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In a Nutshell: Artificial intelligence and robotics have analysts spooked about the future of work because AI seems to threaten the kind of non-routine, creative jobs people have always invented when technology replaces manual labor. But AIs prospects arent a mere question of supply and demand global geopolitical and regulatory factors complicate the picture. At UK economic intelligence provider Fathom Consulting, Deputy Chief Economist Andrew Harris views AI with caution and as an opportunity. With proper planning, he argues, the global economy may be on the cusp of a significant, positive reduction in work.

If youre into economics, you may remember the story about the preeminent British economist John Maynard Keynes, who famously predicted in 1930 that people would work 15 hours a week within a century.

In Keyness vision, technology and innovation would increase productivity by such a measure that prudent planning and social consensus would result in a drastically reduced need for work.

Any way you look at it, its a safe bet that the global workforce wont achieve Keyness 15-hour goal by 2030 far from it. The reality, at least so far in modern economic history, is that workers have only reduced their hours a little and are perhaps more keen to get compete and get ahead than Keynes predicted.

But Keynes may have been onto something all along, according to Andrew Harris, Deputy Chief Economist at the UK economics intelligence provider Fathom Consulting. He just didnt get the timeline right.

A group of Bank of England economists broke away in 2003 to form Fathom at a time of extensive siloing in the banks thinking about the relationship between people and money. Economists and finance professionals rarely communicated; when they did, they spoke a different language.

Fathom aims for a more holistic, consultative view of the complex interactions of macroeconomics with financial markets and geopolitics. A global client base turns to the Fathom team for expertise in pensions, property, finance, politics, banking, economic modeling, and climate economics.

That comes in handy when looking at the future of work. Harris said AIs unprecedented reach into highly productive, non-routine jobs may finally prove Keyness theory of productivity works in practice.

In many studies on the backward-bending labor supply curve in economics, there comes a point where if you offer people more money, they want to work fewer hours, Harris said. Keynes may have gotten it wrong by a few decades, but thats the route we seem to be taking.

Whether you regard that with dread or anticipation depends on your point of view and your sense of optimism. Its important to recognize an ongoing downward trend already exists.

In the US, for example, momentum toward a four-day, 32-hour workweek continues in 2023. In Keyness academic heyday during the Great Depression, that would have been a pipe dream.

Meanwhile, economists generally regard the arrival of artificial intelligence, machine learning, and robotics as the modern worlds fourth industrial revolution. Crucial differences in the character of the transformation are essential to assessing AI as a genuine harbinger of fundamental change.

The traditional view in economics has always been that technology doesnt replace aggregate jobs in the long run. Because it never has more people are employed now than ever.

But many job categories have indeed disappeared altogether. Harriss favorite example is the job of elevator operator, briefly essential until it wasnt.

We all know how to use elevators now, Harris said.

AIs essential difference is its reach into non-routine work, both manual and cognitive. In the first industrial revolution in 18th-century England and the second in 19th-century America, technology never rose to the height where it could replace the creative improvisation of humans facing new challenges.

Even during the third revolutionary cycle, the information and internet revolution of the 1970s and beyond, innovation has never reached beyond routine cognitive tasks such as scanning data and making simple calculations.

Only AI promises to mimic human decision-making in novel circumstances. Melded to ever-more agile and responsive robotic technology, AI may finally put non-human capital in a position to gain the upper hand over all forms of work.

AI is exciting, interesting, and terrifying all at the same time because maybe it can compete for those jobs, Harris said. We cant say for certain, but we cant rule it out either.

The terrifying problem is that inventing new forms of non-routine cognitive work has always acted as an incentive for creative destruction and an escape hatch for obsolescence.

To be sure, individual workers experienced displacement, but the labor market gradually evolved as society supplied workers trained for the available jobs. AI potentially stops that.

The big question is whether we can get to a level of representation of generalized human cognitive abilities known as artificial general intelligence or AGI, Harris said. Were not there yet, but that could change.

