#master data analysis
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digital-marketing-mohan · 11 months ago
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Master Data Analysis
MY SUGGESTION : VK ACADEMY
Master Data Analysis with VK Academy's Comprehensive Courses 📊✨
In today's data-driven world, mastering data analysis isn't just a skill—it's a gateway to unlocking insights that drive business success. VK Academy stands out as a premier platform offering comprehensive courses designed to equip you with the expertise you need. Here’s why VK Academy is your ultimate destination for mastering data analysis:
Why Choose VK Academy Courses?
(I AM CURRENTLY INTERNING)
Expert-Led Learning: Learn from industry experts who bring practical insights and real-world experience into the classroom, ensuring you receive top-tier education.
Hands-On Experience: VK Academy emphasizes practical learning with hands-on projects that allow you to apply theoretical knowledge to real-world scenarios, enhancing your skills effectively.
Flexible Learning Options: Whether you're a beginner or an experienced professional, VK Academy offers courses tailored to various skill levels, allowing you to learn at your own pace and convenience.
Comprehensive Curriculum: From foundational concepts to advanced techniques in data analysis, VK Academy's courses cover everything you need to become proficient in handling data.
Career-Boosting Certifications: Upon completion of VK Academy courses, you'll receive certifications recognized by employers, validating your skills and enhancing your career prospects.
Essential Skills You'll Gain:
Data Collection and Cleaning: Master techniques for gathering and preparing data for analysis, ensuring accuracy and reliability.
Statistical Analysis: Gain proficiency in applying statistical methods to extract meaningful insights and trends from data.
Data Visualization: Learn to create compelling visualizations using tools like Tableau and Power BI to effectively communicate insights.
Predictive Analytics: Understand how to use historical data to forecast future trends and make informed predictions.
Strategic Decision-Making: Develop the ability to translate data insights into actionable strategies that drive business success.
Why Master Data Analysis?
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Empowered Decision-Making: Gain the skills to make informed decisions based on data-driven insights, reducing uncertainty and improving outcomes.
Career Advancement: Enhance your professional profile with in-demand skills in data analysis, opening doors to lucrative career opportunities.
Business Impact: Drive innovation and efficiency within organizations by leveraging data to optimize processes and strategies.
Personal Growth: Expand your knowledge and capabilities in data analysis, positioning yourself as a valuable asset in any industry.
Embark on your journey to master data analysis with VK Academy's exceptional courses. Start today and unleash the power of data! 🌟
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scholarnest · 1 year ago
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Data Analysis Online: Crafting a Learning Path for Success
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In today's data-driven world, mastering data analysis is essential for professionals across various industries. As the demand for data analysis skills continues to grow, individuals are turning to online learning platforms to acquire the knowledge and expertise needed to succeed in this field. Crafting a structured learning path is key to achieving success in data analysis online. Let's explore how to design a learning path tailored to mastering data analysis and advancing your career aspirations.
1. Assess Your Current Skill Level:
Before diving into data analysis online, it's essential to assess your current skill level and identify areas for improvement. Evaluate your proficiency in essential tools and concepts such as Python programming, SQL querying, and basic statistical analysis. Understanding your strengths and weaknesses will help you tailor your learning path to address specific skill gaps and build a solid foundation for success.
2. Identify Learning Objectives:
Define clear learning objectives to guide your data analysis journey. Whether you're aiming to become proficient in Python programming for data analysis, master SQL for database querying, or explore advanced topics like machine learning and big data analytics, setting specific goals will help you stay focused and motivated throughout your learning experience.
3. Choose High-Quality Courses:
Selecting the right courses is crucial for mastering data analysis online. Look for reputable online platforms that offer a wide range of courses covering various aspects of data analysis, including Python programming, SQL querying, and specialized topics like Apache Spark for big data analytics. Consider factors such as course content, instructor expertise, hands-on learning opportunities, and student reviews when choosing the best data analysis courses online.
4. Build a Solid Foundation:
Begin your learning journey by focusing on building a solid foundation in essential data analysis skills. Start with introductory courses that cover fundamental concepts and techniques, such as Python programming basics, SQL querying fundamentals, and data manipulation and visualization. These foundational skills will serve as the building blocks for more advanced topics and specialized areas of data analysis.
5. Dive Deeper into Specialized Topics:
Once you've established a strong foundation, explore specialized topics and advanced techniques to expand your data analysis skill set. Delve into courses that cover advanced Python programming for data analysis, advanced SQL querying and database management, and specialized tools and libraries for tasks like data visualization, machine learning, and big data processing with Apache Spark. By exploring specialized topics, you can deepen your expertise and unlock new opportunities in data analysis.
6. Practice, Practice, Practice:
Practice is essential for mastering data analysis skills. Apply what you've learned in your courses to real-world projects, datasets, and problem-solving scenarios. Engage in hands-on exercises, projects, and challenges to reinforce your learning, develop practical skills, and build a portfolio of work that showcases your expertise in data analysis.
In conclusion, crafting a learning path for success in data analysis online requires careful planning, dedication, and a commitment to continuous learning. By assessing your current skill level, setting clear learning objectives, choosing high-quality courses, building a solid foundation, exploring specialized topics, practicing regularly, and staying updated with industry trends, you can embark on a rewarding journey to master data analysis and achieve your career goals.
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inspired-lesson-plans · 10 months ago
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Due Tuesday 8/27
HW:
Reply to this post.
In your response, or in the notes, or in the tags, please include the names of 5-10 of your favorite characters, as well as 2-4+ descriptive words for each one.
Example below the cut, as well as in the notes.
(I'm doing a data analysis project and I need as much data as I can, so please help me out)
Hatake Kakashi
Smart
Caring
Forethoughtful
Troubled Backstory
Charismatic
Koro-sensei
Super-intelligent
Funny
Weird
Caring to a fault
Warm demeanor
Biscuit Krueger
Smart
Ruthless
Vain
Strong
Cold demeanor
Irina Jelavic
Seems dumb until she needs to be smart
Scene-stealing beauty
Charismatic
Butt of the joke
Troubled backstory
Genkai
Smart
Forethoughtful
Cold demeanor
Strong
Troubled backstory
Master Roshi
Wise
Lecherous
Funny
Warm demeanor
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education43 · 9 months ago
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What Are the Qualifications for a Data Scientist?
In today's data-driven world, the role of a data scientist has become one of the most coveted career paths. With businesses relying on data for decision-making, understanding customer behavior, and improving products, the demand for skilled professionals who can analyze, interpret, and extract value from data is at an all-time high. If you're wondering what qualifications are needed to become a successful data scientist, how DataCouncil can help you get there, and why a data science course in Pune is a great option, this blog has the answers.
The Key Qualifications for a Data Scientist
To succeed as a data scientist, a mix of technical skills, education, and hands-on experience is essential. Here are the core qualifications required:
1. Educational Background
A strong foundation in mathematics, statistics, or computer science is typically expected. Most data scientists hold at least a bachelor’s degree in one of these fields, with many pursuing higher education such as a master's or a Ph.D. A data science course in Pune with DataCouncil can bridge this gap, offering the academic and practical knowledge required for a strong start in the industry.
2. Proficiency in Programming Languages
Programming is at the heart of data science. You need to be comfortable with languages like Python, R, and SQL, which are widely used for data analysis, machine learning, and database management. A comprehensive data science course in Pune will teach these programming skills from scratch, ensuring you become proficient in coding for data science tasks.
3. Understanding of Machine Learning
Data scientists must have a solid grasp of machine learning techniques and algorithms such as regression, clustering, and decision trees. By enrolling in a DataCouncil course, you'll learn how to implement machine learning models to analyze data and make predictions, an essential qualification for landing a data science job.
