It's not a book but I really like the Elements of AI two-part course series that the University of Helskini provided (financial) support for: the two courses in the Elements of AI series consist of a pure theory course and the second course is a hands-on / applied course. Because not everyone who is seeking to learn about AI has programming skills the second course is a 'choose your own adventure' type course, with one track involving lots of programming, one 'middle of the road' option with just a touch of coding, and the other track not involving any programming whatsoever (suitable for executives, IMO).
I've recommended this course (just the first one if you're a time-constrained executive) to C-suite colleagues in the past who wanted to become more informed about ML, DL and AI, but who didn't want a deeply technical explanation a la Andrew Ng's Coursera courses or similar content.
The Elements of AI courses touch upon the statistical underpinnings of the space (there's a unit on Bayes' Theorem), the societal implications of automated decision-making process (job creation, etc.), what tasks are "doable with AI today" and which tasks are definitely _not_ doable with A(G)I, etc.
Helping non-technical folks develop an intuition about what is possible with "AI" is crucial, I think, to having a workplace and a society that can talk realistically about the benefits and detriments of robotic data processing such as ML, DL, AI.
"Real World AI" by Alyssa Simpson Rochwerger and Wilson Pang is the best book I've read on AI for people in leadership positions - it gets just enough in the weeds to really explain what's going on while still staying high level enough to address things that managers/executives would want to know. It also has several real world case studies that show both the promise and the risk of AI
I think I'm getting quite good at detecting them now. I just had to read the first five words to immediately see that something was wrong. Was fun at first reading this kind of comment but it's becoming bothersome.
It's not a book but I really like the Elements of AI two-part course series that the University of Helskini provided (financial) support for: the two courses in the Elements of AI series consist of a pure theory course and the second course is a hands-on / applied course. Because not everyone who is seeking to learn about AI has programming skills the second course is a 'choose your own adventure' type course, with one track involving lots of programming, one 'middle of the road' option with just a touch of coding, and the other track not involving any programming whatsoever (suitable for executives, IMO).
https://www.elementsofai.com/
I've recommended this course (just the first one if you're a time-constrained executive) to C-suite colleagues in the past who wanted to become more informed about ML, DL and AI, but who didn't want a deeply technical explanation a la Andrew Ng's Coursera courses or similar content.
The Elements of AI courses touch upon the statistical underpinnings of the space (there's a unit on Bayes' Theorem), the societal implications of automated decision-making process (job creation, etc.), what tasks are "doable with AI today" and which tasks are definitely _not_ doable with A(G)I, etc.
Helping non-technical folks develop an intuition about what is possible with "AI" is crucial, I think, to having a workplace and a society that can talk realistically about the benefits and detriments of robotic data processing such as ML, DL, AI.
"Real World AI" by Alyssa Simpson Rochwerger and Wilson Pang is the best book I've read on AI for people in leadership positions - it gets just enough in the weeds to really explain what's going on while still staying high level enough to address things that managers/executives would want to know. It also has several real world case studies that show both the promise and the risk of AI
I have personally enjoyed the "AI for Everything" series published by Routledge.
I believe this response was produced using chatGTP. These books don't even exist
I think I'm getting quite good at detecting them now. I just had to read the first five words to immediately see that something was wrong. Was fun at first reading this kind of comment but it's becoming bothersome.
We need John to write more books about AI