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The Fate Or Wealth Of Nations: AI, Robotics And Automation

What contributes to the wealth of a nation? Gross national income (GNI) and gross domestic product (GDP) are two well-known measures of a country's economic growth. One measures the earnings of a country, and the other measures the value of the final goods produced by the country. What drives these measures in the twenty-first century? We are now witnessing a pivotal technological divide among countries in their ability to invest in and deploy artificial intelligence (AI) and robotics in the means of production—a divide that is creating AI haves and have-nots.

Individual energy per capita will be enormous as technological change—like AI, automation, and robotics—unleashes the ability of entrepreneurs to build apps and customize workspaces that accompany AI-augmented work partnerships between man and machine. Some economists think they can calculate a nation's GDP, wealth, and overall human happiness by the size and consumption of Big Macs within its borders. I doubt it. In this epoch, we will measure the wealth of a country not by the size and consumption of Big Mac and fries, but rather by a more relevant measure—robotics and AI deployment in the production of products and services.

Let us walk down memory lane: centuries ago, Adam Smith's book The Wealth of Nations proposed a principle of free trade and commerce, and investigated how nations prosper via market exchange. Moving forward to the end of the twentieth century, the esteemed economic historian Alfred Chandler, in the 1997 book Big Business and the Wealth of Nations, proposed that the wealth of a nation was big business, managerial hierarchy, knowledge-intensive industries, and the rapid corporate strategies of unrelated diversification. Almost thirty years later, we are witnessing the power of machine learning and robotic production the likes of which Adam Smith and Alfred Chandler could never have imagined—and integrating these tools with human entrepreneurship.

Despite all the naysayers and doomsayers, widespread data suggests the opposite of AI and robotics taking human jobs; instead, AI-related jobs and skills are opening up employment, markets, and industries. According to Stanford University's Artificial Intelligence Index Report 2023, projections point toward AI's strength capacity and employability for humans as a growth area: AI job growth adds to the productivity of countries—and sorry, not based on the size and consumption of Big Macs!

For the casual observer, it is difficult to discern how AI and robotics private investment might lead to the wealth of a nation. For this, it would benefit us to use the words of Frédéric Bastiat—the seen and the unseen. What is seen in a wealthy country is the consumption of goods (Big Macs) and the manufacturers' production equipment (burger and fry production). However, what goes unseen is the technological deployment and the value chain to produce buns, fries, cups, and equipment for in-store and app-enabled orders.

What else is seen? We see vehicles, food in the grocery stores, smartphones, and other valuable gadgets. We see, as consumers, various goods for purchase and the lightning-fast speed of consumer goods delivered to our doorsteps, app-enabled services to protect our homes, or even smartphone laundry applications that allow us to start and stop our appliances when we are away from home. These modern examples of AI support are irrefutable and are exemplars of how AI technology has enhanced our happiness; the way we interface in the marketplace is dependent on AI to some extent.

However, what is unseen is the AI technology used to produce the everyday goods we prize the most. AI and robotics are an economic backbone that make all this economic expansion happen behind the scenes. Disdaining AI is akin to liking the taste of sausage but being repulsed by the way it is made. In other words, consumption (which we all do) begets a better and stronger demand for the mechanism to produce more in different ways than have traditionally been used.

Think about this: What explains how I can get what I want and how you can get what you want in the marketplace? In other words, what helps us produce and trade with one another? A central planning board? No. The wealth of a nation is determined not only by its productive powers and its productive entrepreneurs but also by its productive citizens who produce for their fellow man via the use of modern technology.

Take, for example, Adam Smith's pin factory. Smith writes in The Wealth of Nations that

...A workman not educated to this business . . . Nor acquainted with the use of machinery employed in it . . . Could scarce, perhaps, with his utmost industry, make one pin in a day, certainly could not make twenty. . . . I have seen a small factory of this kind where ten men only were employed, and where some of them consequently performed two or three distinct operations. But though they were very poor, and therefore indifferently accommodated with the necessary machinery, they could, when they exerted themselves, make among them about twelve pounds of pins in a day.

