Thursday, August 21, 2025

Hidden Risks of Passkeys Surface in Study on Abuse Scenarios

Passkeys, the cryptographic alternative to passwords, have been rolled out across hundreds of major online services over the past few years. Backed by large technology companies, they are marketed as being safer and more convenient than traditional logins. Unlike passwords, which can be guessed, stolen, or phished, passkeys rely on encrypted credentials stored on a device and verified through biometrics or PINs. This shift has been hailed as a milestone toward a password-free internet, with millions of users already relying on the system for everyday accounts.

Looking beyond technical threats

While passkeys are designed to resist phishing and large-scale account takeovers, researchers warn that the technology may overlook a different class of risk. A new study led by Cornell University, together with partners at New York University and the University of Wisconsin, looked at what happens when digital security tools are used in the context of interpersonal abuse. These are situations where an attacker may be a partner, relative, or caregiver with physical or remote access to a victim’s devices. Unlike traditional hackers, such adversaries can exploit social proximity, coercion, or trust, creating attack surfaces that conventional security models rarely address.

A framework for identifying misuse

To investigate these overlooked risks, the researchers created what they call an “abusability analysis framework.” It is a six-stage process designed to uncover how security features, intended to protect accounts, can instead be repurposed for harm. The framework moves from defining possible threat models to testing real-world services and summarising abuse scenarios in plain terms. By applying this structured method, the team examined 19 popular platforms that already support passkeys, including large technology firms, retailers, and social apps.

Abuse pathways uncovered

Testing revealed seven main ways in which passkeys could be misused in abusive contexts. Some involved straightforward actions, such as adding an attacker’s fingerprint or face scan to a victim’s device. Others were more technical, including exporting a passkey through AirDrop or synchronisation tools so that it could be used from another device indefinitely. Attackers could also register their own passkey on a victim’s account or revoke legitimate ones remotely, leaving the account owner locked out.

The study also documented cases where passkey entries could be manipulated to display misleading information. Spoofed device names or login locations could make it harder for a victim to detect unauthorised access. Because many services do not provide detailed alerts when passkeys are added, removed, or exported, the abuse often remains invisible.

Scenarios drawn from everyday life

The researchers illustrated their findings through real-world scenarios that mirror daily digital interactions. In one case, a teenager copied a schoolmate’s Roblox login and used account settings to revoke all existing passkeys, cutting the victim off from their games with no recovery options. In another, a partner secretly exported a TikTok passkey from an unlocked phone using AirDrop, maintaining long-term access to private messages even after the victim reset their password. In workplace settings, colleagues were able to take advantage of unattended devices to register or exploit passkeys without the account holder’s knowledge.

These examples showed how interpersonal threats differ from anonymous cyberattacks. The abuse typically arises not from technical sophistication but from ordinary moments of shared access, such as borrowing a device or knowing a login code.

Inconsistent protections across services

A striking finding was how unevenly different platforms handle passkey management. Some companies offered basic protections such as email notifications when a passkey was added or revoked, while others gave no warning at all. Certain services did not allow users to revoke passkeys once created, or failed to terminate active sessions even after revocation. In several cases, cloned or exported passkeys continued to work with no way for the victim to detect or disable them.

The study also noted that service dashboards often use vague or misleading labels, such as generic device names, that obscure what credentials are active. Spoofing techniques, like changing a browser’s reported information or using a VPN, made it easy for attackers to disguise their activity further. These design flaws compounded the difficulty for victims trying to understand whether their accounts had been compromised.

Recommendations for safer design

To address these gaps, the researchers outlined practical steps that service providers could adopt. Clearer user interfaces for passkey management, consistent notifications when credentials are changed, and stricter limits on exporting or sharing passkeys were among the main suggestions. The study also urged companies to adopt the abusability analysis framework as part of their product testing. By simulating real-world abuse scenarios before rolling out new features, developers could reduce the risks that vulnerable users face.

