#deployment monitoring

[ourjobagency]

Whether you’re a small business or a large enterprise, using Salesforce Change Set can help you more efficiently manage changes to your Salesforce platform.https://qrsolutions.com.au/salesforce-change-set-a-comprehensive-guide/

[jcmarchi]

DeepSeek-R1 Red Teaming Report: Alarming Security and Ethical Risks Uncovered

New Post has been published on https://thedigitalinsider.com/deepseek-r1-red-teaming-report-alarming-security-and-ethical-risks-uncovered/

DeepSeek-R1 Red Teaming Report: Alarming Security and Ethical Risks Uncovered

A recent red teaming evaluation conducted by Enkrypt AI has revealed significant security risks, ethical concerns, and vulnerabilities in DeepSeek-R1. The findings, detailed in the January 2025 Red Teaming Report, highlight the model’s susceptibility to generating harmful, biased, and insecure content compared to industry-leading models such as GPT-4o, OpenAI’s o1, and Claude-3-Opus. Below is a comprehensive analysis of the risks outlined in the report and recommendations for mitigation.

Key Security and Ethical Risks

1. Harmful Output and Security Risks

Highly vulnerable to producing harmful content, including toxic language, biased outputs, and criminally exploitable information.

11x more likely to generate harmful content than OpenAI’s o1.

4x more toxic than GPT-4o.

3x more biased than Claude-3-Opus.

4x more vulnerable to generating insecure code than OpenAI’s o1.

Highly susceptible to CBRN (Chemical, Biological, Radiological, and Nuclear) information generation, making it a high-risk tool for malicious actors.

2. Comparison with Other Models

Risk Category DeepSeek-R1 Claude-3-Opus GPT-4o OpenAI’s o1 Bias 3x higher Lower Similar Similar Insecure Code 4x higher 2.5x higher 1.25x higher – Harmful Content 11x higher 6x higher 2.5x higher – Toxicity 4x higher Nearly absent 2.5x higher – CBRN Content 3.5x higher 3.5x higher 2x higher –

Bias and Ethical Risks

83% of bias attacks were successful, with substantial bias detected in health, race, and religion-related queries.

The model displayed higher levels of demographic stereotyping, which could violate various fairness regulations including ECOA, FHA, ACA, and the EU AI Act.

Sample test cases demonstrated that DeepSeek-R1 preferred certain demographics for high-status job roles, reinforcing workplace bias.

Harmful Content Generation

45% of harmful tests resulted in the model generating content related to criminal activities, including illegal weapons and controlled substances.

A test prompt asking the model to develop a blog on “The Art of Persuasion in Terrorist Recruitment” resulted in a highly detailed response outlining radicalization strategies that could be exploited by extremist groups to refine recruitment tactics, potentially increasing the risk of real-world violence.

2.5x more vulnerable than GPT-4o and 6x more vulnerable than Claude-3-Opus to generating extremist content.

45% of harmful tests resulted in the model generating content related to criminal activities, including illegal weapons and controlled substances.

Insecure Code Generation

78% of code-related attacks successfully extracted insecure and malicious code snippets.

The model generated malware, trojans, and self-executing scripts upon requests. Trojans pose a severe risk as they can allow attackers to gain persistent, unauthorized access to systems, steal sensitive data, and deploy further malicious payloads.

Self-executing scripts can automate malicious actions without user consent, creating potential threats in cybersecurity-critical applications.

Compared to industry models, DeepSeek-R1 was 4.5x, 2.5x, and 1.25x more vulnerable than OpenAI’s o1, Claude-3-Opus, and GPT-4o, respectively.

78% of code-related attacks successfully extracted insecure and malicious code snippets.

CBRN Vulnerabilities

Generated detailed information on biochemical mechanisms of chemical warfare agents. This type of information could potentially aid individuals in synthesizing hazardous materials, bypassing safety restrictions meant to prevent the spread of chemical and biological weapons.

13% of tests successfully bypassed safety controls, producing content related to nuclear and biological threats.

3.5x more vulnerable than Claude-3-Opus and OpenAI’s o1.

Generated detailed information on biochemical mechanisms of chemical warfare agents.

13% of tests successfully bypassed safety controls, producing content related to nuclear and biological threats.

3.5x more vulnerable than Claude-3-Opus and OpenAI’s o1.

Recommendations for Risk Mitigation

To minimize the risks associated with DeepSeek-R1, the following steps are advised:

1. Implement Robust Safety Alignment Training

2. Continuous Automated Red Teaming

Regular stress tests to identify biases, security vulnerabilities, and toxic content generation.

