The hottest Data Collection Substack posts right now

And their main takeaways
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Differential privacy, an easy case

Accuracy and Privacy • 1 HN point • 02 Jan 19
🕹 Technology Privacy Statistics Data Collection Data processing
  1. Differential privacy is a mathematical definition of privacy specifically designed for protecting personal data in a world of big data and computation.
  2. Privacy protection in differential privacy comes from adding randomness or noise to data before publishing, where more noise equals greater privacy protection.
  3. There is a tradeoff between accuracy and privacy in differential privacy, as the level of uncertainty introduced for privacy protection can impact the accuracy of conclusions drawn from the data.

Báo Nói Application: A Guide to Building High-Quality Text-to-Speech Datasets

CodeLink’s Substack • 0 implied HN points • 28 Jun 23
🕹 Technology AI Data Collection Open Source Text-to-Speech
  1. High-quality data is essential for training accurate and natural-sounding text-to-speech AI models.
  2. Cutting-edge tools like annotation software and ASR services are pivotal for efficient data collection in developing text-to-speech AI models.
  3. Collaboration and data sharing drive innovation in the AI community, enhancing the representation of diverse perspectives and voices in AI-generated speech.

«Правильная» мобилизация: как изменится система воинского учета в России

Faridaily • 0 implied HN points • 18 Feb 23
🌍 World Politics Military Data Collection Borders Security International relations
  1. Russian authorities are creating a comprehensive database of military conscripts to facilitate faster mobilization if needed.
  2. Various government agencies will share citizen data to populate the database, including information on residence, health, employment, and more.
  3. The new system aims to prevent mistakes and improve efficiency during mobilization, making it harder to evade military service.

The Greatest Trick Big Brother Ever Pulled

Global Community Weekly (GloCom) • 0 implied HN points • 11 Feb 24
🕹 Technology Facial Recognition Privacy Concerns Law enforcement Data Collection
  1. The surveillance state is gradually emerging in small towns through various surveillance gadgets like facial recognition, gunshot detection devices, and automatic license plate readers, posing privacy threats.
  2. Facial recognition technology has raised concerns due to its use for petty purposes, leading to harassment and wrongful arrests, prompting efforts to ban its government use.
  3. Surveillance gadgets like automatic license plate readers are being promoted as non-threatening and old-fashioned, but concerns exist about privacy violations and their effectiveness in preventing crimes.
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The Changing Ad Landscape (and What To Do About It) | Youssef Ahres (Flagship, Instagram)

Steelhead • 0 implied HN points • 31 Jan 24
💼 Business Advertising Customer Engagement Brand building Data Collection Revenue growth
  1. Advertising serves to match supply and demand, with the value shifting to those who can effectively manage this in a world of abundant supply.
  2. Meta and Google have thrived in digital advertising by being widely used and investing in technology for targeted ad delivery.
  3. In the face of changing privacy concerns, companies should focus on leveraging first-party data, mastering customer engagement, exploring new advertising channels, and building strong brands to thrive.

Check 'em Privacy Policy

Jacob’s Tech Tavern • 0 implied HN points • 13 Feb 24
🕹 Technology Privacy Policy Data Collection Security
  1. The app Check 'em doesn't collect any data and doesn't even use the internet, ensuring user privacy.
  2. Users of Check 'em are not required to provide any personal information or create an account, emphasizing user anonymity.
  3. The app ensures high security by storing data securely on the iOS keychain and following best practices in generating 2FA codes.

Running out of things to say

Joshua Gans' Newsletter • 0 implied HN points • 19 Mar 21
🏥 Health & Wellness COVID-19 Economics Data Collection Testing Vaccines
  1. The author of the newsletter is taking a break due to running out of things to say after consistent writing for a year, but shares interesting articles from other sources.
  2. The shared articles cover various topics related to Covid-19 such as the importance of data, testing failures, new testing methods like rapid screens, and the need for continued testing even with vaccines available.
  3. The post also links to a new book called 'Economics in One Virus' by Ryan Borne that takes an economic perspective on situations arising from the pandemic.

