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Is the Algorithm Plotting Against Us? A Layperson's Guide to the Concepts, Math, and Pitfalls of AI
Artificial intelligence is everywhere—it’s in our houses and phones and cars. AI makes decisions about what we should buy, watch, and read, and it won’t be long before AI’s in our hospitals, combing through our records. Maybe soon it will even be deciding who’s innocent, and who goes to jail . . .
But most of us don't understand how AI works. We hardly know what it is.
In Is the Algorithm Plotting Against Us?, AI expert Kenneth Wenger deftly explains the complexity at AI’s heart, demonstrating its potential and exposing its shortfalls. Wenger empowers readers to answer the question—What exactly is AI?—at a time when its hold on tech, society, and our imagination is only getting stronger.
Kenneth Wenger is senior director of research and innovation at CoreAVI and chief technology officer at Squint AI. His work focuses on the intersection of artificial intelligence and determinism, enabling neural networks to execute in safety critical systems. Beyond the research, his interests lie in people and how technology affects society. He lives with his family in Mississauga, Ontario.
But most of us don't understand how AI works. We hardly know what it is.
In Is the Algorithm Plotting Against Us?, AI expert Kenneth Wenger deftly explains the complexity at AI’s heart, demonstrating its potential and exposing its shortfalls. Wenger empowers readers to answer the question—What exactly is AI?—at a time when its hold on tech, society, and our imagination is only getting stronger.
Kenneth Wenger is senior director of research and innovation at CoreAVI and chief technology officer at Squint AI. His work focuses on the intersection of artificial intelligence and determinism, enabling neural networks to execute in safety critical systems. Beyond the research, his interests lie in people and how technology affects society. He lives with his family in Mississauga, Ontario.
264 pages, Hardcover
Published May 1, 2023
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Displaying 1 - 15 of 15 reviews
April 7, 2023
At a crucial moment, this book expands the conversation around AI to the broader public. A brief history of AI is provided; giving context to the current state-of-the-art in algorithms. It introduces critical concepts in an easy-to-read format with examples, diagrams, and plots. Through real-life tasks (e.g. image classification, language translation) and publicly available data, algorithms (e.g. convolutional neural networks) are explained to help the reader understand the “black box” that is AI. Mathematical theory and concepts that form the basis of AI algorithms are described to help readers connect concepts with, perhaps, their own mathematical training. This book includes numerous bibliographical references and resources that one may find useful for delving into more profound aspects of AI.
April 16, 2023
While this was such an easy read, I still walked away from this book with a much bigger picture of both AI's advantages and pitfalls. I feel much more equipped to make my own opinions and decisions surrounding AI now. I was especially engrossed in the book when Wenger talked about how neural networks work - went from just /imagining/ how AI works to actually /knowing/ how AI works - pretty incredible.
April 29, 2023
With the exception of a brief period during my dissertation (and it was 1996 so the last century) during which my path was hindered by neural networks, I had not read anything more about it, much less become informed/concerned about the current debate on AI.
This book not only traces the history of neural networks, the larger biases they incur because of how they work, but how from them we then came to talk about artificial intelligence. Not that I haven't seen Terminator, on the contrary, but let's just say that for now I see it a bit like the author, and I would say that it seems rather premature to pose the problem of artificial intelligence consciously deciding to destroy us, considering that we still don't understand what consciousness in humans consists of.
Clearly, however, the book is by no means easy to being summed up in these few words, but what is very appreciable in my opinion is the author's attempt to explain the functioning of the algorithms underlying convolutional neural networks (CNNs) and how they could be used in the medical field, for example, where they could greatly accelerate the discovery of tumors for example or facilitate a diagnosis based on a CT scan or PET scan.
Clearly, because the author is a serious person, there are also the various situations where the inferences, and thus the conclusions that the linear regression algorithms were arriving at, were absolutely wrong because they were poorly constructed from initial assumptions, and far from ready for a Skynet-like conspiracy.
Con l'eccezione di un breve periodo durante la mia tesi di laurea (e correva il 1996 quindi il secolo scorso) durante il quale il mio percorso é stato intralciato dalle reti neurali, non mi era piú capitato di leggere qualcosa a riguardo e tanto meno di informarmi/preoccuparmi dell'attuale dibattito sull'IA.
