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The Human-Machine Team: How to Create Synergy Between Human & Artificial Intelligence That Will Revolutionize Our World
One of the world's leading managers in the field of Artificial Intelligence unveils the secrets to creating synergy between human and artificial intelligence that will revolutionize our world. Today, we are merely at the threshold of the acceleration of the Digital Era. But what will happen in the coming years, when artificial intelligence (AI) is going to dramatically change the world? A machine can use big data to generate information better than humans. However, a machine can’t understand context, doesn’t have feelings or ethics, and can’t think ‘out of the box’. Therefore, rather than prioritize between humans and machines, we should create The Human-Machine Team, which will combine human intelligence and artificial intelligence, creating a ‘super cognition’. Brigadier General Y.S, an expert analyst, technology director, commander of an elite intelligence unit, and winner of the prestigious Israel Defense Prize for his artificial intelligence based anti-terrorism project, wrote his book, The Human-Machine Team, to address how the combination between human and artificial intelligence can solve national security challenges and threats, lead to victory in war, and be a growth engine for humankind. He offers a new perspective on how to lead nations and organizations to the future that has already become the present.
200 pages, Kindle Edition
Published August 17, 2021
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Displaying 1 - 7 of 7 reviews
September 26, 2024
Good book with some bold thoughts.
April 16, 2024
This was interesting book about integration of human and machine to get more out of both of them. It opens up some new perspectives on the subject, especially when it comes to use of high technology.
So to start with things that I liked....
Finally someone talking about integration of humans and machines and making them more than sum of the parts. For this alone this book is great.
Requirement to quickly test some of the concepts, learn what can be learned, drop the unnecessary and use the gold nuggets found (what author calls 4x4 approach). This means experimental units to use new cutting edge technology, find its weak spots, report back, use the enhancements and repeat the cycle. Management needs to follow the same approach and constantly re-check the state of all of the elements in play (akin to popular agile methodologies in software development), redefine goals and move on. Basically improve in the incremental way. All of this sounds catchy, but is total nightmare if you have multi-discipline teams working together. Rewards are great in case this approach catches up, but it is painful and not so straight forward path and people in charge need to accept that [at least in the beginning] good portion of effort will result in failures (concepts proving as not so applicable or useful), but this is goal because in the end only those elements that are truly applicable will remain - for security purposes this is the goal. Price-wise this might be a little bit overwhelming and I am not sure how it would work for defense/security state organizations. Commercial companies would just drop something after few iterations because they do not want to spend too much on something that might not give them big returns. This is generally not a way to run government or state btw no matter how much we fool ourselves with efficiency. Private enterprise would just terminate (of course managers would get money and move forward) and leave work-force in whatever pile of manure company made - can you imagine defense/security organization acting like this? Changing personnel every so often? It just does not work like that. Private enterprises do offset this by huge paychecks to work-force (while it works) but this is something that government system just cannot do.
But OK, as a way to speed things up, keep everyone engaged, this is interesting approach (especially again in security domain) and if well led and drilled can produce a lot of good things during peacetime (mind you during wartime this is the way defense/security operates).
Bibliography section is truly a gem, dont miss it. Author gives comments on some of the literature that will expand the knowledge on the topic and give further research topics for those interested.
Things that I dont like that much.
Requirement to collect tonnes of data. I know this is already done (and mostly by private enterprises in a hush-hush-pinky-promise-we-wont-abuse-it way) but to condone it on a state security level and keep all under full surveillance (i.e. detecting unknown phone in the area as an alert - wth?) is something current "freedom-loving" countries aspire to (and do) but something that needs to be prevented. Software and data is glitchy and while there might be very low number of cases of wrong identification - for those people Kafka's Process will be something from a rosy fairy tale. Just look at the recent events in the Middle East - people tend to simplify things (and as a consequence so do used algorithms). One would expect that with all of the data collected on the Palestinians, IDF would be precise, targeting only areas with the militants (or so fairy tale goes). Instead they just used all the data and tools and identification to - basically do what they would have done in 1980s or early 1990s, drop bombs all over the place where they have found traces of the militants. So why use all shiny tools etc if you could simply use ground surveillance and human spies to figure out these locales. Again this is all under assumption goal was anti-terrorism and not something else. So collecting and hoarding data is not an answer to anything. Making sensible data collection, now that would be a goal (or at least one would think) but to start from heaps of static just to be on the safe side seems like a way that will result in lots of false positives and treating general information and people's interests during peace time as if it was war time - everyone is potential enemy! A little bit too paranoid to feel safe at all.