Balancing benefits with social realities

Passkeys remain a promising step forward in defending against phishing and other technical threats, but the study highlights that technical strength is not the whole story. When a device or account is already exposed to someone within a victim’s social circle, the strongest cryptography cannot prevent misuse. The research shows that digital security must take social realities into account, ensuring that authentication tools work not only against remote attackers but also in the complex dynamics of personal relationships.


Notes: This post was edited/created using GenAI tools. Image: DIW-Aigen.

Read next: Tech Giants Share AI Environmental Costs, but Gaps Remain
by Web Desk via Digital Information World

Tech Giants Share AI Environmental Costs, but Gaps Remain

Google reports Gemini prompts use minimal energy and water, but experts criticize incomplete methods hiding true footprint.

Google’s Numbers for Gemini

Google has published an analysis of how much power and water its Gemini chatbot uses. The company says that a single text prompt requires about 0.24 watt-hours of electricity, 0.26 milliliters of water, and creates the equivalent of 0.03 grams of carbon dioxide. By its measure, this is about the same as running a television for nine seconds.

The report highlights large efficiency improvements over the past year. Google claims it has cut the electricity needed per prompt by more than thirty times since mid-2024, while emissions tied to each request have dropped at a similar pace.

Mistral’s Higher Figures

French startup Mistral published its own assessment earlier this summer. For its “Le Chat” assistant, a typical response of about 400 tokens uses 50 milliliters of water and produces more than one gram of carbon dioxide. The company also included information about training. Building its Large 2 model was said to release over 20 kilotons of carbon dioxide and require more than 280,000 cubic meters of water, close to the volume of one hundred Olympic swimming pools.

What Experts Say Is Missing

Specialists in energy and computing argue that the reports are incomplete. In Google’s case, the water figure covers only the cooling systems inside its data centers. It does not account for the far larger volumes tied to electricity production, since power plants also rely heavily on water for cooling and steam. Analysts point out that leaving out this factor hides a major part of the impact.

Another concern is how emissions are measured. Google used a market-based method, which takes into account the renewable energy it invests in. A location-based method, which reflects the actual mix of power sources in the grid where a data center runs, would often show higher values. Critics say that without this, the report gives only part of the picture.

Different Methods, Different Outcomes

Google says its numbers are based on the median prompt to avoid skew from extreme cases that use unusually high resources. It has not provided token counts or typical word lengths for those prompts. Earlier academic studies relied on averages and included both direct and indirect water use, which led to far higher numbers, in some cases more than 50 milliliters per request.

Mistral’s study, while narrower, urged the industry to move toward common reporting standards. It suggested that clearer comparisons could help buyers and developers pick models with lower environmental costs.

Broader Trends in AI Use

Efficiency gains, while real, do not always translate into lower overall demand. As systems get cheaper and faster to run, people tend to use them more, which raises total consumption. Google’s sustainability report shows this effect. Even as Gemini became more efficient, the company’s total carbon emissions increased. Since 2019, its footprint has risen by more than half, largely due to the growing use of AI services.

Independent estimates underline the uncertainty. One outside analysis found that a query to OpenAI’s GPT-4o uses about 0.3 watt-hours of electricity, slightly more than Google’s figure for Gemini. Actual impact depends on model size, type of output, and which power grid handles the request.

A Partial Accounting

The reports from Google and Mistral provide an early view of AI’s environmental costs. They show that queries can appear small in isolation but raise bigger questions at scale. Without independent audits, consistent metrics, and full inclusion of indirect effects, the true footprint of artificial intelligence remains unsettled.


Notes: This post was edited/created using GenAI tools. Image: DIW-Aigen.

Read next: AI vs. SEO: How AI-Powered Search is Changing the Way We Find Content in 2025
by Irfan Ahmad via Digital Information World

AI vs. SEO: How AI-Powered Search is Changing the Way We Find Content in 2025

With the widespread adoption of AI-tools, search is changing fast. Generative AI, including Google's AI Overviews, ChatGPT, and Perplexity, has flipped traditional SEO playbooks. And the pressure’s real: 66% of consumers expect AI to replace traditional search entirely within five years.