Questo libro non solo ripercorre la storia delle reti neurali, dei bias piú grandi nei quali incorrono per via del loro funzionamento, ma di come da esse siamo arrivati poi a parlare di intelligenza artificiale. Non che io non abbia visto Terminator, anzi, ma diciamo che per ora la vedo un po' come l'autore e direi che mi sembra piuttosto prematuro porsi il problema di un'intelligenza artificiale che coscientemente decida di distruggerci, considerato che ancora non abbiamo capito in cosa consista la coscienza negli esseri umani.
Chiaramente peró il libro non é affatto riassumibile in queste poche parole, ma quello che é molto apprezzabile secondo me, é il tentativo dell'autore di spiegare il funzionamento degli algoritmi alla base delle reti neurali convolute (CNN) e di come questi possano essere utilizzati per esempio in ambito medico, dove potrebbero accelerare di molto la scoperta dei tumori per esempio o agevolare una diagnosi basata su una tac o una pet.
Chiaramente, siccome l'autore é una persona seria, ci sono anche le varie situazioni in cui le inferenze e quindi le conclusioni a cui arrivavano gli algoritmi delle regressioni lineari, erano assolutamente sbagliate perché mal costruite a partire dalle ipotesi, e lungi dall'essere pronti per un complotto tipo Skynet.
I received from the Publisher a complimentary digital advanced review copy of the book in exchange for a honest review.
This book not only traces the history of neural networks, the larger biases they incur because of how they work, but how from them we then came to talk about artificial intelligence. Not that I haven't seen Terminator, on the contrary, but let's just say that for now I see it a bit like the author, and I would say that it seems rather premature to pose the problem of artificial intelligence consciously deciding to destroy us, considering that we still don't understand what consciousness in humans consists of.
Clearly, however, the book is by no means easy to being summed up in these few words, but what is very appreciable in my opinion is the author's attempt to explain the functioning of the algorithms underlying convolutional neural networks (CNNs) and how they could be used in the medical field, for example, where they could greatly accelerate the discovery of tumors for example or facilitate a diagnosis based on a CT scan or PET scan.
Clearly, because the author is a serious person, there are also the various situations where the inferences, and thus the conclusions that the linear regression algorithms were arriving at, were absolutely wrong because they were poorly constructed from initial assumptions, and far from ready for a Skynet-like conspiracy.
Con l'eccezione di un breve periodo durante la mia tesi di laurea (e correva il 1996 quindi il secolo scorso) durante il quale il mio percorso é stato intralciato dalle reti neurali, non mi era piú capitato di leggere qualcosa a riguardo e tanto meno di informarmi/preoccuparmi dell'attuale dibattito sull'IA.
Questo libro non solo ripercorre la storia delle reti neurali, dei bias piú grandi nei quali incorrono per via del loro funzionamento, ma di come da esse siamo arrivati poi a parlare di intelligenza artificiale. Non che io non abbia visto Terminator, anzi, ma diciamo che per ora la vedo un po' come l'autore e direi che mi sembra piuttosto prematuro porsi il problema di un'intelligenza artificiale che coscientemente decida di distruggerci, considerato che ancora non abbiamo capito in cosa consista la coscienza negli esseri umani.
Chiaramente peró il libro non é affatto riassumibile in queste poche parole, ma quello che é molto apprezzabile secondo me, é il tentativo dell'autore di spiegare il funzionamento degli algoritmi alla base delle reti neurali convolute (CNN) e di come questi possano essere utilizzati per esempio in ambito medico, dove potrebbero accelerare di molto la scoperta dei tumori per esempio o agevolare una diagnosi basata su una tac o una pet.
Chiaramente, siccome l'autore é una persona seria, ci sono anche le varie situazioni in cui le inferenze e quindi le conclusioni a cui arrivavano gli algoritmi delle regressioni lineari, erano assolutamente sbagliate perché mal costruite a partire dalle ipotesi, e lungi dall'essere pronti per un complotto tipo Skynet.
I received from the Publisher a complimentary digital advanced review copy of the book in exchange for a honest review.
May 22, 2023
I received a copy of this book from the publisher in exchange for an honest review.