Second thing is incorporation of all IT giant corporations to become for all means and purposes parts of the military industrial complex. This will cause issues because these same corporations will become isolated from other parts of the world, and Internet, such as we know it, will become (unfortunately) set of independent national/alliance level of networks. End result? Basically ruining the very benefits we currently reap. Why would say China keep on using say Azure or AWS, if they know US, South Korea and Japan are utilizing the very same companies (and using who knows what from the company through legal system since these are all companies registered in the West) for hosting their own defense/security/spying systems. We can pretend that these systems are separated etc but they are not, why show one's belly to the enemy just for the sake of convenience? This will split Internet apart and instead of unifying network create separate networks and make information exchange very very difficult, if not impossible, because censorship systems will be in place all over the place (yes, even in "freedom loving" countries). This is just natural progression, all of this started during the epidemic and very soon age of knowledge exchange (in a public way) will be over.
And things that truly make puke.
For some reason in the middle of the presentation (this is general look and feel of the book - collection of notes and thoughts and brain storming ideas) we get to the comment how increasing number of women in these AI enhanced experimental units would raise the level of information sharing between the units and departments. Optimal number would be to increase the number of women in high ranks/management positions to 51%, to quote the author. And to further quote the author - state/organization that achieves this will be leader in the field.
Now you might ask why 51%, why not more if women are so prone to data sharing? Probably because this does not have anything to do with the data sharing but with current views on society. To this I would even joke and say - why do you say women share data better, because of the view of woman as a gossip person? Does not make sense does it.
Data sharing is not biochemically imprinted into people - it is part of the culture people grow up in. Somebody might be more disinclined to trust someone when they first meet them but in general society and [especially when it comes to this niche] work culture will determine the level of trust between parts of the state/organization. I have worked with men and women, had men and women bosses - and they all behaved in the same professional way as expected of their rank and position. To think that in some secret security organization (again topic of the book) women will be more predisposed to sharing data, especially after a career in the field spanning multiple years is idiocy to say the least.
Because of this I had to take on star off. This short paragraph looks like something injected into the book just to make it current. It stands out in a very weird way, like if you would find chapter on ancient civilizations in the middle of your cookbook - it is just nonsensical.
Interesting book, with some very good insights but also with some weird urge to make it more current in the most idiotic way possible.
My advice is give it a try, there is definitely something to learn here.
So to start with things that I liked....
Finally someone talking about integration of humans and machines and making them more than sum of the parts. For this alone this book is great.
Requirement to quickly test some of the concepts, learn what can be learned, drop the unnecessary and use the gold nuggets found (what author calls 4x4 approach). This means experimental units to use new cutting edge technology, find its weak spots, report back, use the enhancements and repeat the cycle. Management needs to follow the same approach and constantly re-check the state of all of the elements in play (akin to popular agile methodologies in software development), redefine goals and move on. Basically improve in the incremental way. All of this sounds catchy, but is total nightmare if you have multi-discipline teams working together. Rewards are great in case this approach catches up, but it is painful and not so straight forward path and people in charge need to accept that [at least in the beginning] good portion of effort will result in failures (concepts proving as not so applicable or useful), but this is goal because in the end only those elements that are truly applicable will remain - for security purposes this is the goal. Price-wise this might be a little bit overwhelming and I am not sure how it would work for defense/security state organizations. Commercial companies would just drop something after few iterations because they do not want to spend too much on something that might not give them big returns. This is generally not a way to run government or state btw no matter how much we fool ourselves with efficiency. Private enterprise would just terminate (of course managers would get money and move forward) and leave work-force in whatever pile of manure company made - can you imagine defense/security organization acting like this? Changing personnel every so often? It just does not work like that. Private enterprises do offset this by huge paychecks to work-force (while it works) but this is something that government system just cannot do.
But OK, as a way to speed things up, keep everyone engaged, this is interesting approach (especially again in security domain) and if well led and drilled can produce a lot of good things during peacetime (mind you during wartime this is the way defense/security operates).
Bibliography section is truly a gem, dont miss it. Author gives comments on some of the literature that will expand the knowledge on the topic and give further research topics for those interested.
