also known for performing a facelift on global pop star Sia, whose before-and-after results Griffin described as “the best” she had ever seen.
This round of surgery included a facelift, blepharoplasty (eyelid surgery), a fox eye lift, and chin work. “There’s a stitch in my chin, which you’re probably not going to see unless you’re under me, but not in that way,” she joked.
Far from glamorising the experience, Griffin admitted the healing process was challenging. “I’m going to be honest, it’s painful,” she said. “So, these people who say it’s like getting a tooth filled? No. It’s painful.”
She described the immediate aftermath in blunt detail, saying she spent the first days in a “rich lady recovery place” before going home with a nurse. “The first night there are drains that come out of your chin… it’s disgusting. But the vanity takes over,” she confessed.
Kathy Griffin’s long history with cosmetic surgery
Griffin has been open about cosmetic procedures since her early career. She had her first nose job at 26 after being told repeatedly she would “work more” with a smaller nose. Over the years, she’s had breast augmentation, a brow lift, liposuction, facial peels, and now three facelifts.
Her 2009 memoir, Official Book Club Selection, included unfiltered post-surgery images, something she says she shared to show the reality behind the procedures. “I want women to know what lipo looks like. Are you sure you don’t want to just work out a little more?” she wrote at the time.
Kathy Griffin discusses vanity behind third facelift and difficult recoveryGetty Images
Why is Kathy Griffin talking about it now?
While many celebrities keep cosmetic work private, Griffin has built her brand on telling uncomfortable truths, whether about Hollywood politics, her health, or her appearance. Her candid approach continues to spark public conversation about the pressures women, especially in entertainment, face to maintain a youthful image.
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Her latest facelift adds to a decades-long discussion she’s had with her audience about beauty standards, body image, and self-acceptance, even if she admits that a touch of vanity still plays a role.
AI can make thousands of podcast episodes every week with very few people.
Making an AI podcast episode costs almost nothing and can make money fast.
Small podcasters cannot get noticed. It is hard for them to earn.
Advertisements go to AI shows. Human shows get ignored.
Listeners do not mind AI. Some like it.
A company can now publish thousands of podcasts a week with almost no people. That fact alone should wake up anyone who makes money from talking into a mic.
The company now turns out roughly 3,000 episodes a week with a team of eight. Each episode costs about £0.75 (₹88.64) to make. With as few as 20 listens, an episode can cover its cost. That single line explains why the rest of this story is happening.
When AI takes over podcasts human creators are struggling to keep up iStock
The math that changes the game
Podcasting used to be slow and hands-on. Hosts booked guests, edited interviews, and hunted sponsors. Now, the fixed costs, including writing, voice, and editing, can be automated. Once that system is running, adding another episode barely costs anything; it is just another file pushed through the same machine.
To see how that changes the landscape, look at the scale we are talking about. By September 2025, there were already well over 4.52 million podcasts worldwide. In just three months, close to half a million new shows joined the pile. It has become a crowded marketplace worth roughly £32 billion (₹3.74 trillion), most of it fuelled by advertising money.
That combination of a huge market plus near-zero marginal costs creates a simple incentive: flood the directories with niche shows. Even tiny audiences become profitable.
What mass production looks like
These AI shows are not replacements for every human program. They are different products. Producers use generative models to write scripts, synthesise voice tracks, add music, and publish automatically. Topics are hyper-niche: pollen counts in a mid-sized city, daily stock micro-summaries, or a five-minute briefing on a single plant species. The episodes are short, frequent, and tailored to narrow advertiser categories.
That model works because advertisers can target tiny audiences. If an antihistamine maker can reach fifty people looking up pollen data in one town, that can still be worth paying for. Multiply that by thousands of micro-topics, and the revenue math stacks up.
How mass-produced AI podcasts are drowning out real human voicesiStock
Where human creators lose
Podcasting has always been fragile for independent creators. Most shows never break even. Discoverability is hard. Promotion costs money. Now, add AI fleets pushing volume, and the problem worsens.
Platforms surface content through algorithms. If those algorithms reward frequency, freshness, or sheer inventory, AI producers gain an advantage. Human shows that take weeks to produce with high-quality narrative, interviews, or even investigative pieces get buried.
Advertisers chasing cheap reach will be tempted by mass AI networks. That will push down the effective CPMs (cost per thousand listens) for many categories. Small hosts who relied on a few branded reads or listener donations will see the pool shrink.
What listeners get and what they lose
Not every listener cares if a host is synthetic. Some care only about the utility: a quick sports update, a commute briefing, or a how-to snippet. For those use cases, AI can be fine, or even better, because it is faster, cheaper, and always on.
But the thing is, a lot of podcast value comes from human quirks. The long-form interview, the offbeat joke, the voice that makes you feel known—those are hard to fake. Studies and industry voices already show 52% of consumers feel less engaged with content. The result is a split audience: one side tolerates or prefers automated, functional audio; the other side pays to keep human voices alive.
When cheap AI shows flood the market small creators lose their edgeiStock
Legal and ethical damage control
Mass AI podcasting raises immediate legal and ethical questions.
Copyright — Models trained on protected audio and text can reproduce or riff on copyrighted works.
Impersonation — Synthetic voices can mirror public figures, which risks deception.
Misinformation — Automated scripts without fact-checking can spread errors at scale.
Transparency — Few platforms force disclosure that an episode is AI-generated.
If regulators force tighter rules, the tiny profit margin on each episode could disappear. That would make the mass-production model unprofitable overnight. Alternatively, platforms could impose labelling and remove low-quality feeds. Either outcome would reshape the calculus.
How the industry can respond through practical moves
The ecosystem will not collapse overnight.
Label AI episodes clearly.
Use discovery algorithms that reward engagement, not volume.
Create paywalls, memberships, or time-listened metrics.
Use AI tools to help humans, not replace them.
Industry standards on IP and voice consent are needed to reduce legal exposure. Platforms and advertisers hold most of the cards here. They can choose to favour volume or to protect quality. Their choice will decide many creators’ fates.
Three short scenarios, then the point
Flooded and cheap — Platforms favour volume. Ads chase cheap reach. Many independent shows vanish, and audio becomes a sea of similar, useful, but forgettable feeds.
Regulated and curated — Disclosure rules and smarter discovery reward listener engagement. Human shows survive, and AI fills utility roles.
Hybrid balance — Creators use AI tools to speed up workflows while keeping control over voice and facts. New business models emerge that pay for depth.
All three are plausible. The industry will move towards the one that matches where platforms and advertisers put their money.
Can human podcasters survive the flood of robot-made showsiStock
New rules, old craft
Machines can mass-produce audio faster and cheaper than people. That does not make them better storytellers. It makes them efficient at delivering information. If you are a creator, your defence is simple: make content machines cannot copy easily. Tell stories that require curiosity, risk, restraint, and relationships. Build listeners who will pay for that difference.
If you are a platform or advertiser, your choice is also simple: do you reward noise or signal? Reward signal, and you keep what made podcasting special. Reward noise, and you get scale and a thinner, cheaper industry in return. Either way, the next few years will decide whether podcasting stays a human medium with tools or becomes a tool-driven medium with a few human highlights. The soundscape is changing. If human creators want to survive, they need to focus on the one thing machines do not buy: trust.
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