Intelligent machine systems are improving our lives by optimizing logistics, detecting fraud, creating art, doing research, and giving translations. As these systems improve in capability, our world gets more efficient and, as a result, richer.
Alphabet, Amazon, Facebook, IBM, and Microsoft, as well as people such as Stephen Hawking and Elon Musk, think that the moment has come to discuss the practically limitless terrain of artificial intelligence. In many respects, this is a new frontier for ethics and risk assessment just as much as for growing technologies. So, what concerns and discussions keep AI specialists up at night?
The hierarchy of labor is largely concerned with automation. As we develop methods to automate tasks, we can free up space for individuals to take on more sophisticated responsibilities, shifting from the physical labor that dominated the pre-industrial world to the cognitive delivery that defines strategic and administrative work in our globalized society.
Consider trucking: it employs millions of people in the United States alone. What will happen to them if Elon Musk's self-driving trucks become widely accessible in the next decade? The same thing might happen to office employees and the rest of the global workforce. However, self-driving trucks are an ethical decision considering the decreased chance of accidents.
This brings us to the subject of how we will spend our time. Most individuals still depend on selling their time to support themselves and their families. This option will allow individuals to find significance in non-labor activities such as caring for their families, participating in community activities, and discovering new ways to contribute to human civilization.
If we make it through the shift, we may one day look back and think it was savage that humans were forced to sell the bulk of their waking hours to survive.
Our economic system is founded on remuneration for contributions to the economy, which is often measured using hourly pay. When it comes to goods and services, the bulk of businesses still relies on hourly labor. However, by using artificial intelligence, a firm may substantially reduce its reliance on human labor, resulting in fewer individuals receiving money. As a result, those who own AI-driven enterprises will earn all the money.
We already see an increasing wealth disparity, with start-up founders reaping a disproportionate share of the economic surplus they generate. In 2014, the three largest firms in Detroit and the three largest corporations in Silicon Valley produced about the same revenues... Only in Silicon Valley were there ten times as many workers.
How can we organize a fair post-labor economy if we envision a post-work society?
AI bots are getting more adept at simulating human interaction and relationships. Eugene Goostman, a bot, won the Turing Challenge for the first time in 2015. Person raters utilized text input to interact with an unknown entity in this task, then judged whether they were conversing with a human or a computer. Eugene Goostman duped more than half of the human raters into believing they were speaking with someone.
This is only the start of an era in which we will routinely deal with computers as if they were people, whether in customer service or sales. While humans are restricted in the amount of time and attention they can devote to another person, artificial bots may devote nearly infinite resources to developing connections.
The future frontier of human reliance is technology addiction. Even though few of us are aware of it, we are already seeing how robots may activate the reward centers in the human brain. Consider clickbait headlines and video games. These headlines are often adjusted using A/B testing, a basic algorithmic optimization for content to attract our attention. This and other techniques make many videos and mobile games addicting.
On the other side, we can create of another use for software that has previously been shown to be successful in directing human attention and initiating particular activities. When applied correctly, this can move society toward more desirable behavior. However, in the wrong hands, it might be harmful.
4. Artificial Insanity
Learning is the source of intelligence, whether a person or a computer. Systems often undergo a training phase in which they "learn" to recognize the correct patterns and behave in response to their input. Once a system has been completely trained, it may enter the test phase, when it is subjected to more instances, and its performance is evaluated.
The training process can only cover some scenarios a system would encounter in the real world. These systems can be duped in ways that humans cannot. Random dot patterns, for example, may cause a system to "see" objects that aren't there. If we depend on AI to usher us into a new era of labor, security, and efficiency, we must ensure that the machine works as intended and that humans cannot manipulate it to their own goals.
5. AI Bias
Artificial intelligence has significantly more processing speed and capacity than humans, but it cannot always be trusted to be fair and unbiased. Google and its parent firm, Alphabet, are among the leaders in artificial intelligence, as seen by Google Photos uses AI to recognize people, objects, and settings. However, it may go awry, like when a camera's racial sensitivity is off or when software used to forecast future offenders exhibits prejudice towards black individuals.
We must remember that AI systems are designed by humans, who might be prejudiced and judgmental. Once again, artificial intelligence may catalyze beneficial change if employed correctly or by people who want societal improvement.
The more powerful a technology grows, the more it may be utilized for evil and good. This is true not just for robots designed to replace human troops or autonomous weaponry but also for AI systems that might harm if misused. Because these battles will not be waged just on the battlefield, cybersecurity will become even more crucial. After all, we're working with a system that is orders of magnitude quicker and more competent than ourselves.
7. Genie Villains
What if artificial intelligence became hostile to us? We must be concerned about more than simply rivals. This does not imply becoming "bad" as a person would or in the way Hollywood movies portray AI catastrophes. Rather, we may envisage a powerful AI system as a "genie in a bottle," capable of fulfilling desires but with disastrous unintended effects.
There is likely to be malice at work in the case of a computer, merely a lack of knowledge of the full context in which the request was expressed. Consider an AI system that is tasked with eradicating cancer across the planet. After much computation, it produces a formula that does bring about the abolition of cancer - by murdering everyone on the earth. The machine would have easily accomplished its aim of "no more cancer," but not in the manner humans planned.
Humans are at the top of the food chain for reasons other than sharp teeth and powerful muscles. Human superiority is largely attributable to our inventiveness and intellect. We can defeat larger, quicker, and stronger animals by constructing and using instruments to control them, such as cages and weapons, and cognitive techniques, such as training and conditioning.
This raises an important concern regarding artificial intelligence: will AI have the same edge over humanity one day? We also can't depend on just "drawing the plug" since a sufficiently evolved computer may predict this maneuver and protect itself. Some refer to this as the "singularity": the moment when humans are no longer the most intelligent species on the planet.
9. Robot Privileges
While neuroscientists are still attempting to uncover the mysteries of conscious experience, we are learning more about the fundamental principles of reward and aversion. In some ways, we are developing analogous reward and aversion processes in artificial intelligence systems. Even basic creatures have these systems. Reinforcement learning, for example, is analogous to dog training in that increased behaviour is rewarded with a virtual reward.
These systems are now quite superficial but are growing increasingly intricate and life-like. Could we regard a system to be in pain when its reward mechanisms provide negative feedback? Furthermore, genetic algorithms function by simultaneously constructing multiple system instances, with only the most effective "surviving" and combining them to generate the next generation of instances. This occurs across many generations and is a method of system improvement. Instances that fail are removed. When do we consider genetic algorithms to be a sort of mass murder?
Examining their legal position is not a big jump when we accept machines as creatures capable of perception, emotion, and action. Should they be handled as if they were intelligent animals? Will we think about the pain of "feeling" machines?
Some ethical problems are about reducing suffering, while others are about risking unpleasant results. While we contemplate these hazards, we should also remember that technological advancement generally implies a better life for everyone. Artificial intelligence has enormous promise, and it is up to us to utilize it responsibly.
Featured image: Image by pch.vector
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