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The deluge of ethics principles

Roos de Jong explaining different ethical principles
In the last couple of years, there have been intensive discussions about what “ethical” and humane AI is and hould entail. Companies, scientists and international organizations have drawn up and signed various ethical guidelines, principles and codes. There are many, many lists here, you see just a few of them in all these documents, there are also some clear similarities . You could say there is a global convergence emerging around five ethical principles.
Four of them are actually key bioethical principles in the health care domain. All choices for a patient are made with the intent to do good. Similarly, many people stayed at a I should be directed and at promoting well-being, peace and happiness. It is argued that I should be aimed at creating socio-economic opportunities, preserving dignity and sustaining the planet. Do no harm is an important principle in medical ethics as well. Also, in the field of AI, there’s a lot of discussion on taking cautions against the many potentially negative consequences of overusing or misusing AI think of malicious hacking, but also the loss of skills or trust, for instance, Respecting a person’s freedom to choose.
What is right for them is a third bio-ethica principle. In AI discussions, this is about striking a balance between the decision-making power we retain for ourselves and at which we dedicate to AI. Treating and providing care fairly to all patients is a fourth bio-ethical principle that we also see reflected in discussions on ethical AI There is a lot of focus on eliminating discrimination. In addition, it is also about equal access to the benefits of AI and about respecting potentially vulnerable groups and persons. Many stakeholders seem to recognize that not only medical technologies affecting our bodies or brain, but also I can affect our lives in a fundamental way that it can influence our thinking, social life, actions and humanity.
However, these principles are quite abstract. Interestingly, the discussion on ethics often mainly revolves around another fifth principle, and that, in a way enables the other principles. This is to principles expec ability. I should be understandable, interpretable or explainable. And actually, this is exactly what is so challenging about AI, especially if lots of variables are taken into account and machine learning techniques are involved . The workings of an AI system can become completely invisible or unintelligible to its users. Sometimes this is referred to as a black box. This principle is therefore about the necessity to know how to decision making processes of AI work and who is responsible for the way they work.
This is also about the so-called FAT- principles are all about. And as there are all kinds of ways in which biases can sneak into an AI decision, a lot of attention goes to ensuring that algorithms do not discriminate. They should be fair. The algorithm needs to be carefully designed and awareness is needed with regard to data collection and categorization or labeling practices. Think about hiring tools. Even if an algorithm processes the inputs in the same way and never have has an off day. This does not automatically lead to fair outcomes and greater diversity. For instance, problems could occur because the training data are not representative or contain human biases, which simply get automated. When using these tools.
As mentioned before, it is key to understand AI based decisions and arrange responsibility for them. Employers who purchase a certain AI tool for their job application procedures do not always have a clear understanding of the choices and assumptions underlying the algorithm. Who can check the decision making processes or intervene when systems fail or when unforeseen undesirable effects occur
to enable fairness and accountability? Openness is needed. In other words, communication about the workings of the AI and disclosure of data sets or mechanisms behind the processing of the data. However, the secrecy in AI industry and tech companies can be a major hurdle to enable this.

Now that you have learned about the wide variety of ethical challenges related to AI, it might not surprise you that several big tech companies, governments, and all kinds of organisations have come up with lists of ethical principles for the development and deployment of AI. In this video we will delve into the different ethical principles that have come up in discussions on AI. Below you can read more about attempts to reach collective standards and harmonised rules.

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