Everyone's talking about AI and often it is with a sense of fear and paranoia. Many people hear the term and envision some dystopian landscape like I, Robot or The Matrix, rather than recognizing that AI is already present in our everyday lives, from language processing platforms (chatbots, ChatGPT) and targeted marketing (those hyperspecific ads as you scroll your social media) to self-driving cars and manufacturing robots.
This book's subtitle says the information inside is geared toward a layperson, and I have a bit of an issue with that. I suppose the problem there is with the term itself, as in who falls into that category. I have what I would consider an "intermediate beginner" knowledge regarding AI, in that I have taken several college courses on computer programming, am scientifically literate, and try to read any news articles regarding the topic. This book definitely tested my intelligence (lots of data sets, math, and statistical models) and to be honest, was probably about two levels over my head. I enjoyed the challenge of diving into this subject but my eyes definitely glazed over in spots. This is no fault of the author, but rather a note toward this book's intended audience. I would suggest this to readers with intermediate or advanced knowledge of AI.
Come chat with me about books here, too:
Blog | Instagram
Everyone's talking about AI and often it is with a sense of fear and paranoia. Many people hear the term and envision some dystopian landscape like I, Robot or The Matrix, rather than recognizing that AI is already present in our everyday lives, from language processing platforms (chatbots, ChatGPT) and targeted marketing (those hyperspecific ads as you scroll your social media) to self-driving cars and manufacturing robots.
This book's subtitle says the information inside is geared toward a layperson, and I have a bit of an issue with that. I suppose the problem there is with the term itself, as in who falls into that category. I have what I would consider an "intermediate beginner" knowledge regarding AI, in that I have taken several college courses on computer programming, am scientifically literate, and try to read any news articles regarding the topic. This book definitely tested my intelligence (lots of data sets, math, and statistical models) and to be honest, was probably about two levels over my head. I enjoyed the challenge of diving into this subject but my eyes definitely glazed over in spots. This is no fault of the author, but rather a note toward this book's intended audience. I would suggest this to readers with intermediate or advanced knowledge of AI.
Come chat with me about books here, too:
Blog | Instagram
April 26, 2023
A fantastic book written by an author who has an amazing knack for taking an incredibly complex subject matter and explaining it in a way that is very digestible for your average AI layperson. As someone just starting to wrap my head around this subject, I found Ken’s book to be extremely insightful and knowledgeable, while not going completely over my head. He writes with style and humour too! A great read that I would recommend to anyone who wants to better understand AI!
June 5, 2023
If you have any awareness of current science events, technological advances, social or public conversations, or media editorials, then you have read something about Artificial Intelligence, or AI. The discussion, highly public, held at a high level, and freighted with far-reaching statements by all involved, all too often—and very unfortunately—features sweeping gloom-and-doom pronouncements. These statements are like catnip to media outlets which crave them for the clicks they can get, but do very little to illuminate a very important emerging technology.
Cutting through this thicket is well worth it. This is where Kenneth Wenger comes in. He’s the director of research and innovation at CoreAVI and chief technology officer at Squint AI. His book, Is the Algorithm Plotting Against Us?, is a tonic. It’s a very useful and well-laid-out primer on the nuts and bolts of AI, and a convincing agenda for informing the discussion of many of the concerns being expressed.
He makes the logical assumption that his audience knows nothing about computer science, the structure of microchips, or the architecture of neural networks. And yes, he will lead you step by step to a good grounding in the science and technology of it all. Concise, highly readable, and logical, he takes his readers from ground zero to a good basic understanding of the pitfalls and the potential of this technology. That is the main reason he sat down to his word processor, and the chief virtue of the book. He is eminently successful at the task he set for himself.
Without digging too deeply into the normative social issues—you should read the book!—Wenger gives the reader a crystal-clear perspective on current problems, and thereby establishes where the current debate should be. While acknowledging the sometimes rash and far-fetched statements made by scientists and “thought leaders,” Wenger would have us focus on current problems besetting this technology, which is in its infancy. His finishing touch is polemical, in fact, since he has observed, and has grave doubts about, some of the applications to which AI has been put.
I could go on, because I enjoyed and value this book very much, but I would make a hash of it: I would never be able in a review of this length to present the flow and logic as elegantly as he does. There is a fair amount of math in it, but don’t let that put you off! Wenger always explains it, and always in terms that an 8th-Grade math student could follow.
