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?

AI EthicsOct 27

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.

AI EthicsOct 23

Generative AI Ethics: Concerns and How to Manage Them?

Generative AI raises important concerns about how knowledge is shared and trusted. Britannica, for instance, has accused Perplexity of reusing its content without consent and even attaching its name to inaccurate answers, showing how these technologies can blur the lines between reliable sources and AI-generated text.

AI EthicsOct 10

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.

AI EthicsOct 10

Handle AI Ethics Dilemmas with Frameworks & Tools

Warner Bros. is suing Midjourney, alleging that its AI image generator unlawfully reproduces copyrighted characters, including Superman and Batman. The lawsuit highlights a broader issue: AI systems trained on copyrighted works raise significant concerns about ownership, fairness, and accountability.

AI EthicsAug 25

Bias in AI: Examples and 6 Ways to Fix it

Interest in AI is increasing as businesses witness its benefits in AI use cases.

AI EthicsAug 23

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.