AI Then and Now
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AI Then and Now
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AI in the late 1980s, starting with rule-based expert systems built in languages like Lisp and Prolog for Fortune 1000 companies and government agencies. Over the decades, my work has evolved from developing expert systems to integrating AI into enterprise applications, advancing through the big-data era, deep learning, and ultimately generative AI.
Later I pioneered approaches that merged knowledge management with AI, providing personalized, knowledge-driven systems. As generative AI and transformers emerged in the late 2010s and 2020s, the focus shifted toward responsible AI, AI ethics, and governance, emphasizing that advancing AI isn’t just about smarter machines—it requires guardrails to ensure alignment with human values. Without governance, AI risks scaling bad decisions at high speed, making ethical oversight essential.
Key themes: AI and the future of work, AI Strategy, Generative AI, AI governance