A recent study from Fractl and Search Engine Land surveyed over 1000 marketers and consumers, revealing how much AI tools like Google’s AI Overviews and ChatGPT are reshaping the ways people are discovering content online.

How AI is Transforming Marketers’ Approaches and Traffic

AI adoption trends

With workers from various industries adapting to this new digital landscape, marketers are no different. Almost all agree that utilizing AI for their content is non-negotiable. The study finds that most marketers (83%) are already on teams that incorporate AI tools in their workflow, with Agency marketers using AI tools at a higher rate (90%) compared to in-house teams (81%).

Yet, most marketers only scratch the surface. Only 4% are actively leveraging AI strategically across their entire workflow, with the rest reporting that their AI usage is limited to accomplishing basic assignments like writing captions or optimizing meta descriptions. Teams are aware of this, and it shows in the numbers: 35% say they’re underusing it, and 47% struggle to integrate it into workflows. Confidence is high (83%), but execution is shallow.

Marketers need to shift their perspective on using AI; it does more than expedite tasks. It fundamentally reshapes the content creation and delivery process.

Impact of Google AI Overviews

Meanwhile, Google’s launch of AI Overviews caused significant disruptions. The study found that 39% of marketers noticed drops in organic traffic almost overnight, especially in tech (44%), travel (43%), and e-commerce (35%), regardless of their rankings.

This wasn’t a glitch, but an unexpected rise of new search behavior. Instead of clicking through multiple top-ranking links to find information, users would be greeted with an AI summary that provided them the answers they were looking for. Ranking number one on Google isn't enough anymore. Marketers now need to optimize their content to ensure that it appears in AI-driven responses.

Many users still rely on Google, but AI Overviews have changed the way they use the Search Engine. 49% of users still use traditional links, but 41% now rely majorly on AI Overviews. 13% of users skip traditional search entirely, migrating to tools like Perplexity and ChatGPT in favor of prompt-based searching.

11% of users stay skeptical about AI’s future, but the majority have spoken; Two-thirds (66%) of users expect AI to supersede traditional search methods in the next 5 years, and their search behavior now relies on AI doing the heavy-lifting.

Ranking #1 won’t matter if AI summaries hog the attention. If your content isn’t built for AI systems, it won’t show up where it counts.

Marketers’ slow adaptation to optimize for AI visibility

AI is becoming heavily adopted by consumers, but marketers' aren’t changing their blueprint. The study revealed that even after the release of AI Overviews, most teams are continuing to stick to their traditional SEO strategies and have yet to allocate funds towards FAQ schema, structured data, or formats that are optimized for AI.

Modern search no longer rewards traditional SEO objectives of getting the highest ranking as much as optimizing content for structure and retrieval by AI tools. Brands that don’t adopt this new approach will fall behind fast.

However, some brands are reworking their strategy to stay competitive. Prioritizing AI visibility, they’re tracking mentions in SGE and ChatGPT, creating targeted copy, and building prompt-based workflows.

Changing Consumer Behaviors, Trust, and Accuracy Concerns

Gen Z’s changing search behaviors

While 69% of Gen Z still use Google to find answers, they’re finding new search methods that better suit their needs.

Rather than shuffling through links, 66% opt for ChatGPT regularly to find answers through conversations and specific questions. 39% also use various social media platforms like Tik-Tok and Instagram for engaging how-to videos and peers’ advice and product recommendations.

Gen Z’s search is now an amalgamation of prompting and watching content to get informed. It’s crucial that content is optimized for this, as ignoring these platforms means missing out on connecting with the next generation of consumers.