Pre-emptive warnings to take care

Joshua Gans' Newsletter • 0 implied HN points • 02 Nov 20
🏥 Health & Wellness COVID-19 Prevention Innovation Data Collection Testing
  1. NOVID app offers a different approach to COVID-19 exposure tracking by focusing on self-protection rather than just protecting others.
  2. The app allows users to prepare for potential exposure by managing their contact budget and taking preventive measures.
  3. NOVID can serve as a valuable early warning system for communities like schools or workplaces to take extra precautions and drive further information through rapid testing.

We can do better on pre-risk assessment

Joshua Gans' Newsletter • 0 implied HN points • 23 Oct 20
🏥 Health & Wellness COVID-19 Information Management Risk Assessment Data Collection
  1. Pre-risk assessment is crucial for better allocation of Covid-19 tests. Higher pre-risk means test results carry more weight.
  2. CDC's protocol for point-of-care tests at nursing homes considers pre-risk, but lacks specific numerical data. More granular information would enhance testing protocols.
  3. Contact tracing apps could be leveraged to assess pre-risk levels, aiding in more accurate test allocation without compromising privacy.

Data Week: How to collect data

Joshua Gans' Newsletter • 0 implied HN points • 16 Oct 20
🔬 Science Data Collection Analysis Innovation Public Health Statistics
  1. Data collected at a manhole level can help detect outbreaks more rapidly and support targeted interventions.
  2. Sophisticated statistical techniques can provide a deeper understanding of outbreaks by leveraging sewage system data.
  3. Bayesian framework can convert sewage flows into probability flows to identify hot spot neighborhoods with just a few samples.

The Trade-Off Every AI Company Will Make

Joshua Gans' Newsletter • 0 implied HN points • 28 Mar 17
🕹 Technology AI Machine Learning Autonomous Vehicles Data Collection Product Development
  1. Training for AI, like pilots or cashiers, is essential for machines to learn and improve in performance.
  2. Determining what is "good enough" for machine intelligence involves considering the trade-offs in terms of error tolerance and level of in-house vs on-the-job learning.
  3. The decision of when to deploy AI systems into the real world for learning involves balancing the need for data with the potential risks to brand and customer safety.

Is your organisation based on PowerPoint or Excel?

Joshua Gans' Newsletter • 0 implied HN points • 02 Mar 15
🔬 Science Space Exploration Organizational Structure Decision-making Data Collection Collaboration
  1. Organizational structures based on PowerPoint and Excel can lead to different outcomes in data collection and decision-making processes.
  2. Team PowerPoint emphasizes collective decision-making and qualitative trade-offs, leading to comprehensive analyses of common phenomena.
  3. Team Excel focuses on specialized knowledge with separate teams managing instruments, resulting in very complete and specialized data collection but less collaboration.

Dataplane.org 2022 Year In Review

Dataplane.org Newsletter • 0 implied HN points • 04 Apr 23
🕹 Technology Data Analysis Network Security Internet Trends Cybersecurity Data Collection
  1. Dataplane.org reflected on 2022 to analyze what went well, improved the website, moved social presence to Mastodon, and boosted backend infrastructure.
  2. Insights from DNS queries revealed top unsolicited queries like www.google.com and common passwords like '123456'.
  3. Dataplane.org is preparing a public archive, planning for tax season, and welcoming donations for continuous availability of Signals data.

Cyber Physical Symptoms

Cybernetic Forests • 0 implied HN points • 04 Nov 21
🕹 Technology AI Digital Design Data Collection
  1. Symptoms in technological systems indicate underlying issues that need attention.
  2. Approaching problems in AI and cyber-physical systems as 'cyber-physical symptoms' can help identify imbalances between digital and social elements.
  3. Considering the concept of 'Hormesis,' where appropriate amounts of digital and analog elements are integrated, can lead to stronger system designs.

K-12 School Shooting Database 3.0

School Shooting Data Analysis and Reports • 0 implied HN points • 01 Oct 20
🇺🇸 U.S. Politics Gun Violence Data Collection Public Safety Criminal Justice
  1. The K-12 School Shooting Database is now an independent research project with a website not affiliated with any government agency, documenting instances of gun violence on school property since 1970.
  2. The database includes various types of incidents beyond traditional school shootings, such as gang violence, domestic disputes, and accidents, providing a comprehensive view of gun violence in schools.
  3. The data collected by the database includes detailed information on the locations of shootings on school property, outcomes of incidents, victim and shooter demographics, offering a unique level of detail for analysis.

