IN THIS CHAPTER
Working with humans
Solving industrial problems
Developing new technologies
Performing tasks in space
This book helps you understand the history of AI, where it is today, and where it could go tomorrow. However, a technology is useful only as long as it makes some sort of substantial contribution to society. Moreover, the contribution must come with a strong financial incentive, or investors won’t contribute to it. Although the government may contribute to a technology that it sees as useful for military or other purposes for a short time, long-term technological health relies on investor support. Consequently, this chapter focuses on AI components that are useful today, meaning that they’re making a substantial contribution to society right now.
Some people say that the overpromising of AI benefits today could cause another AI winter tomorrow (see “AI winter is coming?” at AI Futures.org). In addition, the fear mongering by certain influential people is causing people to rethink the value of AI, as discussed in “Will Artificial Intelligence Ever Live Up to Its Hype? Scientific American.com. (Fortunately, those with a better view often counter the fear mongering, such as with the view expressed in “Artificial intelligence problem isn’t computers; it’s humanity” at the Daily Illini.com.) Both of these issues are countered by others who feel that a balanced view of AI is ultimately desirable (see “Let’s Not Regulate A.I. Out of Existence” at OneZero.com). Discussion is valuable in assessing any technology, but investors aren’t interested in words; investors are interested in results. This chapter is about results that demonstrate that AI has become integrated into society in a significant enough manner to make another AI winter truly unlikely. Of course, getting rid of the hype so that people can really understand what AI can do for them would be a plus at this point.
Considering Human-Specific Interactions
People drive sales of products. In addition, people decide what to talk about most, which creates buzz, which in turn creates sales. Although you probably won’t hear about the technologies discussed in the following sections on the radio, the level at which they affect people is amazing. In the first case, an active human foot, people will actually be able to walk using prosthetics with nearly the same ease as they walk with a natural foot. Even though the group needing this product is relatively small, the effects can be widely known. The second and third cases have the potential for affecting millions, perhaps billions, of people. They’re mundane offerings, but often the mundane is what becomes expected, which again drives sales. In all three cases, the technologies won’t work without AI, which means that stopping AI research, development, and sales is likely to be met with disdain by the people using the technologies.
Devising the active human foot
Prosthetics are big money. They cost a fortune to make and are a necessary item for anyone missing a limb. Many prosthetics rely on passive technology, which means that they provide no feedback and don’t automatically adjust their functionality to accommodate personal needs. All that has changed in recent years as scientists such as Hugh Herr have created active prosthetics that can simulate the actions of real limbs and automatically adjust to the person using them (see “MIT’s Hugh Herr Reveals Joys (and Challenges) of Commercializing Bionic Limbs” at Robotics Business Review.com). Even though Hugh Herr grabbed major headlines, you can find active technology in all sorts of prosthetics today, including knees, arms, and hands. (See Chapter 7 for a link to Hugh Herr’s TED talk.)
You may wonder about the potential value of using active over passive prosthetics. Medical suppliers are already doing the research (see some results in the report “Economic Value of Advanced Transfemoral Prosthetics” at Rand.org). It turns out that microprocessor-based prosthetics that rely on an AI to ensure that the device interacts properly with the user are a huge win. Not only do people who use active technology prosthetics live longer, but these prosthetics have also reduced direct and indirect medical costs. For example, a person using an active technology prosthetic is less likely to fall. Even though the initial cost of an active technology prosthetic is higher, the costs over time are much smaller.
Performing constant monitoring
Chapter 7 discusses a host of monitoring devices used by medicine to ensure that people get their medications at the right time and in the correct dosage. In addition, medical monitoring can help patients receive care faster after a major incident and even predict when a patient will have a major incident, such as a heart attack. Most of these devices, especially those that are predictive in nature, rely on an AI of some sort to perform the work. However, the question of whether these devices provide a financial incentive for the people creating and using them remains.
Studies are hard to come by, but the study results in “Clinical and economic impact of HeartLogic compared with standard care in heart failure patients” (found at Wiley Online Library) show that remote monitoring of heart patients saves considerable medical costs (besides helping the patient live a happier, longer life). In fact, the use of remote monitoring, even for healthy people, has a significant impact on medical costs (see “Benefits of Remote Patient Monitoring” at blog.prevounce.com). The impact of the savings is so high that remote monitoring is actually changing how medicine works.
