In this election, the contest on Meta’s platforms has become a legal dispute, with Brazil’s Superior Electoral Court (TSE) requiring the company to apply the same rules to President Luiz Inácio Lula da Silva, of the Workers’ Party (PT), and Flávio Bolsonaro, of the Liberal Party (PL), who received the most votes in the first round.

This is equal treatment. Meta must apply the same criteria to both candidates, which does not mean they will have the same reach. The company must not restrict the visibility of the run-off candidates in searches or the distribution of their political content, and it must apply the same criteria when generating images using artificial intelligence . Meanwhile, the TSE’s rule excludes only the candidates’ official profiles from recommendations. Supporter channels and accounts sharing clips remain free to go viral.

Lula’s campaign alleges that Meta failed to ensure equal treatment. Flávio’s profile appeared in searches while Lula’s did not; Meta AI generated images of Flávio but refused to generate images of Lula ( see here ). The tech company denies favouritism and attributes the problems to technical faults. The PL candidate’s campaign also says it has been disadvantaged.

Faced with conflicting accounts, only an audit of internal data examining the criteria rather than the results could provide an answer, with access to records of restrictions and their reasons, ranking scores and the history of code changes. But only the company holds these data, and Brazil’s Electoral Public Prosecutor’s Office concluded that it had not provided everything the TSE requested.

The challenge for future elections, in Brazil and elsewhere, is not to force algorithms to produce identical results, but to ensure their rules are known before campaigning begins and audited throughout the election. Without this, equal treatment becomes merely a promise rather than a right that society can exercise.

This article exclusively represents the opinions of its author, Adriane Buarque de Holanda, and not those of Global South World.

State Information Technology Minister Nara Lokesh has said the development will anchor a technology ecosystem spanning about 100 kilometres and host up to 6 gigawatts of data centre capacity.

Major investors have signed on, with Google pledging around $15 billion for AI infrastructure in the state, while a joint venture between Reliance Industries, Brookfield and Digital Realty is investing a further $11 billion in a large data centre complex.

Lokesh has argued that Andhra Pradesh has planned for the heavy electricity and water demands of the sector, suggesting that excess monsoon water flowing into the Bay of Bengal could be channelled to cool facilities.

However, environmental experts have long warned that large data centres are among the most water-intensive pieces of digital infrastructure. Cooling high-density servers requires constant water circulation, much of which is lost to evaporation.

According to the Environmental and Energy Study Institute , a medium-sized data centre can consume up to 110 million gallons of water annually for cooling, while larger facilities may use as much as 5 million gallons a day — comparable to the needs of a small town.

That demand comes at a sensitive time for India, with UNICEF estimating that waterborne diseases cost the country roughly $600 million each year, with drought- and flood-prone regions affecting around a third of the population in recent years.

Two-thirds of India’s 718 districts face extreme water depletion, according to UNICEF. 

India is also the world’s largest user of groundwater, drawing supplies from more than 30 million access points. Groundwater provides 85% of drinking water in rural areas and nearly half of urban needs.

Beyond on-site consumption, data centres also carry indirect water costs. Power plants supplying electricity — particularly fossil fuel facilities — require substantial volumes of water for steam generation and cooling.

Manufacturing the semiconductor chips that power AI systems is also water-intensive, requiring ultrapure water in large quantities before equipment even reaches a data hall.

As India seeks to cement its place in the global AI race, the challenge will be balancing digital ambition with the realities of a country where access to safe and reliable water remains uneven.