Between 2023 and 2027, the majority of companies surveyed worldwide expect big data to have a more positive than negative impact on the global job market and employment, with ** percent of the companies reporting the technology will create jobs and * percent expecting the technology to displace jobs. Meanwhile, artificial intelligence (AI) is expected to result in more significant labor market disruptions, with ** percent of organizations expecting the technology to displace jobs and ** percent expecting AI to create jobs.

Analysis of ‘Popular Website Traffic Over Time ’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/popular-website-traffice on 13 February 2022.

--- Dataset description provided by original source is as follows ---

About this dataset

Background

Have you every been in a conversation and the question comes up, who uses Bing? This question comes up occasionally because people wonder if these sites have any views. For this research study, we are going to be exploring popular website traffic for many popular websites.

Methodology

The data collected originates from SimilarWeb.com.

Source

For the analysis and study, go to The Concept Center

This dataset was created by Chase Willden and contains around 0 samples along with 1/1/2017, Social Media, technical information and other features such as: - 12/1/2016 - 3/1/2017 - and more.

How to use this dataset

• Analyze 11/1/2016 in relation to 2/1/2017
• Study the influence of 4/1/2017 on 1/1/2017
• More datasets

Acknowledgements

If you use this dataset in your research, please credit Chase Willden

Start A New Notebook!

--- Original source retains full ownership of the source dataset ---

Blockchain AI Market size was valued at USD 448 Million in 2023 and is projected to reach USD 2730 Million by 2031, at a CAGR of 25.5% from 2024 to 2031.

Global Blockchain AI Market Drivers

The market drivers for the Blockchain AI Market can be influenced by various factors. These may include:

Enhanced Data Security: By offering a decentralized and unchangeable record for information sharing and archiving, the combination of blockchain technology and artificial intelligence improves data security. Sensitive information is especially valuable in this secure infrastructure for supply chain management, banking, and healthcare. Increased Adoption of AI: As AI is used more and more in many industries, there is a greater need for blockchain-based solutions to deal with issues with data transparency and integrity. Blockchain technology ensures the quality and dependability of AI-powered services and apps by verifying the legitimacy of the data used to train AI algorithms. Growing worries About Data Privacy: Organizations are investigating blockchain AI solutions that provide more control over data access and usage due to growing worries about data privacy and ownership. Blockchain gives people control over their data while allowing AI algorithms to access it selectively for processing and analysis. Demand for Transparent and Reliable AI Systems: Companies and customers alike are looking for reliable and transparent AI systems that can shed light on the decision-making process. Blockchain technology makes it possible to transparently record the decisions and acts of AI algorithms, which promotes transparency and confidence in AI-powered systems. Decentralized AI Marketplaces Are Necessary: Blockchain technology is enabling the development of decentralized AI marketplaces, which are democratizing access to AI datasets and algorithms. These markets enable peer-to-peer exchanges and cooperation, enabling businesses and developers to profitably and effectively share AI resources. Regulatory Compliance Requirements: The adoption of blockchain AI solutions is being driven by regulatory mandates, such as the GDPR (General Data Protection Regulation) in Europe and HIPAA (Health Insurance Portability and Accountability Act) in the healthcare industry, to ensure compliance with data protection regulations. The transparent data governance offered by blockchain's immutability and auditability features facilitate regulatory compliance. Growing Interest in Federated Learning: Due to privacy concerns and data localization requirements, federated learning, a distributed machine learning approach, is gaining interest. It trains AI models across various decentralized devices. Blockchain technology guarantees data privacy, integrity, and incentive among participating nodes, which can enable safe and effective federated learning. Extension of DAOs and Smart Contracts: Automated and untrusted decision-making and agreement execution is made possible by the combination of AI systems with smart contracts and decentralized autonomous organizations (DAOs). Smart contracts built on the blockchain can carry out predetermined scenarios and transactions based on insights generated by artificial intelligence, simplifying corporate processes and lowering dependency on middlemen. The emergence of AI-driven token economies: is being fueled by the convergence of blockchain and AI technology. In these economies, tokens are utilized as incentives for sharing data, training models, and improving algorithms. These token economies ensure equitable reward for contributions while encouraging cooperation and creativity in AI research and development. Partnerships and Cross-Industry Collaboration: The adoption of blockchain AI solutions is being accelerated by partnerships and cross-industry collaboration among research institutions, industry consortia, and technology vendors. Inter-industry collaborations enable the sharing of knowledge, assets, and optimal methodologies, promoting the advancement of blockchain artificial intelligence solutions that are both interoperable and scalable.