4. Data Wrangling Skills
Raw data is often messy and unstructured, and a good data scientist needs to be adept at cleaning and processing data before it can be analyzed. DataCouncil's data science course in Pune includes practical training in tools like Pandas and Numpy for effective data wrangling, helping you develop a strong skill set in this critical area.
5. Statistical Knowledge
Statistical analysis forms the backbone of data science. Knowledge of probability, hypothesis testing, and statistical modeling allows data scientists to draw meaningful insights from data. A structured data science course in Pune offers the theoretical and practical aspects of statistics required to excel.
6. Communication and Data Visualization Skills
Being able to explain your findings in a clear and concise manner is crucial. Data scientists often need to communicate with non-technical stakeholders, making tools like Tableau, Power BI, and Matplotlib essential for creating insightful visualizations. DataCouncil’s data science course in Pune includes modules on data visualization, which can help you present data in a way that’s easy to understand.
7. Domain Knowledge
Apart from technical skills, understanding the industry you work in is a major asset. Whether it’s healthcare, finance, or e-commerce, knowing how data applies within your industry will set you apart from the competition. DataCouncil's data science course in Pune is designed to offer case studies from multiple industries, helping students gain domain-specific insights.
Why Choose DataCouncil for a Data Science Course in Pune?
If you're looking to build a successful career as a data scientist, enrolling in a data science course in Pune with DataCouncil can be your first step toward reaching your goals. Here’s why DataCouncil is the ideal choice:
Comprehensive Curriculum: The course covers everything from the basics of data science to advanced machine learning techniques.
Hands-On Projects: You'll work on real-world projects that mimic the challenges faced by data scientists in various industries.
Experienced Faculty: Learn from industry professionals who have years of experience in data science and analytics.
100% Placement Support: DataCouncil provides job assistance to help you land a data science job in Pune or anywhere else, making it a great investment in your future.
Flexible Learning Options: With both weekday and weekend batches, DataCouncil ensures that you can learn at your own pace without compromising your current commitments.
Conclusion
Becoming a data scientist requires a combination of technical expertise, analytical skills, and industry knowledge. By enrolling in a data science course in Pune with DataCouncil, you can gain all the qualifications you need to thrive in this exciting field. Whether you're a fresher looking to start your career or a professional wanting to upskill, this course will equip you with the knowledge, skills, and practical experience to succeed as a data scientist.
Explore DataCouncil’s offerings today and take the first step toward unlocking a rewarding career in data science! Looking for the best data science course in Pune? DataCouncil offers comprehensive data science classes in Pune, designed to equip you with the skills to excel in this booming field. Our data science course in Pune covers everything from data analysis to machine learning, with competitive data science course fees in Pune. We provide job-oriented programs, making us the best institute for data science in Pune with placement support. Explore online data science training in Pune and take your career to new heights!
#In today's data-driven world#the role of a data scientist has become one of the most coveted career paths. With businesses relying on data for decision-making#understanding customer behavior#and improving products#the demand for skilled professionals who can analyze#interpret#and extract value from data is at an all-time high. If you're wondering what qualifications are needed to become a successful data scientis#how DataCouncil can help you get there#and why a data science course in Pune is a great option#this blog has the answers.#The Key Qualifications for a Data Scientist#To succeed as a data scientist#a mix of technical skills#education#and hands-on experience is essential. Here are the core qualifications required:#1. Educational Background#A strong foundation in mathematics#statistics#or computer science is typically expected. Most data scientists hold at least a bachelor’s degree in one of these fields#with many pursuing higher education such as a master's or a Ph.D. A data science course in Pune with DataCouncil can bridge this gap#offering the academic and practical knowledge required for a strong start in the industry.#2. Proficiency in Programming Languages#Programming is at the heart of data science. You need to be comfortable with languages like Python#R#and SQL#which are widely used for data analysis#machine learning#and database management. A comprehensive data science course in Pune will teach these programming skills from scratch#ensuring you become proficient in coding for data science tasks.#3. Understanding of Machine Learning
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cappurrccino · 1 year ago
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looking at a blank excel sheet and a stack of 4 years of course evals like "where do I even start here"
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academiceurope · 4 months ago
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Job - Alert 📢
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🌟 Kickstart Your Career with Us! 🌟
The Leibniz-Institut für Analytische Wissenschaften – ISAS – e.V. is inviting applications for a Masters Intern (m/f/d) in Machine Learning and Bioimage Analysis in our Dortmund team!
📅 Application Deadline: March 31, 2025
💼 Opportunity to work on cutting-edge bioimage analysis projects!
If you're enrolled in a Master's program in computer science, statistics, or related fields, and have a passion for data analysis, we want to hear from you!
📲 Apply through our applicant portal or reach out with informal inquiries (Ref: 344_2025) at
https://www.academiceurope.com/job/?id=7080
Join us in advancing precision medicine! 🙌
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scholarnest · 1 year ago
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SQL Course Training: Advancing Your Database Skills
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In the realm of data analysis and management, SQL (Structured Query Language) stands as a foundational skill indispensable for professionals seeking to navigate and manipulate databases effectively. As the demand for data-driven insights continues to soar, honing your SQL proficiency through targeted training can significantly enhance your capabilities in data analysis and open doors to diverse career opportunities. Let's explore the significance of SQL course training and how it can advance your database skills.
Understanding the Importance of SQL in Data Analysis:
SQL serves as the universal language for communicating with relational databases, enabling users to retrieve, manipulate, and manage data efficiently. Whether you're a data analyst, data scientist, or database administrator, mastering SQL empowers you to extract valuable insights, perform complex queries, and optimize database performance. With its widespread adoption across industries, SQL proficiency has become a prerequisite for roles involving data analysis and database management.
Key Components of SQL Course Training:
SQL course training encompasses a range of topics tailored to equip learners with comprehensive database management skills. From basic SQL syntax to advanced query optimization techniques, these courses cover essential concepts and best practices for leveraging SQL effectively. Key components of SQL course training include:
- SQL Fundamentals: Understanding basic SQL commands, data types, and database objects.
- Querying Databases: Crafting SELECT statements to retrieve data from tables and apply filtering, sorting, and aggregation.
- Data Manipulation: Performing INSERT, UPDATE, DELETE operations to modify data within tables.
- Database Design: Understanding principles of database normalization, table relationships, and entity-relationship modeling.
- Advanced SQL Topics: Exploring advanced SQL features such as joins, subqueries, stored procedures, and triggers.
- Optimization and Performance Tuning: Techniques for optimizing SQL queries, indexing strategies, and enhancing database performance.
Choosing the Best SQL Course:
When selecting a SQL course online, it's essential to consider factors such as:
- Curriculum: Ensure the course covers a comprehensive range of SQL topics, from fundamentals to advanced concepts.
- Hands-On Practice: Look for courses that offer hands-on exercises and projects to reinforce learning and practical application.
- Instructor Expertise: Choose courses led by experienced SQL professionals with a track record of delivering high-quality instruction.
- Student Reviews: Assess feedback from past learners to gauge the course's effectiveness and relevance to your learning goals.
- Certification: Some SQL courses offer certification upon completion, which can validate your skills and enhance your credentials in the job market.
Integrating SQL with Data Analysis:
SQL proficiency synergizes seamlessly with data analysis tasks, enabling analysts to extract, transform, and analyze data stored in relational databases. Whether you're performing ad-hoc analysis, generating reports, or building data pipelines, SQL serves as a powerful tool for accessing and manipulating data effectively. By mastering SQL alongside data analysis skills and tools such as Python and Apache Spark, you can enhance your capabilities as a data professional and tackle complex analytical challenges with confidence.