Sick people who forget to take their medications cost the medical establishment huge amounts of money. According to this 2016 article, “Patients skipping meds cost $290 billion per year—can ‘smart’ pills help?” at CNBC.com, the cost in the United States alone at that time was $290 billion a year. (There are ongoing efforts to reduce this waste, as described in papers like “The Prevalence of Unused Medications in Homes” at NCBI.gov. By combining technologies such as Near Field Communication (NFC) (see “Smart Packaging: Looks to Move Forward” at Jones Healthcare Group.com) with apps that rely on an AI, you can track how people take their medications, and when. In addition, the AI can help people remember when to take medications, which ones to take, and how much to use. When coupled with monitoring, even people with special monitoring needs can obtain the right dose of their medications (see “AI Informed Solutions to Promote Medical Adherence” at Xyonix.com).
Developing Industrial Solutions
People drive a ton of small sales. However, when you think about an individual’s spending power, it pales in comparison to what just one organization can spend. The difference is in quantity. However, investors look at both kinds of sales because both generate money — lots of it. Industrial solutions affect organizations. They tend to be expensive, yet industry uses them to increase productivity, efficiency, and most of all, income. It’s all about the bottom line. The following sections discuss how AI affects the bottom line of organizations that use the supplied solutions.
Using AI with 3-D printing
3-D printing began as a toy technology that produced some interesting, but not particularly valuable, results. However, that was before NASA used 3-D printing on the International Space Station (ISS) to produce tools (see “International Space Station’s 3-D Printer” at NASA.gov). Most people will think that the ISS should have taken all the tools it needs when it left Earth. Unfortunately, tools get lost or broken. In addition, the ISS simply doesn’t have enough space to store absolutely every required tool. Three-dimensional printing can also create spare parts, and the ISS certainly can’t carry a full complement of spare parts. Three-dimensional printers work the same in microgravity as they do on Earth (check out the Space Station Research Explorer page at NASA.gov), so 3-D printing is a technology that scientists can use in precisely the same manner in both places.
Meanwhile, industry uses 3-D printing to meet all sorts of demands. Adding an AI to the mix lets the device create an output, see what it has created, and learn from its mistakes (see “3D printers with an AI brain – ENGINEERING.com” at FR24 News.com). This means that industry will eventually be able to create robots that correct their own mistakes — at least to an extent, which will reduce mistakes and increase profits. AI also helps to reduce the risk associated with 3-D printing through products such as Business Case, explained in “The Artificial Intelligence for your 3D Printing Projects” at Sculpteo.com.
Advancing robot technologies
This book contains a wealth of information on how robots are being used, from in the home to medicine to industry. The book also talks about robots in cars, space, and under water. If you’re getting the idea that robots are a significant driving force behind AI, you’re right. Robots are becoming a reliable, accessible, and known technology with a visible presence and a track record of success, which is why so many organizations are investing in even more advanced robots.
Many existing traditional businesses rely on robots today, which is something many people may not know. For example, the oil industry relies heavily on robots to search for new oil sources, perform maintenance, and inspect pipes. In some cases, robots also make repairs in places that humans can’t easily access; such as in pipes (see “Robotics and AI in Oil & Gas” at OGV Energy. Using AI enables engineers to reduce overall risk, which means that oil will also have a potentially smaller environmental impact because of fewer spills.
The reduced price for oil is part of what has driven the oil industry to adopt AI (see “AI in Oil and Gas Market - Growth, Trends, COVID-19 Impact, and Forecasts (2021 - 2026)” at Intrado Global News Wire.com). Because the oil industry is so risk averse, its use of AI makes a good test case for seeing how other businesses will adopt AI. By reviewing articles on the oil industry, you realize that the oil industry waited for successes in the healthcare, finance, and manufacturing industries before making investments of its own. You can expect to see an uptick in AI adoption as successes in other industries grow.
This book covers all sorts of robotic solutions — some mobile, some not. Part 4 of the book covers robots in general, flying robots (which is what drones truly are when you think about it), and self-driving, or SD, cars. Generally, robots can make a profit when they perform a specific kind of task, such as sweeping your floor (the Roomba) or putting your car together. Likewise, drones are money makers now for defense contractors and will eventually become profitable for a significant number of civilian uses as well.
Creating New Technology Environments
Everyone generally looks for new things to buy, which means that businesses need to come up with new things to sell. AI helps people look for patterns in all sorts of things. Patterns often show the presence of something new, such as a new element or a new process for creating something. In the realm of product development, AI’s purpose is to help discover the new product (as opposed to focusing on selling an existing product). By reducing the time required to find a new product to sell, AI helps business improve profits and reduces the cost of research associated with finding new products. The following sections discuss these issues in more detail.
Developing rare new resources
As you can see throughout the book, an AI is especially adept at seeing patterns, and patterns can indicate all sorts of things, including new mineral elements (the “Finding new elements” section of Chapter 16 talks about this aspect of AI). New elements mean new products, which translate into product sales. An organization that can come up with a new material has a significant advantage over the competition. The article “An Economic Perspective on Revolutionary US Inventions” at the blog Virulent Word of Mouse tells you about the economic impact of some of the more interesting inventions out there. Many of these inventions rely on a new process or material that AI can help find with significant ease.