Trust and Quality Control of AI

Marketers’ trust in AI summaries is notably fragile and steadily declining. The study found that only 10% of marketers believe Google’s AI Overviews are excellent, while 53% label them as average or worse. 78% believe that AI summaries are prone to providing misinformation, and only 11% feel search engines are transparent about AI's role.

Having content misrepresented by AI carries significant consequences to brand trust and authority, making accuracy and transparency increasingly critical. Yet, 23% feel that search engines don’t provide info on how rankings and content recommendations are influenced by AI. As users become more reliant on AI for finding content, this risk grows.

While the implementation of AI tools continues to increase in marketing teams, quality assurance efforts haven't kept up. Although 56% of marketers share concerns about the quality and accuracy of AI, they admit that their companies don’t maintain thorough editorial reviews of AI-generated content.

In an environment where misinformation spreads swiftly, rigorous QA practices are no longer optional. In order to scale faster without sacrificing accuracy, teams must think of AI editorial reviews as an essential part of their content production process.

Operational Pressures and the Evolving Role of SEO

AI fatigue and adoption pressures

AI’s quick adoption as an industry staple in marketing has created its own challenges; Over 5 in 6 (85%) marketers feel pressure to use AI in order to stay competitive, with 1 in 2 (52%) feeling it immensely.

However, this sense of urgency increases for those working at bigger organizations, where teams at 250+ employee companies are 18% more likely to lack leadership buy-in than micro-businesses. Without the support and resources of their higher ups to increase upskilling, marketers are experiencing widespread stress and burnout trying to keep up.

Times are changing fast; as marketers continue to fall behind, the pressure increases.

Contrary to popular fears, AI isn’t replacing marketers. However, it's expanding their workloads. Although 66% of marketers say AI saves them 1 to 6 hours per week, this freed-up time typically results in increased expectations and additional responsibilities. Without boundaries or adjusted goals, these efficiency gains could ironically lead to burnout rather than relief.

Take a look at these charts for more insights:








The evolving SEO playbook and strategic response

Yet, despite these pressures, SEO remains vital, it’s simply evolving. Successful brands are merging traditional practices (ranking, backlinks, domain authority) with AI-first strategies such as schema markup, conversational content, and summarization-focused writing designed specifically for AI discovery tools. Leaders are already testing how their content performs across platforms like SGE, ChatGPT, and Perplexity, tracking snippets and optimizing accordingly.

To stay competitive, marketing teams must master three core practices: adhering to SEO fundamentals, developing AI-friendly content, and enhancing quality assurance for automated workflows. The shift isn't coming, it's already here. Brands that rapidly adapt to this new generative search reality won't just survive; they'll thrive by building lasting trust and visibility in an AI-driven world.

Read next: From SEO to SXO: How Search Experience Optimization Is Transforming Digital Marketing


by Irfan Ahmad via Digital Information World

From SEO to SXO: How Search Experience Optimization Is Transforming Digital Marketing

Ad Disclosure: This content is published as part of a paid collaboration.

SEO was the core of digital marketing long ago. Firms were busy crawling their way to the top of search engines, using keywords, back links and technical adjustments. But the game has changed. Through its search engine, consideration is given whether sites actually are enjoyed by people. Such a change has spawned an emerging methodology that refers to Search Experience Optimization (SXO).

Image Source.

What Is Search Experience Optimization?

SXO is an extension of the standard SEO. SXO takes into consideration the entire user journey as opposed to prioritizing only how search engines crawl and rank a page. It simply wants to know the answer to the question: did the visitor get what he or she was seeking and was it an enjoyable experience?

Whereas SEO deals with aspects of being visible, SXO integrates SEO and user experience (UX). It is not only aiming at the traffic but also at maintaining the users engaged and satisfied to take action. To facilitate this transition organic SEO services are usually employed by the businesses. You can explore here how professional support bridges the gap between organic SEO services and SXO.