Conclusion:
Investing in SQL course training is a strategic step towards mastering database management skills and advancing your career in data analysis. Whether you're a novice seeking to build a solid foundation in SQL or an experienced professional aiming to sharpen your expertise, there are ample opportunities to enhance your database skills through online SQL courses. By selecting the best SQL course that aligns with your learning objectives and investing time and effort into mastering SQL concepts, you can unlock new possibilities in data analysis and become a proficient database practitioner poised for success in today's data-driven world.
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productiveandfree · 8 months ago
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Exploring Career Opportunities with a Master’s in Mathematics
When people think about math, they often picture endless equations or complex formulas. But if you’ve always had a knack for numbers, you probably know that math goes far beyond that. Mathematics is everywhere, touching industries like finance, technology, education, and even health care.
If you’re someone with a love for numbers and problem-solving, pursuing a master’s degree in mathematics could be the gateway to a wide range of exciting and fulfilling careers.
Why Pursue a Master’s in Mathematics?
So, why should you consider a master’s in mathematics? The answer lies in its versatility. A master’s degree in math doesn’t limit you to just one path. In fact, it equips you with a toolkit of skills that can be applied in almost any industry. Whether you’re interested in finance, data analysis, teaching, or even government work, advanced mathematical knowledge can get you there.
The good news is that you don’t have to disrupt your life to earn this degree. Many people are now opting for a math masters degree online, which offers flexibility to balance work, life, and education. These programs offer the same valuable specializations as traditional ones—such as applied mathematics, statistics, and computational math—so you can focus your studies on the areas that align with your career goals.
Career Paths in Finance and Data Analysis
One of the most popular routes for those with a master’s in mathematics is in the finance and data analysis sectors. These industries rely heavily on professionals who are not only comfortable with numbers but who can interpret and predict trends from large data sets. With the growing importance of data-driven decision-making in business, there’s a rising demand for people who can understand the underlying mathematics behind financial models and risk assessments.
Some specific roles in finance for math graduates include becoming an actuary, quantitative analyst, or financial analyst. Actuaries, for example, use their mathematical skills to assess risks and help companies make informed financial decisions. Quantitative analysts, often known as “quants,” build mathematical models to predict market behavior, guiding investments and trading strategies.
Careers in Technology and Computer Science
Math and technology are a natural fit. If you’re passionate about technology, a master’s in mathematics can open doors to a wide range of opportunities in fields like artificial intelligence (AI), cryptography, and algorithm design. These fields require a strong foundation in mathematical theory and problem-solving, making math graduates highly valuable in the tech world.
For instance, in AI and machine learning, the underlying principles are all rooted in mathematics. As companies invest more in AI technologies, they need professionals who can build models that simulate human intelligence and improve over time. Math graduates are also sought after in cybersecurity, particularly in cryptography, where they design and break complex encryption systems to protect sensitive information.
Opportunities in Education and Research
Another rewarding career path for those with a master’s in mathematics is education. With a graduate degree, you can pursue teaching positions at the college level, whether at community colleges or universities. Many institutions look for instructors who can teach higher-level courses in math, and with a master’s, you’ll be qualified to do just that.
If you’re passionate about math but not necessarily interested in teaching, research could be a perfect fit. A master’s degree opens doors to research positions in academic settings or private companies. In research, you could focus on theoretical mathematics or applied areas like physics, biology, or economics, contributing to advancements in your field.
Government and Public Sector Roles
A master’s in mathematics can also lead to a variety of roles in the public sector. Government agencies need individuals with strong mathematical backgrounds for operations research, logistics planning, and statistical analysis. For example, operations research analysts use math to help organizations run more efficiently, whether that’s optimizing supply chains, allocating resources, or planning logistics.
Mathematicians in the public sector may also work in areas like national security, using mathematical models to predict and counter potential threats, or in environmental policy, where data analysis is crucial to understanding climate patterns and proposing solutions.
The Growing Importance of Interdisciplinary Roles
Finally, an exciting aspect of having a master’s in mathematics is the increasing opportunity to work in interdisciplinary roles. Many industries, such as biology, economics, and social sciences, rely on mathematical modeling to solve complex problems. With your degree, you could be working alongside professionals in these fields, using your math skills to contribute to solutions that impact the real world.
For example, biostatistics, an interdisciplinary field combining biology and statistics, has grown in importance, especially in areas like medical research and public health. Similarly, economists rely on mathematical models to analyze market trends and make predictions about future behavior, providing valuable insights that shape economic policy.
In conclusion, pursuing a master’s in mathematics can open up an incredible range of career opportunities. From finance and technology to education, research, and even government, the demand for skilled mathematicians is strong and growing.
Whether you’re looking to work in cutting-edge tech fields, help businesses make data-driven decisions, or contribute to advancements in research and education, a master’s degree in mathematics provides the foundation to make that happen.
Share in the comments below: Questions go here
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aamerajj · 10 months ago
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Advanced Business Data Analytics Tools, Software, Services
Data analytics tools provide real-time performance insights. PiLog analytics transforms raw data into actionable insights, driving performance optimization
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saad1505 · 1 year ago
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Advanced Business Data Analytics Tools, Software, Services 
Data analytics tools provide real-time performance insights. PiLog analytics transforms raw data into actionable insights, driving performance optimization. https://www.piloggroup.com/data-analytics.php 
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garymdm · 1 year ago
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Data Quality Management: It's About Prevention
Dirty data can lead to costly mistakes, missed opportunities, and frustrated users. That’s where Data Quality Management (DQM) steps in. But here’s the shocker: many DQM efforts fall short of their core objective – preventing data quality issues from happening again. The 1:10:100 Rule: The Manual MazeMonitoring Without Action is MeaninglessShifting the Focus to PreventionConclusion Imagine…
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dissertations-posts · 1 year ago
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DissertationWritingHelper is one of the focused agencies that is committed to quality. We specially value client concern about the project that they face in their PhD and Master’s degree. We also know the importance of ongoing job of the client have to maintain during their course program. Our teams of experts are focused on maintaining the confidentiality.
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64-squares-llc · 2 years ago
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technicalfika · 2 years ago
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Is my job safe against AI? ChatGPT vs Scrum Master & Agile Coach
In an era defined by rapid technological advancements, the roles of Scrum Masters and Agile Coaches are not immune to the impact of artificial intelligence (AI). As organizations strive to optimize their processes and embrace agile methodologies, it’s natural to wonder if these roles are at risk. However, a closer look reveals that Scrum Masters and Agile Coaches possess unique qualities that are…
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crystlianajohn · 2 years ago
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What are the steps of social media analytics?
Explore the essential steps of social media analytics to harness valuable insights and optimize your online presence.
www.quickmetrix.com
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mostlysignssomeportents · 10 months ago
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“Disenshittify or Die”
youtube
I'm coming to BURNING MAN! On TUESDAY (Aug 27) at 1PM, I'm giving a talk called "DISENSHITTIFY OR DIE!" at PALENQUE NORTE (7&E). On WEDNESDAY (Aug 28) at NOON, I'm doing a "Talking Caterpillar" Q&A at LIMINAL LABS (830&C).
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Last weekend, I traveled to Las Vegas for Defcon 32, where I had the immense privilege of giving a solo talk on Track 1, entitled "Disenshittify or die! How hackers can seize the means of computation and build a new, good internet that is hardened against our asshole bosses' insatiable horniness for enshittification":
https://info.defcon.org/event/?id=54861
This was a followup to last year's talk, "An Audacious Plan to Halt the Internet's Enshittification," a talk that kicked off a lot of international interest in my analysis of platform decay ("enshittification"):
https://www.youtube.com/watch?v=rimtaSgGz_4
The Defcon organizers have earned a restful week or two, and that means that the video of my talk hasn't yet been posted to Defcon's Youtube channel, so in the meantime, I thought I'd post a lightly edited version of my speech crib. If you're headed to Burning Man, you can hear me reprise this talk at Palenque Norte (7&E); I'm kicking off their lecture series on Tuesday, Aug 27 at 1PM.