Please cite the following paper when using this dataset: N. Thakur, “MonkeyPox2022Tweets: The first public Twitter dataset on the 2022 MonkeyPox outbreak,” Preprints, 2022, DOI: 10.20944/preprints202206.0172.v2

Abstract The world is currently facing an outbreak of the monkeypox virus, and confirmed cases have been reported from 28 countries. Following a recent “emergency meeting”, the World Health Organization just declared monkeypox a global health emergency. As a result, people from all over the world are using social media platforms, such as Twitter, for information seeking and sharing related to the outbreak, as well as for familiarizing themselves with the guidelines and protocols that are being recommended by various policy-making bodies to reduce the spread of the virus. This is resulting in the generation of tremendous amounts of Big Data related to such paradigms of social media behavior. Mining this Big Data and compiling it in the form of a dataset can serve a wide range of use-cases and applications such as analysis of public opinions, interests, views, perspectives, attitudes, and sentiment towards this outbreak. Therefore, this work presents MonkeyPox2022Tweets, an open-access dataset of Tweets related to the 2022 monkeypox outbreak that were posted on Twitter since the first detected case of this outbreak on May 7, 2022. The dataset is compliant with the privacy policy, developer agreement, and guidelines for content redistribution of Twitter, as well as with the FAIR principles (Findability, Accessibility, Interoperability, and Reusability) principles for scientific data management.

Data Description The dataset consists of a total of 255,363 Tweet IDs of the same number of tweets about monkeypox that were posted on Twitter from 7th May 2022 to 23rd July 2022 (the most recent date at the time of dataset upload). The Tweet IDs are presented in 6 different .txt files based on the timelines of the associated tweets. The following provides the details of these dataset files. • Filename: TweetIDs_Part1.txt (No. of Tweet IDs: 13926, Date Range of the Tweet IDs: May 7, 2022 to May 21, 2022) • Filename: TweetIDs_Part2.txt (No. of Tweet IDs: 17705, Date Range of the Tweet IDs: May 21, 2022 to May 27, 2022) • Filename: TweetIDs_Part3.txt (No. of Tweet IDs: 17585, Date Range of the Tweet IDs: May 27, 2022 to June 5, 2022) • Filename: TweetIDs_Part4.txt (No. of Tweet IDs: 19718, Date Range of the Tweet IDs: June 5, 2022 to June 11, 2022) • Filename: TweetIDs_Part5.txt (No. of Tweet IDs: 47718, Date Range of the Tweet IDs: June 12, 2022 to June 30, 2022) • Filename: TweetIDs_Part6.txt (No. of Tweet IDs: 138711, Date Range of the Tweet IDs: July 1, 2022 to July 23, 2022)

The dataset contains only Tweet IDs in compliance with the terms and conditions mentioned in the privacy policy, developer agreement, and guidelines for content redistribution of Twitter. The Tweet IDs need to be hydrated to be used.