Why the Shift from SEO to SXO Matters

Online search has changed the way people search. Failing expectations are consumer voice assistants, on-the-go browsing, and AI-powered recommendations. Users desire immediate responses, hassle-free browsing and content that they can trust. When a visitor finds a web site ranked well yet frustrating, the visitor will not hesitate to get out. These actions are measured by search engines. Uninterested or low engagement or high bounce rates are indicators that a page is not adding value. SXO responds in a direct manner to this by putting the user at the forefront.

Core Elements of SXO

To see how SXO works in practice, it helps to look at the essentials:

  • Content relevance: Articles should solve a user’s problem, not just repeat keywords.
  • Website usability: Visitors need clear menus, smooth navigation, and fast-loading pages.
  • Mobile-first design: With most searches done on phones, responsive layouts are no longer optional.
  • Trust signals: Reviews, testimonials, and credible sources show that a site can be trusted.
  • Conversion focus: Every page should guide users toward a next step, such as a sign-up or purchase.

These elements connect traditional SEO with real user needs. When they work together, a website not only ranks higher but also keeps visitors engaged. SXO is about creating a journey that feels effortless, so people want to return and interact again.

How SXO Improves Digital Marketing Results

Traditional SEO often stops at driving clicks. SXO goes further. Its real goal is to turn casual visitors into loyal customers. When search intent matches a smooth and helpful user journey, brands see results such as:

  • Higher engagement rates: people stay longer and explore more content.
  • Improved conversions: clear design and navigation make it easier to complete a purchase or sign up.
  • Stronger brand trust: useful, transparent information builds credibility over time.
  • Sustainable rankings: search engines reward websites that satisfy users consistently.

Together, these outcomes show why SXO matters. It is not about short bursts of traffic but about building lasting relationships with audiences. A site that feels reliable and easy to use will always have an advantage over one that only focuses on keywords.

Practical Steps for Businesses Transitioning to SXO

Shifting from SEO to SXO takes more than technical fixes, it also requires a change in mindset. Some useful first steps include:

  • Analyze user behavior to see where visitors leave your site.
  • Improve speed and mobile design so pages load fast on any device.
  • Publish content that solves real problems, not just content stuffed with keywords.
  • Add clear calls-to-action to guide users through the journey.
  • Track and refine with analytics to measure satisfaction and conversions.

When businesses start with these basics, the results often appear quickly. Visitors feel more comfortable, conversions rise, and search engines reward the improved experience with stronger visibility.

The Role of Content in SXO

Generic content is still the core of the search experience optimization. But its role has increased. Brands need to think about structure, clarity, and value instead of the keyword density. Articles are well designed with headings, points and images that ease the digesting of the information. This is where organic SEO services may help with the shift. Agencies will offer skills in technical optimisation as well as UX-based strategies.

Case Studies: Companies Winning with SXO

Several brands have already embraced SXO with great success:

  • E-commerce platforms redesigned product pages with better filters and recommendations, leading to higher cart completion rates.
  • Educational websites improved readability and accessibility, increasing student engagement and return visits.
  • Local businesses optimized mobile search results with clear maps, reviews, and fast booking options.

These examples prove that SXO is not a theory but a practical strategy for growth.

How SXO Connects with Other Marketing Trends

SXO is not an isolated trend. It aligns closely with other areas of digital marketing:

  • Content marketing: delivering helpful and authentic resources.
  • Social media marketing: driving conversations and feedback that improve user experience.
  • AI personalization: adapting search results and site experiences to individual needs.

For a deeper understanding of how user experience impacts digital performance, an excellent external reference is HubSpot’s guide on customer journey optimization.

Future of Search: Where SXO Is Heading

In the future, SXO can only become more important. The use of search engines will keep changing where websites that give smooth experiences will be rewarded. Neglecting to adapt can mean that the business will pick up traffic, but at the same time missing the opportunity to achieve conversions as those who do adapt to prioritize the full journey. It is reasonable to anticipate that SXO will be combined with AI tools, data-driven personalization and voice search. The given objective is to ensure that each online search is as easy as possible.