How are pins made today? By ten workers using rudimentary machines? Unlikely. Today, people searching for pins can buy as many pins as they might want at any store. And I am almost certain that the mass availability of pins exists because today's pin factories use robotic machines and AI technology to get pins of various colors and designs to consumers in various locations. Without robotics and intelligent AI software and services, would the production of pins be more limited?

In this regard, Alfred Chandler writes, "As was true of the earlier capital-intensive, scale-dependent technologies, unless organizational capabilities were developed and maintained, the critical learning base often disintegrated. Once lost, it was rarely regained. This was probably even more true in the knowledge-intensive, scope-dependent industries of the second half of the [twentieth] century than it was for the capital-intensive and scale-dependent industries of the first period of the modern economic growth." Chandler continues, "Learned product-specific organizational capabilities had to be maintained and enhanced. Once capabilities disintegrated, competitive power rarely returned."

What happens when all is lost: learning, knowledge, capabilities, entrepreneurship? Chandler's point is that if a country shies away from AI and robotics in the production process, it will lose the know-how and the how-to in production over time, thus lowering the country's wealth. Countries that disregard the power of private investment in AI and robotics will be left behind. It becomes apparent in the AI Index Report 2023 that jobs related to the fields supporting and investing in AI, not the size and consumption of Big Macs, will measure future wealth creation. Although Big Macs are tasty, it is hard to believe they measure the economic productivity of a wealthy nation.

Private investment in the production and deployment of AI and robotics contributes to a country's wealth. The AI Index Report 2023 reports, "In 2022 the amount of private investment in AI was 18 times greater than it was in 2013." Figure 1 shows that this investment varies greatly by country. The private sector is wresting AI from the grip of the elite, which will not be an easy task. Given the investment in AI, opening new markets (domestic and international) will promote a nation's prosperity. AI and automation will not cause technological unemployment.

Figure 1: Newly Funded AI Companies by Geographic Area, 2022

Source: Artificial Intelligence Index Report 2023 (Stanford, CA: Stanford University Human-Centered Artificial Intelligence, 2023), fig. 4.2.16.

While the intelligentsia and the elite may turn up their noses at Adam Smith, Alfred Chandler, and Murray Rothbard, the harsh reality is that the investment, use, and deployment of AI increase everyone's freedom, which contributes to the productivity of society. Figure 2 shows that adoption of AI leads to decreased costs and increased revenues across all sectors.

Figure 2: Cost Decrease and Revenue Increase from AI Adoption by Function, 2021

Source: Artificial Intelligence Index Report 2023, fig. 4.3.7.

It is a fact that the costs of production decrease when technology is used. Again, imagine Adam Smith's pin factory's production power if they had access to automation, AI, and robotics! We can see that integrating AI, human energy, and robotics in the production and consumption process grows a country's economy.

Despite what the bogeymen say about the downsides of AI and robotics, the benefits for the creation of wealth of investing in AI, robotics, and automation are visible in the things we consume. However, if a nation does not pursue investment in AI competencies and capabilities in the means of production, that nation will become marginalized—left behind in advancements oriented around global trade and domestic opportunities. Therefore, the wealth of nations will come down to which countries invest in the technological means to integrate human skills with AI, robotics, and automated production.

How Artificial Intelligence Will Transform Businesses

You probably interact with artificial intelligence (AI) on a daily basis and don't even realize it.

Many people still associate AI with science-fiction dystopias, but that characterization is waning as AI develops and becomes more commonplace in our daily lives. Today, artificial intelligence is a household name – and sometimes even a household presence (hi, Alexa!).

While acceptance of AI in mainstream society is a new phenomenon, it is not a new concept. The modern field of AI came into existence in 1956, but it took decades of work to make significant progress toward developing an AI system and making it a technological reality.

In business, artificial intelligence has a wide range of uses. In fact, most of us interact with AI in some form or another on a daily basis. From the mundane to the breathtaking, artificial intelligence is already disrupting virtually every business process in every industry. As AI technologies proliferate, they are becoming imperative to maintain a competitive edge.

What is AI?

