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'AI just feels like another frontier of exclusion' – Sidrah Hassan
In this episode of The AI Lyceum®, Samraj Matharu speaks with Sidrah Hassan, AI Governance and AI Ethics Specialist, about inclusive AI, AI ethics, AI governance, algorithmic bias, trust in AI, transparency, human oversight, and responsible AI in practice.
Sidrah is an AI Governance and Ethics Manager at Kainos, an AI Ethics and Strategy Advisor at Ethical AI Alliance, and has also worked across AI ethics, product, and public education through roles at AND Digital, BBC Scotland, and the AI Safety Collab by ENAIS.
We explore how large language models can reinforce gender bias and racial bias, why inclusive AI must go beyond good intentions, and what trustworthy AI really looks like when systems are used in the real world. The conversation covers training data, representation gaps, AI harms, accountability, human-in-the-loop decision-making, and the challenge of building AI systems that serve people fairly.
Sidrah also discusses agentic AI, AI in healthcare, economic displacement, and the role of storytelling in surfacing subtle harms that are often missed by technical frameworks alone. She explains the thinking behind the AI Harms Map and why lived experience matters when assessing the real impact of AI systems.
This episode is for anyone interested in AI ethics, AI governance, responsible AI, inclusive AI, trustworthy AI, bias in AI systems, AI transparency, and the future of human-centred technology.
EPISODE HIGHLIGHTS
0:00 ➤ Intro / Guest Welcome
1:09 ➤ What inclusive AI looks like in everyday systems
4:34 ➤ LLM bias, training data, and representation gaps
7:09 ➤ How to improve inclusivity in AI
11:00 ➤ What trust in AI really means
13:01 ➤ Building trust in AI systems
20:13 ➤ Is AI ethics a distinct field?
30:17 ➤ Agentic AI, safety, and security
32:45 ➤ Storytelling, lived experience, and AI harms
43:10 ➤ Economic displacement and the future of work
50:21 ➤ AI in healthcare and human judgment
1:00:03 ➤ The AI Harms Map
1:03:48 ➤ A closing question on data and AI use
YouTube
https://www.youtube.com/@The.AI.Lyceum
Spotify
https://open.spotify.com/show/034vux8EWzb9M5Gn6QDMza
Apple
https://podcasts.apple.com/us/podcast/the-ai-lyceum/id1837737167
Amazon
https://music.amazon.com/podcasts/5a67f821-89f8-4b95-b873-2933ab977cd3/the-ai-lyceum
Website
https://theailyceum.com
#AI #AIEthics #AIGovernance #InclusiveAI #ResponsibleAI #TrustworthyAI #AlgorithmicBias #AgenticAI #TheAILyceum
By Samraj Matharu'AI just feels like another frontier of exclusion' – Sidrah Hassan
In this episode of The AI Lyceum®, Samraj Matharu speaks with Sidrah Hassan, AI Governance and AI Ethics Specialist, about inclusive AI, AI ethics, AI governance, algorithmic bias, trust in AI, transparency, human oversight, and responsible AI in practice.
Sidrah is an AI Governance and Ethics Manager at Kainos, an AI Ethics and Strategy Advisor at Ethical AI Alliance, and has also worked across AI ethics, product, and public education through roles at AND Digital, BBC Scotland, and the AI Safety Collab by ENAIS.
We explore how large language models can reinforce gender bias and racial bias, why inclusive AI must go beyond good intentions, and what trustworthy AI really looks like when systems are used in the real world. The conversation covers training data, representation gaps, AI harms, accountability, human-in-the-loop decision-making, and the challenge of building AI systems that serve people fairly.
Sidrah also discusses agentic AI, AI in healthcare, economic displacement, and the role of storytelling in surfacing subtle harms that are often missed by technical frameworks alone. She explains the thinking behind the AI Harms Map and why lived experience matters when assessing the real impact of AI systems.
This episode is for anyone interested in AI ethics, AI governance, responsible AI, inclusive AI, trustworthy AI, bias in AI systems, AI transparency, and the future of human-centred technology.
EPISODE HIGHLIGHTS
0:00 ➤ Intro / Guest Welcome
1:09 ➤ What inclusive AI looks like in everyday systems
4:34 ➤ LLM bias, training data, and representation gaps
7:09 ➤ How to improve inclusivity in AI
11:00 ➤ What trust in AI really means
13:01 ➤ Building trust in AI systems
20:13 ➤ Is AI ethics a distinct field?
30:17 ➤ Agentic AI, safety, and security
32:45 ➤ Storytelling, lived experience, and AI harms
43:10 ➤ Economic displacement and the future of work
50:21 ➤ AI in healthcare and human judgment
1:00:03 ➤ The AI Harms Map
1:03:48 ➤ A closing question on data and AI use
YouTube
https://www.youtube.com/@The.AI.Lyceum
Spotify
https://open.spotify.com/show/034vux8EWzb9M5Gn6QDMza
Apple
https://podcasts.apple.com/us/podcast/the-ai-lyceum/id1837737167
Amazon
https://music.amazon.com/podcasts/5a67f821-89f8-4b95-b873-2933ab977cd3/the-ai-lyceum
Website
https://theailyceum.com
#AI #AIEthics #AIGovernance #InclusiveAI #ResponsibleAI #TrustworthyAI #AlgorithmicBias #AgenticAI #TheAILyceum