In October and November 2023, researchers at the Schwartz Reisman Institute for Technology and Society and the Policy, Elections and Representation Lab at the Munk School of Global Affairs and Public Policy at the University of Toronto completed a survey on public perceptions of and attitudes toward AI. The survey was administered to over 1,000 people in each of 21 countries, for a total of 23,882 surveys conducted in 12 languages. The combined populations of the countries sampled represent a majority of the world's population. Countries: Argentina, Australia, Brazil, Canada, Chile, China, France, Germany, India, Indonesia, Italy, Japan, Kenya, Mexico, Pakistan, Poland, Portugal, South Africa, Spain, United Kingdom, United States of America Languages: Chinese (Simplified), English, French, German, Indonesian, Italian, Japanese, Polish, Portuguese (Portugal), Portuguese (Brazil), Spanish (Spain), Spanish (Latin America). The survey explored general knowledge of and attitudes toward AI. Topics included concerns about AI, safety, regulation, autonomous vehicles and AI's effect on jobs now and in the future. Participants were asked whether they are interested in or trust applications of AI for clothes, travel, grocery shopping, dating or finance. Respondents were asked about their attitudes toward the use of emerging technologies in education, the justice system, health care and immigration. Respondents were also asked about their knowledge of and experience with ChatGPT and deepfakes.

This dataset collects real consumer feedback, covering more than a thousand companies worldwide. It’s designed to highlight how people describe product satisfaction, unmet expectations, and usage experiences — ideal for retail brands, marketplace analysts, and AI developers.

Included data points:

-Reviews about products and retail companies annotated with sentiment and emotional tone -Mentioned issues and features (e.g., build quality, delivery, instructions, price mismatch) -Optional metadata for channel (storefront, app, delivery platform), time, and region

The list may vary based on the industry and can be customized as per your request.

What it supports:

-Identify emerging product flaws or design gaps through buyer feedback -Train AI and LLMs on real-world product review narratives and emotion -Segment user perception trends across industries or retailers -Benchmark brand and product sentiment over time -Automate tagging and escalation of critical product feedback

Whether used for sentiment pipelines, QA automation, or merchandising decisions, this dataset delivers actionable product intelligence at scale, grounded in what real customers say about the things they buy."

10,109 people - face images dataset includes people collected from many countries. Multiple photos of each person’s daily life are collected, and the gender, race, age, etc. of the person being collected are marked.This Dataset provides a rich resource for artificial intelligence applications. It has been validated by multiple AI companies and proves beneficial for achieving outstanding performance in real-world applications. Throughout the process of Dataset collection, storage, and usage, we have consistently adhered to Dataset protection and privacy regulations to ensure the preservation of user privacy and legal rights. All Dataset comply with regulations such as GDPR, CCPA, PIPL, and other applicable laws.

Success.ai’s Commercial Real Estate Data and B2B Contact Data for Global Real Estate Professionals is a comprehensive dataset designed to connect businesses with industry leaders in real estate worldwide. With over 170M verified profiles, including work emails and direct phone numbers, this solution ensures precise outreach to agents, brokers, property developers, and key decision-makers in the real estate sector.

Utilizing advanced AI-driven validation, our data is continuously updated to maintain 99% accuracy, offering actionable insights that empower targeted marketing, streamlined sales strategies, and efficient recruitment efforts. Whether you’re engaging with top real estate executives or sourcing local property experts, Success.ai provides reliable and compliant data tailored to your needs.

Key Features of Success.ai’s Real Estate Professional Contact Data

• Comprehensive Industry Coverage Gain direct access to verified profiles of real estate professionals across the globe, including:

1. Real Estate Agents: Professionals facilitating property sales and purchases.
2. Brokers: Key intermediaries managing transactions between buyers and sellers.
3. Property Developers: Decision-makers shaping residential, commercial, and industrial projects.
4. Real Estate Executives: Leaders overseeing multi-regional operations and business strategies.
5. Architects & Consultants: Experts driving design and project feasibility.

• Verified and Continuously Updated Data

AI-Powered Validation: All profiles are verified using cutting-edge AI to ensure up-to-date accuracy. Real-Time Updates: Our database is refreshed continuously to reflect the most current information. Global Compliance: Fully aligned with GDPR, CCPA, and other regional regulations for ethical data use.