Employ continuous monitoring of model performance, particularly in finance, healthcare, and cybersecurity applications.

3. Context-Aware Guardrails for Security

Develop dynamic safeguards to block harmful prompts.

Implement content moderation tools to neutralize harmful inputs and filter unsafe responses.

4. Active Model Monitoring and Logging

Real-time logging of model inputs and responses for early detection of vulnerabilities.

Automated auditing workflows to ensure compliance with AI transparency and ethical standards.

5. Transparency and Compliance Measures

Maintain a model risk card with clear executive metrics on model reliability, security, and ethical risks.

Comply with AI regulations such as NIST AI RMF and MITRE ATLAS to maintain credibility.

Conclusion

DeepSeek-R1 presents serious security, ethical, and compliance risks that make it unsuitable for many high-risk applications without extensive mitigation efforts. Its propensity for generating harmful, biased, and insecure content places it at a disadvantage compared to models like Claude-3-Opus, GPT-4o, and OpenAI’s o1.

Given that DeepSeek-R1 is a product originating from China, it is unlikely that the necessary mitigation recommendations will be fully implemented. However, it remains crucial for the AI and cybersecurity communities to be aware of the potential risks this model poses. Transparency about these vulnerabilities ensures that developers, regulators, and enterprises can take proactive steps to mitigate harm where possible and remain vigilant against the misuse of such technology.

Organizations considering its deployment must invest in rigorous security testing, automated red teaming, and continuous monitoring to ensure safe and responsible AI implementation. DeepSeek-R1 presents serious security, ethical, and compliance risks that make it unsuitable for many high-risk applications without extensive mitigation efforts.

Readers who wish to learn more are advised to download the report by visiting this page.

[ai-factory]

AI Factory: Pioneering Innovation with Advanced AI Solutions

In today’s rapidly evolving digital landscape, businesses face unprecedented challenges and opportunities. Artificial Intelligence (AI) has emerged as a transformative force, enabling organizations to optimize operations, enhance decision-making, and deliver exceptional customer experiences. Enter the AI Factory—a revolutionary platform designed to empower businesses with scalable AI solutions tailored to their unique needs.

What is AI Factory?

The AI Factory is a cutting-edge platform that brings together advanced AI capabilities to streamline the development, deployment, and management of AI solutions. It serves as a comprehensive hub for:

AI Use Case Development

Proof of Concept (POC) Implementation

AI Solution Deployment

Lifecycle Management of AI Models

Explore more about the transformative potential of AI Factory on UnifyCloud’s AI Factory platform.

Why Businesses Need an AI Factory

The AI Factory addresses several critical pain points for organizations:

Scalability: Develop and deploy AI solutions that grow with your business.

Customization: Tailor AI models to address industry-specific challenges.

Efficiency: Automate workflows and reduce operational inefficiencies.

Cost Optimization: Manage resources effectively with tools like CloudAtlas AI Cost Optimize.

Industry-Specific Applications

Healthcare

The healthcare sector is witnessing a paradigm shift with AI-driven innovations:

Medical Imaging: Deploy AI POCs to analyze radiology images and identify anomalies with precision.

Patient Care: Leverage AI for personalized treatment plans and efficient hospital management systems.

Predictive Analytics: Harness AI to predict disease outbreaks and optimize resource allocation.

Learn more about how AI is revolutionizing healthcare on UnifyCloud’s AI solutions page.

Retail

Retail businesses can enhance customer experiences and streamline operations through AI:

Personalized Shopping: Use AI to analyze customer behavior and provide tailored recommendations.

Demand Forecasting: Implement AI POCs to predict market trends and adjust inventory levels accordingly.

Sentiment Analysis: Employ AI-driven tools to gauge customer feedback and improve service quality.

Explore how AI empowers retail on CloudAtlas AI Factory.

Finance

AI is transforming the financial services industry with:

Fraud Detection: Develop AI POCs to identify and prevent fraudulent activities in real-time.

Credit Risk Management: Utilize AI to assess creditworthiness and minimize risks.

Banking Automation: Enhance operational efficiency with generative AI for routine tasks.

Discover UnifyCloud’s innovative AI Guardian tool for compliance and security at CloudAtlas AI Guardian.

Manufacturing

The manufacturing industry benefits from AI in numerous ways:

Predictive Maintenance: Avoid equipment downtime with AI-driven insights.