If you want to follow the public debate, or if you want to participate in discussions with friends and family, this book is a superb place to start. It’s a straightforward, basic guide not only to the brand-new technology, but to the social issues surrounding it. Wonderful! Take it up!
https://bassoprofundo1.blogspot.com/2...
Cutting through this thicket is well worth it. This is where Kenneth Wenger comes in. He’s the director of research and innovation at CoreAVI and chief technology officer at Squint AI. His book, Is the Algorithm Plotting Against Us?, is a tonic. It’s a very useful and well-laid-out primer on the nuts and bolts of AI, and a convincing agenda for informing the discussion of many of the concerns being expressed.
He makes the logical assumption that his audience knows nothing about computer science, the structure of microchips, or the architecture of neural networks. And yes, he will lead you step by step to a good grounding in the science and technology of it all. Concise, highly readable, and logical, he takes his readers from ground zero to a good basic understanding of the pitfalls and the potential of this technology. That is the main reason he sat down to his word processor, and the chief virtue of the book. He is eminently successful at the task he set for himself.
Without digging too deeply into the normative social issues—you should read the book!—Wenger gives the reader a crystal-clear perspective on current problems, and thereby establishes where the current debate should be. While acknowledging the sometimes rash and far-fetched statements made by scientists and “thought leaders,” Wenger would have us focus on current problems besetting this technology, which is in its infancy. His finishing touch is polemical, in fact, since he has observed, and has grave doubts about, some of the applications to which AI has been put.
I could go on, because I enjoyed and value this book very much, but I would make a hash of it: I would never be able in a review of this length to present the flow and logic as elegantly as he does. There is a fair amount of math in it, but don’t let that put you off! Wenger always explains it, and always in terms that an 8th-Grade math student could follow.
If you want to follow the public debate, or if you want to participate in discussions with friends and family, this book is a superb place to start. It’s a straightforward, basic guide not only to the brand-new technology, but to the social issues surrounding it. Wonderful! Take it up!
https://bassoprofundo1.blogspot.com/2...
May 31, 2023
Book Review
Title: Is the Algorithm Plotting Against Us?: A Layperson's Guide to the Concepts, Math, and Pitfalls of AI by Kenneth Wenger
Genre: Non-Fiction, Technology
Rating: 3.75 Stars
The opening to this book was interesting as it has the aim of educating the reader about AI and the mathematics involved behind the scenes. The author rightly states that the media overexaggerates how far AI has come in recent years leading to a lot of fear and misunderstanding about what AI actually is. Now I don’t normally delve into technology because I don’t understand a lot of the technical aspects but since this is supposed to be a layman’s guide I thought I would give it a try.
Chapter 1 introduces us to the idea of polarization and its consequences, it begins by introducing us to the history of the human mind. We look at how the neuron was discovered and how we learnt of its function and while this alone was an amazing leap in science for humankind, it links even further with how these neuron pathways were used as the basis for almost all modern technology that we have today. McCulloch-Pitts developed the artificial neuron using logic gates and almost all modern technology is based on logic gates. The simplest logic gates are NOT AND and OR, AND gates are used in heavy machinery and are essentially used as a double switch safety function, so the machine will not operate unless both of these switches are “on”. NOT gates are used as signal inverters commonly found in car fuel sensors. The sensor detects the fuel level and when it falls below the sensor’s range then it indicates using a switch that fuel needs to be added. OR gates are used in simple payment systems where the person can pay by either cash or card like in train stations. If no payment is made the gate remained closed but once either payment is made the gate opens.
These logic gates can also be combined to make complex circuit systems, if enough are combined you can build modern computers. Logic gates are also the backbone of most programming languages and it was here that scientists realised that the logic gates could be paired with the artificial neuron and could theoretically produce a functioning model of the human brain. However, it was soon realised that binary inputs were a drawback and this led to Donald Hebb introducing Hebbian learning. Hebbian learning proposed that neurons firing together, strengthened connections between them and was vital to the learning process. For the artificial neuron they realised they had to give weight to the connections and this meant you could fine tune the neuron by adding or decreasing the weight of a connection. Frank Rosenblatt went one step further and developed the perceptron.