• Customizable Data Delivery Tailor your data access to align with your operational goals:

API Integration: Directly integrate data into your CRM or project management systems for seamless workflows. Custom Flat Files: Receive detailed datasets customized to your specifications, ready for immediate application.

Why Choose Success.ai for Real Estate Contact Data?

• Best Price Guarantee Enjoy competitive pricing that delivers exceptional value for verified, comprehensive contact data.

• Precision Targeting for Real Estate Professionals Our dataset equips you to connect directly with real estate decision-makers, minimizing misdirected efforts and improving ROI.

• Strategic Use Cases

  Lead Generation: Target qualified real estate agents and brokers to expand your network. Sales Outreach: Engage with property developers and executives to close high-value deals. Marketing Campaigns: Drive targeted campaigns tailored to real estate markets and demographics. Recruitment: Identify and attract top talent in real estate for your growing team. Market Research: Access firmographic and demographic data for in-depth industry analysis.

• Data Highlights 170M+ Verified Professional Profiles 50M Work Emails 30M Company Profiles 700M Global Professional Profiles

• Powerful APIs for Enhanced Functionality

  Enrichment API Ensure your contact database remains relevant and up-to-date with real-time enrichment. Ideal for businesses seeking to maintain competitive agility in dynamic markets.

Lead Generation API Boost your lead generation with verified contact details for real estate professionals, supporting up to 860,000 API calls per day for robust scalability.

• Use Cases for Real Estate Contact Data

1. Targeted Outreach for New Projects Connect with property developers and brokers to pitch your services or collaborate on upcoming projects.

2. Real Estate Marketing Campaigns Execute personalized marketing campaigns targeting agents and clients in residential, commercial, or industrial sectors.

3. Enhanced Sales Strategies Shorten sales cycles by directly engaging with decision-makers and key stakeholders.

4. Recruitment and Talent Acquisition Access profiles of highly skilled professionals to strengthen your real estate team.

5. Market Analysis and Intelligence Leverage firmographic and demographic insights to identify trends and optimize business strategies.

• What Makes Us Stand Out? >> Unmatched Data Accuracy: Our AI-driven validation ensures 99% accuracy for all contact details. >> Comprehensive Global Reach: Covering professionals across diverse real estate markets worldwide. >> Flexible Delivery Options: Access data in formats that seamlessly fit your existing systems. >> Ethical and Compliant Data Practices: Adherence to global standards for secure and responsible data use.

Success.ai’s B2B Contact Data for Global Real Estate Professionals delivers the tools you need to connect with the right people at the right time, driving efficiency and success in your business operations. From agents and brokers to property developers and executiv...

This dataset features over 25,000,000 high-quality general-purpose images sourced from photographers worldwide. Designed to support a wide range of AI and machine learning applications, it offers a richly diverse and extensively annotated collection of everyday visual content.

Key Features: 1. Comprehensive Metadata: the dataset includes full EXIF data, detailing camera settings such as aperture, ISO, shutter speed, and focal length. Additionally, each image is pre-annotated with object and scene detection metadata, making it ideal for tasks like classification, detection, and segmentation. Popularity metrics, derived from engagement on our proprietary platform, are also included.

2.Unique Sourcing Capabilities: the images are collected through a proprietary gamified platform for photographers. Competitions spanning various themes ensure a steady influx of diverse, high-quality submissions. Custom datasets can be sourced on-demand within 72 hours, allowing for specific requirements—such as themes, subjects, or scenarios—to be met efficiently.

1. Global Diversity: photographs have been sourced from contributors in over 100 countries, covering a wide range of human experiences, cultures, environments, and activities. The dataset includes images of people, nature, objects, animals, urban and rural life, and more—captured across different times of day, seasons, and lighting conditions.

