China

Chinese Big Tech's new fear: crowdsourced, sharable docs

Tech workers are creatively using sharable files to fight exploitation.

A woman walks outside the headquarters of Tencent while looking at her phone.
SHENZHEN, CHINA - AUGUST 19: A woman walks outside the headquarters of Tencent on August 19, 2020 in Shenzhen, Guangdong Province of China. (Photo by VCG/VCG via Getty Images)
VCG / Contributor/ Getty Images

A crowdsourced spreadsheet with a blacklist of bad managers at big Chinese internet platform companies went viral on Chinese social media earlier this week.


Screenshots of the shared Tencent Sheets, the Tencent equivalent of Google Sheets (banned in China), named and shamed managers of specific teams in Chinese Big Tech, detailed working conditions and team dynamics, and included advice for those looking to land jobs on the teams.

The criterion for judging a bad manager is whether they are a so-called "pick-up artist," or PUA. In China, PUA is now a commonly known term referring to the superior in a relationship who gaslights and suppresses their subordinate. For positions that the blacklist didn't recommend, the advice was crisp and urgent: Run! (快逃).

There's no way to verify the authenticity of the information, and Chinese media has reported that the shared spreadsheet was promptly reported for violations and is now inaccessible.

Shared docs have had a banner year in China. Chinese netizens' creative use of shared documents has allowed simple spreadsheets to become a crowdsourcing tool for mutual aid in times of crisis and a self-organizing tool for tech workers seeking to expose grueling working conditions.

Just last month, thousands of white collar Chinese tech workers participated in another collaborative project they called "Worker Lives Matter," sharing their extended work hours, exposing tech companies that still adopted a "996" schedule and workplace cultures. A few weeks later, tech giants from ByteDance to Tencent announced they would strictly follow an 8-hour, 5-workday schedule, in compliance with China's labor laws. It's unknown whether workers' online expose prompted BigTech to abolish a brutal overtime policy that tech workers had long criticized.

This past summer, shared docs played a key role in disaster relief in the flood-stricken Zhengzhou, the capital city of Henan province. Thousands of residents crowdsourced relief assistance over a 48 hour period through a single Tencent doc, rescuing those awaiting rescue. The document contained information including contact information for official and unofficial rescue teams, relief resources, shelter locations, phone-charging stations and online medical consultations.

Grassroots digital crowdsourcing efforts in China first made an impact during the initial COVID-19 outbreak in early 2020. Citizens started shared documents to help catalog reliable news coverage about the epidemic, to list outpatient clinics across Hubei province and to create tools for procuring medical supplies from abroad and clearing customs. Volunteers also raced to archive censored media coverage and threatened personal accounts of those suffering from disease or injustice. In a restrictive media and information environment like China, these shared docs have been essential for Chinese citizens to access reliable information in times of crisis and communicate with wider communities.

Fintech

Judge Zia Faruqui is trying to teach you crypto, one ‘SNL’ reference at a time

His decisions on major cryptocurrency cases have quoted "The Big Lebowski," "SNL," and "Dr. Strangelove." That’s because he wants you — yes, you — to read them.

The ways Zia Faruqui (right) has weighed on cases that have come before him can give lawyers clues as to what legal frameworks will pass muster.

Photo: Carolyn Van Houten/The Washington Post via Getty Images

“Cryptocurrency and related software analytics tools are ‘The wave of the future, Dude. One hundred percent electronic.’”

That’s not a quote from "The Big Lebowski" — at least, not directly. It’s a quote from a Washington, D.C., district court memorandum opinion on the role cryptocurrency analytics tools can play in government investigations. The author is Magistrate Judge Zia Faruqui.

Keep ReadingShow less
Veronica Irwin

Veronica Irwin (@vronirwin) is a San Francisco-based reporter at Protocol covering fintech. Previously she was at the San Francisco Examiner, covering tech from a hyper-local angle. Before that, her byline was featured in SF Weekly, The Nation, Techworker, Ms. Magazine and The Frisc.

The financial technology transformation is driving competition, creating consumer choice, and shaping the future of finance. Hear from seven fintech leaders who are reshaping the future of finance, and join the inaugural Financial Technology Association Fintech Summit to learn more.