The perceptron changed the binary input to a value between 0 and 1 which was more closely aligned with biological neurons. Through this two approaches to creating models were developed: monotypic and genotypic. Monotypic is non adaptable while genotypic is, this meant monotypic was used for studying the brain with a specific set of inputs and desired outputs while genotypic uses well defined functions and compares these to the artificial system. The genotypic approach allows more flexibility in artificial networks and this showed the human mind relied on a statistical system rather than decision based one. For those working on artificial systems this offered a reduction in the number of systems needed for artificial intelligence. In reality, the human brain actually used both systems as it uses specific algorithms for special functions and generical algorithms for most other functions. This introduces the idea of a bias and we are focusing heavily on the input/output process.
The perceptron actually had many practical applications as it was first used in IBM 704 software for punch cards. This software distinguished cards punched on the left versus the right and was later designed for image recognition for images up to 20x20 pixels which developed further into a system that could eliminate noise from phone lines. These systems were ADALINE and MADALINE which are still used today, although it was later pointed out the single-layer perceptron couldn’t implement the XOR logic gate. The single-layer perceptron only solves linear problems and most problems aren’t linearly separable so system needed to be adapted again and this was the beginning of the AI winter.
The book goes into much greater depth about how AI actually work, however, I did find that have a good understanding of either mathematics or computers would be extremely helpful when reading. While it claims to be a layman’s guide, it does get very technical and while the author does their best to explain it I found myself struggling at times. Overall, I found the book to be informative and interesting but slightly too technical to be a true layman’s guide to AI. If you have a background in maths or computer science then this might be the perfect read for you.
Title: Is the Algorithm Plotting Against Us?: A Layperson's Guide to the Concepts, Math, and Pitfalls of AI by Kenneth Wenger
Genre: Non-Fiction, Technology
Rating: 3.75 Stars
The opening to this book was interesting as it has the aim of educating the reader about AI and the mathematics involved behind the scenes. The author rightly states that the media overexaggerates how far AI has come in recent years leading to a lot of fear and misunderstanding about what AI actually is. Now I don’t normally delve into technology because I don’t understand a lot of the technical aspects but since this is supposed to be a layman’s guide I thought I would give it a try.
Chapter 1 introduces us to the idea of polarization and its consequences, it begins by introducing us to the history of the human mind. We look at how the neuron was discovered and how we learnt of its function and while this alone was an amazing leap in science for humankind, it links even further with how these neuron pathways were used as the basis for almost all modern technology that we have today. McCulloch-Pitts developed the artificial neuron using logic gates and almost all modern technology is based on logic gates. The simplest logic gates are NOT AND and OR, AND gates are used in heavy machinery and are essentially used as a double switch safety function, so the machine will not operate unless both of these switches are “on”. NOT gates are used as signal inverters commonly found in car fuel sensors. The sensor detects the fuel level and when it falls below the sensor’s range then it indicates using a switch that fuel needs to be added. OR gates are used in simple payment systems where the person can pay by either cash or card like in train stations. If no payment is made the gate remained closed but once either payment is made the gate opens.
These logic gates can also be combined to make complex circuit systems, if enough are combined you can build modern computers. Logic gates are also the backbone of most programming languages and it was here that scientists realised that the logic gates could be paired with the artificial neuron and could theoretically produce a functioning model of the human brain. However, it was soon realised that binary inputs were a drawback and this led to Donald Hebb introducing Hebbian learning. Hebbian learning proposed that neurons firing together, strengthened connections between them and was vital to the learning process. For the artificial neuron they realised they had to give weight to the connections and this meant you could fine tune the neuron by adding or decreasing the weight of a connection. Frank Rosenblatt went one step further and developed the perceptron.
The perceptron changed the binary input to a value between 0 and 1 which was more closely aligned with biological neurons. Through this two approaches to creating models were developed: monotypic and genotypic. Monotypic is non adaptable while genotypic is, this meant monotypic was used for studying the brain with a specific set of inputs and desired outputs while genotypic uses well defined functions and compares these to the artificial system. The genotypic approach allows more flexibility in artificial networks and this showed the human mind relied on a statistical system rather than decision based one. For those working on artificial systems this offered a reduction in the number of systems needed for artificial intelligence. In reality, the human brain actually used both systems as it uses specific algorithms for special functions and generical algorithms for most other functions. This introduces the idea of a bias and we are focusing heavily on the input/output process.