Things that I dont like that much.
Requirement to collect tonnes of data. I know this is already done (and mostly by private enterprises in a hush-hush-pinky-promise-we-wont-abuse-it way) but to condone it on a state security level and keep all under full surveillance (i.e. detecting unknown phone in the area as an alert - wth?) is something current "freedom-loving" countries aspire to (and do) but something that needs to be prevented. Software and data is glitchy and while there might be very low number of cases of wrong identification - for those people Kafka's Process will be something from a rosy fairy tale. Just look at the recent events in the Middle East - people tend to simplify things (and as a consequence so do used algorithms). One would expect that with all of the data collected on the Palestinians, IDF would be precise, targeting only areas with the militants (or so fairy tale goes). Instead they just used all the data and tools and identification to - basically do what they would have done in 1980s or early 1990s, drop bombs all over the place where they have found traces of the militants. So why use all shiny tools etc if you could simply use ground surveillance and human spies to figure out these locales. Again this is all under assumption goal was anti-terrorism and not something else. So collecting and hoarding data is not an answer to anything. Making sensible data collection, now that would be a goal (or at least one would think) but to start from heaps of static just to be on the safe side seems like a way that will result in lots of false positives and treating general information and people's interests during peace time as if it was war time - everyone is potential enemy! A little bit too paranoid to feel safe at all.
Second thing is incorporation of all IT giant corporations to become for all means and purposes parts of the military industrial complex. This will cause issues because these same corporations will become isolated from other parts of the world, and Internet, such as we know it, will become (unfortunately) set of independent national/alliance level of networks. End result? Basically ruining the very benefits we currently reap. Why would say China keep on using say Azure or AWS, if they know US, South Korea and Japan are utilizing the very same companies (and using who knows what from the company through legal system since these are all companies registered in the West) for hosting their own defense/security/spying systems. We can pretend that these systems are separated etc but they are not, why show one's belly to the enemy just for the sake of convenience? This will split Internet apart and instead of unifying network create separate networks and make information exchange very very difficult, if not impossible, because censorship systems will be in place all over the place (yes, even in "freedom loving" countries). This is just natural progression, all of this started during the epidemic and very soon age of knowledge exchange (in a public way) will be over.
And things that truly make puke.
For some reason in the middle of the presentation (this is general look and feel of the book - collection of notes and thoughts and brain storming ideas) we get to the comment how increasing number of women in these AI enhanced experimental units would raise the level of information sharing between the units and departments. Optimal number would be to increase the number of women in high ranks/management positions to 51%, to quote the author. And to further quote the author - state/organization that achieves this will be leader in the field.
Now you might ask why 51%, why not more if women are so prone to data sharing? Probably because this does not have anything to do with the data sharing but with current views on society. To this I would even joke and say - why do you say women share data better, because of the view of woman as a gossip person? Does not make sense does it.
Data sharing is not biochemically imprinted into people - it is part of the culture people grow up in. Somebody might be more disinclined to trust someone when they first meet them but in general society and [especially when it comes to this niche] work culture will determine the level of trust between parts of the state/organization. I have worked with men and women, had men and women bosses - and they all behaved in the same professional way as expected of their rank and position. To think that in some secret security organization (again topic of the book) women will be more predisposed to sharing data, especially after a career in the field spanning multiple years is idiocy to say the least.
Because of this I had to take on star off. This short paragraph looks like something injected into the book just to make it current. It stands out in a very weird way, like if you would find chapter on ancient civilizations in the middle of your cookbook - it is just nonsensical.
Interesting book, with some very good insights but also with some weird urge to make it more current in the most idiotic way possible.
My advice is give it a try, there is definitely something to learn here.
May 24, 2021
‘The best way to predict the future is to create it’ – Abraham Lincoln
Israeli author Brigadier General Y.S. earned his undergraduate degrees in Middle East Studies and in Psychology and Sociology. In addition he earned his Master’s degree from the National Defense University in Washington, DC. Awarded for is expertise in cyber and data science, he is the commander of an elite intelligence unit and has in depth experience with national security issues and challenges threatening the State of Israel.