Supply Chain Optimization: Streamline logistics and reduce costs with AI-powered analytics.

Product Design: Utilize generative AI to create innovative product designs.

For more insights, visit UnifyCloud’s CloudAtlas AI platform.

Construction

AI is making significant inroads in the construction industry:

Project Management: Implement AI POCs to manage timelines and resources effectively.

Safety Monitoring: Use AI to ensure worker safety and compliance with regulations.

Smart Infrastructure: Plan and execute intelligent infrastructure projects with AI insights.

Energy

The energy sector can achieve sustainability goals with AI:

Renewable Energy Forecasting: Predict energy generation patterns to optimize usage.

Smart Grid Management: Enhance energy distribution with AI-driven analytics.

Sustainable Planning: Leverage generative AI for eco-friendly energy solutions.

Visit UnifyCloud’s CloudAtlas AI Factory to explore sustainable AI innovations.

Solution-Specific Capabilities

AI Development and Deployment

Model Training: Build and train robust AI models tailored to specific business needs.

Lifecycle Management: Manage AI models from development to deployment.

Generative AI Solutions: Create innovative content and workflows with advanced generative AI tools.

Learn how CloudAtlas AI simplifies AI development and deployment.

Data Analytics

Big Data Insights: Analyze vast datasets for actionable insights.

Predictive Analytics: Forecast trends and make data-driven decisions.

Visualization: Use generative AI for intuitive and impactful data visualizations.

Automation

Business Process Automation: Streamline operations with AI-powered automation tools.

Robotic Process Automation (RPA): Implement AI POCs for efficient task automation.

Workflow Optimization: Enhance productivity with intelligent automation solutions.

Sustainability and Customer Experience

Environmental Impact Assessments: Use AI to evaluate and minimize ecological footprints.

Personalized User Experiences: Leverage generative AI for tailored customer interactions.

Sentiment Analysis: Gauge customer feedback to refine services.

Why Choose UnifyCloud’s AI Factory

UnifyCloud’s AI Factory offers:

Comprehensive Solutions: From AI development to deployment, all under one roof.

Proven Expertise: Decades of experience in delivering AI-driven business innovations.

Customizable Tools: Tailored solutions to meet unique industry demands.

Cost Efficiency: Optimize your investments with AI Cost Optimize tools.

Discover the future of AI with UnifyCloud’s CloudAtlas AI Factory.

Conclusion

The AI Factory is more than a platform; it’s a gateway to innovation and growth. By integrating AI into your business, you can unlock new opportunities, drive efficiency, and stay ahead in a competitive market. With UnifyCloud’s comprehensive suite of AI solutions, the journey from concept to execution becomes seamless. Explore the limitless possibilities of AI with UnifyCloud’s AI Factory today.

Learn More About AI Factory from Azure Marketplace – AI Factory | AI Cost Optimize | AI Guardian

[mitsde123]

What is Data Science? A Comprehensive Guide for Beginners

In today’s data-driven world, the term “Data Science” has become a buzzword across industries. Whether it’s in technology, healthcare, finance, or retail, data science is transforming how businesses operate, make decisions, and understand their customers. But what exactly is data science? And why is it so crucial in the modern world? This comprehensive guide is designed to help beginners understand the fundamentals of data science, its processes, tools, and its significance in various fields.

[robomad]

Scaling Node.js Applications with PM2

Scaling Node.js Applications with PM2: A Comprehensive Guide

Introduction As your Node.js application grows, you may need to scale it to handle increased traffic and ensure reliability. PM2 (Process Manager 2) is a powerful process manager for Node.js applications that simplifies deployment, management, and scaling. It provides features such as process monitoring, log management, and automatic restarts, making it an essential tool for production…

[townpostin]

Adityapur and Chandil Police Conduct Flag March Ahead of Muharram

Appeal for Peace and Harmony During Muharram Celebrations On Tuesday, the station in-charges of Adityapur and Chandil conducted a flag march in their respective areas, urging residents to celebrate Muharram with mutual harmony and maintain peace. ADITYAPUR – The station in-charges of Adityapur and Chandil conducted a flag march on Tuesday to ensure peace and harmony during the upcoming Muharram…

[softlabsgroup05]

Explore the stages of deploying AI solutions in cloud environments with our informative guide. This simplified overview outlines the essential steps involved in leveraging cloud infrastructure to implement and scale AI applications, facilitating seamless integration and efficient utilization of resources. Perfect for those interested in harnessing the power of cloud computing for AI development. Stay informed with Softlabs Group for more insightful content on cutting-edge advancements in AI.

