Explainability in AI Accountability: From Black Boxes to Glass Boxes
Why Explainability Matters in AI Demystifying the Black Box Problem AI […]
Ethics & Policy in AI
Ethics and policy in AI focus on ensuring that artificial intelligence is developed and used responsibly, addressing issues such as privacy, bias, transparency, and accountability. Key ethical considerations include mitigating biases in AI algorithms to prevent discrimination, safeguarding personal data to protect privacy, and ensuring AI decisions are transparent and explainable. Policy measures often involve creating regulations and guidelines to govern AI development, promoting ethical standards, and fostering collaboration between governments, industry, and academia to address the societal impacts of AI
Bias in Synthetic Data: Are We Replicating Human Errors or Correcting Them?
AI infrastructures and algorithms need more and more synthetic data, so
Testing AI Sentience: Is a New Turing Test Needed?
What Is Sentience in AI, and Why Does It Matter? Defining
Invasive BCIs: What’s at Stake If Your Brain Gets Hacked?
With invasive brain-computer interfaces (BCIs) becoming a reality, the connection between
The Alignment Problem in Agentic AI: A Threat to Control?
As AI systems evolve toward more complex, autonomous decision-making, a crucial