Before examining how AI technologies are impacting the business world, it's important to define the term. "Artificial intelligence" is a broad term that refers to any type of computer software that engages in humanlike activities – including learning, planning and problem-solving. Calling specific applications "artificial intelligence" is like calling a car a "vehicle" – it's technically correct, but it doesn't cover any of the specifics. To understand what type of AI is predominant in business, we have to dig deeper.

Machine learning

Machine learning is one of the most common types of AI in development for business purposes today. Machine learning is primarily used to process large amounts of data quickly. These types of AIs are algorithms that appear to "learn" over time.

If you feed a machine-learning algorithm more data its modeling should improve. Machine learning is useful for putting vast troves of data – increasingly captured by connected devices and the Internet of Things – into a digestible context for humans.

For example, if you manage a manufacturing plant, your machinery is likely hooked up to the network. Connected devices feed a constant stream of data about functionality, production and more to a central location. Unfortunately, it's too much data for a human to ever sift through; and even if they could, they would likely miss most of the patterns. [Related: Artificial Insurance? How Machine Learning Is Transforming Underwriting]

Machine learning can rapidly analyze the data as it comes in, identifying patterns and anomalies. If a machine in the manufacturing plant is working at a reduced capacity, a machine-learning algorithm can catch it and notify decision-makers that it's time to dispatch a preventive maintenance team.

But machine learning is also a relatively broad category. The development of artificial neural networks – an interconnected web of artificial intelligence "nodes" – has given rise to what is known as deep learning.

Machine learning is useful for putting vast troves of data – increasingly captured by connected devices and the Internet of Things – into a digestible context for humans.

Deep learning

Deep learning is an even more specific version of machine learning that relies on neural networks to engage in what is known as nonlinear reasoning. Deep learning is critical to performing more advanced functions – such as fraud detection. It can do this by analyzing a wide range of factors at once.

For instance, for self-driving cars to work, several factors must be identified, analyzed and responded to simultaneously. Deep learning algorithms are used to help self-driving cars contextualize information picked up by their sensors, like the distance of other objects, the speed at which they are moving and a prediction of where they will be in 5-10 seconds. All this information is calculated at once to help a self-driving car make decisions like when to change lanes.

Deep learning has a great deal of promise in business and is likely to be used more often. Older machine-learning algorithms tend to plateau in their capability once a certain amount of data has been captured, but deep learning models continue to improve their performance as more data is received. This makes deep learning models far more scalable and detailed; you could even say deep learning models are more independent.

AI and business today

Rather than serving as a replacement for human intelligence and ingenuity, artificial intelligence is generally seen as a supporting tool. Although AI currently has a difficult time completing commonsense tasks in the real world, it is adept at processing and analyzing troves of data much faster than a human brain could. Artificial intelligence software can then return with synthesized courses of action and present them to the human user. In this way, we can use AI to help game out pfossible consequences of each action and streamline the decision-making process.

"Artificial intelligence is kind of the second coming of software," said Amir Husain, founder and CEO of machine-learning company SparkCognition. "It's a form of software that makes decisions on its own, that's able to act even in situations not foreseen by the programmers. Artificial intelligence has a wider latitude of decision-making ability as opposed to traditional software."

Those traits make AI highly valuable throughout many industries – whether it's simply helping visitors and staff make their way around a corporate campus efficiently, or performing a task as complex as monitoring a wind turbine to predict when it will need repairs.

Common uses of AI

Some of the most standard uses of AI are machine learning, cybersecurity, customer relationship management, internet searches and personal assistants.

Machine learning

Machine learning is used often in systems that capture vast amounts of data. For example, smart energy management systems collect data from sensors affixed to various assets. The troves of data are then contextualized by machine-learning algorithms and delivered to your company's decision-makers to better understand energy usage and maintenance demands.


Artificial intelligence is even an indispensable ally when it comes to looking for holes in computer network defenses, Husain said. Believe it or not, AI systems can recognize a cyberattack, as well as other cyberthreats, by monitoring patterns from data input. Once it detects a threat, it can backtrack through your data to find the source and help  to prevent a future threat. That extra set of eyes – one that is as diligent and continuous as AI – will serve as a great benefit in preserving your infrastructure.