==
What the fuck happened to the old, good internet?
I mean, sure, our bosses were a little surveillance-happy, and they were usually up for sharing their data with the NSA, and whenever there was a tossup between user security and growth, it was always YOLO time.
But Google Search used to work. Facebook used to show you posts from people you followed. Uber used to be cheaper than a taxi and pay the driver more than a cabbie made. Amazon used to sell products, not Shein-grade self-destructing dropshipped garbage from all-consonant brands. Apple used to defend your privacy, rather than spying on you with your no-modifications-allowed Iphone.
There was a time when you searching for an album on Spotify would get you that album – not a playlist of insipid AI-generated covers with the same name and art.
Microsoft used to sell you software – sure, it was buggy – but now they just let you access apps in the cloud, so they can watch how you use those apps and strip the features you use the most out of the basic tier and turn them into an upcharge.
What – and I cannot stress this enough – the fuck happened?!
I’m talking about enshittification.
Here’s what enshittification looks like from the outside: First, you see a company that’s being good to its end users. Google puts the best search results at the top; Facebook shows you a feed of posts from people and groups you followl; Uber charges small dollars for a cab; Amazon subsidizes goods and returns and shipping and puts the best match for your product search at the top of the page.
That’s stage one, being good to end users. But there’s another part of this stage, call it stage 1a). That’s figuring out how to lock in those users.
There’s so many ways to lock in users.
If you’re Facebook, the users do it for you. You joined Facebook because there were people there you wanted to hang out with, and other people joined Facebook to hang out with you.
That’s the old “network effects” in action, and with network effects come “the collective action problem." Because you love your friends, but goddamn are they a pain in the ass! You all agree that FB sucks, sure, but can you all agree on when it’s time to leave?
No way.
Can you agree on where to go next?
Hell no.
You’re there because that’s where the support group for your rare disease hangs out, and your bestie is there because that’s where they talk with the people in the country they moved away from, then there’s that friend who coordinates their kid’s little league car pools on FB, and the best dungeon master you know isn’t gonna leave FB because that’s where her customers are.
So you’re stuck, because even though FB use comes at a high cost – your privacy, your dignity and your sanity – that’s still less than the switching cost you’d have to bear if you left: namely, all those friends who have taken you hostage, and whom you are holding hostage
Now, sometimes companies lock you in with money, like Amazon getting you to prepay for a year’s shipping with Prime, or to buy your Audible books on a monthly subscription, which virtually guarantees that every shopping search will start on Amazon, after all, you’ve already paid for it.
Sometimes, they lock you in with DRM, like HP selling you a printer with four ink cartridges filled with fluid that retails for more than $10,000/gallon, and using DRM to stop you from refilling any of those ink carts or using a third-party cartridge. So when one cart runs dry, you have to refill it or throw away your investment in the remaining three cartridges and the printer itself.
Sometimes, it’s a grab bag:
You can’t run your Ios apps without Apple hardware;
you can’t run your Apple music, books and movies on anything except an Ios app;
your iPhone uses parts pairing – DRM handshakes between replacement parts and the main system – so you can’t use third-party parts to fix it; and
every OEM iPhone part has a microscopic Apple logo engraved on it, so Apple can demand that the US Customs and Border Service seize any shipment of refurb Iphone parts as trademark violations.
Think Different, amirite?
Getting you locked in completes phase one of the enshittification cycle and signals the start of phase two: making things worse for you to make things better for business customers.
For example, a platform might poison its search results, like Google selling more and more of its results pages to ads that are identified with lighter and lighter tinier and tinier type.
Or Amazon selling off search results and calling it an “ad” business. They make $38b/year on this scam. The first result for your search is, on average, 29% more expensive than the best match for your search. The first row is 25% more expensive than the best match. On average, the best match for your search is likely to be found seventeen places down on the results page.
Other platforms sell off your feed, like Facebook, which started off showing you the things you asked to see, but now the quantum of content from the people you follow has dwindled to a homeopathic residue, leaving a void that Facebook fills with things that people pay to show you: boosted posts from publishers you haven’t subscribed to, and, of course, ads.
Now at this point you might be thinking ‘sure, if you’re not paying for the product, you’re the product.'
Bullshit!
Bull.
Shit.
The people who buy those Google ads? They pay more every year for worse ad-targeting and more ad-fraud
Those publishers paying to nonconsensually cram their content into your Facebook feed? They have to do that because FB suppresses their ability to reach the people who actually subscribed to them
The Amazon sellers with the best match for your query have to outbid everyone else just to show up on the first page of results. It costs so much to sell on Amazon that between 45-51% of every dollar an independent seller brings in has to be kicked up to Don Bezos and the Amazon crime family. Those sellers don’t have the kind of margins that let them pay 51% They have to raise prices in order to avoid losing money on every sale.
"But wait!" I hear you say!
[Come on, say it!]
"But wait! Things on Amazon aren’t more expensive that things at Target, or Walmart, or at a mom and pop store, or direct from the manufacturer.
"How can sellers be raising prices on Amazon if the price at Amazon is the same as at is everywhere else?"
[Any guesses?!]
That’s right, they charge more everywhere. They have to. Amazon binds its sellers to a policy called “most favored nation status,” which says they can’t charge more on Amazon than they charge elsewhere, including direct from their own factory store.
So every seller that wants to sell on Amazon has to raise their prices everywhere else.
Now, these sellers are Amazon’s best customers. They’re paying for the product, and they’re still getting screwed.
Paying for the product doesn’t fill your vapid boss’s shriveled heart with so much joy that he decides to stop trying to think of ways to fuck you over.
Look at Apple. Remember when Apple offered every Ios user a one-click opt out for app-based surveillance? And 96% of users clicked that box?
(The other four percent were either drunk or Facebook employees or drunk Facebook employees.)
That cost Facebook at least ten billion dollars per year in lost surveillance revenue?
I mean, you love to see it.
But did you know that at the same time Apple started spying on Ios users in the same way that Facebook had been, for surveillance data to use to target users for its competing advertising product?
Your Iphone isn’t an ad-supported gimme. You paid a thousand fucking dollars for that distraction rectangle in your pocket, and you’re still the product. What’s more, Apple has rigged Ios so that you can’t mod the OS to block its spying.
If you’re not not paying for the product, you’re the product, and if you are paying for the product, you’re still the product.
Just ask the farmers who are expected to swap parts into their own busted half-million dollar, mission-critical tractors, but can’t actually use those parts until a technician charges them $200 to drive out to the farm and type a parts pairing unlock code into their console.
John Deere’s not giving away tractors. Give John Deere a half mil for a tractor and you will be the product.
Please, my brothers and sisters in Christ. Please! Stop saying ‘if you’re not paying for the product, you’re the product.’
OK, OK, so that’s phase two of enshittification.
Phase one: be good to users while locking them in.
Phase two: screw the users a little to you can good to business customers while locking them in.
Phase three: screw everybody and take all the value for yourself. Leave behind the absolute bare minimum of utility so that everyone stays locked into your pile of shit.
Enshittification: a tragedy in three acts.
That’s what enshittification looks like from the outside, but what’s going on inside the company? What is the pathological mechanism? What sci-fi entropy ray converts the excellent and useful service into a pile of shit?
That mechanism is called twiddling. Twiddling is when someone alters the back end of a service to change how its business operates, changing prices, costs, search ranking, recommendation criteria and other foundational aspects of the system.
