Every time you use AI, it’s costing more than you think.

Did you know a simple chatbot query uses enough water to fill a bottle?

Now, multiply that by millions of users—can you see the impact?

Let’s explore what we can do about this and how AI will help us.

Here’s what you’re going to explore in this post:

• Amazon AI: New AI tool

• LinkedIn AI: Data training

• Energy usage of AI: What’s the future?

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🤖 Amazon AI

Amazon’s New AI: Making Shopping Easier for Everyone

Amazon just launched this AI assistant called Amelia, and it’s kind of a big deal for sellers but it’s great news for us shoppers too. Let me break it down for you.

The Details:

• Meet Amelia: It’s Amazon’s new AI helper that’s going to help sellers keep things running smoothly. Think better stock management and faster answers to questions.

• Always In Stock: Amelia helps sellers predict and fix supply problems, so stuff you want doesn’t go out of stock so often.

• Better Listings to help you: The AI makes product descriptions and images better, so you don’t have to guess what you’re buying.

• Instant Support: Got a question like, “Is this for kids or adults?”—Amelia’s got you covered, fast.

• Quick Review Summaries: Don’t have time to read all the reviews? Amelia pulls out the key points, so you get the gist without all the scrolling.

So, What’s in It for Us?

Even though this AI is for sellers, it’s really going to help us as buyers. More stuff in stock, quicker answers, and better product details—it’s just making shopping easier and faster for everyone.

🛑 LinkedIn AI

LinkedIn is Using Your Data for AI Training

AI is creeping into every corner of social media, and LinkedIn is no exception.

The Microsoft-owned platform, popular among professionals, has introduced AI-driven features like job-seeker chatbots, AI-powered writing help, and recruiter tools.

However, LinkedIn has been quietly using your data to train these AI models, and many users aren’t happy about it.

The Details:

• Automatic Data Collection: LinkedIn’s Senior VP, Blake Lawit, recently revealed that LinkedIn has been collecting user data—like profile information and posts—to train its AI tools. This was done automatically, without explicitly asking for user consent.

• EU Users Excluded: Due to strict GDPR regulations, LinkedIn does not collect data from European Union users for AI training. They’ve committed not to do so in the future either, providing some peace of mind for EU members.

• Privacy Concerns is giving me chills: LinkedIn's approach has sparked a wave of concern about transparency and data privacy. Users are feeling blindsided by how their information is being used without clear communication from the platform.

• Opt-Out Process: While data already collected cannot be reclaimed, you can stop LinkedIn from using your data for AI training going forward.

  Here’s how: Log into your LinkedIn account and go to the Data privacy tab. Click on Data for Generative AI Improvement. Toggle the setting off to opt-out.

Keep Your Data Safe LinkedIn’s data practices are a wake-up call about the importance of knowing how your information is used. As AI continues to evolve, companies will increasingly leverage user data for model training, often without clear user consent. Now’s the time to dig into those privacy settings and take control of your data.

⚡️ Energy for AI

The Hidden Environmental Costs of AI: A Bottle of Water Per Email

AI chatbots like ChatGPT are changing how we interact with technology, but there’s an unseen cost: the environmental impact of their energy and water usage. Each interaction with these chatbots consumes resources that may surprise you.

The Details

• Water Consumption:

  • A 100-word email generated by ChatGPT uses about 519 milliliters of water—just over a standard bottle.

  • If one in ten working Americans (roughly 16 million people) sends a similar email weekly for a year, that totals over 435 million liters, equivalent to Rhode Island’s household water use for 1.5 days.

  • Cooling data centers often use water systems, transferring heat away just like our bodies sweat.

• Electricity Usage:

  • Each 100-word email consumes 0.14 kilowatt-hours (kWh) of electricity, similar to running 14 LED bulbs for an hour.

  • For a year, this equals 121,517 megawatt-hours (MWh), enough to power all homes in D.C. for 20 days.

• Wider Impacts:

  • Data centers in hot regions rely heavily on electricity for cooling, driving up power bills and straining local grids. Others use water cooling, risking depleting scarce water resources, especially in drought-prone areas.

  • Microsoft, Google, and Meta have faced scrutiny for their resource usage, often consuming large shares of local water and electricity supplies.

AI’s environmental footprint is often overlooked but significant. From cooling servers to consuming electricity, every chatbot query adds up. While tech giants pledge greener operations, meeting these promises remains challenging.

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