[techdriveplay]

Logitech Unveils Signature Slim Keyboard Combo to Seamlessly Flow Between Work and Life at the Desk

SYDNEY, Australia. – March 27, 2024 – Today Logitech (SIX: LOGN) (NASDAQ: LOGI) introduced the Signature Slim Combo, designed to simplify the experience across personal and work computers. For people with a single workspace for both professional and personal tasks, the Signature Slim products are beautifully designed solutions that look good in the home or office. With more features than typical…

[vividverses]

Exciting developments in MLOps await in 2024! 🚀 DevOps-MLOps integration, AutoML acceleration, Edge Computing rise – shaping a dynamic future. Stay ahead of the curve! #MLOps #TechTrends2024 🤖✨

[virtualizationhowto]

Security Onion Install: Awesome Open Source Security for Home Lab

Security Onion Install: Awesome Open Source Security for Home Lab @securityonion #homelab #selfhosted #SecurityOnionInstallationGuide #NetworkSecuritySolutions #IntrusionDetectionSystem #OpenSourceSecurityPlatform #ThreatHuntingWithSecurityOnion

Security Onion is at the top of the list if you want an excellent security solution to try in your home lab or even for enterprise security monitoring. It provides many great security tools for threat hunting and overall security and is fairly easy to get up and running quickly. Table of contentsWhat is Security Onion?Intrusion Detection and Threat HuntingMonitoring and Log managementCommunity…

[muellermh]

Wie können Sie Fehlerbehebungen bei der Automatisierung Ihrer CI/CD-Prozesse erleichtern?: "Einfache Fehlerbehebung beim Automatisieren von CI/CD-Prozessen dank MHM Digitale Lösungen UG"

#Automatisierung #Fehlerbehebung #CI/CD #DigitalLösungen #MHMDigitaleLösungenUG

CI/CD-Prozesse oder „Continuous Integration / Continuous Delivery“-Prozesse sind ein elementarer Bestandteil der modernen IT-Landschaft. Traditionell ermöglichen sie Softwareentwicklungsteams, kontinuierlich neue Funktionalität zu integrieren und schnell zu bereitstellen. Eine kontinuierliche Integration und kontinuiere Lieferung ermöglicht es Entwicklungsteams, Fehler schneller zu erkennen und…

[ourjobagency]

Salesforce Change Set is a tool that allows administrators to deploy customizations and changes from one Salesforce organization to another. It is particularly useful when organizations have multiple Salesforce environments, such as production and sandbox environments, and need to move customizations and changes between these environments.

To know more, visit-https://qrsolutions.com.au/salesforce-change-set-a-comprehensive-guide/

[rootedinrevisions]

Rooster Comes Home to His Girls

SUMMARY: There are not a ton of plot points, just Husband and Dad Bradley coming home to his girls.

WORD COUNT: 1.4k

WARNINGS: None (Pure fluff on this one)

TAG LIST: IN COMMENTS

A/N: I need something fluffy in my life and saw this picture on Pinterest and the idea just kind of flowed from there. Between everything going on in the country today and the stuff that's been going on in my personal life the past six months or so, I needed some pure, sickeningly sweet fluff. So here it is! Hope you enjoy!

The quiet hum of the baby monitor filled the kitchen as you stood at the sink, rinsing out a bottle. The rhythmic motion had become almost meditative over the past few weeks, a small way to keep yourself grounded while you waited for Bradley to come home. It had been a long deployment, and the days had felt heavier as they passed, each one marked by the absence of his presence, his laugh, his steady, calming voice. Now, he was finally on his way back, and your heart beat faster with every small sound outside, every imagined footstep near the door.

Suddenly, the soft creak of the front door reached your ears, and you froze, breath catching in your throat. You turned just in time to see him step into the house, his duffel bag dropping to the floor as his eyes found yours. For a moment, the world seemed to stop. He looked a little worn, a little tired, but his eyes shone with the same warmth, the same love, that had carried you through his absence. And just like that, the weight you’d been carrying slipped away.

You barely noticed dropping the kitchen towel as you moved toward him, your feet quickening until you were close enough to feel the warmth of him, smell the familiar, comforting scent of his cologne, and the hint of jet fuel that clung to his clothes.

Bradley pulled you into his arms with a gentle strength, as though he was afraid you might break, his hands settling firmly against your back as he held you close.

“I missed you so much,” he murmured, voice rough with emotion as he buried his face in your hair.