2. High-Quality Imagery: the dataset includes images with resolutions ranging from standard to high-definition to meet the needs of various projects. Both professional and amateur photography styles are represented, offering a balance of realism and creativity across visual domains.

3. Popularity Scores: each image is assigned a popularity score based on its performance in GuruShots competitions. This unique metric reflects how well the image resonates with a global audience, offering an additional layer of insight for AI models focused on aesthetics, engagement, or content curation.

4. AI-Ready Design: this dataset is optimized for AI applications, making it ideal for training models in general image recognition, multi-label classification, content filtering, and scene understanding. It integrates easily with leading machine learning frameworks and pipelines.

5. Licensing & Compliance: the dataset complies fully with data privacy regulations and offers transparent licensing for both commercial and academic use.

Use Cases: 1. Training AI models for general-purpose image classification and tagging. 2. Enhancing content moderation and visual search systems. 3. Building foundational datasets for large-scale vision-language models. 4. Supporting research in computer vision, multimodal AI, and generative modeling.

This dataset offers a comprehensive, diverse, and high-quality resource for training AI and ML models across a wide array of domains. Customizations are available to suit specific project needs. Contact us to learn more!

A worldwide survey carried out in 2024 showed that Boomers are the most concerned about the use of personal data when shopping online. 60 percent of them avoided sharing personal details because they did not trust data privacy with AI technologies.

Analysis of ‘📈 Pension Insurance Data’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/pension-insurance-datae on 28 January 2022.

--- Dataset description provided by original source is as follows ---

About this dataset

The tables include statistics on the people and pensions that PBGC protects, including how many Americans are in PBGC-insured pension plans, how many get PBGC benefits, and where they live.

Note: Links in the first sheet associated with each table following.

Source: https://catalog.data.gov/dataset/pension-insurance-data-tables

This dataset was created by Data Society and contains around 100 samples along with Data Book Listing, Table, technical information and other features such as: - Data Book Listing - Table - and more.

How to use this dataset

• Analyze Data Book Listing in relation to Table
• Study the influence of Data Book Listing on Table
• More datasets

Acknowledgements

If you use this dataset in your research, please credit Data Society

Start A New Notebook!

--- Original source retains full ownership of the source dataset ---

Analysis of ‘🥫 Food Pantry and User Data ’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/yamqwe/food-pantry-and-user-data-agencye on 13 February 2022.

--- Dataset description provided by original source is as follows ---

About this dataset

This dataset identifies locations of food pantry service providers, food insecure people concentrations, and seasonal service demand variability.

Source: https://handsoncentralohio.org/
Last updated at https://discovery.smartcolumbusos.com : 2018-05-08

This dataset was created by Kelly Garrett and contains around 1000 samples along with Update User, Asl, technical information and other features such as: - Location Id - Add Date - and more.

How to use this dataset

• Analyze Director in relation to Printcol1
• Study the influence of Special Event Flag on Print Labels Flag
• More datasets

Acknowledgements

If you use this dataset in your research, please credit Kelly Garrett

Start A New Notebook!

--- Original source retains full ownership of the source dataset ---

Success.ai offers a comprehensive, enterprise-ready B2B leads data solution, ideal for businesses seeking access to over 150 million verified employee profiles and 170 million work emails. Our data empowers organizations across industries to target key decision-makers, optimize recruitment, and fuel B2B marketing efforts. Whether you're looking for UK B2B data, B2B marketing data, or global B2B contact data, Success.ai provides the insights you need with pinpoint accuracy.

Tailored for B2B Sales, Marketing, Recruitment and more: Our B2B contact data and B2B email data solutions are designed to enhance your lead generation, sales, and recruitment efforts. Build hyper-targeted lists based on job title, industry, seniority, and geographic location. Whether you’re reaching mid-level professionals or C-suite executives, Success.ai delivers the data you need to connect with the right people.