In his introductory notes, the author states, ‘The viewpoint of this book is that since the development of AI, we can, and should, look at the last 40-50 years as just “foreplay” for the big changes that are about to occur in the coming years. Human cognition was the major factor that led to the development of humankind. Therefore, the ability of a machine to perform human cognition, and the ability of The Human-Machine Team to learn together and think together will create a new world...In our generation, technology is not just technology that helps people; it is AI that changes people. It is AI that changes the idea of knowledge and communication…The Human-Machine Team discusses how to lead nations and organizations at this threshold of the acceleration of the Digital Era when AI is changing the basic rules.’
The author places his concepts in the schemata of history, reminding us of the three major revolutions: the Agricultural Revolution, the industrial Revolution, and The Digital Revolution. Offering significant insights into the Digital Revolution, he shares the current and future breakthroughs of robotics, artificial intelligence, nanotechnology, quantum computing, biotechnology, the Internet of Things (IoT), 3-D printing, and autonomous vehicles.
The manner in which the author discusses super-cognition (synergetic learning between humans and machines), the FAST concept (Foundation, Acceleration, and Singularity Time), the impact of AI on national security measures, and dealing with the challenges of Digital Revolution from the perspective of war in so logical a manner that the information becomes completely accessible. The future belongs to the nations and organizations that enable the AI Revolution.
After his concise presentation of his ideas, the author closes with ‘The Human-Machine Team is just part of the beginning of the journey that nations and organizations must make in order to acquire the new potentials that the era of AI is bringing… instead of choosing between human intelligence and artificial intelligence, we should choose to unite the two in a team that learns together and shapes the future together. This is a fascinating book written by a keen authority on the subject of AI.
Israeli author Brigadier General Y.S. earned his undergraduate degrees in Middle East Studies and in Psychology and Sociology. In addition he earned his Master’s degree from the National Defense University in Washington, DC. Awarded for is expertise in cyber and data science, he is the commander of an elite intelligence unit and has in depth experience with national security issues and challenges threatening the State of Israel.
In his introductory notes, the author states, ‘The viewpoint of this book is that since the development of AI, we can, and should, look at the last 40-50 years as just “foreplay” for the big changes that are about to occur in the coming years. Human cognition was the major factor that led to the development of humankind. Therefore, the ability of a machine to perform human cognition, and the ability of The Human-Machine Team to learn together and think together will create a new world...In our generation, technology is not just technology that helps people; it is AI that changes people. It is AI that changes the idea of knowledge and communication…The Human-Machine Team discusses how to lead nations and organizations at this threshold of the acceleration of the Digital Era when AI is changing the basic rules.’
The author places his concepts in the schemata of history, reminding us of the three major revolutions: the Agricultural Revolution, the industrial Revolution, and The Digital Revolution. Offering significant insights into the Digital Revolution, he shares the current and future breakthroughs of robotics, artificial intelligence, nanotechnology, quantum computing, biotechnology, the Internet of Things (IoT), 3-D printing, and autonomous vehicles.
The manner in which the author discusses super-cognition (synergetic learning between humans and machines), the FAST concept (Foundation, Acceleration, and Singularity Time), the impact of AI on national security measures, and dealing with the challenges of Digital Revolution from the perspective of war in so logical a manner that the information becomes completely accessible. The future belongs to the nations and organizations that enable the AI Revolution.
After his concise presentation of his ideas, the author closes with ‘The Human-Machine Team is just part of the beginning of the journey that nations and organizations must make in order to acquire the new potentials that the era of AI is bringing… instead of choosing between human intelligence and artificial intelligence, we should choose to unite the two in a team that learns together and shapes the future together. This is a fascinating book written by a keen authority on the subject of AI.
Read
April 8, 2024On the morning of October 7th, I was glued to the news as the kibbutz that my relatives helped build, and where many live, had been overtaken by terrorists. I was scared every time an update or a death notice was shared, fearing it might be a relative.
I remember in that moment, trying to understand — how could this happen?
There were two primary intelligence failures that led to that awful day: Israel's sensor technology, serving as warning mechanisms and the first line of defence, were all preemptively destroyed, preventing Israel from having knowledge of what was happening, impairing its ability to respond; and Israel leveraged the intelligence information it had to form inferences about the state of Hamas, but did not sufficiently appreciate how much intelligence it lacked (which would have led to different inferences).
The Human Machine Team outlines the IDF's vision for building AI-based systems to enhance its defence posture. This work is important and ultimately very promising, but like any system, it can fail.