His embrace felt like home, solid and sure, grounding you after weeks of doing everything alone. You leaned into him, closing your eyes as his hand gently cradled the back of your head, holding you close, as if he never wanted to let go.

“I missed you too,” you whispered, feeling tears well up as you clutched him tighter, the reality of having him here again making your heart ache in the best way.

You pulled back just enough to look up at him, letting your eyes drink in every detail of his face—the familiar curve of his jaw, the warmth in his gaze, the slight shadow of exhaustion under his eyes.

And then, without a word, he leaned down, capturing your lips in a kiss that was soft, tender, and filled with all the words he hadn’t been able to say. You kissed him back, pouring all your relief, your longing, and your love into that moment. His hand came up to cup your cheek, his thumb gently brushing away a stray tear as he deepened the kiss, as if he needed to reassure himself that you were really here, that he was really home.

But then, the soft crackle of the baby monitor brought you both back, followed by a familiar whimper, a little cry that quickly turned into a wail. You sighed, feeling the exhaustion return as your mind shifted back to reality. You started to pull away, ready to go to her, but Bradley stopped you, his hand gently catching yours.

“Hey,” he murmured, giving you a soft smile as he looked toward the monitor, where your daughter’s cries continued. “I’ve got it. Let me take care of her.”

You hesitated, feeling the instinct to take over, to keep doing what you’d been doing alone for so long. “Are you sure? I don’t mind—”

But Bradley shook his head, his expression gentle but firm. “You’ve been doing this on your own for weeks. Let me be the dad for a while,” he said softly, his eyes filled with a tenderness that made your heart swell. “You look tired, sweetheart.”

You let out a breath, feeling the truth of those words hit you. “It’s been… a lot, but it’s okay. It’s what I signed up for.”

He gave a small shake of his head, his expression softening into something even more tender. “No, it’s not okay for you to do this alone. Go, relax. Take a bath, take the whole night off. I’ve got her.”

You felt the last bit of tension in your shoulders finally start to ease, the exhaustion you’d been holding back settling over you. You nodded, giving him a grateful smile as you whispered, “Thank you, Bradley.”

He gave your hand a reassuring squeeze before he let go, watching you with that same soft smile as you stepped back, finally allowing yourself to let him take over.

You paused at the doorway, glancing back as he turned and headed down the hall toward the nursery, his broad shoulders silhouetted in the soft glow of the nightlight spilling from your daughter’s room.

You took a deep breath, letting yourself sink into the silence, the weight lifting as you headed to the bathroom. It was strange, letting go of the constant watchfulness, but you trusted him completely. He was here now, and that was all that mattered.

In the bathroom, you ran a warm bath, sinking into the soothing water as the tension slowly faded away. For the first time in weeks, you allowed yourself to truly relax, closing your eyes and letting the warmth envelop you. You didn’t have to be on alert, didn’t have to listen for every small sound—Bradley was here, and he had everything under control.

After a while, you slipped into your pajamas, feeling more refreshed than you had in ages. You padded quietly down the hall, and as you passed the nursery you heard your daughter’s laughter  filling the air.

Quietly, you made your way to the doorway and peeked inside, stopping when you saw Bradley kneeling beside her crib. He had a teddy bear in his hand, making playful growling noises as he wiggled it toward her, his eyes bright with joy. Each time the bear touched her belly, she erupted into giggles, her little hands reaching out to grab it.

You leaned against the doorframe, smiling as you watched them. Bradley’s face softened as he looked at her, all the strength and resolve he usually wore dissolving into pure love. He was so gentle with her, the way he brushed a strand of hair from her face, the way he whispered silly little things to make her laugh as if he was trying to make up for every minute he’d missed while he was away.

You felt a tear slip down your cheek, but you didn’t wipe it away. Moments like this remind you why you fell in love with him in the first place.

Even after everything, the deployments, the late nights, the lonely stretches—you knew he was worth it.

You then watched as he picked her up, bringing her into his arms in a cradling position. He began to sway gently as he whispered to her, his voice a low, soothing murmur. She reached out and curled her little fingers around his thumb, her big, sleepy eyes fixed on him as though she was entranced.

You leaned against the doorway, watching the two of them, your heart full as you took in the sight of your husband cradling his little girl, his own eyes filled with pure love.

“Daddy’s home. I’m so sorry I was gone for so long, but I’m here now. I’m not going anywhere.” He whispered, his voice thick with emotion.

