第14章サイバー資源の品質とサイバーコンピューティングのガバナンス

The challenges we face with an autonomous system, which is a system that can operate with limited human control, are ever-changing. The theory is that if every car in the world was autonomous, there would be no more accidents. This is a myth because, as we know, computers are prone to failure. Individuals who wish to hack autonomous vehicles will do so to possibly cause harm. Many people cannot manage the sense of not being in control of a vehicle while it is driving, even when they are behind the wheel. Humans, by nature, prefer to be in control of their environments.

Autonomous vehicles rely on sensory data to function. This data provides perception, decision-making, and execution of real-time data analysis. The vehicles rely on cloud mapping services for navigation and other cloud data for weather and environmental issues. If any of these channels are interrupted, the vehicle must function based on the last known data. This information may be insufficient, or erroneous data may be used for decision-making. This will change the perception of the vehicle and may lead to the system’s inability to make safe decisions.

The vehicles are expensive to manufacture. Autonomous vehicles can also refer to drones and smart homes. Any device that could work independently of humans is at risk for false data. With smart homes, there is also the challenge of power outages. While these platforms are in constant development, and many companies are contributing to the enhancement and evolution of these devices, as a society, we need to analyze how we will integrate them into our lives. Theoretically, as the autonomous machinery increases, it should seamlessly fit within the metaverse. The TRMs interoperability and adaptability will be challenged, and data mining and decision-making through more developed AI mediums will continue to challenge the functionality of immersive technology.

The great hope for autonomous vehicles, and in reality it is most true, is that autonomous machinery will be faster than human interactive computing and will provide humans the opportunities to repurpose themselves so they do not have to do the tasks these autonomous entities can provide. The issue is that we need more computer scientists studying AI/ML and a greater devotion to nanotechnology. All companies must enhance their quality assurance protocols, and the world cannot be the testbed for software. The ISO 22737:2021 Intelligent Transport Systems and ISO 39003:2023 Road Traffic Safety must continue to evolve to handle the newest technology. Standards cannot be an afterthought for autonomous platforms.

As previously discussed in the chapter, there are two bases of AI in the world: Turing and Lovelace forms of AI. Robotic platforms cannot exist without implementing one of the two types of AI. Since robotics has not been proven to create thoughts spontaneously, the Lovelace form of AI does not seem to be implantable. Therefore, we can assume that AI based on algorithmic analysis will be the current resolution for robotics with machines working toward the Lovelace form of AI. If we consider humanoid robotics, much can be done with predictive AI and the advancements in neurosciences.

The Human Brain Project seeks to find disorders in human consciousness. Although this project is currently on hold because of its ambitious goals, we can still learn from the foundations they established. Henry Markram, creator of the Human Brain Project, spent many years trying to reverse-engineer the brain to understand brain disorders like autism. In a 2009 TED talk, Markram said that he would be able to figure out the brain and create simulations in the form of holograms that will be able to think and talk with you. His foundation did not meet its goals, but it did advance brain model research in previously analyzed areas. This will help with the creation of robotic brains that can think. The challenge is that the neurological community cannot agree on one concise development course. This has led to the delay and descension of scientists leaving the project.

The TRMs quality assurance and software engineering are challenged every step of the way with robotics. An ethical dilemma also comes with all robotics: Do we need a robot that can function the same way as a human? If that is the case, when they are developed, will humans become obsolete? Science fiction movies have warned about robots taking over the world. If the quality assurance and software engineering skills increase to a point where a robot is created that can truly think, the world will experience a new set of challenges.