Brands, publishers, MarTech vendors, and beyond recently gathered in NYC for Advertising Week and swapped ideas on the future of marketing and advertising. The overarching message from many brands was one we’ve heard before: First-party data is like gold, especially for personalization. But it takes more than “owning” the data to make it valuable. Scale and accuracy […]
Ask a Data Ethicist: How Can You Learn More About Data and AI Ethics?
It was about this time last year that I pitched the team at DATAVERSITY the idea of this monthly column on data ethics. There’s certainly been no shortage of interesting questions to cover and I’ve enjoyed writing about both the practical and more philosophical aspects of this topic. As we wrap up this year and […]
The Growing Importance of AI Governance
New technologies often engender fear and foreboding among people outside tech industries. The latest example of this trend is artificial intelligence (AI), which is a topic of much concern and misunderstanding among the public. It’s easy to dismiss these qualms as the common human tendency to mistrust the unknown. However, much of the alarm about AI […]
Synthetic Data Generation: Addressing Data Scarcity and Bias in ML Models
There is no doubt that machine learning (ML) is transforming industries across the board, but its effectiveness depends on the data it’s trained on. The ML models traditionally rely on real-world datasets to power the recommendation algorithms, image analysis, chatbots, and other innovative applications that make it so transformative. However, using actual data creates two significant challenges […]
Book of the Month: “AI Governance Comprehensive”
Welcome to December 2024’s “Book of the Month” column. This month, we’re featuring “AI Governance Comprehensive: Tools, Vendors, Controls, and Regulations” by Sunil Soares, available for free download on the YourDataConnect (YDC) website. This book offers readers a strong foundation in AI governance. While the emergence of generative AI (GenAI) has brought AI governance to […]
Essential Components for Effective Data Management in the AI Era
Imagine a world where your data not only tells a story but also anticipates your next move – this is the promise of effective data management in the AI era. As organizations try to deal with vast amounts of information, three key components have emerged as essential for unlocking the full potential of data: metadata, […]
AI Data Governance Spotlights Privacy and Quality
The emergence of artificial intelligence (AI) brings data governance into sharp focus because grounding large language models (LLMs) with secure, trusted data is the only way to ensure accurate responses. So, what exactly is AI data governance? Let’s define “AI data governance” as the process of managing the data product lifecycle within AI systems. To keep it […]
Unreliable Data Is Essential for AI Progress, and That’s Not a Bad Thing
In May, OpenAI announced a partnership with Reddit to train its language models using the forum’s extensive collection of user-generated content. OpenAI’s goal of enhancing its models’ ability to respond to real-world conversations and diverse linguistic patterns seemed straightforward. But the decision quickly sparked concerns – namely, the potential inclusion of misinformation and biased content in the […]
The AI Paradox: Why Investment Doesn’t Guarantee Success Without Privacy and Security
Year after year, organizations across industries have continued to push the limits of their technology capabilities through the increased adoption of AI. To put this into perspective, global investments in AI more than doubled in 2023, reaching $200 billion, and the market is now expected to reach a valuation of nearly $2 trillion within the next […]
Evolving Data Governance in the Age of AI: Insights from Industry Experts
The AI revolution isn’t coming: It’s here, and organizational governance structures are woefully unprepared. While 64% of businesses expect AI to increase productivity, most AI models fail. This result highlights a stark gap between potential and reality. Getting timely and usable data sets for AI training and analysis is crucial for becoming data-driven. At the heart of this multi-faceted challenge lies […]