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'60 Leaders' is an initiative that brings together diverse views from global thought leaders on a series of topics – from innovation and artificial intelligence to social media and democracy. It is created and distributed on principles of open collaboration and knowledge sharing. Created by many, offered to all.

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'60 Leaders on Artificial Intelligence' brings together unique insights on the topic of Artificial Intelligence - from the latest technical advances to ethical concerns and risks for humanity. The book is organized into 17 chapters - each addressing one question through multiple answers reflecting a variety of backgrounds and standpoints. Learn how AI is changing how businesses operate, how products are built, and how companies should adapt to the new reality. Understand the risks from AI and what should be done to protect individuals and humanity. View the leaders. 

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'60 Leaders on Innovation' is the book that brings together unique insights and ‘practical wisdom’ on innovation. The book is organized into 22 chapters, each presenting one question and multiple answers from 60 global leaders. Learn how innovative companies operate and how to adopt effective innovation strategies. Understand how innovation and experimentation methods blend with agile product development. Get insights from the experts on the role of the C-Suite for innovation. Discover ways that Innovation can help humanity solve big problems like climate change.

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What is the impact of AI on society and everyday life?

Michael Wu

Q.

Throughout the first three industrial revolutions, humans have learned to leverage machines to automate various tasks. We use machines to augment our limited physical strength, endurance, memory, and computing capability. However, until recently, there were no machines to augment our decision-making capability. Hence, most of the high-paying jobs in the post-industrial era involve skilled labor that requires substantial decision-making. Only the most mundane and mindless tasks are automated by mechanical machines. Yet, many of these machines still require human operators to make decisions, whether it’s as complex as driving a truck, or simply deciding when to switch a machine on and off.

Today, as AI-based technologies become more pervasive, ma-chines can augment our cognitive capacity and automate our complex decision-making processes for the first time. This will dramatically change the way we work, leading to the Fourth Industrial Revolution . Many tasks that were reserved for humans and require some level of human decisions, can be automated as long as we can collect enough data to train an AI to mimic those human decisions and actions.

One of the most significant benefits of AI is the huge efficiency it brings. Since many tasks can now be automated completely and without humans being the bottleneck, they can be executed much faster. Moreover, since AI does not need to eat or sleep, it can work 24/7, leading to further productivity increase. As with any machine automation, AI can eliminate careless human errors, and provide greater consistency in our complex decision-making processes.

Individuals can benefit tremendously from AI because it can eliminate the mundane and repetitive tasks that nobody likes to do. Whether it’s something as simple as deciding which movie to watch, adding items to our shopping list or having them delivered automatically, or getting home safely and quickly, AI can automate these tasks, allowing us to spend our valuable time on more important things. Not only do we get convenience and save time, but also, we get better and more personalized experiences.
Now let’s expand our scope and look at AI’s impact on businesses. Today, many enterprises, especially large ones, have many inefficient or simply broken business processes (e.g. in customer service). These in-efficiencies have many negative side-effects on the business, as they often result in higher operating costs (e.g. hiring more staff). Furthermore, when these processes touch their customers, the poor customer experience can erode brand equity and customer loyalty.

However, as with individuals, businesses can also realize a dramatic efficiency gain from AI. Fixing the inefficiencies in business can indirectly cut costs and improve customer experience. But beyond that, businesses can also improve their customer experience directly using personalization AI (e.g. recommender systems) and create more engaging brand interactions via conversational AI (e.g. chatbots and virtual assistants).

Unlike consumer AI tools that automate simple everyday decisions, business AI can be trained to automate decisions that are often highly technical, domain-specific, and have a much lower tolerance for error. Business AI is much less known to the consumers because they are often used by highly specialized experts. They are used to augment human experts, to not only automate but also optimize their high-stake decisions that often have a direct impact on the company’s top line (e.g. real-time dynamic pricing). Hence AI can also help enterprises improve margins, and revenues, and drive greater profitability.

Now let’s further expand our scope and examine AI’s impact on our society. As companies and individuals strive to realize greater efficiency from AI, our society as a whole will also function more efficiently. Since the first industrial revolution, we have spent less and less time at work. If this trend continues, maybe in the not too distant future, AI automation could allow our society to function so efficiently that it can support a Universal Basic Income (UBI). Perhaps, we will no longer need to work for survival, but instead, we work because we want to, for the passion, the experience, and the sense of fulfillment.