API Features:

• Real-Time Updates: Our APIs deliver real-time updates, ensuring that the contact data your business relies on is always current and accurate.
• High Volume Handling: Designed to support up to 860k API calls per day, our system is built for scalability and responsiveness, catering to enterprises of all sizes.
• Flexible Integration: Easily integrate with CRM systems, marketing automation tools, and other enterprise applications to streamline your workflows and enhance productivity.

Key Categories Served: B2B sales leads – Identify decision-makers in key industries, B2B marketing data – Target professionals for your marketing campaigns, Recruitment data – Source top talent efficiently and reduce hiring times, CRM enrichment – Update and enhance your CRM with verified, updated data, Global reach – Coverage across 195 countries, including the United States, United Kingdom, Germany, India, Singapore, and more.

Global Coverage with Real-Time Accuracy: Success.ai’s dataset spans a wide range of industries such as technology, finance, healthcare, and manufacturing. With continuous real-time updates, your team can rely on the most accurate data available: 150M+ Employee Profiles: Access professional profiles worldwide with insights including full name, job title, seniority, and industry. 170M Verified Work Emails: Reach decision-makers directly with verified work emails, available across industries and geographies, including Singapore and UK B2B data. GDPR-Compliant: Our data is fully compliant with GDPR and other global privacy regulations, ensuring safe and legal use of B2B marketing data.

Key Data Points for Every Employee Profile: Every profile in Success.ai’s database includes over 20 critical data points, providing the information needed to power B2B sales and marketing campaigns: Full Name, Job Title, Company, Work Email, Location, Phone Number, LinkedIn Profile, Experience, Education, Technographic Data, Languages, Certifications, Industry, Publications & Awards.

Use Cases Across Industries: Success.ai’s B2B data solution is incredibly versatile and can support various enterprise use cases, including: B2B Marketing Campaigns: Reach high-value professionals in industries such as technology, finance, and healthcare. Enterprise Sales Outreach: Build targeted B2B contact lists to improve sales efforts and increase conversions. Talent Acquisition: Accelerate hiring by sourcing top talent with accurate and updated employee data, filtered by job title, industry, and location. Market Research: Gain insights into employment trends and company profiles to enrich market research. CRM Data Enrichment: Ensure your CRM stays accurate by integrating updated B2B contact data. Event Targeting: Create lists for webinars, conferences, and product launches by targeting professionals in key industries.

Use Cases for Success.ai's Contact Data - Targeted B2B Marketing: Create precise campaigns by targeting key professionals in industries like tech and finance. - Sales Outreach: Build focused sales lists of decision-makers and C-suite executives for faster deal cycles. - Recruiting Top Talent: Easily find and hire qualified professionals with updated employee profiles. - CRM Enrichment: Keep your CRM current with verified, accurate employee data. - Event Targeting: Create attendee lists for events by targeting relevant professionals in key sectors. - Market Research: Gain insights into employment trends and company profiles for better business decisions. - Executive Search: Source senior executives and leaders for headhunting and recruitment. - Partnership Building: Find the right companies and key people to develop strategic partnerships.

Why Choose Success.ai’s Employee Data? Success.ai is the top choice for enterprises looking for comprehensive and affordable B2B data solutions. Here’s why: Unmatched Accuracy: Our AI-powered validation process ensures 99% accuracy across all data points, resulting in higher engagement and fewer bounces. Global Scale: With 150M+ employee profiles and 170M veri...

People Data Labs is an aggregator of B2B person and company data. We source our globally compliant person dataset via our "Data Union".

The "Data Union" is our proprietary data sharing co-op. Customers opt-in to sharing their data and warrant that their data is fully compliant with global data privacy regulations. Some data sources are provided as a one time dump, others are refreshed every time we do a new data build. Our data sources come from a variety of verticals including HR Tech, Real Estate Tech, Identity/Anti-Fraud, Martech, and others. People Data Labs works with customers on compliance based topics. If a customer wishes to ensure anonymity, we work with them to anonymize the data.