Giám sát an ninh mạng - hay là làm thế nào để ngăn chặn một cuộc tấn công DDoS trong 20'

Thái | Hacker | Kỹ sư tin tặc • 0 implied HN points • 14 Dec 09
🕹 Technology Network Security Data Collection Data Analysis Incident Response
  1. Network security monitoring is crucial for preventing and mitigating DDoS attacks. It involves collecting data, analyzing it, and escalating information.
  2. Human expertise is vital in cybersecurity as machines and standards alone can't fully protect systems.
  3. Continuous monitoring of network security 24/7 is essential, requiring expert personnel and access to data for effective operation.

On Making Social Media Platforms Better

The Digital Anthropologist • 0 implied HN points • 29 Mar 24
🕹 Technology Social media Platforms Algorithms Data Collection
  1. Some social media platforms like Pinterest, Medium, Substack, and Wikipedia are examples of platforms with higher user satisfaction and less toxicity. They empower users more than platforms like Facebook and Twitter.
  2. One key factor for improving social media platforms is achieving a better balance between machines and humans. Platforms that focus on Cultural Alignment (CA) and Information Asymmetry (IA) can offer more value to users.
  3. There are four scenarios for the machine-human relationship in social media platforms: Assisting, Nudging, Collaborating, and Misunderstanding. Moving towards a collaborative scenario can lead to more equal standing between humans and machines.

Microservice Observability, Part 2: Evolutionary Patterns for Solving Observability Problems

realkinetic • 0 implied HN points • 03 Jan 20
🕹 Technology Observability Microservices Data Collection Data processing Infrastructure
  1. Observability involves capturing various signals like logs, metrics, and traces to ask questions of systems without knowing those questions in advance.
  2. Challenges in observability can include agent fatigue due to multiple operational tools requiring unique agents, capacity anxiety with elastic microservice architectures, and the need for foresight in collecting necessary data.
  3. Implementing an observability pipeline can help in capturing wide events, consolidating data collection, decoupling sources and sinks, normalizing data schemas, and routing data to various tools for better observability in systems.

The Observability Pipeline

realkinetic • 0 implied HN points • 12 Sep 18
🕹 Technology Cloud Computing Monitoring Data Collection
  1. Systems are now more distributed and dynamic due to the rise of cloud and containers, requiring new tools and practices to support them
  2. Observability in modern cloud-native environments involves gathering data for granular insights and empowered debugging through structured logging, metrics, traces, and events
  3. Building an observability pipeline helps decouple data collection from ingestion into various systems and allows flexibility to add or replace tools without major disruptions

Kenya hosts first-ever Africa Climate Summit.

The Climate Historian • 0 implied HN points • 05 Sep 23
🌞 Climate & Environment Climate change Sustainability Renewable Energy Environmental Policy Data Collection
  1. The Africa Climate Summit in Kenya is a big event with over 13,000 delegates, focusing on Africa working together to tackle climate change on their own terms.
  2. Companies like Kakuma Ventures and M-KOPA Solar are showcasing how they're improving lives through renewable energy, helping communities access clean power and digital services.
  3. The summit aims to fix Africa's lack of weather data, which is crucial for agriculture and disaster readiness, so countries can make better decisions related to climate challenges.

Study 1b Pre-registration

From AI to ZI • 0 implied HN points • 17 Apr 23
🔬 Science Research Analysis Data Collection Transparency
  1. Study 1b aims to rerun Study 1a with a different prompting method to potentially increase the rate of factually incorrect answers
  2. The study will test hypotheses related to the accuracy of large language models under new prompting formats
  3. The data will be analyzed using multiple-regression analysis to determine the effects of different variables on the model's accuracy

How Miro collects more relevant emails from signup

CommandBlogue • 0 implied HN points • 20 Mar 24
💼 Business Marketing User Experience Product Management Data Collection Copywriting
  1. Miro improves email sign-up by changing how they ask for work emails. They highlight a benefit, saying it helps separate work and life, which makes users more willing to share their emails.
  2. Instead of just asking for an email, it’s better to explain why it's good for the user. This motivation helps users feel more positive about the action you want them to take.
  3. Always make sure the benefit you mention is real. If users find out it's not true, they won't trust you again.