Keep ReadingShow less
FTA
The Financial Technology Association (FTA) represents industry leaders shaping the future of finance. We champion the power of technology-centered financial services and advocate for the modernization of financial regulation to support inclusion and responsible innovation.
Enterprise

AWS CEO: The cloud isn’t just about technology

As AWS preps for its annual re:Invent conference, Adam Selipsky talks product strategy, support for hybrid environments, and the value of the cloud in uncertain economic times.

Photo: Noah Berger/Getty Images for Amazon Web Services

AWS is gearing up for re:Invent, its annual cloud computing conference where announcements this year are expected to focus on its end-to-end data strategy and delivering new industry-specific services.

It will be the second re:Invent with CEO Adam Selipsky as leader of the industry’s largest cloud provider after his return last year to AWS from data visualization company Tableau Software.

Keep ReadingShow less
Donna Goodison

Donna Goodison (@dgoodison) is Protocol's senior reporter focusing on enterprise infrastructure technology, from the 'Big 3' cloud computing providers to data centers. She previously covered the public cloud at CRN after 15 years as a business reporter for the Boston Herald. Based in Massachusetts, she also has worked as a Boston Globe freelancer, business reporter at the Boston Business Journal and real estate reporter at Banker & Tradesman after toiling at weekly newspapers.

Image: Protocol

We launched Protocol in February 2020 to cover the evolving power center of tech. It is with deep sadness that just under three years later, we are winding down the publication.

As of today, we will not publish any more stories. All of our newsletters, apart from our flagship, Source Code, will no longer be sent. Source Code will be published and sent for the next few weeks, but it will also close down in December.

Keep ReadingShow less
Bennett Richardson

Bennett Richardson ( @bennettrich) is the president of Protocol. Prior to joining Protocol in 2019, Bennett was executive director of global strategic partnerships at POLITICO, where he led strategic growth efforts including POLITICO's European expansion in Brussels and POLITICO's creative agency POLITICO Focus during his six years with the company. Prior to POLITICO, Bennett was co-founder and CMO of Hinge, the mobile dating company recently acquired by Match Group. Bennett began his career in digital and social brand marketing working with major brands across tech, energy, and health care at leading marketing and communications agencies including Edelman and GMMB. Bennett is originally from Portland, Maine, and received his bachelor's degree from Colgate University.

Enterprise

Why large enterprises struggle to find suitable platforms for MLops

As companies expand their use of AI beyond running just a few machine learning models, and as larger enterprises go from deploying hundreds of models to thousands and even millions of models, ML practitioners say that they have yet to find what they need from prepackaged MLops systems.

As companies expand their use of AI beyond running just a few machine learning models, ML practitioners say that they have yet to find what they need from prepackaged MLops systems.

Photo: artpartner-images via Getty Images

On any given day, Lily AI runs hundreds of machine learning models using computer vision and natural language processing that are customized for its retail and ecommerce clients to make website product recommendations, forecast demand, and plan merchandising. But this spring when the company was in the market for a machine learning operations platform to manage its expanding model roster, it wasn’t easy to find a suitable off-the-shelf system that could handle such a large number of models in deployment while also meeting other criteria.

Some MLops platforms are not well-suited for maintaining even more than 10 machine learning models when it comes to keeping track of data, navigating their user interfaces, or reporting capabilities, Matthew Nokleby, machine learning manager for Lily AI’s product intelligence team, told Protocol earlier this year. “The duct tape starts to show,” he said.

Keep ReadingShow less
Kate Kaye

Kate Kaye is an award-winning multimedia reporter digging deep and telling print, digital and audio stories. She covers AI and data for Protocol. Her reporting on AI and tech ethics issues has been published in OneZero, Fast Company, MIT Technology Review, CityLab, Ad Age and Digiday and heard on NPR. Kate is the creator of RedTailMedia.org and is the author of "Campaign '08: A Turning Point for Digital Media," a book about how the 2008 presidential campaigns used digital media and data.

Latest Stories
Bulletins