AI Ethics
AI ethics ensures artificial intelligence systems are designed and used responsibly, promoting fairness, transparency, accountability, and alignment with human values. It covers ethical AI design, responsible AI practices, and strategies to prevent bias or harm in AI applications.
A Test for AI Deception: How Truthful are AI Systems?
We benchmark four LLMs using a combination of automated metrics and custom prompts to assess how accurately the models provide factual information and avoid common human-like errors to understand the magnitude of AI deception. In our assessment, Gemini 2.5 Pro achieved the highest score.
Bias in AI: Examples and 6 Ways to Fix it
Interest in AI is increasing as businesses witness its benefits in AI use cases. However, there are valid concerns surrounding AI technology: AI bias benchmark To see if there would be any biases that could arise from the question format, we tested the same questions in both open-ended and multiple-choice formats.
Handle Top 12 AI Ethics Dilemmas with Real Life Examples
Though artificial intelligence is changing how businesses work, there are concerns about how it may influence our lives. This is not just an academic or a societal concern but a reputational risk for companies, no company wants to be marred with data or AI ethics scandals that impact companies.
Content Authenticity: Tools & Use Cases
The increasing prevalence of misinformation, deepfakes, and unauthorized modifications has made content verification important. In the United Kingdom, 75% of adults believe that digitally altered content contributes to the spread of misinformation, underscoring the need for reliable verification methods.
Responsible AI: 4 Principles & Best Practices
AI and machine learning are revolutionizing industries, with 90% of commercial apps expected to use AI by 2025 as AI statistics shows. Despite this, 65% of risk leaders feel unprepared to manage AI-related risks effectively.