The artificial neuron, neural networks, training, gradient descent to deep nets, language and vision models, narrow, and general intelligence, generative AI
AI, strategy and business models
Digital business strategy, enterprise to eco systems, digital platforms, competition and smart connected products, business models in AI
Business value of AI:
AI-business value mechanism, value creation, AI for business functions-Marketing, Operations, and HR; and business domains-Manufacturing, and Healthcare
Algorithmic decision making
Machines for decisions, learning algorithms-decision support to decision-making, conversational agents and anthropomorphism, social structure, demographic disparity and prejudice, the spectrum of cognitive biases, social media and the echo chamber effects, the changing role of general managers; interpretability, explainability and decision stakes, accuracy vs interpretability, solutions and limitations
AI Risks
AI risk and sources, AI bias, types of bias, hallucination and jailbreaking, business-AI alignment; risk management-technological solutions: unlearning and forgetting, robustness checks, debiasing, data sharing and differential privacy
Responsible AI and regulation
Fairness and its categories, fair equality of opportunities, philosophy of policy, fairness and policy, model selection for fairness, Governance, and regulation, human values vs market-oriented regulation, AI innovation-regulation trade off, emerging regulations and compliance in select geographies