"You really can't have enough cybersecurity experts to look at these problems, because of scale and increasing complexity," Husain added. "Artificial intelligence is playing an increasing role here as well."

Customer relationship management

Artificial intelligence is also changing customer relationship management (CRM) systems. Software programs like Salesforce and Zoho require heavy human intervention to remain current and accurate. But when you apply AI to these platforms, a normal CRM system transforms into a self-updating, auto-correcting system that stays on top of your relationship management for you.

For those in brand-new companies, read our Zoho CRM review, or our review of Salesforce to learn about one of the most popular CRMs.

A great example of how AI can help with customer relationships is demonstrated in the financial sector. Dr. Hossein Rahnama, founder and CEO of AI concierge company Flybits and visiting professor at the Massachusetts Institute of Technology, worked with TD Bank to integrate AI with regular banking operations.

"Using this technology, if you have a mortgage with the bank and it's up for renewal in 90 days or less … if you're walking by a branch, you get a personalized message inviting you to go to the branch and renew purchase," Rahnama said. "If you're looking at a property for sale and you spend more than 10 minutes there, it will send you a possible mortgage offer. [Related: CRM vs. Marketing Automation: What's the Difference?]

Internet and data research

Artificial intelligence uses a vast amount of data to identify patterns in people's search behaviors and provide them with more relevant information regarding their circumstances. As people use their devices more, and as the AI technology becomes even more advanced, users will have a more customizable experience. This means the world for your small businesses, because you will have an easier time targeting a very specific audience.

"We're no longer expecting the user to constantly be on a search box Googling what they need," Rahnama added. "The paradigm is shifting as to how the right information finds the right user at the right time."

Digital personal assistants

Artificial intelligence isn't just available to create a more customized experience for your customers. It can also transform the way your company operates from the inside. AI bots can be used as personal assistants to help manage your emails, maintain your calendar and even provide recommendations for streamlining processes.

You can also program these AI assistants to answer questions for customers who call or chat online. These are all small tasks that make a huge difference by providing you extra time to focus on implementing strategies to grow the business.

Rather than serving as a replacement for human intelligence and ingenuity, artificial intelligence is generally seen as a supporting tool. Humans can use AI to game out possible consequences and streamline the decision-making process.

The future of AI

How might artificial intelligence be used in the future? It's hard to say how the technology will develop, but most experts see those "commonsense" tasks becoming even easier for computers to process. That means robots will become extremely useful in everyday life.

"AI is starting to make what was once considered impossible possible, like driverless cars," said Russell Glenister, CEO and founder of Curation Zone. "Driverless cars are only a reality because of access to training data and fast GPUs, which are both key enablers. To train driverless cars, an enormous amount of accurate data is required, and speed is key to undertake the training. Five years ago, the processors were too slow, but the introduction of GPUs made it all possible."

Glenister added that graphic processing units (GPUs) are only going to get faster, improving the applications of artificial intelligence software across the board.

"Fast processes and lots of clean data are key to the success of AI," he said.

Dr. Nathan Wilson, co-founder and CTO of Nara Logics, said he sees AI on the cusp of revolutionizing familiar activities like dining. Wilson predicted that AI could be used by a restaurant to decide which music to play based on the interests of the guests in attendance. Artificial intelligence could even alter the appearance of the wallpaper based on what the technology anticipates the aesthetic preferences of the crowd might be.

If that isn't far out enough for you, Rahnama predicted that AI will take digital technology out of the two-dimensional, screen-imprisoned form to which people have grown accustomed. Instead, he foresees that the primary user interface will become the physical environment surrounding an individual.

"We've always relied on a two-dimensional display to play a game or interact with a webpage or read an e-book," Rahnama said. "What's going to happen now with artificial intelligence and a combination of [the Internet of Things] is that the display won't be the main interface – the environment will be. You'll see people designing experiences around them, whether it's in connected buildings or connected boardrooms. These will be 3D experiences you can actually feel." [Interacting with digital overlays in your immediate environment? Sounds like a job for augmented reality.]

AI is predicted to take digital technology out of the two-dimensional screen form and instead become the physical environment surrounding an individual.

What does AI mean for the worker?

