Many concerns about AI revolve around discrimination and bias. Often, these come in the form of quaint predictions (AI will destroy the industries that make photographic film, cassette tapes, and vinyl records). More pressing concerns include the need to provide efficient, accessible processes for people to challenge the use or outcomes of an AI system. This requires understanding and addressing the following five key ethical principles.
Currently, there is no single solution for ensuring fairness in AI. However, there are several avenues that are being explored. These include focusing on data, developing guiding principles, and promoting interpretable AI that allows us to understand how the results emerged. While there is no one-box solution, these efforts will help to mitigate bias in AI. Another important factor is to ensure that the system is not biased in ways that are illegal or harmful. This includes examining the context of a decision to determine whether it is based on sensitive attributes such as age or sex. Moreover, it is also crucial to consider whether the sensitive attribute is critical for achieving the desired outcome. For example, an AI program might be able to identify patterns of discrimination by using sensitive features such as sex and race. However, the same model might be unfair in other ways. Therefore, it is essential to develop an interdisciplinary approach that considers the social factors that influence human decision-making. This will allow businesses to ensure that their AI decision-making is not violating legal or moral norms.
An AI system should be reliable and trustworthy throughout its lifecycle. This includes providing transparent and responsible disclosure, enabling people to understand the reasons behind AI decisions (such as key factors used) and the ability to find out when their data is being used by an AI system. This principle also includes the requirement to respect and uphold privacy rights. Many companies collect data for their AI systems, including social media photos and comments, online purchases and more. However, not all of this information is given back to the original creators of that content, such as the app Lensa AI, which was criticized for using its technology to create “cool” cartoon-looking profile photos without giving proper credit or payment to artists. It is important that people can have redress when an AI system impacts them in a significant way. This includes efficient, accessible mechanisms to challenge the use of or outputs of an AI system, including in cases of human-centered bias. This principle should be supported by effective education and outreach efforts, as well as robust review and auditing processes for AI systems.
Transparency is an essential part of the ethics of AI. It entails making decisions public and clearly explaining how they were made. It also requires identifying potential risks and putting safeguards in place to prevent misuse of the technology. However, this can be difficult because algorithms are black boxes that are prone to unfair bias and lack transparency. One way to address this issue is by requiring businesses that use AI in high stakes applications to create rigorous explainability processes and methods. This will enable Americans to understand how and why these systems make the decisions they do, which will help build trust. Another way to address this issue is by promoting policies that promote diversity, non-discrimination and fairness. This can be achieved by ensuring that AI is transparent and inclusive, and that it is not discriminating against minorities or vulnerable populations. It can also be achieved by requiring companies to make their data and decision-making processes available to the public. These efforts are a great start, but they must be supplemented by actual technology policy that can drive standardization and establish regulations.
Many concerns about AI revolve around discrimination and bias. Often, these come in the form of quaint predictions (AI will destroy the industries that make photographic film, cassette tapes, and vinyl records). More pressing concerns include the need to provide efficient, accessible processes for people to challenge the use or outcomes of an AI system. This requires understanding and addressing the following five key ethical principles.A key concern with AI is the potential for harm, but there are many other issues that require attention as well. As a result, the six sets of ethical principles for AI (and machine ethics) include both an emphasis on doing good and a warning against doing harm. Beneficence takes a page from healthcare ethics, where doctors take an oath to “do no harm.” The same principle should apply to AI: “Do only good” (beneficence) and “don’t do any harm” (non-maleficence). This is particularly important in the context of AI that may be used for human health, including remote monitoring systems that can track people’s movements. These systems pose both privacy tradeoffs and the risk of eroding autonomy, as people might modify their behaviour in order to comply with these technologies. There should also be a clear process for challenging AI decisions that have significant impacts on individuals, communities or environments — so-called redress. This is an opportunity to create a system that promotes diversity and inclusion, and avoids unfair bias in AI decisions.
Many governments and other groups are working on creating a framework for AI ethics. They are using a variety of approaches to help them create a strong set of guidelines, including public outreach, regulations, economics, governance, and security. This will ensure that the aims of AI are aligned with broader societal goals. For AI systems to respect human autonomy they must be able to understand and reason about the world, be transparent, minimize harmful bias, provide access for all individuals, and include mechanisms and safeguards to prevent misuse and malicious use. They also need to be designed to be inclusive and able to be challenged. Science fiction has toyed with the idea of ethical AI for some time. For example, Spike Jonze’s film Her, where a computer user falls in love with his operating system, explores how machines can affect our lives and relationships. This theme is also a major focus of the Mass Effect series of video games by BioWare, where conflict between those who bestow organic rights on artificial moral patients and those who continue to see them as disposable machinery is a key narrative element.