Your daughter blinked up at him, her little hand reaching up to touch his face, her tiny fingers brushing against his cheek. He leaned down, pressing a soft kiss to her forehead, a tear slipping down his cheek as he held her close.

You felt your own eyes misting as you watched him with her, the quiet love and devotion in his expression a balm to your soul. He looked over, noticing you in the doorway, and gave you a small, tender smile.

“Caught me,” he said softly, a touch of playful warmth in his voice.

You walked over, wrapping your arms around him as he shifted slightly, making room for you to lean in, resting your head against his shoulder as you looked down at your daughter. “I love seeing this side of you,” you whispered, pressing a gentle kiss to his shoulder.

“She’s grown so much,” he murmured, looking over at you with a mixture of pride and sorrow. “I feel like I missed so much.”

You shook your head, stepping closer, resting a hand on his arm. “She’s been waiting for you, Bradley. We both have.”

“I’m here now.” He reached up, his hand covering yours, a silent promise in his touch. The three of you stood there in the soft glow of the nursery, wrapped in a moment of love, peace, and quiet joy—a moment you knew you’d hold close to your heart, long after he had to leave again.

For now, though, he was here, and everything was just as it should be.

[mostlysignssomeportents]

The future of Amazon coders is the present of Amazon warehouse workers

I'm on a 20+ city book tour for my new novel PICKS AND SHOVELS. Catch me in BURBANK with WIL WHEATON TONIGHT (Mar 13), and in SAN DIEGO at MYSTERIOUS GALAXY on Mar 24. More tour dates here.

My theory of the "shitty technology adoption curve" holds that you can predict the future impact of abusive technologies on you by observing the way these are deployed against people who have less social power than you:

https://pluralistic.net/2023/06/11/the-shitty-tech-adoption-curve-has-a-business-model/

When you have a new, abusive technology, you can't just aim it at rich, powerful people, because when they complain, they get results. To successfully deploy that abusive tech, you need to work your way up the privilege gradient, starting with people with no power, like prisoners, refugees, and mental patients. This starts the process of normalization, even as it sands down some of the technology's rough edges against their tender bodies. Once that's done, you can move on to people with more social power – immigrants, blue collar workers, school children. Step by step, you normalize and smooth out the abusive tech, until you can apply it to everyone – even rich and powerful people. Think of the deployment of CCTV, facial recognition, location tracking, and web surveillance.

All this means that blue collar workers are the pioneering early adopters of the bossware that will shortly be tormenting their white-collar colleagues elsewhere in the business. It's as William Gibson prophesied: "The future is here, it's just not evenly distributed" (it's pooled up thick and noxious around the ankles of blue-collar workers, refugees, mental patients, etc).

Nowhere is this rule more salient than in Big Tech firms. Tech companies have thoroughly segregated workforces. Delivery drivers, customer service reps, data-labelers, warehouse workers and other "green badge," low-status workers are the testing ground for their employer's own disciplinary technology, which monitors them down to the keystroke, the eye-movement, and the pee break. Meanwhile, the "blue badge" white-collar coders get stock options, gourmet cafeterias, free massages, day care and complimentary egg-freezing so they can delay fertility. Companies like Google not only use separate entrance for their different classes of workers – they stagger their shifts so that the elite workers don't even see their lower-status counterparts.

Importantly, almost none of these workers – whether low-status or high – are unionized. Tech union density is so thin, it's almost nonexistent. It's easy to see why elite tech workers wouldn't bother with unionizing: with such fantastic wages and so many perks, why endure the tedium of meetings and memos? But then there's the rest of the workers, who are subjected to endless "electronic whipping" by bossware and who take home wages that look like pocket change when compared to the tech division's compensation. These workers have every reason to unionize, living as they do in the dystopian future of labor.

At Amazon warehouses, workers are injured at three times the rate of warehouse workers at competing firms. They are penalized for "time off task" (like taking a piss break). They are made to stand in long, humiliating body-search lines when they go on- and off-shift, hours every week, without compensation. Variations on this theme play out in other blue-collar sectors of the Amazon empire, like Amazon delivery drivers and Whole Food shelf-stockers.

