Ever since the birth of computation with Alan Turing, humans have put high hopes on the power of computers and artificial intelligence (AI). AI is expected to bring significant and diverse benefits to society – from greater efficiency and productivity to tackling a number of difficult global problems, such as climate change, poverty, disease, and conflict.
AI technologies shape our societies. They have an enormous impact on our daily lives. At the same time, multiple legal and societal issues have revealed the potential of these technologies to produce undesirable impacts. Algorithms can enhance already existing biases. They can discriminate. They can threaten our security, manipulate us and have lethal consequences.
For these reasons, people need to explore the ethical, social and legal aspects of AI systems. There is a common call for the ethics of AI – meaning how are we to develop and use this technology in an ethically acceptable and sustainable way? What are the ethical and moral principles we should adopt and follow?
In this course, we'll take a look at the ethical issues related to contemporary AI, open up their background in philosophy and give them an interpretation in terms of computer and other sciences. The goal of course is to develop skills for ethical thinking. The course provides a guide – or a roadmap – on the ethically sustainable design, implementation and use of AI. It will introduce you to basic ethical concepts, their theoretical background, and their role in discussion on contemporary AI.
What is AI?
Artificial intelligence is an overall term describing a set of different kinds of techniques to make computers behave in some kind of intelligent fashion. There is no agreed definition of AI, but in general the ability to perform tasks without supervision and to learn so as to improve performance are key parts of AI.
Machine learning is a big topic in AI. Machine learning is a set of algorithms which by themselves learn to make decisions or to structure data. Supervised and unsupervised learning are based on data, while reinforcement learning is where the algorithm uses trial and error to learn to make sequences of decisions.
FAQs
AI ethics are important because AI technology is meant to augment or replace human intelligence—but when technology is designed to replicate human life, the same issues that can cloud human judgment can seep into the technology.
What are 3 main concerns about the ethics of AI? ›
But there are many ethical challenges: Lack of transparency of AI tools: AI decisions are not always intelligible to humans. AI is not neutral: AI-based decisions are susceptible to inaccuracies, discriminatory outcomes, embedded or inserted bias. Surveillance practices for data gathering and privacy of court users.
What is the conclusion of AI ethics? ›
AI should be tracking human interests and values, and its functioning should benefit us and not lead to any existential risks, according to the ideal of value alignment.
Is AI ethical or unethical? ›
Artificial intelligence (AI) has the potential to revolutionize the world, but it can also be used unethically. There are several potential negative consequences of unethical AI use. They include biases and discrimination, violations of privacy and human rights, and unintended harm.
Is ChatGPT ethical? ›
The analysis finds ChatGPT could provide high-level societal and ethical benefits. However, it also raises significant ethical concerns across social justice, individual autonomy, cultural identity, and environmental issues.
Can AI be biased? ›
AI bias, also referred to as machine learning bias or algorithm bias, refers to AI systems that produce biased results that reflect and perpetuate human biases within a society, including historical and current social inequality.
What is an example of unethical AI? ›
The Bad Side of Artificial Intelligence
One example of this is AI algorithms sending tech job openings to men but not women. There have been several studies and news articles written that have shown evidence of discriminatory outcomes due to bias in AI.
Why is AI so controversial? ›
Here are some key reasons for the controversy: Ethical Concerns:Bias and Fairness: AI systems may inherit biases present in training data, leading to biased outcomes. Ensuring fairness and mitigating bias in AI algorithms is a significant ethical challenge.
How many AI ethics are there? ›
Ethical principles
In the review of 84 ethics guidelines for AI, 11 clusters of principles were found: transparency, justice and fairness, non-maleficence, responsibility, privacy, beneficence, freedom and autonomy, trust, sustainability, dignity, solidarity.
What is AI ethics in one sentence? ›
Ethics is a set of moral principles which help us discern between right and wrong. AI ethics is a multidisciplinary field that studies how to optimize AI's beneficial impact while reducing risks and adverse outcomes.
The data used to train AI can be biased. If the data is not representative of the whole population, the AI will be biased too. For example, if a system is trained on a data set of men, it will be biased against women. - People who design AI systems can also be biased.
How do we make AI not biased more ethical? ›
Use Representative Data
Basically, the quality of data you are using to train and test AI algorithms influences the outcomes. To ensure that you are building an ethical and bias-free artificial intelligence, train it using a full-spectrum of data. Data vetting is another fundamental component.
What is AI ethics why it is necessary? ›
AI ethics is a system of moral principles and techniques intended to inform the development and responsible use of artificial intelligence technology. As AI has become integral to products and services, organizations are starting to develop AI codes of ethics.
Should you be polite to AI? ›
It turns out that AI likes feedback, especially positive and polite feedback. AI performs better, as we all do, when it enjoys working with you and understands what you like and don't like. In short, it collaborates better when we are nicer.
Should artificial intelligence be trusted why or why not? ›
Just like humans, AI systems can make mistakes. For example, a self-driving car might mistake a white tractor-trailer truck crossing a highway for the sky. But to be trustworthy, AI needs to be able to recognize those mistakes before it is too late.
Should AI deserve rights? ›
The question of AI rights remains largely hypothetical, contingent on future advancements in AI capabilities, particularly concerning autonomy and consciousness. While parallels can be drawn from the animal rights movement, AI's distinct nature as a human-created, non-sentient entity presents unique challenges.