With all these new AI uses comes the daunting question of whether machines will force humans out of work. The jury is still out: Some experts vehemently deny that AI will automate so many jobs that millions of people find themselves unemployed, while other experts see it as a pressing problem.

"The structure of the workforce is changing, but I don't think artificial intelligence is essentially replacing jobs," Rahnama said. "It allows us to really create a knowledge-based economy and leverage that to create better automation for a better form of life. It might be a little bit theoretical, but I think if you have to worry about artificial intelligence and robots replacing our jobs, it's probably algorithms replacing white-collar jobs such as business analysts, hedge fund managers and lawyers."

While there is still some debate on how, exactly, the rise of artificial intelligence will change the workforce, experts agree there are some trends we can expect to see.

Will AI create jobs?

Some experts believe that, as AI is integrated into the workforce, it will actually create more jobs – at least in the short term.

Wilson said the shift toward AI-based systems will likely cause the economy to add jobs that facilitate the transition.

"Artificial intelligence will create more wealth than it destroys," he said, "but it will not be equitably distributed, especially at first. The changes will be subliminally felt and not overt. A tax accountant won't one day receive a pink slip and meet the robot that is now going to sit at her desk. Rather, the next time the tax accountant applies for a job, it will be a bit harder to find one."

Wilson said he anticipates that AI in the workplace will fragment long-standing workflows, creating many human jobs to integrate those workflows.

What about after the transition?

First and foremost, this is a transition that will take years – if not decades – across different sectors of the workforce. So, these projections are harder to identify, but some other experts like Husain are worried that once AI becomes ubiquitous, those additional jobs (and the ones that had already existed) may start to dwindle.

Because of this, Husain said he wonders where those workers will go in the long term. "In the past, there were opportunities to move from farming to manufacturing to services. Now, that's not the case. Why? Industry has been completely robotized, and we see that automation makes more sense economically."

Husain pointed to self-driving trucks and AI concierges like Siri and Cortana as examples, stating that as these technologies improve, widespread use could eliminate as many as 8 million jobs in the U.S. Alone.

"When all these jobs start going away, we need to ask, 'What is it that makes us productive? What does productivity mean?'" he added. "Now we're confronting the changing reality and questioning society's underlying assumptions. We must really think about this and decide what makes us productive and what is the value of people in society. We need to have this debate and have it quickly, because the technology won't wait for us."

A shift to more specialized skills

As AI becomes a more integrated part of the workforce, it's unlikely that all human jobs will disappear. Instead, many experts have begun to predict that the workforce will become more specialized. These roles will require a higher amount of that which automation can't (yet) provide – like creativity, problem-solving and qualitative skills.

Essentially, there is likely to always be a need for people in the workforce, but their roles may shift as technology becomes more advanced. The demand for specific skills will shift, and many of these jobs will require a more advanced, technical skill set.

AI is the future

Whether rosy or rocky, the future is coming quickly, and artificial intelligence will certainly be a part of it. As this technology develops, the world will see new startups, numerous business applications and consumer uses, the displacement of certain jobs and the creation of entirely new ones. Along with the Internet of Things, artificial intelligence has the potential to dramatically remake the economy, but its exact impact remains to be seen.

David Cotriss contributed to the writing and reporting in this article. Source interviews were conducted for a previous version of this article.

Machine Learning Or Automation: What's The Difference?

Major players in the tech industry are pushing the boundaries of self-determining computers, especially as cutting-edge technologies like artificial intelligence (AI) and machine learning become more mainstream. While many professionals understand that these technologies will make their jobs easier – or even take over specific tasks – others are feeling confusion. One common question is, what's the difference between machine learning and automation?

What's the difference between machine learning and automation?

Let's start with machine learning, a subset of AI.

"It's an evolution," said Andreas Roell, managing partner of Analytics Ventures, a consultancy that helps businesses adopt AI. "AI fits into the bucket of workload analysis or task analysis. Business intelligence also sits in that same bucket. It's taking data, then analyzing it." [Related article: How Artificial Intelligence Is Transforming Business]

Machine learning is typically a later-stage development, where machines take in data on their own and then analyze it, Roell explained. The biggest difference is that "machine learning identifies data signals relevant for the future," he added. 