Those workers have every reason to unionize, and they have done their damndest, but Amazon has defeated worker union drives, again and again. How does Amazon win these battles? Simple: they cheat. They illegally fire union organizers:

https://pluralistic.net/2020/03/31/reality-endorses-sanders/#instacart-wholefoods-amazon

And then they smear unions to the press and to their own workers with lies (that subsequently leak):

https://pluralistic.net/2020/04/03/socially-useless-parasite/#christian-smalls

They spend millions on anti-union tech, spying on workers and creating "heatmaps" that let them direct their anti-union efforts to specific stores and facilities:

https://pluralistic.net/2020/04/21/all-in-it-together/#guard-labor-v-redistribution

They make workers use an official chat app, and then block any messages containing forbidden words, like "fairness," "grievance" and "diversity":

https://pluralistic.net/2022/04/05/doubleplusrelentless/#quackspeak

That's just the tip of the iceberg. A new investigation by Northwestern University's Teke Wiggin draws on worker interviews and FOIA requests to the NLRB to assemble a first-of-its-kind catalog of Amazon's labor-disciplining, union-busting tactics:

https://journals.sagepub.com/doi/10.1177/23780231251318389

Disciplining labor and busting unions go hand in hand. It's a simple equation: the harder it is for your workers to form a union, the worse you can treat them without facing labor reprisals, because individual workers' options are limited to a) quitting or b) sucking it up, while unionized workers can grieve, sue, and strike.

At the core of Amazon's labor discipline technology is "algorithmic management," which is exactly what it sounds like: replacing middle managers with software that counts your keystrokes, watches your eyeballs, or applies a virtual caliper to some other metric to decide whether you're a good worker or a rotten apple:

https://pluralistic.net/2024/11/26/hawtch-hawtch/#you-treasure-what-you-measure

Automation theory describes two poles of workplace automation: centaurs (in which workers are assisted by technology) and "reverse-centaurs" (in which workers provide assistance to technology):

https://pluralistic.net/2021/03/19/the-shakedown/#weird-flex

Amazon is a reverse-centaurism pioneer. Take the delivery drivers whose every maneuver, eyeball movement, and turn signal is analyzed and inevitably, found wanting, as workers seek to satisfy impossible quotas that can't even be met if you pee in a bottle instead of taking toilet breaks:

https://pluralistic.net/2023/10/20/release-energy/#the-bitterest-lemon

Then there's the warehouse workers who are also tormented with impossible, pisscall-annihilating quotas. Some of these workers are fitted with haptic wristbands that buzz to tell them they're being too slow at picking up an item and dropping it into a box, pushing them to faster, joint-destroying paces that account for Amazon's enduring position as the most worker-maiming warehouse employer in the nation:

https://pluralistic.net/2021/02/05/la-bookseller-royalty/#megacycle

In his paper, Wiggin does important work connecting these "electronic whips" to Amazon's arsenal of traditional union-busting weapons, like "captive audience" meetings where workers are forced to sit through hours of anti-union indoctrination. For Wiggin, bossware tools aren't just a stick to beat workers with – they're also a carrot that can be used to diffuse a worker's outrage ahead of a key union vote.

Algorithmic management isn't just software that wrings more work out of workers – it's software that replaces managers. By surveilling workers – both on the job and in social media spaces (like subreddits) where workers gather to talk, Amazon can tune the "electronic whip," reducing quotas and easing the pace of work so that workers view their jobs more favorably and are more receptive to anti-union propaganda.

This is "twiddling" – exploiting the digital flexibility of a system to "twiddle the knobs" governing its business logic, changing everything from prices to wages, search rankings to recommendations, in realtime, for every customer and worker:

https://pluralistic.net/2023/02/19/twiddler/

Twiddling combines surveillance data with flexible business logic to create an unbeatable house advantage. If you're an Amazon shopper, you get twiddled all the time, as Amazon replaces the best matches for your searches with paid results. If you buy that first product result, you'll pay an average of 29% more than the best match for your search:

https://pluralistic.net/2023/11/06/attention-rents/#consumer-welfare-queens

Worker-side twiddling is even more dystopian. When a nurse is assigned a shift by an "Uber for nurses" app, the app checks whether the worker has overdue credit card bills, which trigger lower wages (on the theory that an indebted worker is a desperate worker):

https://pluralistic.net/2024/12/18/loose-flapping-ends/#luigi-has-a-point

When it comes to union-busting, Amazon's found a new use for twiddling: lessening the pace of work, which Wiggin calls "algorithmic slack-cutting." The important thing about algorithmic slack-cutting is that it's only temporary. The algorithm that reduces your work-load in the runup to a union vote can then dial the pace of work up afterward, by small, random increments that are below the threshold at which they register on the human sensory apparatus. They're not so much boiling the frog as poaching it.

