The Multi-Billion Dollar Industry That Makes Its Living From Your Data
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The Multi-Billion Dollar Industry That Makes Its Living From Your Data

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The Multi-Billion Dollar Personal Data Ecosystem

The Multi-Billion Dollar Industry That Makes Its Living From Your Data

In the ocean ecosystem, plankton is the raw material that fuels an entire food chain. These tiny organisms on their own aren’t that remarkable, but en masse, they have a huge impact on the world.

Here on dry land, the massive volume of content and meta data we produce fuels a marketing research industry that is worth nearly $50 billion. Every instant message, page click, and step you take now produces a data point that can be used to build a detailed profile of who you are.

Every breath you take, Every move you make

The coarse-grained demographics and contact information of yesteryear seems quaint compared to today’s sophisticated data collection battleground. In the past, marketers would make judgement calls on your likely income and family structure based on where you lived, and you’d receive “targeted” mail and calls from telemarketers. Loyalty programs and the emergence of web analytics pushed things a little further.

Today, the steady march of technological advancement has created a vast data collection empire that measures every aspect of your digital life and, increasingly, your offline life as well. Facebook alone uses nearly one hundred data points to target ads to you – everything from your marital status to whether you’ve been on vacation lately or not. Telecoms have access to extremely detailed information on your location. Apple has biometric data.

Also watching your every move are web trackers. “Cookie-syncing” is one of the sneaky ways advertisers can follow you around the internet. Basically, cookie-syncing allows third parties to share browsing information at such a large scale that even the NSA “piggybacks” off them for surveillance purposes.

The recent sales growth of smart speakers will only increase the breadth of data companies collect and analyze. Amazon and Google have both filed patents for technology that would essentially allow them to mine audio recordings for keywords. Advertisers could potentially target you with diapers before your family and friends even know you’re expecting a baby.

Following the ones and zeros

While web trackers and companies like Apple and Google are collecting a lot of personal and behavioral data, it’s the whales of the data ecosystem – data brokers – who are creating increasingly detailed profiles on almost everyone.

Data brokers trade on the privacy of consumers and operate in the shadows.

– Senator Al Franken (D-Minn)

The goal of data brokers, such as Experian or Acxiom, is to siphon up as much personal data as possible and apply it to profiles. This data comes from a wide variety of sources. Your purchases, financial history, internet activity, and even psychographic attributes are mixed with information from public records to create a robust dossier. Digital profiles are then sorted into one of thousands of categories to help optimize advertising efforts.

Fear the shadow profile?

According to Pew Research, 91% of Americans “agree” or “strongly agree” that people have lost control over how personal information is collected and used.

Though optimizing clickthroughs is a big business, companies are increasingly moving beyond advertising to extract value from their growing data pipeline. Amalgamated data is increasingly being viewed as a clever way to assess risk in the decision-making process (e.g. hiring, insurance, loan or housing applications), and the stakes for consumers are going up in the process.

For example, a man may feel comfortable sharing their HIV status on Grindr (for practical reasons), but may not want that information going to a third party. (Unfortunately, that really happened.)

In 2015, Facebook filed a patent for a service that would help insurance companies vet people based on the credit ratings of their social network.

The More You Know

Below the surface of our screens, our digital profiles continue to take shape.

Measures like adjusting website privacy controls and clearing cookies are a good start, but that’s only a fraction of the data companies are collecting. Not only do data brokers make it hard to officially opt out, their partnerships with corporations and advanced data collection methods cast such a wide net, that it’s almost impossible to exclude individual people.

Data brokers have operated with very little scrutiny or oversight, but that may be changing. Under intense public and governmental pressure, Facebook recently cut ties with data brokers. For a company that has bullishly pursued monetization of user data at every turn, the move is a sign that the public sentiment is changing.

The more information on the personal data industry, visit Cracked Labs’ report on the issue.

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Infographic: Generative AI Explained by AI

What exactly is generative AI and how does it work? This infographic, created using generative AI tools such as Midjourney and ChatGPT, explains it all.

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Generative AI Explained by AI

After years of research, it appears that artificial intelligence (AI) is reaching a sort of tipping point, capturing the imaginations of everyone from students saving time on their essay writing to leaders at the world’s largest tech companies. Excitement is building around the possibilities that AI tools unlock, but what exactly these tools are capable of and how they work is still not widely understood.

We could write about this in detail, but given how advanced tools like ChatGPT have become, it only seems right to see what generative AI has to say about itself.

Everything in the infographic above – from illustrations and icons to the text descriptions⁠—was created using generative AI tools such as Midjourney. Everything that follows in this article was generated using ChatGPT based on specific prompts.

Without further ado, generative AI as explained by generative AI.

Generative AI: An Introduction

Generative AI refers to a category of artificial intelligence (AI) algorithms that generate new outputs based on the data they have been trained on. Unlike traditional AI systems that are designed to recognize patterns and make predictions, generative AI creates new content in the form of images, text, audio, and more.

Generative AI uses a type of deep learning called generative adversarial networks (GANs) to create new content. A GAN consists of two neural networks: a generator that creates new data and a discriminator that evaluates the data. The generator and discriminator work together, with the generator improving its outputs based on the feedback it receives from the discriminator until it generates content that is indistinguishable from real data.

Generative AI has a wide range of applications, including:

  • Images: Generative AI can create new images based on existing ones, such as creating a new portrait based on a person’s face or a new landscape based on existing scenery
  • Text: Generative AI can be used to write news articles, poetry, and even scripts. It can also be used to translate text from one language to another
  • Audio: Generative AI can generate new music tracks, sound effects, and even voice acting

Disrupting Industries

People have concerns that generative AI and automation will lead to job displacement and unemployment, as machines become capable of performing tasks that were previously done by humans. They worry that the increasing use of AI will lead to a shrinking job market, particularly in industries such as manufacturing, customer service, and data entry.

Generative AI has the potential to disrupt several industries, including:

  • Advertising: Generative AI can create new advertisements based on existing ones, making it easier for companies to reach new audiences
  • Art and Design: Generative AI can help artists and designers create new works by generating new ideas and concepts
  • Entertainment: Generative AI can create new video games, movies, and TV shows, making it easier for content creators to reach new audiences

Overall, while there are valid concerns about the impact of AI on the job market, there are also many potential benefits that could positively impact workers and the economy.

In the short term, generative AI tools can have positive impacts on the job market as well. For example, AI can automate repetitive and time-consuming tasks, and help humans make faster and more informed decisions by processing and analyzing large amounts of data. AI tools can free up time for humans to focus on more creative and value-adding work.

How This Article Was Created

This article was created using a language model AI trained by OpenAI. The AI was trained on a large dataset of text and was able to generate a new article based on the prompt given. In simple terms, the AI was fed information about what to write about and then generated the article based on that information.

In conclusion, generative AI is a powerful tool that has the potential to revolutionize several industries. With its ability to create new content based on existing data, generative AI has the potential to change the way we create and consume content in the future.

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