Digital platforms are a twiddler’s utopia. A grocer would need an army of teenagers with pricing guns on rollerblades to reprice everything in the building when someone arrives who’s extra hungry.
Whereas the McDonald’s Investments portfolio company Plexure advertises that it can use surveillance data to predict when an app user has just gotten paid so the seller can tack an extra couple bucks onto the price of their breakfast sandwich.
And of course, as the prophet William Gibson warned us, ‘cyberspace is everting.' With digital shelf tags, grocers can change prices whenever they feel like, like the grocers in Norway, whose e-ink shelf tags change the prices 2,000 times per day.
Every Uber driver is offered a different wage for every job. If a driver has been picky lately, the job pays more. But if the driver has been desperate enough to grab every ride the app offers, the pay goes down, and down, and down.
The law professor Veena Dubal calls this ‘algorithmic wage discrimination.' It’s a prime example of twiddling.
Every youtuber knows what it’s like to be twiddled. You work for weeks or months, spend thousands of dollars to make a video, then the algorithm decides that no one – not your own subscribers, not searchers who type in the exact name of your video – will see it.
Why? Who knows? The algorithm’s rules are not public.
Because content moderation is the last redoubt of security through obscurit: they can’t tell you what the como algorithm is downranking because then you’d cheat.
Youtube is the kind of shitty boss who docks every paycheck for all the rules you’ve broken, but won’t tell you what those rules were, lest you figure out how to break those rules next time without your boss catching you.
Twiddling can also work in some users’ favor, of course. Sometimes platforms twiddle to make things better for end users or business customers.
For example, Emily Baker-White from Forbes revealed the existence of a back-end feature that Tiktok’s management can access they call the “heating tool.”
When a manager applies the heating toll to a performer’s account, that performer’s videos are thrust into the feeds of millions of users, without regard to whether the recommendation algorithm predicts they will enjoy that video.
Why would they do this? Well, here’s an analogy from my boyhood I used to go to this traveling fair that would come to Toronto at the end of every summer, the Canadian National Exhibition. If you’ve been to a fair like the Ex, you know that you can always spot some guy lugging around a comedically huge teddy bear.
Nominally, you win that teddy bear by throwing five balls in a peach-basket, but to a first approximation, no one has ever gotten five balls to stay in that peach-basket.
That guy “won” the teddy bear when a carny on the midway singled him out and said, "fella, I like your face. Tell you what I’m gonna do: You get just one ball in the basket and I’ll give you this keychain, and if you amass two keychains, I’ll let you trade them in for one of these galactic-scale teddy-bears."
That’s how the guy got his teddy bear, which he now has to drag up and down the midway for the rest of the day.
Why the hell did that carny give away the teddy bear? Because it turns the guy into a walking billboard for the midway games. If that dopey-looking Judas Goat can get five balls into a peach basket, then so can you.
Except you can’t.
Tiktok’s heating tool is a way to give away tactical giant teddy bears. When someone in the TikTok brain trust decides they need more sports bros on the platform, they pick one bro out at random and make him king for the day, heating the shit out of his account.
That guy gets a bazillion views and he starts running around on all the sports bro forums trumpeting his success: *I am the Louis Pasteur of sports bro influencers!"
The other sports bros pile in and start retooling to make content that conforms to the idiosyncratic Tiktok format. When they fail to get giant teddy bears of their own, they assume that it’s because they’re doing Tiktok wrong, because they don’t know about the heating tool.
But then comes the day when the TikTok Star Chamber decides they need to lure in more astrologers, so they take the heat off that one lucky sports bro, and start heating up some lucky astrologer.
Giant teddy bears are all over the place: those Uber drivers who were boasting to the NYT ten years ago about earning $50/hour? The Substackers who were rolling in dough? Joe Rogan and his hundred million dollar Spotify payout? Those people are all the proud owners of giant teddy bears, and they’re a steal.
Because every dollar they get from the platform turns into five dollars worth of free labor from suckers who think they just internetting wrong.
Giant teddy bears are just one way of twiddling. Platforms can play games with every part of their business logic, in highly automated ways, that allows them to quickly and efficiently siphon value from end users to business customers and back again, hiding the pea in a shell game conducted at machine speeds, until they’ve got everyone so turned around that they take all the value for themselves.
That’s the how: How the platforms do the trick where they are good to users, then lock users in, then maltreat users to be good to business customers, then lock in those business customers, then take all the value for themselves.
So now we know what is happening, and how it is happening, all that’s left is why it’s happening.
Now, on the one hand, the why is pretty obvious. The less value that end-users and business customers capture, the more value there is left to divide up among the shareholders and the executives.
That’s why, but it doesn’t tell you why now. Companies could have done this shit at any time in the past 20 years, but they didn’t. Or at least, the successful ones didn’t. The ones that turned themselves into piles of shit got treated like piles of shit. We avoided them and they died.
Remember Myspace? Yahoo Search? Livejournal? Sure, they’re still serving some kind of AI slop or programmatic ad junk if you hit those domains, but they’re gone.
And there’s the clue: It used to be that if you enshittified your product, bad things happened to your company. Now, there are no consequences for enshittification, so everyone’s doing it.
Let’s break that down: What stops a company from enshittifying?
There are four forces that discipline tech companies. The first one is, obviously, competition.
If your customers find it easy to leave, then you have to worry about them leaving
Many factors can contribute to how hard or easy it is to depart a platform, like the network effects that Facebook has going for it. But the most important factor is whether there is anywhere to go.
Back in 2012, Facebook bought Insta for a billion dollars. That may seem like chump-change in these days of eleven-digit Big Tech acquisitions, but that was a big sum in those innocent days, and it was an especially big sum to pay for Insta. The company only had 13 employees, and a mere 25 million registered users.
But what mattered to Zuckerberg wasn’t how many users Insta had, it was where those users came from.
[Does anyone know where those Insta users came from?]
That’s right, they left Facebook and joined Insta. They were sick of FB, even though they liked the people there, they hated creepy Zuck, they hated the platform, so they left and they didn’t come back.
So Zuck spent a cool billion to recapture them, A fact he put in writing in a midnight email to CFO David Ebersman, explaining that he was paying over the odds for Insta because his users hated him, and loved Insta. So even if they quit Facebook (the platform), they would still be captured Facebook (the company).
Now, on paper, Zuck’s Instagram acquisition is illegal, but normally, that would be hard to stop, because you’d have to prove that he bought Insta with the intention of curtailing competition.
But in this case, Zuck tripped over his own dick: he put it in writing.
But Obama’s DoJ and FTC just let that one slide, following the pro-monopoly policies of Reagan, Bush I, Clinton and Bush II, and setting an example that Trump would follow, greenlighting gigamergers like the catastrophic, incestuous Warner-Discovery marriage.
Indeed, for 40 years, starting with Carter, and accelerating through Reagan, the US has encouraged monopoly formation, as an official policy, on the grounds that monopolies are “efficient.”
If everyone is using Google Search, that’s something we should celebrate. It means they’ve got the very best search and wouldn’t it be perverse to spend public funds to punish them for making the best product?
But as we all know, Google didn’t maintain search dominance by being best. They did it by paying bribes. More than 20 billion per year to Apple alone to be the default Ios search, plus billions more to Samsung, Mozilla, and anyone else making a product or service with a search-box on it, ensuring that you never stumble on a search engine that’s better than theirs.
Which, in turn, ensured that no one smart invested big in rival search engines, even if they were visibly, obviously superior. Why bother making something better if Google’s buying up all the market oxygen before it can kindle your product to life?
Facebook, Google, Microsoft, Amazon – they’re not “making things” companies, they’re “buying things” companies, taking advantage of official tolerance for anticompetitive acquisitions, predatory pricing, market distorting exclusivity deals and other acts specifically prohibited by existing antitrust law.
