State of AI Report Notes Continued Challenges
The misunderstandings business leaders have about the inner workings of AI and machine learning processes could continue to hamper adoption.
Topic: Reasonable AI
Study Outlines Industry and Public AI Perceptions
Although public perception is changing, there’s still a serious disconnect. The public today still isn’t quite sure what positive benefits AI brings to …
Three Methods Researchers Use To Understand AI Decisions
Making sense of AI decisions is important to researchers, decision-makers, and the wider public. Fortunately, there are methods available to ensure we know …
The Growing Importance of Ethical Data Labeling
For data labeling to be ethical and truly successful, organizations need to ensure that the people behind the tech feel that they are involved in the world …
NIST: AI Bias Goes Way Beyond Data
NIST makes a strong argument for looking beyond data and even the ML processes to discover and destroy AI
Leveraging Knowledge Graphs to Enrich Machine Learning
By combining knowledge graphs and machine learning, organizations can extend the capabilities of ML and ensure the results derived from their models have solid …
$580M to Anyone Who Can Understand What Happens Inside Our Favorite AIs?
It is relatively common knowledge that AI systems can exhibit biases that stem from their programming and data
Algorithmic Destruction: The Ultimate Consequences of Improper Data Use
The FTC is serious about data being properly collected and used. In several cases, it has ordered what is called the algorithmic destruction of AI systems …
Challenge: Mimic Humanity in Artificial Intelligence Systems
Reliance on AI has been growing exponentially, creating urgent demand for greater transparency and trust in AI
AI Summit NYC: A Return to Normal
This year’s AI Summit returned to an in-person event where many of the sessions focused on the need for responsible AI and ethical AI to eliminate bias.