In 2024, the IDF's most significant use of AI involves incorporating all forms of signals intelligence + drones to maintain a visual record of all movement + with human/live intelligence, into a database. This supports Deep Learning models, enabling predictions on questions such as: Is there a tunnel located here? Is a specific person a member of Hamas? Were certain weapons smuggled into a location? A variety of other AI tools play a major role in this conflict, including autonomous vehicles and weapons, stabilization/aiming technologies, and live identity recognition, among others.
One of the big questions following the war is can AI make an army too lethal? In the current conflict, the IDF has not only orders of magnitude more legitimate military targets to strike than its past wars, but more than any other army in history. The ability to leverage AI to increase a military target list by 10-100X, may mark a qualitatively change in the essence on what types of military strikes are legally permissible.
It's also interesting to read a book that focuses on the Deep Learning paradigm, whereas from 2022 onwards, everything became oriented solely around large language models.
I remember in that moment, trying to understand — how could this happen?
There were two primary intelligence failures that led to that awful day: Israel's sensor technology, serving as warning mechanisms and the first line of defence, were all preemptively destroyed, preventing Israel from having knowledge of what was happening, impairing its ability to respond; and Israel leveraged the intelligence information it had to form inferences about the state of Hamas, but did not sufficiently appreciate how much intelligence it lacked (which would have led to different inferences).
The Human Machine Team outlines the IDF's vision for building AI-based systems to enhance its defence posture. This work is important and ultimately very promising, but like any system, it can fail.
In 2024, the IDF's most significant use of AI involves incorporating all forms of signals intelligence + drones to maintain a visual record of all movement + with human/live intelligence, into a database. This supports Deep Learning models, enabling predictions on questions such as: Is there a tunnel located here? Is a specific person a member of Hamas? Were certain weapons smuggled into a location? A variety of other AI tools play a major role in this conflict, including autonomous vehicles and weapons, stabilization/aiming technologies, and live identity recognition, among others.
One of the big questions following the war is can AI make an army too lethal? In the current conflict, the IDF has not only orders of magnitude more legitimate military targets to strike than its past wars, but more than any other army in history. The ability to leverage AI to increase a military target list by 10-100X, may mark a qualitatively change in the essence on what types of military strikes are legally permissible.
It's also interesting to read a book that focuses on the Deep Learning paradigm, whereas from 2022 onwards, everything became oriented solely around large language models.
September 12, 2024
If you're looking at this book as a way to gain novel insights into modern AI applications in the military, it's unlikely you're going to find it. It reads more like a managerial exercise in explaining data science at large to one's superiors.
What it does do, however, is give one insight into the Israeli mindset when it comes to defense, and generally how it approaches its neighbors. A lot of the strategies mentioned already show use today with psyops being highly prevalent on social media platforms already.
I regularly found myself thinking that a country probably wouldn't have to pursue such dystopic measures if it probably didn't pursue lebensraum as a defense strategy but alas the author is a product of his upbringing and I can't fault them for that.
I will say that I did find the epilogue amusing and will definitely add the 4x4 method to my repertoire of strategic planning skills.
What it does do, however, is give one insight into the Israeli mindset when it comes to defense, and generally how it approaches its neighbors. A lot of the strategies mentioned already show use today with psyops being highly prevalent on social media platforms already.
I regularly found myself thinking that a country probably wouldn't have to pursue such dystopic measures if it probably didn't pursue lebensraum as a defense strategy but alas the author is a product of his upbringing and I can't fault them for that.
I will say that I did find the epilogue amusing and will definitely add the 4x4 method to my repertoire of strategic planning skills.
August 25, 2024
I wish Mr. Adriel added more substance to the “hows” of using AI in his work rather than cryptically speaking his general opinions on the future benefits of AI-human cooperation. As if he periodically thinks he says too much and digresses into neutral general talk.
Having said that I have to admit that the book contains few very interesting points which every patient reader will find worth of reading the whole book.
Having said that I have to admit that the book contains few very interesting points which every patient reader will find worth of reading the whole book.
May 2, 2024
Humans invented the machine that can beat them.
Culture eats strategy for breakfast.
Data is the new oil.
Culture eats strategy for breakfast.
Data is the new oil.
Displaying 1 - 7 of 7 reviews