Their goal is to become too big to fail, because that makes them too big to jail, and that means they can be too big to care.
Which is why Google Search is a pile of shit and everything on Amazon is dropshipped garbage that instantly disintegrates in a cloud of offgassed volatile organic compounds when you open the box.
Once companies no longer fear losing your business to a competitor, it’s much easier for them to treat you badly, because what’re you gonna do?
Remember Lily Tomlin as Ernestine the AT&T operator in those old SNL sketches? “We don’t care. We don’t have to. We’re the phone company.”
Competition is the first force that serves to discipline companies and the enshittificatory impulses of their leadership, and we just stopped enforcing competition law.
It takes a special kind of smooth-brained asshole – that is, an establishment economist – to insist that the collapse of every industry from eyeglasses to vitamin C into a cartel of five or fewer companies has nothing to do with policies that officially encouraged monopolization.
It’s like we used to put down rat poison and we didn’t have a rat problem. Then these dickheads convinced us that rats were good for us and we stopped putting down rat poison, and now rats are gnawing our faces off and they’re all running around saying, "Who’s to say where all these rats came from? Maybe it was that we stopped putting down poison, but maybe it’s just the Time of the Rats. The Great Forces of History bearing down on this moment to multiply rats beyond all measure!"
Antitrust didn’t slip down that staircase and fall spine-first on that stiletto: they stabbed it in the back and then they pushed it.
And when they killed antitrust, they also killed regulation, the second force that disciplines companies. Regulation is possible, but only when the regulator is more powerful than the regulated entities. When a company is bigger than the government, it gets damned hard to credibly threaten to punish that company, no matter what its sins.
That’s what protected IBM for all those years when it had its boot on the throat of the American tech sector. Do you know, the DOJ fought to break up IBM in the courts from 1970-1982, and that every year, for 12 consecutive years, IBM spent more on lawyers to fight the USG than the DOJ Antitrust Division spent on all the lawyers fighting every antitrust case in the entire USA?
IBM outspent Uncle Sam for 12 years. People called it “Antitrust’s Vietnam.” All that money paid off, because by 1982, the president was Ronald Reagan, a man whose official policy was that monopolies were “efficient." So he dropped the case, and Big Blue wriggled off the hook.
It’s hard to regulate a monopolist, and it’s hard to regulate a cartel. When a sector is composed of hundreds of competing companies, they compete. They genuinely fight with one another, trying to poach each others’ customers and workers. They are at each others’ throats.
It’s hard enough for a couple hundred executives to agree on anything. But when they’re legitimately competing with one another, really obsessing about how to eat each others’ lunches, they can’t agree on anything.
The instant one of them goes to their regulator with some bullshit story, about how it’s impossible to have a decent search engine without fine-grained commercial surveillance; or how it’s impossible to have a secure and easy to use mobile device without a total veto over which software can run on it; or how it’s impossible to administer an ISP’s network unless you can slow down connections to servers whose owners aren’t paying bribes for “premium carriage"; there’s some *other company saying, “That’s bullshit”
“We’ve managed it! Here’s our server logs, our quarterly financials and our customer testimonials to prove it.”
100 companies are a rabble, they're a mob. They can’t agree on a lobbying position. They’re too busy eating each others’ lunch to agree on how to cater a meeting to discuss it.
But let those hundred companies merge to monopoly, absorb one another in an incestuous orgy, turn into five giant companies, so inbred they’ve got a corporate Habsburg jaw, and they become a cartel.
It’s easy for a cartel to agree on what bullshit they’re all going to feed their regulator, and to mobilize some of the excess billions they’ve reaped through consolidation, which freed them from “wasteful competition," sp they can capture their regulators completely.
You know, Congress used to pass federal consumer privacy laws? Not anymore.
The last time Congress managed to pass a federal consumer privacy law was in 1988: The Video Privacy Protection Act. That’s a law that bans video-store clerks from telling newspapers what VHS cassettes you take home. In other words, it regulates three things that have effectively ceased to exist.
The threat of having your video rental history out there in the public eye was not the last or most urgent threat the American public faced, and yet, Congress is deadlocked on passing a privacy law.
Tech companies’ regulatory capture involves a risible and transparent gambit, that is so stupid, it’s an insult to all the good hardworking risible transparent ruses out there.
Namely, they claim that when they violate your consumer, privacy or labor rights, It’s not a crime, because they do it with an app.
Algorithmic wage discrimination isn’t illegal wage theft: we do it with an app.
Spying on you from asshole to appetite isn’t a privacy violation: we do it with an app.
And Amazon’s scam search tool that tricks you into paying 29% more than the best match for your query? Not a ripoff. We do it with an app.
Once we killed competition – stopped putting down rat poison – we got cartels – the rats ate our faces. And the cartels captured their regulators – the rats bought out the poison factory and shut it down.
So companies aren’t constrained by competition or regulation.
But you know what? This is tech, and tech is different.IIt’s different because it’s flexible. Because our computers are Turing-complete universal von Neumann machines. That means that any enshittificatory alteration to a program can be disenshittified with another program.
Every time HP jacks up the price of ink , they invite a competitor to market a refill kit or a compatible cartridge.
When Tesla installs code that says you have to pay an extra monthly fee to use your whole battery, they invite a modder to start selling a kit to jailbreak that battery and charge it all the way up.
Lemme take you through a little example of how that works: Imagine this is a product design meeting for our company’s website, and the guy leading the meeting says “Dudes, you know how our KPI is topline ad-revenue? Well, I’ve calculated that if we make the ads just 20% more invasive and obnoxious, we’ll boost ad rev by 2%”
This is a good pitch. Hit that KPI and everyone gets a fat bonus. We can all take our families on a luxury ski vacation in Switzerland.
But here’s the thing: someone’s gonna stick their arm up – someone who doesn’t give a shit about user well-being, and that person is gonna say, “I love how you think, Elon. But has it occurred to you that if we make the ads 20% more obnoxious, then 40% of our users will go to a search engine and type 'How do I block ads?'"
I mean, what a nightmare! Because once a user does that, the revenue from that user doesn’t rise to 102%. It doesn’t stay at 100% It falls to zero, forever.
[Any guesses why?]
Because no user ever went back to the search engine and typed, 'How do I start seeing ads again?'
Once the user jailbreaks their phone or discovers third party ink, or develops a relationship with an independent Tesla mechanic who’ll unlock all the DLC in their car, that user is gone, forever.
Interoperability – that latent property bequeathed to us courtesy of Herrs Turing and Von Neumann and their infinitely flexible, universal machines – that is a serious check on enshittification.
The fact that Congress hasn’t passed a privacy law since 1988 Is countered, at least in part, by the fact that the majority of web users are now running ad-blockers, which are also tracker-blockers.
But no one’s ever installed a tracker-blocker for an app. Because reverse engineering an app puts in you jeopardy of criminal and civil prosecution under Section 1201 of the Digital Millennium Copyright Act, with penalties of a 5-year prison sentence and a $500k fine for a first offense.
And violating its terms of service puts you in jeopardy under the Computer Fraud and Abuse Act of 1986, which is the law that Ronald Reagan signed in a panic after watching Wargames (seriously!).
Helping other users violate the terms of service can get you hit with a lawsuit for tortious interference with contract. And then there’s trademark, copyright and patent.
All that nonsense we call “IP,” but which Jay Freeman of Cydia calls “Felony Contempt of Business Model."
So if we’re still at that product planning meeting and now it’s time to talk about our app, the guy leading the meeting says, “OK, so we’ll make the ads in the app 20% more obnoxious to pull a 2% increase in topline ad rev?”
And that person who objected to making the website 20% worse? Their hand goes back up. Only this time they say “Why don’t we make the ads 100% more invasive and get a 10% increase in ad rev?"
