Information Processing: What you call data processing when people are so disgusted with it they won't let it be discussed in their presence.

Okay, so the user wants a news article based on that sentence about Information Processing being a term used when people are so disgusted with data processing they don't want to discuss it. Let me break it down.

First, I need to understand what "Information Processing" means here. It's like a euphemism for data processing when people are really against it. Maybe it's about privacy concerns, data misuse, or unethical practices. The article should explore why there's such disgust.

I should start by setting the scene. Maybe describe a recent event or trend where data processing has caused backlash. Like a big data scandal or something. Then, introduce the term "Information Processing" as a rebranding attempt.

Next, I'll need to explain why people are disgusted. Mention privacy breaches, surveillance, maybe Cambridge Analytica or similar cases. Use quotes from experts to add credibility.

I should also talk about how companies are responding. Are they actually changing practices, or just the terminology? Maybe include examples of companies facing backlash.

Include a section on public reaction. Have there been protests, boycotts, or new regulations? GDPR in Europe could be relevant here.

Finally, discuss the implications. Is this shift in terminology helping, or is it just covering up the real issues? Maybe end with a call for more transparency and ethical practices.

Need to make sure the article flows smoothly, is informative, and covers different angles. Keep it neutral but highlight the tension between businesses and the public. Aim for at least 500 characters, so probably around 700-800 words to be safe.

Let me check if I'm missing anything. Maybe include how this affects different sectors—government, tech, healthcare. Also, future outlook: will this rebranding work, or will people catch on?

Alright, time to write it out in a formal news style without a title. Make sure each paragraph transitions well and supports the main idea.
In recent years, a growing wave of public resistance has emerged against the pervasive use of data collection and analysis by corporations, governments, and tech platforms. What was once blandly referred to as "data processing" has become so ethically fraught and politically charged that many now recoil at the mere mention of the practice. This shift has given rise to a curious linguistic phenomenon: the rebranding of "data processing" as "information processing" in certain circles, a euphemism deployed when the original term provokes such visceral discomfort that it derails conversations entirely.

The roots of this aversion trace back to a cascade of high-profile scandals, from unauthorized facial recognition systems to the covert sale of personal data for targeted advertising. A 2023 Pew Research study revealed that 78% of respondents view data collection practices as "invasive," while 64% actively distrust institutions that rely on them. "People aren't just skeptical—they're furious," explained Dr. Elena Torres, a sociologist specializing in digital ethics. "When I present research on data harvesting at conferences, attendees often demand I use terms like 'information optimization' instead. The original language has become radioactive."

This lexical pivot is particularly evident in corporate settings. Internal memos from major tech firms, leaked earlier this year, show executives instructing teams to avoid "trigger words" like "data mining" or "tracking" in favor of phrases such as "insight development" or "knowledge enhancement." Critics argue this linguistic sleight of hand obscures the realities of surveillance capitalism. "Calling it 'information processing' doesn’t change the fact that companies are scraping our lives for profit," said activist Harper Zhou, founder of the watchdog group Data Rights Now. "It’s like calling deforestation 'tree relocation'—softer language doesn’t solve the harm."

The tension has spilled into policymaking. In the European Union, debates over the AI Act saw legislators clash over whether to ban certain "data processing" methods outright or regulate them under broader "information governance" frameworks. Meanwhile, grassroots movements have adopted increasingly confrontational tactics: employees at a prominent analytics firm staged a walkout last month after discovering their project—marketed internally as "information enrichment"—involved sourcing datasets from conflict zones without consent.

Psychologists suggest the disgust response stems from a profound sense of violation. "People feel reduced to commodities," said Dr. Rajiv Mehta, a behavioral researcher. "When they hear 'data processing,' they envision their intimate moments—texts, location history, health records—being fed into algorithms. The euphemism is an attempt to sanitize that dehumanization."

Yet not everyone sees the terminology shift as nefarious. Some industry leaders argue that "information processing" better reflects evolving technical realities. "Modern systems don’t just process raw data; they derive meaning from interconnected knowledge networks," contended Clara Deng, CEO of a machine learning startup. "The backlash is understandable, but language must evolve alongside technology."

As the debate rages, one thing is clear: the public’s tolerance for opaque data practices has evaporated. Whether rebranding the problem as "information processing" will quell the outrage—or deepen the distrust—remains an open question. For now, the words we use to describe these systems have become as contested as the systems themselves.