Generative AI: Impact of Responsible AI
summary
Covers why generative AI shifts risk from research to production and what concrete controls look like: traces the model leap to Transformers (Dec 6 2017), flags 2 million AI‑generated texts per second (May 2023 forum) and Goldman Sachs’ 300 million jobs estimate, catalogs harms (deepfakes, bias, IP, adversarial relabeling with a 2020 Tesla case), and describes a seven‑year PWC Responsible AI toolkit plus monitoring and governance patterns intended to detect failures and limit deployment. Good if wanting specific risks, datasets‑as‑fuel framing, and practical mitigation examples; skip if seeking math or code.
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chapters (20)
- 0:00Introduction
- 1:09AI and generative AI basics
- 2:34Transformers and AI evolution
- 3:37AI surpassing human performance
- 4:39Super AI risks and singularity
- 6:06AI consciousness limits
- 7:11Video deepfakes with generative AI
- 9:41Ethics and bias in generative AI
- 11:49Misinformation from AI content
- 14:00AI news personalization risks
- 15:43AI goals and unintended effects
- 16:50Defining AI system goals
- 17:53IP and AI training data
- 18:34Responsible AI toolkits
- 20:22Enterprise risks and job loss
- 21:46Responsible AI regulations
- 22:30Barriers to AI adoption
- 23:12Data risks in AI
- 23:54Job loss and soft skills
- 24:57Soft skills analysis and closing
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