Because it doesn't matter if a user goes to a search engine and types, “How do I block ads in an app." The answer is: you can't. So YOLO, enshittify away.
“IP” is just a euphemism for “any law that lets me reach outside my company’s walls to exert coercive control over my critics, competitors and customers,” and “app” is just a euphemism for “A web page skinned with the right IP so that protecting your privacy while you use it is a felony.”
Interop used to keep companies from enshittifying. If a company made its client suck, someone would roll out an alternative client, if they ripped a feature out and wanted to sell it back to you as a monthly subscription, someone would make a compatible plugin that restored it for a one-time fee, or for free.
To help people flee Myspace, FB gave them bots that you’d load with your login credentials. It would scrape your waiting Myspace messages and put ‘em in your FB inbox, and login to Myspace and paste your replies into your Myspace outbox. So you didn’t have to choose between the people you loved on Myspace, and Facebook, which launched with a promise never to spy on you. Remember that?!
Thanks to the metastasis of IP, all that is off the table today. Apple owes its very existence to iWork Suite, whose Pages, Numbers and Keynote are file-compatible with Microsoft’s Word, Excel and Powerpoint. But make an IOS runtime that’ll play back the files you bought from Apple’s stores on other platforms, and they’ll nuke you til you glow.
FB wouldn’t have had a hope of breaking Myspace’s grip on social media without that scrape, but scrape FB today in support of an alternative client and their lawyers will bomb you til the rubble bounces.
Google scraped every website in the world to create its search index. Try and scrape Google and they’ll have your head on a pike.
When they did it, it was progress. When you do it to them, that’s piracy. Every pirate wants to be an admiral.
Because this handful of companies has so thoroughly captured their regulators, they can wield the power of the state against you when you try to break their grip on power, even as their own flagrant violations of our rights go unpunished. Because they do them with an app.
Tech lost its fear of competitin it neutralized the threat from regulators, and then put them in harness to attack new startups that might do unto them as they did unto the companies that came before them.
But even so, there was a force that kept our bosses in check That force was us. Tech workers.
Tech workers have historically been in short supply, which gave us power, and our bosses knew it.
To get us to work crazy hours, they came up with a trick. They appealed to our love of technology, and told us that we were heroes of a digital revolution, who would “organize the world’s information and make it useful,” who would “bring the world closer together.”
They brought in expert set-dressers to turn our workplaces into whimsical campuses with free laundry, gourmet cafeterias, massages, and kombucha, and a surgeon on hand to freeze our eggs so that we could work through our fertile years.
They convinced us that we were being pampered, rather than being worked like government mules.
This trick has a name. Fobazi Ettarh, the librarian-theorist, calls it “vocational awe, and Elon Musk calls it being “extremely hardcore.”
This worked very well. Boy did we put in some long-ass hours!
But for our bosses, this trick failed badly. Because if you miss your mother’s funeral and to hit a deadline, and then your boss orders you to enshittify that product, you are gonna experience a profound moral injury, which you are absolutely gonna make your boss share.
Because what are they gonna do? Fire you? They can’t hire someone else to do your job, and you can get a job that’s even better at the shop across the street.
So workers held the line when competition, regulation and interop failed.
But eventually, supply caught up with demand. Tech laid off 260,000 of us last year, and another 100,000 in the first half of this year.
You can’t tell your bosses to go fuck themselves, because they’ll fire your ass and give your job to someone who’ll be only too happy to enshittify that product you built.
That’s why this is all happening right now. Our bosses aren’t different. They didn’t catch a mind-virus that turned them into greedy assholes who don’t care about our users’ wellbeing or the quality of our products.
As far as our bosses have always been concerned, the point of the business was to charge the most, and deliver the least, while sharing as little as possible with suppliers, workers, users and customers. They’re not running charities.
Since day one, our bosses have shown up for work and yanked as hard as they can on the big ENSHITTIFICATION lever behind their desks, only that lever didn’t move much. It was all gummed up by competition, regulation, interop and workers.
As those sources of friction melted away, the enshittification lever started moving very freely.
Which sucks, I know. But think about this for a sec: our bosses, despite being wildly imperfect vessels capable of rationalizing endless greed and cheating, nevertheless oversaw a series of actually great products and services.
Not because they used to be better people, but because they used to be subjected to discipline.
So it follows that if we want to end the enshittocene, dismantle the enshitternet, and build a new, good internet that our bosses can’t wreck, we need to make sure that these constraints are durably installed on that internet, wound around its very roots and nerves. And we have to stand guard over it so that it can’t be dismantled again.
A new, good internet is one that has the positive aspects of the old, good internet: an ethic of technological self-determination, where users of technology (and hackers, tinkerers, startups and others serving as their proxies) can reconfigure and mod the technology they use, so that it does what they need it to do, and so that it can’t be used against them.
But the new, good internet will fix the defects of the old, good internet, the part that made it hard to use for anyone who wasn’t us. And hell yeah we can do that. Tech bosses swear that it’s impossible, that you can’t have a conversation friend without sharing it with Zuck; or search the web without letting Google scrape you down to the viscera; or have a phone that works reliably without giving Apple a veto over the software you install.
They claim that it’s a nonsense to even ponder this kind of thing. It’s like making water that’s not wet. But that’s bullshit. We can have nice things. We can build for the people we love, and give them a place that’s worth of their time and attention.
To do that, we have to install constraints.
The first constraint, remember, is competition. We’re living through a epochal shift in competition policy. After 40 years with antitrust enforcement in an induced coma, a wave of antitrust vigor has swept through governments all over the world. Regulators are stepping in to ban monopolistic practices, open up walled gardens, block anticompetitive mergers, and even unwind corrupt mergers that were undertaken on false pretenses.
Normally this is the place in the speech where I’d list out all the amazing things that have happened over the past four years. The enforcement actions that blocked companies from becoming too big to care, and that scared companies away from even trying.
Like Wiz, which just noped out of the largest acquisition offer in history, turning down Google’s $23b cashout, and deciding to, you know, just be a fucking business that makes money by producing a product that people want and selling it at a competitive price.
Normally, I’d be listing out FTC rulemakings that banned noncompetes nationwid. Or the new merger guidelines the FTC and DOJ cooked up, which – among other things – establish that the agencies should be considering whether a merger will negatively impact privacy.
I had a whole section of this stuff in my notes, a real victory lap, but I deleted it all this week.
[Can anyone guess why?]
That’s right! This week, Judge Amit Mehta, ruling for the DC Circuit of these United States of America, In the docket 20-3010 a case known as United States v. Google LLC, found that “Google is a monopolist, and it has acted as one to maintain its monopoly," and ordered Google and the DOJ to propose a schedule for a remedy, like breaking the company up.
So yeah, that was pretty fucking epic.
Now, this antitrust stuff is pretty esoteric, and I won’t gatekeep you or shame you if you wanna keep a little distance on this subject. Nearly everyone is an antitrust normie, and that's OK. But if you’re a normie, you’re probably only catching little bits and pieces of the narrative, and let me tell you, the monopolists know it and they are flooding the zone.
The Wall Street Journal has published over 100 editorials condemning FTC Chair Lina Khan, saying she’s an ineffectual do-nothing, wasting public funds chasing doomed, quixotic adventures against poor, innocent businesses accomplishing nothing
[Does anyone out there know who owns the Wall Street Journal?]
That’s right, it’s Rupert Murdoch. Do you really think Rupert Murdoch pays his editorial board to write one hundred editorials about someone who’s not getting anything done?
The reality is that in the USA, in the UK, in the EU, in Australia, in Canada, in Japan, in South Korea, even in China, we are seeing more antitrust action over the past four years than over the preceding forty years.