Clearly, we are not there yet! Today, our AI systems are only capable of learning from specific data sources and automating point decisions in a narrow domain (i.e. Artificial Narrow Intelligence, ANI ). However, since technological progress occurs at an exponential rate, it won’t be too long until AI matches human intelligence (i.e. Artificial General Intelligence, AGI ) or even surpasses it (i.e. Artificial Superintelligence, ASI ). When this happens, ASI could potentially rewrite themselves to make them even more intelligent. This positive feedback of intelligence would grow indefinitely, leading to more and more world-changing innovations at an increasing rate. Humans simply cannot adapt to those rapid and dramatic changes, let alone the existential threat of an ASI. This uncontrollable technological explosion is often referred to as technological singularity .

Although the looming singularity is frightening, It’s unfruitful to speculate about a knowingly unpredictable future that’s far away. Stemming from the mass adoption of AI, there are already many societal challenges that we must deal with long before we reach the singularity. As AI automates more human work in a market society driven by competition and profit maximization, it’s inevitable that companies will reduce their human workforce to cut costs. What will humans do then? Perhaps, we’ll need a new economy in the future that is driven by maximizing happiness rather than profit.

Since AI advancements progress at an exponential rate, it will be challenging to retrain and upskill the human workforce fast enough for them to keep stable jobs. Although technological innovation always creates more jobs in the long term, large-scale job displacement in the short term is a problem we must address. Moreover, if the pace of change is fast enough, our current education policy, where we front-load education early in an individual’s life, may no longer be practical. So we may also need a new education system.

According to the renowned sociologist, Gerhard Lenski, as technology enables more efficient production, it will lead to a greater surplus. This not only supports a larger society but also allows members of a society to specialize more, thus creating greater inequality. Since the efficiency gained from AI is huge, the inequality it creates is also extreme. This is already very apparent in the income disparity between tech and non-tech workers across the globe. Despite the appeal of UBI, it will likely further increase inequality as it would go to everyone equally regardless of their income. Some inequality is good, as it not only motivates people but also enables large-scale projects that require huge investments. However, too much inequality is definitely bad, as it leads to more crime, reduces social mobility, and undermines the fairness and trust of social institutions.

What about the looming singularity and the existential threat? If you must squeeze a comment out of me on this matter, consider this: All AI systems learn from data. But these training data are created by humans, as they are digital records of our past actions and encapsulate our past decisions. So AI is really learning from us, humans, and AI will mimic our decision processes.

Therefore, if we do run into a situation where our interests are in conflict with AI, the best way to ensure that AI doesn’t destroy us is for us to be better role models for AI now. That means we, as a human race, must learn to not kill each other whenever we run into conflicts. In short, the best way to ensure our own survival is for us to be better humans. We must learn to be more compassionate, more empathic, more environmentally conscious, etc. So our decisions and action can be used to train an AGI (or ASI) that mimics these ‘better-human’ qualities.

This may sound impossible in today’s society because we must compete and struggle for survival, which often brings out the worst of our human nature. However, in an AI-augmented future, we may not need to work for survival, and our economy may no longer be driven by competition. So with the help of AI, maybe we can be better humans before we reach the singularity.

"Since the efficiency gained from AI is huge, the inequality it creates is also extreme."

Dr. Michael Wu is the Chief AI Strategist at PROS (NYSE: PRO). He’s been appointed as a Senior Research Fellow at the Ecole des Ponts Business School for his work in Data Science, and he serves as an advisor and lecturer for UC Berkeley Extension’s AI programs. Prior to PROS, Michael was the Chief Scientist at Lithium for a decade. His R&D won him recognition as an Influential Leader by CRM Magazine. Michael has served as a DOE fellow at the Los Alamos National Lab. Prior to industry, Michael re-ceived his triple major undergraduate degree in Applied Math, Physics, and Molecular & Cell Biology; and his Ph.D. from UC Berkeley’s Biophysics program.

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Michael Wu

"Large-scale job displacement in the short term is a problem we must address."

Chief AI Strategist

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