Conclusion

The changes in digital marketing have been massive, with one being the transition of business SEO practices to the adoption of SXO. Old time strategies will no longer do. The secret of success is to not only provide information, but to have a memorable positive experience in that process. The SXO is something that the companies incorporating it into practice now will experience a higher position and conversion strength and increased trust among their audiences. It is time to adjust.


by Asim BN via Digital Information World

Google Photos adds conversational editing and new transparency tools

Google Photos is gaining a feature that lets people describe the edits they want instead of searching through menus. The new option, shown during Google’s latest launch event, will first appear on the Pixel 10 in the United States. Other Android and iOS devices will follow in the weeks ahead.

A person can now type or speak a request, such as removing an object in the background, brightening a dark shot, or repairing an older photo. The app interprets the command and applies the change automatically. People who are unsure where to start can use a simple request like “make it better,” while those who want precision can follow up with more specific directions until the picture looks right.

Multiple ways to adjust photos

The tool is flexible. Someone can ask for a single change, or combine several in one instruction, like fixing colors and clearing reflections together. It also works by tapping or circling a part of the image, which triggers targeted suggestions for that area.


Beyond basic adjustments, Google is adding creative options. A user might swap a background, place props such as sunglasses on a subject, or create playful variations without needing to touch sliders or advanced settings.

Transparency in edits

Alongside the new editing method, Google Photos will begin supporting C2PA Content Credentials. This standard records how an image was captured or modified, and whether AI was part of the process. Pixel 10 devices will be the first to embed these details directly in the camera and in Photos, even for images that did not involve AI. The feature will later expand to other platforms.

A mix of convenience and clarity

With these changes, Google is aiming to make photo editing less technical while also providing clearer records of how images are produced. The updates are designed to simplify everyday use while addressing growing concerns around the origin and authenticity of digital pictures.

Notes: This post was edited/created using GenAI tools.

Read next: Chrome VPN Extension Found Secretly Recording Users’ Screens


by Asim BN via Digital Information World

Chrome VPN Extension Found Secretly Recording Users’ Screens

A Chrome extension promoted as a free VPN service, and even carrying a verified badge in the store, has been caught doing the opposite of what users expected. Instead of protecting people’s privacy, it was silently capturing what appeared on their screens and sending the data elsewhere. As per KoiSecurity, more than 100,000 people had installed it by the time researchers uncovered what was happening.

How it unfolded

FreeVPN.One was not a sudden arrival. It had been in the Chrome Web Store for years, mostly unnoticed, operating as a straightforward tool. That changed in 2025. A sequence of updates pushed it far from its original function. In April, a new permission allowed it to see every site a user opened. Two months later, an update introduced scripting rights, supposedly to improve security. Then, in July, came the turning point, hidden screenshot capture built directly into the extension.

What this meant in practice was simple: each time a web page loaded, the extension paused for a moment, let the content render, then grabbed a snapshot of the visible tab. That image, combined with details like the web address, the tab identifier, and a unique number tied to the user, was quietly sent off to a remote server. No alert. No visible sign that anything had happened.

What was at stake

Screenshots don’t just show browsing activity; they show everything. A bank login form half-filled with account details. A company spreadsheet opened in a cloud service. Private photos in an online gallery. Even personal messages sitting in a chat window. All of it can be frozen in an image and transmitted in seconds, without the user ever knowing.


Later versions of the extension made the transfers harder to spot by encrypting the traffic with AES-256-GCM and RSA key wrapping. The encryption didn’t make the behavior less invasive, it simply disguised it so network monitoring tools would struggle to distinguish it from normal, legitimate connections.

More power than a VPN needs

A genuine VPN extension only needs a narrow set of permissions to function, mainly proxy handling and storage. FreeVPN.One demanded more. It asked to interact with all tabs, to run scripts on every website, and to read every URL visited. Each permission on its own might raise eyebrows. Taken together, they created the basis for round-the-clock monitoring.