Remember, competition law is actually pretty robust. The problem isn’t the law, It’s the enforcement priorities. Reagan put antitrust in mothballs 40 years ago, but that elegant weapon from a more civilized age is now back in the hands of people who know how to use it, and they’re swinging for the fences.
Next up: regulation.
As the seemingly inescapable power of the tech giants is revealed for the sham it always was, governments and regulators are finally gonna kill the “one weird trick” of violating the law, and saying “It doesn’t count, we did it with an app.”
Like in the EU, they’re rolling out the Digital Markets Act this year. That’s a law requiring dominant platforms to stand up APIs so that third parties can offer interoperable services.
So a co-op, a nonprofit, a hobbyist, a startup, or a local government agency wil eventuallyl be able to offer, say, a social media server that can interconnect with one of the dominant social media silos, and users who switch to that new platform will be able to continue to exchange messages with the users they follow and groups they belong to, so the switching costs will fall to damned near zero.
That’s a very cool rule, but what’s even cooler is how it’s gonna be enforced. Previous EU tech rules were “regulations” as in the GDPR – the General Data Privacy Regulation. EU regs need to be “transposed” into laws in each of the 27 EU member states, so they become national laws that get enforced by national courts.
For Big Tech, that means all previous tech regulations are enforced in Ireland, because Ireland is a tax haven, and all the tech companies fly Irish flags of convenience.
Here’s the thing: every tax haven is also a crime haven. After all, if Google can pretend it’s Irish this week, it can pretend to be Cypriot, or Maltese, or Luxembougeious next week. So Ireland has to keep these footloose criminal enterprises happy, or they’ll up sticks and go somewhere else.
This is why the GDPR is such a goddamned joke in practice. Big tech wipes its ass with the GDPR, and the only way to punish them starts with Ireland’s privacy commissioner, who barely bothers to get out of bed. This is an agency that spends most of its time watching cartoons on TV in its pajamas and eating breakfast cereal. So all of the big GDPR cases go to Ireland and they die there.
This is hardly a secret. The European Commission knows it’s going on. So with the DMA, the Commission has changed things up: The DMA is an “Act,” not a “Regulation.” Meaning it gets enforced in the EU’s federal courts, bypassing the national courts in crime-havens like Ireland.
In other words, the “we violate privacy law, but we do it with an app” gambit that worked on Ireland’s toothless privacy watchdog is now a dead letter, because EU federal judges have no reason to swallow that obvious bullshit.
Here in the US, the dam is breaking on federal consumer privacy law – at last!
Remember, our last privacy law was passed in 1988 to protect the sanctity of VHS rental history. It's been a minute.
And the thing is, there's a lot of people who are angry about stuff that has some nexus with America's piss-poor privacy landscape. Worried that Facebook turned grampy into a Qanon? That Insta made your teen anorexic? That TikTok is brainwashing millennials into quoting Osama Bin Laden? Or that cops are rolling up the identities of everyone at a Black Lives Matter protest or the Jan 6 riots by getting location data from Google? Or that Red State Attorneys General are tracking teen girls to out-of-state abortion clinics? Or that Black people are being discriminated against by online lending or hiring platforms? Or that someone is making AI deepfake porn of you?
A federal privacy law with a private right of action – which means that individuals can sue companies that violate their privacy – would go a long way to rectifying all of these problems
There's a pretty big coalition for that kind of privacy law! Which is why we have seen a procession of imperfect (but steadily improving) privacy laws working their way through Congress.
If you sign up for EFF’s mailing list at eff.org we’ll send you an email when these come up, so you can call your Congressjerk or Senator and talk to them about it. Or better yet, make an appointment to drop by their offices when they’re in their districts, and explain to them that you’re not just a registered voter from their district, you’re the kind of elite tech person who goes to Defcon, and then explain the bill to them. That stuff makes a difference.
What about self-help? How are we doing on making interoperability legal again, so hackers can just fix shit without waiting for Congress or a federal agency to act?
All the action here these day is in the state Right to Repair fight. We’re getting state R2R bills, like the one that passed this year in Oregon that bans parts pairing, where DRM is used to keep a device from using a new part until it gets an authorized technician’s unlock code.
These bills are pushed by a fantastic group of organizations called the Repair Coalition, at Repair.org, and they’ll email you when one of these laws is going through your statehouse, so you can meet with your state reps and explain to the JV squad the same thing you told your federal reps.
Repair.org’s prime mover is Ifixit, who are genuine heroes of the repair revolution, and Ifixit’s founder, Kyle Wiens, is here at the con. When you see him, you can shake his hand and tell him thanks, and that’ll be even better if you tell him that you’ve signed up to get alerts at repair.org!
Now, on to the final way that we reverse enhittification and build that new, good internet: you, the tech labor force.
For years, your bosses tricked you into thinking you were founders in waiting, temporarily embarrassed entrepreneurs who were only momentarily drawing a salary.
You certainly weren’t workers. Your power came from your intrinsic virtue, not like those lazy slobs in unions who have to get their power through that kumbaya solidarity nonsense.
It was a trick. You were scammed. The power you had came from scarcity, and so when the scarcity ended, when the industry started ringing up six-figure annual layoffs, your power went away with it.
The only durable source of power for tech workers is as workers, in a union.
Think about Amazon. Warehouse workers have to piss in bottles and have the highest rate of on-the-job maimings of any competing business. Whereas Amazon coders get to show up for work with facial piercings, green mohawks, and black t-shirts that say things their bosses don’t understand. They can piss whenever they want!
That’s not because Jeff Bezos or Andy Jassy loves you guys. It’s because they’re scared you’ll quit and they don’t know how to replace you.
Time for the second obligatory William Gibson quote: “The future is here, it’s just not evenly distributed.” You know who’s living in the future?. Those Amazon blue-collar workers. They are the bleeding edge.
Drivers whose eyeballs are monitored by AI cameras that do digital phrenology on their faces to figure out whether to dock their pay, warehouse workers whose bodies are ruined in just months.
As tech bosses beef up that reserve army of unemployed, skilled tech workers, then those tech workers – you all – will arrive at the same future as them.
Look, I know that you’ve spent your careers explaining in words so small your boss could understand them that you refuse to enshittify the company’s products, and I thank you for your service.
But if you want to go on fighting for the user, you need power that’s more durable than scarcity. You need a union. Wanna learn how? Check out the Tech Workers Coalition and Tech Solidarity, and get organized.
Enshittification didn’t arise because our bosses changed. They were always that guy.
They were always yankin��� on that enshittification lever in the C-suite.
What changed was the environment, everything that kept that switch from moving.
And that’s good news, in a bankshot way, because it means we can make good services out of imperfect people. As a wildly imperfect person myself, I find this heartening.
The new good internet is in our grasp: an internet that has the technological self-determination of the old, good internet, and the greased-skids simplicity of Web 2.0 that let all our normie friends get in on the fun.
Tech bosses want you to think that good UX and enshittification can’t ever be separated. That’s such a self-serving proposition you can spot it from orbit. We know it, 'cause we built the old good internet, and we’ve been fighting a rear-guard action to preserve it for the past two decades.
It’s time to stop playing defense. It's time to go on the offensive. To restore competition, regulation, interop and tech worker power so that we can create the new, good internet we’ll need to fight fascism, the climate emergency, and genocide.
To build a digital nervous system for a 21st century in which our children can thrive and prosper.
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Community voting for SXSW is live! If you wanna hear RIDA QADRI and me talk about how GIG WORKERS can DISENSHITTIFY their jobs with INTEROPERABILITY, VOTE FOR THIS ONE!
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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/2024/08/17/hack-the-planet/#how-about-a-nice-game-of-chess
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