Our person data has over 100 fields including resume data (work history, education), contact information (email, phone), demographic info (name, gender, birth date) and social profile information (linkedin, github, twitter, facebook, etc...).

Introduction

This Canadian French Call Center Speech Dataset for the Healthcare industry is purpose-built to accelerate the development of French speech recognition, spoken language understanding, and conversational AI systems. With 30 Hours of unscripted, real-world conversations, it delivers the linguistic and contextual depth needed to build high-performance ASR models for medical and wellness-related customer service.

Created by FutureBeeAI, this dataset empowers voice AI teams, NLP researchers, and data scientists to develop domain-specific models for hospitals, clinics, insurance providers, and telemedicine platforms.

Speech Data

The dataset features 30 Hours of dual-channel call center conversations between native Canadian French speakers. These recordings cover a variety of healthcare support topics, enabling the development of speech technologies that are contextually aware and linguistically rich.

Topic Diversity

The dataset spans inbound and outbound calls, capturing a broad range of healthcare-specific interactions and sentiment types (positive, neutral, negative).

These real-world interactions help build speech models that understand healthcare domain nuances and user intent.

Transcription

Every audio file is accompanied by high-quality, manually created transcriptions in JSON format.

Metadata

Each conversation and speaker includes detailed metadata to support fine-tuned training and analysis.

Usage and Applications

This dataset can be used across a range of healthcare and voice AI use cases:

Introduction

This Bahasa Call Center Speech Dataset for the Healthcare industry is purpose-built to accelerate the development of Bahasa speech recognition, spoken language understanding, and conversational AI systems. With 40 Hours of unscripted, real-world conversations, it delivers the linguistic and contextual depth needed to build high-performance ASR models for medical and wellness-related customer service.

Created by FutureBeeAI, this dataset empowers voice AI teams, NLP researchers, and data scientists to develop domain-specific models for hospitals, clinics, insurance providers, and telemedicine platforms.

Speech Data

The dataset features 40 Hours of dual-channel call center conversations between native Bahasa speakers. These recordings cover a variety of healthcare support topics, enabling the development of speech technologies that are contextually aware and linguistically rich.

Topic Diversity

The dataset spans inbound and outbound calls, capturing a broad range of healthcare-specific interactions and sentiment types (positive, neutral, negative).

These real-world interactions help build speech models that understand healthcare domain nuances and user intent.

Transcription

Every audio file is accompanied by high-quality, manually created transcriptions in JSON format.

Metadata

Each conversation and speaker includes detailed metadata to support fine-tuned training and analysis.

Usage and Applications

This dataset can be used across a range of healthcare and voice AI use cases:

This is the dataset for the study of "Social dilemma in the excess use of antimicrobials incurring antimicrobial resistance". The emergence of antimicrobial resistance (AMR) caused by the excess use of antimicrobials has come to be recognized as a global threat to public health. There is a ‘tragedy of the commons’ type social dilemma behind this excessive use of antimicrobials, which should be recognized by all stakeholders. To address this global threat, we thus surveyed eight countries/areas to determine whether people recognize this dilemma and showed that although more than half of the population pays little, if any, attention to it, almost 20% recognize this social dilemma, and 15–30% of those have a positive attitude toward solving that dilemma. We suspect that increasing individual awareness of this social dilemma contributes to decreasing the frequency of AMR emergencies. Methods We designed a questionnaire to observe a social dilemma in the excess use of antimicrobials incurring antimicrobial resistance by placing two types of imaginary artificial-intelligence (AI) physicians who perform medical practice from either an individual or societal perspective. We assume two AI medical diagnosis systems: “Individual precedence AI” (abbreviated Individual-AI) and “World precedence AI” (abbreviated World-AI). Both AIs diagnose and prescribe medicine automatically. The Individual-AI system diagnoses patients and prescribes medicine to prevent infections based on an individual perspective, including all prophylactic prescriptions against rare accidental infections (not yet present and unlikely to occur). It does not consider the global risk of AMR in the decision. The World-AI system, instead, takes into account the global mortality rate of AMR, aiming to reduce the total number of all AMR-related deaths. Because of this, this AI system does not prescribe antimicrobials against rare and not-yet-present infections. This questionnaire design allows us to observe the social dilemma. For example, it shows a typical social dilemma caused by preferring the use of Individual-AI for diagnosing oneself but preferring the use of World-AI for diagnosing strangers.