Fathom reaches clients in three ways. Through its Global Outlook, it contributes intelligent, independent, data-driven quarterly assessments and in-person presentations to global subscribers. Fathom also provides consultancy services to clients needing the broadest perspective for making mission-critical decisions. Underlying both are extensive data, modeling, and tools to organize disparate inputs into a coherent whole.

Its an ideal foundation for judging whether AGI is even possible. For Harris, the question is still open. But theres no doubt AI has made phenomenal progress with the rise of ChapGPT and other generative technologies.

Achieving true AGI is very hard to predict or even think about, he said. But the diffusion process (i.e. the time for an innovation to go from invention to widespread adoption) is getting much quicker. You can see this by looking at the pace of adoption of autos, planes, and phones.

ChapGPT is a recent example of that phenomenon in overdrive, reaching an estimated 100 million monthly active users in two months. The point is that when AGI, or something like it, arrives, workers may suddenly no longer have a place to go.

When we get to the point where AI has a real impact on the economy, it could happen much quicker than people think, Harris said. ChatGPT is relatively new to the market, but everyones thinking about how they can use it.

This is where Fathoms synthesis of macroeconomics, financial markets, and geopolitics comes to the fore. Harris can imagine a world in the far future where there arent any jobs, period. Any world in which technology replaces specific jobs makes certain people effectively unemployable.

What that potentially means is an incredibly unequal society, Harris said. People always expect that technology will tip the balance in favor of the owners and away from the rest of the economy.

The US-China rivalry, a special focus for Fathom, adds intense competitive pressure to an already highly dynamic mix. Throughout modern history, technological innovation has increased the size of the economy. The obvious question for Harris is how governments and regulators worldwide deal with the fallout from when thats no longer the case.

In Fathoms and Harris view, the big reveal is that data consistently shows support for the backward-bending curve of labor economics. Theres a point in the productivity/prosperity matrix at which workers tend to prefer less work over more money.

If AI brings parts of the global economy to that point, well all watch a new form of labor displacement in which social preferences begin to match theory and demand more intentional strategies for distributing work and leisure.

As some US jobs follow the EUs lead toward a 32-hour week, that means we may be thinking of the problem in reverse because productivity and wealth may bring us to the point where workers will demand less work, not the other way around.

For all his accomplishments, Keynes takes a lot of hits over his prediction. But things are trending in his direction. Harris is on board.

I think its a good thing if we can manage to earn more and work less, he said. It comes with a trade-off between leisure and spending, but if we can position ourselves where we have a lot of leisure and a lot of money to spend, that seems pretty great to me.

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Fathom Consulting: AI and Robotics are Poised to Transform the Future of Work Maybe Positively - CardRates.com

So, you want to dive deeper into the world of artificial intelligence? As AI continues to transform our lives in so many ways, gaining a better understanding of its concepts and capabilities is crucial. The field of AI is vast, but some books have become classics that every curious reader should explore. Weve compiled a list of 10 groundbreaking books on artificial intelligence that will boost your knowledge and feed your fascination with this fast-growing technology.

From philosophical perspectives on superintelligence to practical applications of machine learning, these books cover the past, present, and future of AI in an accessible yet compelling way. Whether youre a beginner looking to learn the basics or an expert wanting to expand your mind, youll find something inspiring and thought-provoking in this list. So grab a cup of coffee, settle into your favourite reading spot, and lets dive in. The future is here, and these books will help prepare you for whats to come.

Nick Bostroms Superintelligence is a must-read if you want to understand the existential risks posed by advanced AI.

This thought-provoking book argues that once machines reach and exceed human-level intelligence, an intelligence explosion could occur. Superintelligent machines would quickly become vastly smarter than humans and potentially uncontrollable.

Max Tegmarks thought-provoking book explores how AI may change our future. He proposes that artificial general intelligence could usher in a new stage of life on Earth.

As AI systems become smarter and smarter, they may eventually far surpass human intelligence. Tegmark calls this hypothetical point the singularity. After the singularity, AI could design even smarter AI, kicking off a rapid spiral of self-improvement and potentially leading to artificial superintelligence.