Seeing what can’t be seen
Human vision doesn’t see the broad spectrum of light that actually exists in nature. And even with augmentation, humans struggle to think at a very small scale or a very large scale. Biases keep humans from seeing the unexpected. Sometimes a random pattern actually has structure, but humans can’t see it. An AI can see what humans can’t see and then act upon it. For example, when looking for stresses in metal (see “Automatic Inspection of Metallic Surface Defects Using Genetic Algorithms” at ResearchGate.net), an AI can see the potential for fatigue and act upon it. The cost savings can be monumental when dealing with precision metal surfaces, which are scanned using a waveguide sensor (explained in “Intelligent Detection of Cracks in Metallic Surfaces Using a Waveguide Sensor Loaded with Metamaterial Elements at NCBI.gov.)
Working with AI in Space
Chapter 16 takes you on a tour of what AI can potentially do in space. Even though plans for performing these tasks are on the drawing board, most of them are government sponsored, which means that they provide an opportunity that may not necessarily result in a profit. You also find some business-related research projects in Chapter 16. In this case, the business is actually looking to make a profit but may not be making one today. The following sections look at space in another way and point to what’s happening today. AI is currently enabling businesses to earn money working in space, which gives businesses an incentive to keep investing in both AI and in space-related projects.
Delivering goods to space stations
Perhaps the greatest AI commercial success story in space so far is the resupply of the ISS by companies such as SpaceX and Orbital ATK (see “Commercial Resupply Services Overview” at NASA.gov).
The organizations make money with each trip, of course, but NASA benefits as well. In fact, the United States as a whole has enjoyed these benefits from the venture:
· Reduced cost for delivering materials, instead of using vehicles from other countries to resupply the ISS
· Increased use of U.S.-based facilities such as the Kennedy Space Center, which means that the cost of these facilities is amortized over a long time frame
· Added launch centers for future space flights
· More available payload capacity for satellites and other items
SpaceX and Orbital ATK interact with lots of other businesses. Consequently, even though only two companies might appear to benefit from this arrangement, many others benefit as subsidiary partners. The use of AI makes all this possible, and it’s happening right this second. Companies are earning money from space today, not waiting until tomorrow, as you might think from news reports. That the earnings come from what is essentially a mundane delivery service doesn’t make any difference.
Space deliveries are essentially new. Many Internet-based businesses ran at a deficit for years before becoming profitable. However, SpaceX, at least, appears to be in a position to possibly earn money after some early losses (see “Revisiting SpaceX’s $36-Billion Valuation After Its First Manned Mission” at Forbes.com). Space-based businesses will take time to ramp up to the same financial impact that earth-based businesses of the same sort enjoy today.
Mining extraplanetary resources
Space mining is currently undergoing the equivalent of an AI winter (see “How the asteroid-mining bubble burst” at MIT Technology Review.com — may be available only to subscribers). However, the problem that space mining is supposed to fix still remains: The Earth still has limited resources that are growing more limited by the day (see “Is space mining the eco-friendly choice?” at Astronomy.com). Consequently, people are still looking for ways to make space mining work because the potential for making a profit are so huge. One current idea is to mine the moon (see “Arcs of ‘lightning' on the moon could be the future of lunar mining” at Space.com) using a number of intriguing techniques, such as ablative arc mining (explained in “Ablative Arc Mining for In-Situ Resource Utilization” at NASA.gov). The point is that AI will most definitely be part of any space-mining endeavor (see “Artificial Intelligence and Space Mining: the Gateway to Infinite Riches” at aidaily.co.uk).
Exploring other planets
It seems likely that humans will eventually explore and even colonize other planets, with Mars being the likely first candidate. Elon Musk recently made the headlines by offering to use his wealth in the colonization effort (https://www.businessinsider.com/worlds-richest-person-elon-musk-dedicate-wealth-mars-colony-2021-1). After people get to other worlds, including the moon, many people think that the only way to make money will be through the sale of intellectual property or possibly the creation of materials that only that particular world will support (see “Is There A Fortune To Be Made On Mars?” at Forbes.com).
Unfortunately, although some people are making money on space exploration today, we likely won’t see any actual profit from space exploration for a while. Still, some companies are making a profit today by providing the various tools needed to design the trip. Research does fund the economy. However, the world is also in a buyer-beware environment filled with scam artists. For example, 78,000 people signed up for a trip to Mars (see “78,000 People Apply for One-Way Trip to Mars” at Time.com), but the company eventually went bankrupt (“The company that promised a one-way ticket to Mars is bankrupt” at The Verge.com).