Controversial TikTok personality Kyle Marisa Roth dies at 36
Her rise to internet fame was marked by her bold takes on current events in pop culture and her willingness to dissect celebrity gossip, she also used her catchphrase, “You want more? I’ll give you more,” was a popular feature of her content.”
By Vibhuti PathakApr 16, 2024
TikTok personality Kyle Marisa Roth, known for her unvarnished opinions on celebrities and controversial Hollywood "blind items," has died at the age of 36. Her passing was announced on April 15 by her sister Lindsay, who shared the news with fans on Instagram.
In her post, Lindsay Roth shared the family's devastation and uncertainty regarding the cause of Kyle's death, stating, "This is not a platform for personal life shares but so many of my connections on this platform go back years and I have a devastating loss to share. My daughter Kyle has passed away. She touched some of your lives personally and some of your lives via her immense life on another platform."
The outpouring of grief from Kyle's fans and followers has been evident on social media. In her Instagram post, Lindsay promised to update fans on memorial plans and offered her heartfelt condolences to those who loved Kyle's content, writing, "I am so sorry to those learning about this loss right now. Any prayers, thoughts, blessings, or intentions for this soul's smooth transition are welcomed."
Kyle's mother, Jacquie Roth, also addressed the loss in a heartfelt LinkedIn message. She described her daughter's death as a "devastating loss" and emphasised how her vibrant presence had touched the lives of many people. "Kyle loved and lived fiercely. Nothing makes sense now and we'll understand more in the next few days. Be kind to one another, please," Jacquie wrote.
Since the news of Kyle's passing, there has been a significant outpouring of support for her family, including condolences from celebrity fans. Julia Fox, who starred in the film Uncut Gems, expressed her sadness in a comment under Lindsay's Instagram post: "I know I never met Kyle in real life, but I felt like I knew her. I'm so devastated and have been crying ever since the news leaked on TikTok. I hope she did not suffer, and I hope she knew how much she touched our lives."
Fox continued, "She was a ray of sunshine, and I will miss her deeply."
Over the past few years, Kyle Marisa Roth has built a loyal following of more than 170,000 fans on TikTok. Her rise to internet fame was marked by her bold takes on current events in pop culture and her willingness to dissect celebrity gossip. Her catchphrase, "You want more? I'll give you more," was a popular feature of her content, which often focused on controversial topics in the entertainment industry.
Kyle's sudden death has left her fans and followers in shock. While the circumstances surrounding her death remain unclear, many are left remembering her as a passionate and lively figure in the world of social media.
For those who appreciated Kyle's content, her passing is a significant loss, and her sister Lindsay's promise to update fans on memorial plans offers a glimmer of hope for those seeking to honour her life and memory.
As the Roth family grapples with this tragic loss, many hope that Kyle's legacy will live on through the memories and experiences she shared with her followers. Her distinctive voice and bold approach to discussing celebrity culture made her a standout personality in the online world.
As her family, friends, and fans remember Kyle, they reflect on her impact and the unique perspective she brought to her online community. Kyle Marisa Roth's untimely death has undoubtedly left a void in the world of TikTok and celebrity gossip, but her memory will live on through the content she created and the people she inspired.
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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