While Artificial Intelligence (AI) models can potentially transform our personal and professional lives, they pose significant challenges and risks for our society. To ensure that… Read More »ESG: The “Vital Signs” for Responsible and Ethical AI Outcomes
Interview with Egle B. Thomas, PhD, MBA After a nice four week break, the AI Think Tank Podcast is back for its 12 show. I had the… Read More »Global AI Trends In Business and Humanity – Show 12
The Harvard Business Review article “Has Generative AI Peaked?” raised a troubling concern concerning Generative AI (GenAI): “This brings us to an unsettling yet entirely… Read More »Avoid GenAI Model Collapse and Death by Averages
The current fascination with Generative AI (GenAI) – especially as manifested by OpenAI’s ChatGPT – has raised public awareness of Artificial Intelligence (AI) and its… Read More »Synergy of Generative, Analytical, Causal, and Autonomous AI
In my previous blog, “GenAI Maturity: From Productivity To Effectiveness,” I discussed the dramatic disparities between the organizational mindset of using Generative AI (GenAI) to… Read More »Nine Categories of Innovation-Driven Prompt Engineering
As I work with more organizations using Generative AI (GenAI) tools like OpenAI’s ChatGPT and Microsoft’s Copilot, I see an interesting dilemma – many organizations… Read More »GenAI Maturity: From Productivity To Effectiveness
It is unlikely that AI safety for superintelligence and artificial general intelligence could be achieved directly without a track from current risks. Already, there are… Read More »Computing: Where should AI safety for superintelligence and AGI start?
The Chief Data Officer (CDO) role has evolved significantly over the past five to seven years. It has transitioned from a CIO Mini-me, focused on… Read More »Talking to a CDO? Think Like an Economist
“It’s not the AI technologies that fail; it’s the organization.” That might be a somewhat controversial viewpoint, but it emphasizes an important truth: Artificial Intelligence… Read More »Critical Importance of Stakeholder-centric Design with AI
Training data is the cornerstone of AI algorithms – the quality of outputs is contingent on the data the AI model was trained on. The… Read More »From chaos to creation: How data labeling drives success in generative AI