The perceptron actually had many practical applications as it was first used in IBM 704 software for punch cards. This software distinguished cards punched on the left versus the right and was later designed for image recognition for images up to 20x20 pixels which developed further into a system that could eliminate noise from phone lines. These systems were ADALINE and MADALINE which are still used today, although it was later pointed out the single-layer perceptron couldn’t implement the XOR logic gate. The single-layer perceptron only solves linear problems and most problems aren’t linearly separable so system needed to be adapted again and this was the beginning of the AI winter.
The book goes into much greater depth about how AI actually work, however, I did find that have a good understanding of either mathematics or computers would be extremely helpful when reading. While it claims to be a layman’s guide, it does get very technical and while the author does their best to explain it I found myself struggling at times. Overall, I found the book to be informative and interesting but slightly too technical to be a true layman’s guide to AI. If you have a background in maths or computer science then this might be the perfect read for you.
This entire review has been hidden because of spoilers.
May 19, 2023
Is the Algorithm Plotting Against Us? by Kenneth Wenger is a wonderful overview, or introduction depending on your previous knowledge, of the history and current state of AI functionality as well as a glimpse both at the ethics of current and future uses.
While my first degrees were in EE which, at the time, included the burgeoning field of computer science (I had to start more Fortran programs over because someone knocked all the punch cards off my desk), once I went back to school in the 90s in the humanities my math skills have slowly deteriorated. This book does an excellent job of making the math as well as the logic of AI understandable for any reader who is interested. Depending on what you're bringing to the book, it is still going to take being an active reader to get the most from it, but it is quite accessible and actually a very engaging read.
We all need to have some understanding of what is and is not, at this point, possible with AI, as well as where it could go and whether we want it to go there. There are plenty of over-the-top "news" stories that overblow either the advantages or the pitfalls, designed to make their readers either oppose or welcome the technology with blinders on. It is our responsibility to have at least a basic knowledge so we can voice our opinions, and have those opinions make sense based on what actually is. Wenger has given us just such a resource, one that arms us with a solid foundation whether we want to dive deeper or simply maintain a layperson's level of understanding. We have to be informed in order to make informed decisions.
While this is certainly an excellent introduction for those with no real understanding of what AI actually is, it is also a valuable text for those with some decent understanding but perhaps has focused so much on one aspect that the big picture has become hazy. In other words, this is for any reader with an interest in AI and our future, no matter what your current level of understanding may be.
Reviewed from a copy made available by the author via Edelweiss.
While my first degrees were in EE which, at the time, included the burgeoning field of computer science (I had to start more Fortran programs over because someone knocked all the punch cards off my desk), once I went back to school in the 90s in the humanities my math skills have slowly deteriorated. This book does an excellent job of making the math as well as the logic of AI understandable for any reader who is interested. Depending on what you're bringing to the book, it is still going to take being an active reader to get the most from it, but it is quite accessible and actually a very engaging read.
We all need to have some understanding of what is and is not, at this point, possible with AI, as well as where it could go and whether we want it to go there. There are plenty of over-the-top "news" stories that overblow either the advantages or the pitfalls, designed to make their readers either oppose or welcome the technology with blinders on. It is our responsibility to have at least a basic knowledge so we can voice our opinions, and have those opinions make sense based on what actually is. Wenger has given us just such a resource, one that arms us with a solid foundation whether we want to dive deeper or simply maintain a layperson's level of understanding. We have to be informed in order to make informed decisions.
While this is certainly an excellent introduction for those with no real understanding of what AI actually is, it is also a valuable text for those with some decent understanding but perhaps has focused so much on one aspect that the big picture has become hazy. In other words, this is for any reader with an interest in AI and our future, no matter what your current level of understanding may be.
Reviewed from a copy made available by the author via Edelweiss.
May 18, 2023
I am a former humanities major working in education that enjoys reading introductory STEM books written by professionals in the field. My knowledge of AI and the math behind it is minimal, and while it does seem intimidating I was curious about the concepts behind it and how it works.
