The reopening of a coal mine this year near the central Indian village of Chichordi rekindled farmer Dilip Madre's hopes he would finally be compensated for the ruin of his once-bountiful turmeric field and be able to buy a bigger farm further away.
A decade after mining began in his part of western Maharashtra state, Madre and 200 villagers are seeking financial recompense for the losses they say the industry has caused them.
Their land is no longer productive, they argue, covered in rubble, soot, dust and waste sand from the mine, as groundwater levels recede and trucks pass by, dropping coal and debris.
It has been a long wait for the farmers, stretched by the mine's closure in 2015 after a court ruled India's mining blocks were allocated illegally and had to be re-examined.
Soon after, the mine was handed back to its owner, state-run Karnataka Power Corporation Ltd (KPCL), but operations only began again this year after outstanding litigation was resolved, company officials said.
The delay has dashed villagers' hopes of jobs and cash payments for their barren fields - echoing bitter experiences in other Indian coal hubs, energy experts said.
"I thought we would benefit from mining but there have been only losses and uncertainty. My land is infertile now," said Madre, 52, recalling how he used to earn about 500,000 rupees ($6,788) a year from his turmeric crop.
He once hoped to set up a turmeric processing factory and export the spice, but is still waiting for KPCL to buy his farm.
"I want to give (them) this land and get my freedom," Madre told the Thomson Reuters Foundation, standing outside a small grocery shop he runs to make ends meet. "We are in the coal belt. They need our land and we should get something."
Energy transition experts and locals said many communities in coal-producing areas still believe their future hinges on the carbon-heavy fuel, despite the losses they blame on mining.
Often hopes for jobs and land sales are thwarted, while mining companies reap most of the benefits, they added, suggesting it would be better to break the dependence on coal.
A 2020 study looking at 22 coal-rich districts, by the International Forum for Environment, Sustainability and Technology (iFOREST), showed about half their population was impoverished, with poor health, education and living standards.
"Coal mining didn't bring in the benefits local communities assumed it would - but even if they are unhappy, they will be the first to resist the closure of coal mines as a coal-centric economy has limited growth and investment in other sectors," said Srestha Banerjee of iFOREST, a New Delhi-based think-tank.
"Whatever they are getting, or hope to get, is dependent on coal," she added.
STOP AND START
In 2014, when India's top court scrapped all but four of 218 coal blocks allocated by the government over the past two decades, ruling that its practice of selective allocation was illegal and arbitrary, silence engulfed Baranj village.
Located on the opencast mine's edge, a couple of miles from Chichordi, Baranj had earlier been identified as affected by the mine, meaning its residents were compensated for the farmland acquired for mining and about 150 given work.
"We were at a loss when the mine shut. Even though only a few people had found work in the mine, their families were dependent on their earnings," said Sandeep Jiwane, 42, who runs a Baranj tea-shop.
The mine has now reopened but local people said their losses outweighed the benefits from its activities so far.
"Entire families worked on farms, and now one among them has been offered a job. Many sit at home all day because they don't have farms to work on anymore," said Jiwane.
"But then, the only money we are able to make is because of coal. There is no other work here," he said.
Among those who have found a job is Sadhna Subhash Balpane, 40, who waves green and red flags to manage the movement of trucks and dumpers on a broken road leading to the coal mine.
"I earn 5,000 rupees monthly for an eight-hour shift. I used to work as a farm labourer earlier, but there are no farmlands any more in this village," said Balpane, whose husband is a tailor in a nearby town.
Another local, Gautam Punwalkar, 44, counts the trucks going in and out of the mine each day - but he had to seek low-paid daily wage work for five years when the mine was shut.
"I am happy I got this work back when the mine reopened," he said.
COMPENSATION
Houses in Baranj and Chichordi villages have massive cracks running through the walls, and inhabitants tell stories of collapsing houses and utensils crashing down when mine blasting happens, as often as three times a day.
Yet the villagers stay, adamant they will not leave their homes, which now resemble a bombed-out hamlet, as they continue to negotiate rehabilitation or a price for their land.
Baranj locals are due to have their battered homes restored, after living in them for about a decade.
KPCL officials said they were working on options for the housing, all wages owed had been paid and compensation for loss of land to mining in Chichordi was being processed.
Houses in Chichordi, however, fall outside the officially designated mining area, said V. Ponnuraj, KPCL's managing director, making it harder for occupants to access support.
'SITTING ON GOLD'
Campaigners called for efforts to create alternative jobs in coal hubs, given the twin challenges for residents: rising poverty due to mining and cutting of the feeble coal lifeline in a couple of decades as India transitions to green energy.
"We have to target the next employable generation and try and bring them away from coal," said Samrat Sengupta, programme director for climate change and renewable energy with the Centre for Science and Environment, a Delhi-based advocacy group.
Vocational training to service electric vehicles or repair electric stoves would help prepare locals for the growing clean industries of the future, he added.
But Chichordi locals said they would not give up on coal yet.
"We know we are sitting on gold and we will get the benefit," said Abdul Jamel Shaikh, a restaurant owner who wants to sell his farmland for mining. "I want them to take my land, my house and compensate me. We have suffered for years."
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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