One feature made the spying less obvious. The extension displayed an option labelled “AI Threat Detection.” That button, when pressed, warned that screenshots and URLs might be uploaded for checking. And indeed, when clicked, it sent data for analysis. The difference is that, behind the scenes, it was already doing the same thing constantly, whether the button was pressed or not.

The developer’s stance

When researchers reached out, the developer argued that the screenshot capture was part of background scanning designed to protect against harmful domains. The evidence did not support that claim. Captures were recorded even on mainstream services such as Google Sheets and Google Photos, hardly suspicious sites. The developer said the images were analyzed briefly and not stored, but offered no proof.

Requests for company information or developer credentials went unanswered. The only contact point was a generic email, and the associated website resolved to a basic template page, giving no sign of a real organization behind the product.

Bigger questions about oversight

Despite the findings, the extension remained available in the Chrome Web Store at the time of reporting. That raises concerns about how well Google’s security checks actually work. In theory, both automated scans and human reviews are supposed to prevent malicious code from slipping through. In reality, a tool that shifted from VPN to spyware managed to stay listed, complete with a verified badge and prominent placement.

The lesson for users

This case illustrates a recurring problem. Extensions that appear free, useful, and even certified can, with a single update, transform into surveillance tools. Once broad permissions are granted, there is little visibility into what is happening in the background. And once sensitive information leaves a device — whether a password, a message, or a photograph — there is no way for a user to verify how it is being used.

What began as a VPN branded around privacy ended up functioning as a window into people’s digital lives. For those who installed it, the cost of a free service was hidden in plain sight.

Notes: This post was edited/created using GenAI tools.

Read next: 

• Inside the Water Crisis of Data Centers: Google, Meta, and the Hidden Costs of AI Growth

DeepSeek V3.1 Expands China’s AI Push With Open-Source Frontier Model


by Irfan Ahmad via Digital Information World

Wednesday, August 20, 2025

Inside the Water Crisis of Data Centers: Google, Meta, and the Hidden Costs of AI Growth

As demand for artificial intelligence technology boosts construction and proposed construction of data centers around the world, those computers require not just electricity and land, but also a significant amount of water. Data centers use water directly, with cooling water pumped through pipes in and around the computer equipment. They also use water indirectly, through the water required to produce the electricity to power the facility. The amount of water used to produce electricity increases dramatically when the source is fossil fuels compared with solar or wind.

A 2024 report from the Lawrence Berkeley National Laboratory estimated that in 2023, U.S. data centers consumed 17 billion gallons (64 billion liters) of water directly through cooling, and projects that by 2028, those figures could double – or even quadruple. The same report estimated that in 2023, U.S. data centers consumed an additional 211 billion gallons (800 billion liters) of water indirectly through the electricity that powers them. But that is just an estimate in a fast-changing industry.

We are researchers in water law and policy based on the shores of Lake Michigan. Technology companies are eyeing the Great Lakes region to host data centers, including one proposed for Port Washington, Wisconsin , which could be one of the largest in the country. The Great Lakes region offers a relatively cool climate and an abundance of water, making the region an attractive location for hot and thirsty data centers.

The Great Lakes are an important, binational resource that more than 40 million people depend on for their drinking water and supports a US$6 trillion regional economy . Data centers compete with these existing uses and may deplete local groundwater aquifers .

Our analysis of public records, government documents and sustainability reports compiled by top data center companies has found that technology companies don’t always reveal how much water their data centers use. In a forthcoming Rutgers Computer and Technology Law Journal article, we walk through our methods and findings using these resources to uncover the water demands of data centers.

In general, corporate sustainability reports offered the most access and detail – including that in 2024, one data center in Iowa consumed 1 billion (3.8 billion liters) gallons of water – enough to supply all of Iowa’s residential water for five days .

How do data centers use water?

