Transparency - Deepstash

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Transparency means openly sharing how AI systems work, from data use to decision-making processes, fostering trust and informed user interaction.

Example - AI in Social Media: When social media platforms explain how their algorithms tailor user feeds, they promote transparency, empowering users to better control their online experience.


45 reads




Fairness in AI ensures that AI systems treat everyone equally, without bias against any gender, race, or ethnicity. It aims to prevent discrimination and promote equality.

Example - Application Tracking Systems (ATS): If an ...


49 reads



Robustness is about making AI reliable in unforeseen conditions, ensuring it performs well even when faced with challenges like data changes or attacks.

Example - Facial Recognition: A robust facial recognition system accura...


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Privacy focuses on protecting personal data from misuse or unauthorized access, emphasizing the responsible management of sensitive information.

Example - Fitbit watches: Privacy in devices like Fitbit ensures users' health ...


33 reads

Adhering to the six pillars of AI ethics — Accountability, Fairness, Explainability, Transparency, Robustness, and Privacy — ensures AI systems are developed responsibly. These principles guide organizations in using AI while safeguarding users' rights and safety. Comm...



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Accountability means making sure someone is responsible for the actions and outcomes of AI systems. It’s about being ready to fix mistakes and improve the system when needed.

Example - Self-driving vehicles: For AI-driven ca...


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Artificial Intelligence (AI) has become an integral part of our daily lives, influencing decisions from personalised recommendations to critical healthcare diagnostics. Now with the ChatGPT, LLMs and other Generative AI technologies being emerging at a jet speed, there ar...


73 reads



Explainability is about making AI's decision-making transparent, so users can understand and trust how it reaches its conclusions.

Example - AI in Finance: For an AI deciding on loan approvals, explainability means it can sh...


51 reads




Serial Entrepreneur | AI ML and Blockchain

Explore pillars of Trustworthy and Responsible AI

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Ensuring transparency and accountability in the realm of AI ethics stands as a formidable challenge, one that is central to fostering trust in AI systems and ensuring their responsible use.

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