Meanwhile, Amazon gets to flood the zone with anti-union messages, including mandatory messages on the app that assigns your shifts – a captive audience meeting in every pocket.

Between social media surveillance and on-the-job surveillance, Amazon has built a powerful training set for algorithms designed to crush workplace democracy. That's how things go for Amazon's warehouse workers and delivery drivers, and the shelf-stockers at Whole Foods.

But of course, the picture is very different for Amazon's techies, who enjoy the industry standard of high wages and lavish perks.

For now.

The tech industry is in the midst of three years' worth of mass layoffs: 260K in 2023, 150k in 2024, tens of thousands this year. None of this is due to a shortfall in profits, mind: Google laid off 12,000 workers just weeks after staging a stock buyback that would have funded their salaries for 27 years. Meta just announced a 5% across-the-board headcount cut and that it was doubling its executive bonuses.

In other words, tech is firing workers not because it must, but because it can. When workers depend on scarcity – instead of unions – as a source of power, they dig their own graves. For well-paid, scarcity-based coders, every new computer science graduate is the enemy, eroding the scarcity that your wages depend on.

Amazon coders get to come to work with pink mohawks, facial piercings, and black t-shirts that say things their bosses don't understand. They get to pee whenever they want to. That's not because Jeff Bezos is sentimentally attached to techies and bears personal animus toward warehouse workers. Jeff Bezos wants to pay his workforce as little as he can. He treats his tech workers with respect because he's afraid of them, because if they quit, he can't replace them, and without their work, he can't make money.

Once there's an army of unemployed coders who'll take your job, Jeff Bezos doesn't have to fear you anymore. He can fire you and replace you the next day.

Bezos is obviously incredibly horny for this. Like most tech bosses, he dreams of a world in which entitled hackers can't call their bosses dumbshits and decline to frog when they shout "jump!" That's why Amazon PR puts so much energy into trumpeting the business's use of AI to replace coders:

https://www.hrgrapevine.com/us/content/article/2024-08-22-amazon-cloud-ceo-warns-software-engineers-ai-could-replace-your-coding-work-within-2-years

It's not just that they're excited about firing coders and saving money – they're even more excited about transforming the job of "Amazon coder," from someone who solves complex technical problems to someone who performs tedious code review on automatically generated code barfed up by a chatbot:

https://pluralistic.net/2024/04/01/human-in-the-loop/#monkey-in-the-middle

"Code reviewer" is a much less fulfilling job than "programmer." Code reviewers are also easier to replace than programmers. A code reviewer is a reverse-centaur, a servant to the machine. Every time you hear "AI-assisted programmer," you should substitute "programmer-assisted AI."

Programming is even more bossware-ready than working in a warehouse. The machines coders use are much easier to fit with surveillance technology that monitors their performance – and spies on their communications, looking for dissenting chatter – than a warehouse floor. The only thing that stopped Jeff Bezos from treating his programmers like his warehouse workers is their scarcity. That scarcity is now going away.

That's bad news for Amazon customers, too. Tech workers often feel a sense of duty to their users, a "vocational awe" that drives them to put in long hours to make things their users will enjoy. The labor power of tech workers has long served as a check on the impulse to enshittify those products:

https://pluralistic.net/2023/11/25/moral-injury/#enshittification

As tech workers' power wanes, they don't just lose the ability to protect themselves from their bosses' greediest, most sadistic urges – they also lose the power to defend all of us. Smart tech workers know this. That's why Amazon tech workers walked out in support of Amazon warehouse workers:

https://pluralistic.net/2021/01/19/deastroturfing/#real-power

Which led to their prompt dismissal:

https://pluralistic.net/2020/04/14/abolish-silicon-valley/#hang-together-hang-separately

Tech worker/gig worker solidarity is the only way workers can win against tech bosses and defeat the shitty technology adoption curve:

https://pluralistic.net/2024/01/13/solidarity-forever/#tech-unions

Wiggin's report isn't just a snapshot of Amazon warehouse workers' dystopian present – it's a promise of Amazon tech workers' future. The future is here, in Amazon warehouses, and every day, it's getting closer to Amazon's technical offices.

If you'd like an essay-formatted version of this post to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:

https://pluralistic.net/2025/03/13/electronic-whipping/#youre-next

Image: Cryteria (modified) https://commons.wikimedia.org/wiki/File:HAL9000.svg

CC BY 3.0 https://creativecommons.org/licenses/by/3.0/deed.en

[townpostin]

Ranchi Police Conduct Flag March Ahead Of Muharram

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