Is the Algorithm Plotting Against Us shows us the basic history of innovation that led to artificial intelligence as we know it today and the neural networks and mathematical concepts behind them. It helps us understand the essentials behind discerning the uses of artificial intelligence, current concerns, and limitations. Wenger sought to inform the "layperson" on how to understand the concepts behind artificial intelligence and where actual concerns could and should be placed, and I think that was accomplished as my "one-mandatory-college-statistics-course self" managed to follow along.
Overall, it is a good introductory book into the language and world of artificial intelligence for those of us who are not educated in this field. I think the basic understanding I gained from some of the concepts presented has made me feel more confident in understanding some of the limitations and current concerns present in the use of artificial intelligence. I appreciate a beginner-friendly book that can illustrate how artificial intelligence affects us now and how it can affect us in the future.
I was sent a free book and am voluntarily leaving my honest review.
Is the Algorithm Plotting Against Us shows us the basic history of innovation that led to artificial intelligence as we know it today and the neural networks and mathematical concepts behind them. It helps us understand the essentials behind discerning the uses of artificial intelligence, current concerns, and limitations. Wenger sought to inform the "layperson" on how to understand the concepts behind artificial intelligence and where actual concerns could and should be placed, and I think that was accomplished as my "one-mandatory-college-statistics-course self" managed to follow along.
Overall, it is a good introductory book into the language and world of artificial intelligence for those of us who are not educated in this field. I think the basic understanding I gained from some of the concepts presented has made me feel more confident in understanding some of the limitations and current concerns present in the use of artificial intelligence. I appreciate a beginner-friendly book that can illustrate how artificial intelligence affects us now and how it can affect us in the future.
I was sent a free book and am voluntarily leaving my honest review.
April 19, 2023
Ken's book, Is the Algorithm Plotting Against us? is all about providing everyone access to the how, the why, and the rest of all the questions you may be asking yourself when you hear the terms neural networks and AI. There are many interesting facts about AI I learned and lots of the background to it I think will allow everyone to become more familiar and speak intelligently on these subjects. Great for all the IT professionals out there in distribution and more.
May 22, 2023
I enjoyed this book. Unlike other books I’ve read on AI, this book actually explains how AI works. It’s based on statistics and probability, and the book goes into quite a bit of detail on this. I didn’t quite understand everything but I easily gleaned enough that I was able to understand and enjoy the great discussion on the implications of AI. This makes the book a worthwhile read. Thank you to Edelweiss and Working Fires Foundation for the digital review copy.
April 5, 2023
An important read at a time when AI is dominating the news cycle—and much of our lives. It seems urgent to understand what AI can and cannot do, and Ken offers wonderful explanations of the basics of AI. He then delves into the philosophical implications of this technology, philosophical points and questions that become less and less hypothetical as AI's popular use spreads. Thank you, Ken!
April 21, 2023
A friend gave me an advance copy of this book. I was amazed because, I'm not a math person, but I came away really feeling like I understand the basics of how AI works. And now with AI being in the news all the time, I'm much more confident in my ability to tell what's hype, what's actually worrisome, what's exciting.
May 12, 2023
Even if it talks about complex concepts and algorithms it's easy to follow and a very informative book.
It's relevant as AI is going to affect us in more than one way.
Highly recommended.
Many thanks to the publisher for this arc, all opinions are mine
It's relevant as AI is going to affect us in more than one way.
Highly recommended.
Many thanks to the publisher for this arc, all opinions are mine
April 19, 2023
A clear explanation of the nuts and bolts of AI algorithms. We're hearing so much about AI these days, and this book is perfect for anyone who's curious about how these things work.
After giving the reader a basic understanding of how AI algorithms function, the author then discusses the ethical implications of where we apply them. He makes clear how the two go hand in hand: If we don't know how they operate, how can we make engage in reasonable discussions about where they should or shouldn't be deployed?
And these discussions are essential in a world where AI's influence isn't going away but will continue to get stronger.
After giving the reader a basic understanding of how AI algorithms function, the author then discusses the ethical implications of where we apply them. He makes clear how the two go hand in hand: If we don't know how they operate, how can we make engage in reasonable discussions about where they should or shouldn't be deployed?
And these discussions are essential in a world where AI's influence isn't going away but will continue to get stronger.
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