The servers and routers in data centers work hard and generate a lot of heat . To cool them down, data centers use large amounts of water – in some cases over 25% of local community water supplies. In 2023, Google reported consuming over 6 billion gallons of water (nearly 23 billion liters) to cool all its data centers.

In some data centers, the water is used up in the cooling process. In an evaporative cooling system , pumps push cold water through pipes in the data center. The cold water absorbs the heat produced by the data center servers, turning into steam that is vented out of the facility. This system requires a constant supply of cold water.

In closed-loop cooling systems , the cooling process is similar, but rather than venting steam to the air, air-cooled chillers cool down the hot water. The cooled water is then recirculated to cool the facility again. This does not require constant addition of large volumes of water, but it uses a lot more energy to run the chillers. The actual numbers showing those differences, which likely vary by the facility, are not publicly available.

One key way to evaluate water use is the amount of water that is considered “ consumed ,” meaning it is withdrawn from the local water supply and used up – for instance, evaporated as steam – and not returned to its source.

For information, we first looked to government data, such as that kept by municipal water systems, but the process of getting all the necessary data can be onerous and time-consuming, with some denying data access due to confidentiality concerns. So we turned to other sources to uncover data center water use.

Sustainability reports provide insight

Many companies, especially those that prioritize sustainability, release publicly available reports about their environmental and sustainability practices, including water use. We focused on six top tech companies with data centers: Amazon, Google, Microsoft, Meta, Digital Realty and Equinix. Our findings revealed significant variability in both how much water the companies’ data centers used, and how much specific information the companies’ reports actually provided.


Sustainability reports offer a valuable glimpse into data center water use. But because the reports are voluntary, different companies report different statistics in ways that make them hard to combine or compare. Importantly, these disclosures do not consistently include the indirect water consumption from their electricity use, which the Lawrence Berkeley Lab estimated was 12 times greater than the direct use for cooling in 2023. Our estimates highlighting specific water consumption reports are all related to cooling.

Amazon releases annual sustainability reports , but those documents do not disclose how much water the company uses. Microsoft provides data on its water demands for its overall operations, but does not break down water use for its data centers. Meta does that breakdown , but only in a companywide aggregate figure. Google provides individual figures for each data center.

In general, the five companies we analyzed that do disclose water usage show a general trend of increasing direct water use each year. Researchers attribute this trend to data centers .

A closer look at Google and Meta

To take a deeper look, we focused on Google and Meta, as they provide some of the most detailed reports of data center water use.

Data centers make up significant proportions of both companies’ water use. In 2023, Meta consumed 813 million gallons of water globally (3.1 billion liters) – 95% of which, 776 million gallons (2.9 billion liters), was used by data centers.


For Google, the picture is similar, but with higher numbers. In 2023, Google operations worldwide consumed 6.4 billion gallons of water (24.2 billion liters), with 95%, 6.1 billion gallons (23.1 billion liters), used by data centers.

Google reports that in 2024, the company’s data center in Council Bluffs, Iowa, consumed 1 billion gallons of water (3.8 billion liters), the most of any of its data centers.

The Google data center using the least that year was in Pflugerville, Texas, which consumed 10,000 gallons (38,000 liters) – about as much as one Texas home would use in two months . That data center is air-cooled, not water-cooled, and consumes significantly less water than the 1.5 million gallons (5.7 million liters) at an air-cooled Google data center in Storey County, Nevada. Because Google’s disclosures do not pair water consumption data with the size of centers, technology used or indirect water consumption from power, these are simply partial views, with the big picture obscured.

Given society’s growing interest in AI, the data center industry will likely continue its rapid expansion. But without a consistent and transparent way to track water consumption over time, the public and government officials will be making decisions about locations, regulations and sustainability without complete information on how these massive companies’ hot and thirsty buildings will affect their communities and their environments.

This post was originally published on TheConversation.

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by Web Desk via Digital Information World