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AI in market research may be better than the real thing

AI in market research may be better than the real thing
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Data security risks associated with AI implementation

As AI continues to transform businesses, it is crucial for organizations to prioritize data security and governance ....

Data Backup , Acceptable Use ,

How Marketers Can Incorporate Text-To-Image Generative AI Tools

To understand how generative AI tools can be used by marketing teams, I connected with Praveen Krishnamurthy, who is conducting research on this topic ....

Praveen Krishnamurthy , Owen Jones , Product Marketing Manager ,

For AI to Deliver on Its Promises, People Need to Trust It

Analysis: New tools from Google, Microsoft and others assume people are willing to trust AI to do the heavy lifting for them. ....

United States , New York , Greg Brockman , Mohsen Bayati , Sundar Pichai , Sam Altman , Arun Chandrasekaran , Hanan Hibshi , Scarlett Johansson , Meta Cambridge Analytica , Robert Seamans , Carnegie Mellon University Information Networking Institute , Google Finally Feels Likea Search Company , Bentley University , Stanford Graduate School Of Business , New York Times , Pew Research , York University Stern School Of Business , Cambridge Analytica , Big Tech , Google Finally Feels Like , Research Company , Gemini Live , Gemini Nano , Copilot Plus , Stanford Graduate School ,

Information | Free Full-Text | Privacy and Security Mechanisms for B2B Data Sharing: A Conceptual Framework

In the age of digitalization, business-to-business (B2B) data sharing is becoming increasingly important, enabling organizations to collaborate and make informed decisions as well as simplifying operations and hopefully creating a cost-effective virtual value chain. This is crucial to the success of modern businesses, especially global business. However, this approach also comes with significant privacy and security challenges, thus requiring robust mechanisms to protect sensitive information. After analyzing the evolving status of B2B data sharing, the purpose of this study is to provide insights into the design of theoretical framework solutions for the field. This study adopts technologies including encryption, access control, data anonymization, and audit trails, with the common goal of striking a balance between facilitating data sharing and protecting data confidentiality as well as data integrity. In addition, emerging technologies such as homomorphic encryption, blockchain, and ....

Cheng Xu , Matt Blaze , Kete Wang , Permissioned Blockchain , Data Storage Technology , Service Daa , Research Significance , Linux Foundation , Data Encryption Technology , General Data Protection Regulation , Hyperledger Fabric , Peer To Electronic Cash System , Practical Byzantine Fault Tolerance , Data Storage , Data Encryption , Access Control , Data Access , Transaction Audit , Hyperledger Project , Privacy Preservation ,