Automation is frequently confused with AI. Like automation, AI is designed to streamline tasks and speed workflows. But the difference is that automation is fixed solely on repetitive, instructive tasks, and after it performs a job, it thinks no further.

There's a good chance you use automation without even realizing it – for example, by automating emails to customers, automating the way you generate invoices, or automatically logging a help-desk inquiry. Workplace automation saves time and allows workers to focus on higher-priority initiatives. It's a reliable, computerized workhorse, able to show up and get the job done. 

Machine learning takes these tasks and layers them in an element of prediction. Whereas automation would continue to do exactly as you requested – say, send invoices on a specific day – machine learning predicts when the invoices should go out, who did or did not receive one, and when payments are on the verge of being late.

Learn more about automated email marketing by reading our in-depth Zoho CRM review and our review of Constant Contact.

Is AI the same as automation?

No, AI and automation are not the same. Automation involves an entire category of technologies that provide activity or work without human involvement. For example, say an old-style water wheel represents automation, translating the power of falling water into a repetitive nonhuman activity or mechanical work. There is nothing about the water wheel that involves artificial intelligence; it just keeps doing the same thing over and over.

We often associate automation with computers, but it's been around for ages.

"If you can take the resources that you have and come up with some sort of silver bullet and that turns them into radically better efficiency for what you're getting back, that is going to be evolutionary dynamite," zoologist Antone Martinho-Truswell told Gizmodo. "You're going to do fantastically well, as we have. Our nearest relatives are all endangered because of us."

AI, on the other hand, involves a machine exhibiting and practicing something similar to what we describe as human thinking – that is, the ability to interact in thousands of ways with the world around us without receiving any prior explicit coding or instructions. Think, for instance, of how AI digital assistants like Siri or Alexa can understand and respond to our questions and commands. 

The rate at which companies adopt AI is continuing to grow. Companies that have adopted AI are finding extensive cost savings, according to the McKinsey report on the state of AI in 2021, which interviewed 1,800 business leaders from various industries worldwide. 

According to the McKinsey survey results, 27% of companies that responded found an increase attributable to AI of at least 5% in earnings before interest and taxes (EBIT).

Will AI create new job opportunities?

Machine learning works to understand data, leveraging what Roell called data signals to drive future intelligence. It's not simply performing an "if X, then Y" task stream; it's essentially thinking through data much like a human.

"There's a lot of fear around AI, that it will eliminate jobs," Roell said. "That's not what it's supposed to do; it's making the way we work easier. But what it will do is lead to entirely new categories of jobs being created."

Roell gave the example of call center employees now being used to categorize the vast amounts of data used by AI. Several companies have taken this approach.

"Now that is true innovation," Roell said.

Can machine learning be automated?

Machine learning can be automated when it involves the same activity again and again. However, the fundamental nature of machine learning deals with the opposite: variable conditions. In this regard, machine learning must be able to function independently and with different solutions to match different demands. There is a higher likelihood that machine learning would be applied to determining unknown prediction scenarios.

However, the principle could apply in automated systems as a safeguard or as an element of automation, according to the Brookings Institution. For example, a computer system used to move Amazon.Com boxes could learn millions upon millions of weights so that it could flag a box on the conveyor belt that doesn't match known inventory when it senses the anomaly along the way from the shelf to the shipping truck.

Workplace automation software uses rule-based logic to automate manual work, such as sending follow-up emails.

Will we see an AI world in 2022?

Not quite, according to Stanford University's Artificial Intelligence Index Report 2022. AI systems are a business tech trend being more broadly deployed into the global economy. With this increasing deployment comes a commensurate increase in AI capabilities. Language models are becoming ever more accurate, image classification training times are quickly decreasing, and AI systems are increasingly affordable. 

However, there are still substantial gaps between AI systems focused on particular activities and general-purpose thinking AI systems. 

Adam Uzialko and Joanna Furlong contributed to the writing and reporting in this article. Source interviews were conducted for a previous version of this article.

This post first appeared on Autonomous AI, please read the originial post: here

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Earth Will Lock in a Future of 1.5°C of Warming By 2029


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