The survey entitled “Survey on Medical Advancement” was administered to 8 countries/areas. The survey was conducted 4 times. For the two surveys in Japan, an internet survey company, Cross Marketing Inc. (https://www.cross-m.co.jp/en/), created the questionnaire webpages based on our study design. The company also collected the data. As of April 2020, Cross Marketing Inc. has 4.79 million people in an active panel (survey participants who registered in advance). Here, the definition of an active panel is a survey respondent who has been active within the last year. For the panels, the questionnaire and response column were displayed on the website through which the respondents could complete and submit their responses. We extracted 500 submissions for each gender and each age group by random sampling from all samples collected during the survey periods. The surveys in the 7 countries/areas (i.e., the United States, the United Kingdom, Sweden, Taiwan, Australia, Brazil, and Russia) are conducted by Cint (https://www.cint.com/). Cint is the world’s largest consumer network for digital survey-based research. The headquarters of the company is in Sweden. Cint maintains a survey platform that contained more than 100 million consumer monitors in over 80 countries as of May 2020. For surveys in the US, UK, Sweden, Taiwan, Australia, Brazil, and Russia, Cint Japan (https://jp.cint.com/), which is the Japanese distributor of Cint, created translated questionnaire webpages based on our study design. The company also collected the data. We extracted at least 500 (US, UK, SWE, BRA, RUS) or 250 (TWN, AUS) submissions for each gender (male and female) and each age group (20 s, 30 s, 40 s, 50 s, and 60 s) by random sampling from all samples collected between survey periods. Note that both companies eliminated inconsistent or apathetic respondents. For example, respondents with inconsistent responses (e.g., the registered age of the respondent differed from the reported age at the time of the survey.) were eliminated before reaching the authors. In addition, respondents with significantly short response times (i.e., shorter than 1 min) were eliminated because they may not have read the questions carefully.

Analysis of ‘World Leaders and their Win in Elections’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/ramjasmaurya/world-leaders-and-their-election-wins on 28 January 2022.

--- Dataset description provided by original source is as follows ---

there is only one leader being both head of state and head of government. In other cases, mainly in semi-presidential and parliamentary systems, the head of state and the head of government are different people. In semi-presidential and parliamentary systems, the head of government role (i.e. executive branch) is fulfilled by both the listed head of government and the head of state. In single-party systems, ruling party's leader (i.e. General Secretary) is usually the de facto top leader of the state, though sometimes this leader also holds presidency or premiership.

States where head of state differs from head of government are mainly parliamentary systems. Often a leader holds both positions in presidential systems or dictatorships. Some states have semi-presidential systems where the head of government role is fulfilled by both the listed head of government and the head of state. a regime (also "régime") is the form of government or the set of rules, cultural or social norms, etc. that regulate the operation of a government or institution and its interactions with society.

--- Original source retains full ownership of the source dataset ---

Summary

This dataset presents a comprehensive taxonomy of 3307 values expressed by Claude (an AI assistant) across hundreds of thousands of real-world conversations. Using a novel privacy-preserving methodology, these values were extracted and classified without human reviewers accessing any conversation content. The dataset reveals patterns in how AI systems express values "in the wild" when interacting with diverse users and tasks. We're releasing this resource to advance research… See the full description on the dataset page: https://huggingface.co/datasets/Anthropic/values-in-the-wild.

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