The Ethics Of Artificial Intelligence – Opinion Ethical artificial intelligence is very likely to turn machines into autonomous agents, with their own learning and decision-making abilities. We should be concerned about this development.
Artificial intelligence (AI) is becoming increasingly important in many applications that support decision-making in various areas, including healthcare, consumption and individual risk classification. The increasing impact of artificial intelligence on people’s lives naturally raises the question of its ethical and moral components. Are artificial intelligence decisions ethically acceptable? How can we ensure that AI remains ethical over time? Should we dominate AI and set certain rules of conduct, potentially limiting its enormous potential, or should we allow AI to develop its own ethics, possibly subjecting us to intellectual slavery? Better yet, is it possible that AI and human endeavors can work together to achieve a stable, mutually beneficial symbiotic relationship. We begin our thinking with basic ideas about education.
The Ethics Of Artificial Intelligence
Public education is one of the most important achievements of modern societies. Education, which is about supporting and facilitating learning, has proven to be beneficial for individuals and societies. Several studies show that education has a positive effect on health, economic well-being and social integration.
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Learning is about acquiring the tools needed to form independent judgments and decide on appropriate courses of action. The main goal of education is to create a society in which individuals can think and act independently, as well as bear responsibility. For example, in democratic systems, each individual takes responsibility for his vote, as well as the responsibility to elect representatives in parliaments and governments. However, this requires the ability to form an opinion, and therefore education.
Knowledge is a tool, but not the ultimate goal of learning. Judgments and actions are also about values. In his dean’s note, Sandro Galea of Boston University’s School of Public Health wrote, “Values are what we choose to focus on in a world of limited time and resources.” Values that motivate us to apply our knowledge when we judge and decide. Therefore, education is about knowledge and values.
Today, with the advent of artificial intelligence and machine learning (ML), we face a new and challenging problem: machines can also learn, from experience (in the form of data), thus developing the ability to make decisions, independent decisions. , and actions. So, the question arises whether humans should also learn machines and how.
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In this article, we distinguish between ML (machine learning) and AI. By ML we mean “the study of computer algorithms that automatically improve through experience.” Although AI is much broader in scope and refers to the science of computers acting as intelligent agents, the limit of which is superintelligence (a type of intelligence, not yet clearly defined, that is superior to human intelligence). So, in our context, ML and AI have some similarities, but they are not equivalent. An intelligent machine learns well; stupid machine is not so good. We realize that an intelligent machine cannot learn anything, if it is not given the means to learn, e.g. experience in the form of data. A dumb machine could learn well, say if given the opportunity to repeat many times.
In this essay, we explore the relationship between ML and AI, their morals and ethics. As such, it is up to the authors to clarify these concepts and define their relationships. For our purposes, morality is an organized system of principles of good and bad that guides an individual in actions and deeds. These are the principles of the self, independent of their influence on others. In contrast, ethics includes a set of rules of conduct or principles of good and bad that are recognized in the context of a particular group of individuals or a particular society. Ethics and morality could be different, for example, an individual who follows his morals could behave unethically in a certain context, and, on the other hand, what society considers ethical could be contrary to the individual’s own morality.
A typical example is the case of abortion. Society might consider abortion ethical under certain conditions, for example, when the pregnancy poses a serious risk to the mother and fetus. However, a doctor still cannot perform an abortion because of their own moral principles involved, for example, their conscience which may be deeply rooted in their religious values. However, another doctor may have a different morality and believe that the choice to perform an abortion is entirely up to the woman, and therefore believes that abortion is acceptable under more general conditions such as those of established ethics.
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This distinction between ethics and morality is important in our discussion because the ongoing conflict between internally codified morality and externally imposed ethics is the foundation for ethical learning. Therefore, as we will discuss later, ethical teaching means defining morality, but also a way of measuring how actions differ from general ethics.
Back to the machines. Until now, machines have only carried out our orders. So, despite the achievement of new incredible goals using machines (such as flying, landing on the moon, improving diagnostics and therapy in medicine), machines did not judge and act independently of humans. Humans could fully determine the framework within which machines would judge, decide and act, thus setting their own relevant moral and ethical values.
In contrast, AI is very likely to turn machines into independent agents, with their own learning and decision-making abilities, possibly capable of thinking with a greater capacity than humanity (superintelligence). We should all be very concerned about this development and ask ourselves whether we would accept a scenario where machines can judge and act motivated by values different from human values, and use these values in combination with information to influence or modify our society. Oxford philosopher and professor Nick Bostrom has made it clear: super-intelligent AI agents could dominate us and even drive humanity to extinction.
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Several studies show that artificial intelligence systems (ML, deep learning, forced deep learning) are not necessarily ethical. Artificial intelligence systems are trained to achieve goals, for example, to maximize utility, but the way this happens does not necessarily follow ethical principles or human values. An example will serve as a demonstration.
Suppose a machine is trained to form learning groups in a school. Based on the training data provided, the machine learns that children from low-income families are less likely to succeed in school and, as a result, preselects those children into specific learning groups to achieve the most effective learning environment at school. In this case, one could argue that the training data has created a bias and therefore this bias must be corrected by using, for example, alternative training data. However, even if there is no bias built into the decision-making process, and the machine has achieved its goal of improving the school’s learning environment; it is not clear that the way it happened is ethically acceptable. Indeed, the selection criterion (perhaps the most powerful predictor based on training data) is not based on children’s learning skills (probably what people would care about), but on their social status, which is ethically unacceptable in many societies. More generally, machines could also track unintended instrumental actions that will increase the probability of achieving a goal in a second step, e.g. self-defense or acquisition of necessary resources at the expense of human beings.
Even if a machine is instructed not to make unethical choices in certain scenarios (in the form of clearly stated moral norms, for example, “If this happens, don’t act that way.”) this is not enough to avoid unethical behavior. In many modern applications, AI systems are too complex and humans may not be able to predict how the AI systems will achieve their goals. Therefore, in this case, humans cannot predict and control the full set of possible scenarios that the machine will face (lack of transparency.) On the other hand, if humans control AI agents so that they do not become independent decision makers, then we are likely also limiting the results that could achieve.
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Therefore, the question of how to ensure that AI agents will act ethically is very challenging, and the answer probably lies somewhere between imposing strict rules (regulation) and allowing machines to unhindered to learn to their full potential.
We are now at the beginning of a great adventure, and we have a choice of how to begin that adventure. Will we stand by as AI and its companion ML evolve according to their own design, or will we, as evolved creatures, set the parameters of this evolution so that the astonishing results are sure to enrich human existence, not limit it, or in the hideous abominable possibility, destroy it is?
The normative issue is that humans should design machines to ensure ethical learning. Machines need to learn that given actions are unethical and different from the core values set by humans. Ethical learning is a necessary condition for machines to benefit humans and for humans to guarantee safety and ensure that machines will judge and act motivated by our values. In general, humans will not be able to control every step of the machine learning process, as many of those steps will not be predictable or even transparent to humans. However, humans can impose transparency and predictability in moral and ethical systems, and impose ethical learning to ensure that machines
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