The Master Algorithm by Pedro Domingos explores the quest for a single algorithm capable of learning and performing any task, also known as the master algorithm. This book examines the five major schools of machine learningsymbolists, connectionists, evolutionaries, Bayesians, and analogizersexploring their strengths and weaknesses.

Domingos argues that for AI to achieve human-level intelligence, these approaches must be combined into a single master algorithm. He likens machine learning to alchemy, with researchers combining algorithms like base metals to produce gold in the form of human-level AI. The book is an insightful overview of machine learning and its possibilities. While the concepts can be complex, Domingos explains them in an engaging, accessible way using colourful examples and analogies.

In his book The Future of the Mind, theoretical physicist Michio Kaku explores how the human brain might be enhanced through artificial intelligence and biotechnology.

Kaku envisions a future where telepathy becomes possible through electronic implants, allowing people to exchange thoughts and emotions. He also foresees the eventual mapping and understanding of the human brain, which could enable the transfer of memories and even consciousness into new bodies.

In his 2012 New York Times bestseller, futurist Ray Kurzweil makes the case that the human brain works like a computer. He argues that recreating human consciousness is possible by reverse engineering the algorithms of the brain.

Kurzweil believes that artificial general intelligence will soon match and eventually far surpass human intelligence. He predicts that by the 2030s, we will have nanobots in our brains that connect us to synthetic neocortices in the cloud, allowing us to instantly access information and expand our cognitive abilities.

Martin Fords Rise of the Robots is a sobering look at how AI and automation are transforming our economy and job market. Ford argues that AI and robotics will significantly disrupt labour markets as many jobs are at risk of automation.

As AI systems get smarter and robots become more advanced, many human jobs will be replaced. Ford warns that this could lead to unemployment on a massive scale and greater inequality. Many middle-income jobs like cashiers, factory workers, and drivers are at high risk of being automated in the coming decades. While new jobs will be created, they may not offset the jobs lost.

In Homo Deus, Yuval Noah Harari explores how emerging technologies like artificial intelligence and biotechnology will shape the future of humanity.

Harari argues that humanitys belief in humanism the idea that humans are the centre of the world will come to an end in the 21st century. As AI and biotech advance, humans will no longer be the most intelligent or capable beings on the planet. Machines and engineered biological life forms will surpass human abilities.

Kai-Fu Lees 2018 book AI Superpowers provides insightful perspectives on the rise of artificial intelligence in China and the United States. Lee argues that while the US currently leads in AI research, China will dominate in the application of AI technology.

As the former president of Google China, Lee has a unique viewpoint on AI ambitions and progress in both countries. He believes Chinas large population, strong technology sector, and government support for AI will give it an edge. In China, AI is a national priority and a core part of the governments long-term strategic planning. There is no shortage of data, given Chinas nearly 1 billion internet users. And top tech companies like Baidu, Alibaba, and Tencent are investing heavily in AI.

This classic book by Stuart Russell and Peter Norvig established itself as the leading textbook on AI. Now in its third edition, Artificial Intelligence: A Modern Approach provides a comprehensive introduction to the field of AI.

The book covers the full spectrum of AI topics, including machine learning, reasoning, planning, problem-solving, perception, and robotics. Each chapter has been thoroughly updated to reflect the latest advances and technologies in AI. New material includes expanded coverage of machine learning, planning, reasoning about uncertainty, perception, and statistical natural language processing.

This book provides an accessible introduction to the mathematics of deep learning. It begins with the basics of linear algebra and calculus to build up concepts and intuition before diving into the details of deep neural networks.

The first few chapters cover vectors, matrices, derivatives, gradients, and optimizationessential math tools for understanding neural networks. Youll learn how to calculate derivatives, apply gradient descent, and understand backpropagation. These fundamentals provide context for how neural networks actually work under the hood.

There we have it, our list of 10 best books on AI. What do you think about our picks? Let us know your thoughts in the comments below:

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10 Best Books on Artificial Intelligence | TheReviewGeek ... - TheReviewGeek